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# Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study

Maxime Raffray, Louise Bourasseau, Cécile Vigneau, Cécile Couchoud, Clémence Béchade, François Glowacki, Sahar Bayat, Rein Registry

► To cite this version:

Maxime Raffray, Louise Bourasseau, Cécile Vigneau, Cécile Couchoud, Clémence Béchade, et al. Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study. PLoS ONE, 2024, 19 (3), pp.e0299601. 10.1371/journal.pone.0299601. hal-04528810

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# Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study

Maxime Raffray, Louise Bourasseau, Cécile Vigneau, Cécile Couchoud, Clémence Béchade, François Glowacki, Sahar Bayat, Rein Registry

► To cite this version:

Maxime Raffray, Louise Bourasseau, Cécile Vigneau, Cécile Couchoud, Clémence Béchade, et al.. Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study. PLoS ONE, 2024, 19 (3), pp.e0299601. 10.1371/journal.pone.0299601 . hal-04528810

HAL Id: hal-04528810

https://ehesp.hal.science/hal-04528810v1

Submitted on 31 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

RESEARCH ARTICLE

# Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study

Maxime Raffray<sup>1</sup>, Louise Bourasseau<sup>1</sup>, Cécile Vigneau<sup>2*</sup>, Cécile Couchoud<sup>3</sup>, Clémence Béchade<sup>4</sup>, François Glowacki<sup>5</sup>, Sahar Bayat<sup>1</sup>, on behalf of the REIN registry<sup>¶</sup>

1 Univ Rennes, EHESP, CNRS, Inserm, Arènes—UMR 6051, RSMS (Recherche sur les Services et Management en Santé), Rennes, France, 2 Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail), Rennes, France, 3 Renal Epidemiology and Information Network (REIN) Registry, Biomedicine Agency, Saint-Denis-La-Plaine, France, 4 Néphrologie, CHU Clemenceau, Caen, France, 5 Service de néphrologie, Hôpital Huriez, CHRU de Lille, Lille, France

¶ Membership of the REIN registry is provided in the Acknowledgments.

* cecile.vigneau@chu-rennes.fr

## Abstract

<figure><img src="image_4.png" /></figure>

OPEN ACCESS

**Citation:** Raffray M, Bourasseau L, Vigneau C, Couchoud C, Béchade C, Glowacki F, et al. (2024) Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study. PLoS ONE 19(3): e0299601.
https://doi.org/10.1371/journal.pone.0299601

**Editor:** Chikezie Hart Onwukwe, Isawiya General Hospital, Governorate of Gurayyat, SAUDI ARABIA

**Received:** November 24, 2023

**Accepted:** February 13, 2024

**Published:** March 27, 2024

**Peer Review History:** PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0299601

**Copyright:** © 2024 Raffray et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

**Data Availability Statement:** The data used in the study cannot be shared publicly because it comprises of healthcare use at the individual level of French citizen (SNDS database). Data from the

## Background

In the last two decades, sex and gender differences have been documented in chronic kidney disease (CKD) management, including access to renal replacement therapy and its outcomes. The objectives of this study were to 1) compare the pre-dialysis healthcare utilization in men and women, and 2) examine the sex-specific factors associated with emergency dialysis start.

## Methods

Adult patients with CKD who started dialysis in France in 2015 were extracted from the Renal Epidemiology and Information Network registry. Patients were matched to the French National Health Data System database to extract healthcare utilization data for the 2 years before dialysis start. Frequencies and monthly rates of consultations and hospitalizations were compared between men and women. Logistic regression analyses were performed separately in the two groups.

## Results

Among the 8856 patients included, 3161 (35.7%) were women. Median age (71 years) and estimated glomerular filtration rate (8.1 and 7.7 ml/min for men and women) were similar between groups at dialysis start. Monthly consultations rates with a general practitioner and nephrology-related care were similar between women and men. Some sex-specific differences were found: higher frequencies of consultations with a psychiatrist in women and more frequent hospitalizations for circulatory system diseases in men. Emergency dialysis start rate was 30% in both groups. Emergency dialysis start was associated with acute nephropathy, compared with slowly progressive nephropathy, in women but not in men (OR = 1.48, p<0.01 vs 1.15, p = 0.18).
<figure><img src="image_2.png" /></figure>

RESEARCH ARTICLE

# Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study

Maxime Raffray<sup>1</sup>, Louise Bourasseau<sup>1</sup>, Cécile Vigneau<sup>2*</sup>, Cécile Couchoud<sup>3</sup>, Clémence Béchade<sup>4</sup>, François Glowacki<sup>5</sup>, Sahar Bayat<sup>1</sup>, on behalf of the REIN registry<sup>¶</sup>

1 Univ Rennes, EHESP, CNRS, Inserm, Arènes—UMR 6051, RSMS (Recherche sur les Services et Management en Santé), Rennes, France, 2 Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail), Rennes, France, 3 Renal Epidemiology and Information Network (REIN) Registry, Biomedicine Agency, Saint-Denis-La-Plaine, France, 4 Néphrologie, CHU Clemenceau, Caen, France, 5 Service de néphrologie, Hôpital Huriez, CHRU de Lille, Lille, France

¶ Membership of the REIN registry is provided in the Acknowledgments.

* cecile.vigneau@chu-rennes.fr

## Abstract

<figure><img src="image_3.png" /></figure>

OPEN ACCESS

**Citation:** Raffray M, Bourasseau L, Vigneau C, Couchoud C, Béchade C, Glowacki F, et al. (2024) Sex-related differences in pre-dialysis trajectories and dialysis initiation: A French nationwide retrospective study. PLoS ONE 19(3): e0299601.
https://doi.org/10.1371/journal.pone.0299601

**Editor:** Chikezie Hart Onwukwe, Isawiya General Hospital, Governorate of Gurayyat, SAUDI ARABIA

**Received:** November 24, 2023

**Accepted:** February 13, 2024

**Published:** March 27, 2024

**Peer Review History:** PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0299601

**Copyright:** © 2024 Raffray et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

**Data Availability Statement:** The data used in the study cannot be shared publicly because it comprises of healthcare use at the individual level of French citizen (SNDS database). Data from the

## Background

In the last two decades, sex and gender differences have been documented in chronic kidney disease (CKD) management, including access to renal replacement therapy and its outcomes. The objectives of this study were to 1) compare the pre-dialysis healthcare utilization in men and women, and 2) examine the sex-specific factors associated with emergency dialysis start.

## Methods

Adult patients with CKD who started dialysis in France in 2015 were extracted from the Renal Epidemiology and Information Network registry. Patients were matched to the French National Health Data System database to extract healthcare utilization data for the 2 years before dialysis start. Frequencies and monthly rates of consultations and hospitalizations were compared between men and women. Logistic regression analyses were performed separately in the two groups.

## Results

Among the 8856 patients included, 3161 (35.7%) were women. Median age (71 years) and estimated glomerular filtration rate (8.1 and 7.7 ml/min for men and women) were similar between groups at dialysis start. Monthly consultations rates with a general practitioner and nephrology-related care were similar between women and men. Some sex-specific differences were found: higher frequencies of consultations with a psychiatrist in women and more frequent hospitalizations for circulatory system diseases in men. Emergency dialysis start rate was 30% in both groups. Emergency dialysis start was associated with acute nephropathy, compared with slowly progressive nephropathy, in women but not in men (OR = 1.48, p<0.01 vs 1.15, p = 0.18).
SNDS are available from the French Health Data
Hub (https://smex-ctp.trendmicro.com:443/wis/
clicktime/v1/query?url=https%3a%2f%2fwww.
health%2ddata%2dhub.fr%2fdepot&umid=
cbfb002f-8daa-401b-b5fe-59ff4db6872a&auth=
cb5fd73bba5cd044cb5e5d90152ce147860ea990-
d41f3f7e4e4e3a1074ee8ec2f11c75ea6e0d08ca)
for researchers who meet the criteria for access to
confidential data. The process will require
authorization from the French Data Protection
Authority (Commission nationale de l'informatique
et des libertés). For this particular study, access
was granted by the French Data Protection
Authority (Commission nationale de l'informatique
et des libertés, CNIL authorization N° 917021).
Additionally, the REIN registry data was linked with
the SNDS data with the approuval of the relevant
French committees, the Comité consultatif sur le
traitement de l'information en matière de recherche
(CCTIRS) and the French Data Protection Authority
(Commission nationale de l'informatique et des
libertés) (CNIL N° 903188). Information about the
data of the REIN registry can be requested by mail
to Dr. Cécile Couchoud who coordinates the REIN
registry at the French Biomedicine Agency (cecile.
couchoud@biomedecine.fr). We have joined the
authorizations cited during the submission
process.

**Funding:** This research was funded by a PhD grant from University of Rennes 1, France. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

**Competing interests:** The authors have declared
that no competing interests exist.

Conclusions

This study found similar quantitative pre-dialysis healthcare utilization in men and women.
To better understand sex/gender differences in CKD care trajectories, future research
should focus on patients with CKD who are unknown to nephrology services, on patients
receiving conservative care and on the sex/gender-specific mechanisms underlying care
decision-making.

Introduction

Sex (biological) and gender (sociocultural construct)-specific differences have been documented for many diseases and various health-related areas (e.g. epidemiology, physiopathology, response to treatment and outcomes) [1]. Sex/gender-related differences and disparities also concern the interaction with healthcare, including access and utilization [2–6]. Chronic Kidney Disease (CKD) is not exempt from sex/gender-specific differences [7, 8]. In many countries, prevalence estimations show higher proportion of women with stage 3 to 5 CKD compared with men [7, 9–14]. However, more men start renal replacement therapy, including dialysis [15], possibly due to faster CKD progression [16–18], higher mortality rate in women, or disparity in its access [19].

In the last two decades, sex-related differences have been documented throughout CKD care including hemodialysis outcomes and access to transplantation [7, 20]. Women receiving hemodialysis have poorer health-related quality of life [21, 22], higher symptom burden and severity [23–25], higher hospitalization rates [26] and higher withdrawal risk [27]. Women also are less likely to being referred [28] and waitlisted for transplantation [29–31], and to receive a kidney transplant [32, 33].

Knowledge is limited on the healthcare utilization and trajectories leading to renal replace-
ment therapy. In France, dialysis is provided by both public and private facilities. Dialysis
treatment is 100% covered by social security and thus ownership of the facility should not be
associated with its access. However, it is not known whether and how care trajectories differ
between men and women before dialysis initiation.

Additionally, Emergency Dialysis Start (EDS) remains frequent in patients with CKD [34-
36] and the sex/gender-specific risk factors of EDS have not been explored. Understanding
these potential differences and disparities could contribute to targeted and personalized inter-
ventions and could improve the care of men and women with CKD.

Therefore, in this study, we wanted to describe and compare in men and women the pre-
dialysis healthcare utilization in the last 2 years before dialysis initiation. We also examined the
sex-specific factors associated with EDS.

**Materials and methods**

1) Population studied and data collected

Patients and their individual data were collected from two French national databases. First, all
adult patients who started dialysis in 2015 were identified in the Renal Epidemiology and
Information Network (REIN) registry. This database records all patients with CKD who start
renal replacement therapy in France and follows their care trajectories (e.g. waitlisting and
transplant, dialysis withdrawal, death) [37, 38]. The REIN registry collects socio-demographic,
clinical and laboratory data, initial kidney disease and comorbidities, renal replacement
SNDS are available from the French Health Data
Hub (https://smex-ctp.trendmicro.com:443/wis/
clicktime/v1/query?url=https%3a%2f%2fwww.
health%2ddata%2dhub.fr%2fdepot&umid=
cbfb002f-8daa-401b-b5fe-59ff4db6872a&auth=
cb5fd73bba5cd044cb5e5d90152ce147860ea990-
d41f3f7e4e4e3a1074ee8ec2f11c75ea6e0d08ca)
for researchers who meet the criteria for access to
confidential data. The process will require
authorization from the French Data Protection
Authority (Commission nationale de l'informatique
et des libertés). For this particular study, access
was granted by the French Data Protection
Authority (Commission nationale de l'informatique
et des libertés, CNIL authorization N° 917021).
Additionally, the REIN registry data was linked with
the SNDS data with the approval of the relevant
French committees, the Comité consultatif sur le
traitement de l'information en matière de recherche
(CCTIRS) and the French Data Protection Authority
(Commission nationale de l'informatique et des
libertés) (CNIL N° 903188). Information about the
data of the REIN registry can be requested by mail
to Dr. Cécile Couchoud who coordinates the REIN
registry at the French Biomedicine Agency (cecile.
couchoud@biomedecine.fr). We have joined the
authorizations cited during the submission
process.

**Funding:** This research was funded by a PhD grant from University of Rennes 1, France. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

**Competing interests:** The authors have declared
that no competing interests exist.

Conclusions

This study found similar quantitative pre-dialysis healthcare utilization in men and women. To better understand sex/gender differences in CKD care trajectories, future research should focus on patients with CKD who are unknown to nephrology services, on patients receiving conservative care and on the sex/gender-specific mechanisms underlying care decision-making.

Introduction

Sex (biological) and gender (sociocultural construct)-specific differences have been docu-
mented for many diseases and various health-related areas (e.g. epidemiology, physiopathol-
ogy, response to treatment and outcomes) [1]. Sex/gender-related differences and disparities
also concern the interaction with healthcare, including access and utilization [2–6]. Chronic
Kidney Disease (CKD) is not exempt from sex/gender-specific differences [7, 8]. In many
countries, prevalence estimations show higher proportion of women with stage 3 to 5 CKD
compared with men [7, 9–14]. However, more men start renal replacement therapy, including
dialysis [15], possibly due to faster CKD progression [16–18], higher mortality rate in women,
or disparity in its access [19].

In the last two decades, sex-related differences have been documented throughout CKD care including hemodialysis outcomes and access to transplantation [7, 20]. Women receiving hemodialysis have poorer health-related quality of life [21, 22], higher symptom burden and severity [23–25], higher hospitalization rates [26] and higher withdrawal risk [27]. Women also are less likely to being referred [28] and waitlisted for transplantation [29–31], and to receive a kidney transplant [32, 33].

Knowledge is limited on the healthcare utilization and trajectories leading to renal replace-
ment therapy. In France, dialysis is provided by both public and private facilities. Dialysis
treatment is 100% covered by social security and thus ownership of the facility should not be
associated with its access. However, it is not known whether and how care trajectories differ
between men and women before dialysis initiation.

Additionally, Emergency Dialysis Start (EDS) remains frequent in patients with CKD [34-
36] and the sex/gender-specific risk factors of EDS have not been explored. Understanding
these potential differences and disparities could contribute to targeted and personalized inter-
ventions and could improve the care of men and women with CKD.

Therefore, in this study, we wanted to describe and compare in men and women the pre-
dialysis healthcare utilization in the last 2 years before dialysis initiation. We also examined the
sex-specific factors associated with EDS.

**Materials and methods**

1) Population studied and data collected

Patients and their individual data were collected from two French national databases. First, all
adult patients who started dialysis in 2015 were identified in the Renal Epidemiology and
Information Network (REIN) registry. This database records all patients with CKD who start
renal replacement therapy in France and follows their care trajectories (e.g. waitlisting and
transplant, dialysis withdrawal, death) [37, 38]. The REIN registry collects socio-demographic,
clinical and laboratory data, initial kidney disease and comorbidities, renal replacement
therapy start modalities and context, including EDS. EDS is defined as a first dialysis initiated in the 24 hours following the identification of life threatening risks by a nephrologist. Three nephrologists (including the authors CV and CC) reviewed and classified the initial kidney diseases of the included patients in three groups according to their usual progression rate: slowly progressive, acute, and uncertain/variable nephropathy (S1 Table in S1 File).

As the REIN registry does not contain data on the pre-dialysis period, a deterministic record linkage was done with the French National Health Data System (SNDS), described elsewhere [39]. The SNDS is a nationwide database that covers 99% of the French population and contains data on a) all reimbursement of non-hospital-based outpatient healthcare (e.g. consultations, laboratory tests, and drug deliveries) and b) all hospital activity (i.e. inpatient and outpatient stays, diagnoses, procedures, and length of stay) [40]. However, it does not contain the results of laboratory tests (e.g. blood creatinine). The deterministic record linkage allowed extracting from the SNDS database healthcare data for the 2 years before dialysis start. The 2 years window was chosen and deemed appropriate for studying EDS based on the French CKD management guidelines recommending starting preparation for dialysis at least 1 year before its foreseeable start [41]. For the care trajectories analyses, healthcare data on consultations with all medical specialties, blood creatinine measurements, and hospitalizations were used [42]. REIN registry patients who could not be matched in the SNDS database and patients without information on dialysis start context (emergency or planned) were excluded.

## 2) Ethics statement

The REIN registry was approved by the relevant French committees, the Comité consultatif sur le traitement de l'information en matière de recherche (CCTIRS) and the Commission nationale de l'informatique et des libertés (CNIL N° 903188). Patients are informed about the registration in the REIN registry and their right to not participate (opt out) by the nephrology clinic.

Additionally, the permission to access the raw data used in our study (the SNDS data linked with the REIN registry data) was granted by the French Data Protection Authority (Commission Nationale Informatique et Liberté, CNIL authorization N° 917021). All data used in this study was anonymized before its use. Data was accessed between 10/01/2018 and 12/31/2021. All methods in this study were performed in accordance with relevant guidelines and regulations.

## 3) Analyses

Characteristics at dialysis start were described and compared between men and women. As the study population was not a sample, but the dialysis incident population in 2015, absolute differences and not p-values were used for comparison between groups (i.e. women and men).

Consultations were classified depending on the medical specialty: general practitioner (GP), nephrologist, and all other medical specialties. Hospitalizations were categorized in function of the main medical reason of admission (main diagnosis, International Classification of Diseases-10 codes; S2 Table in S1 File) and duration: a) hospitalizations related to dialysis preparation, b) <24-hour hospitalizations (all diagnoses), c) ≥24-hour hospitalizations related to nephrology, and d) ≥24-hour hospitalizations unrelated to nephrology. To describe the changes in healthcare utilization over time, incidence densities (or monthly consultation and hospitalization incidence rates) were calculated and plotted for the 24 months before dialysis start. Analyses were also stratified by age (<60 and ≥60 years), but no sex difference was observed.
therapy start modalities and context, including EDS. EDS is defined as a first dialysis initiated
in the 24 hours following the identification of life threatening risks by a nephrologist. Three
nephrologists (including the authors CV and CC) reviewed and classified the initial kidney dis-
eases of the included patients in three groups according to their usual progression rate: slowly
progressive, acute, and uncertain/variable nephropathy (S1 Table in S1 File).

As the REIN registry does not contain data on the pre-dialysis period, a deterministic record linkage was done with the French National Health Data System (SNDS), described elsewhere [39]. The SNDS is a nationwide database that covers 99% of the French population and contains data on a) all reimbursement of non-hospital-based outpatient healthcare (e.g. consultations, laboratory tests, and drug deliveries) and b) all hospital activity (i.e. inpatient and outpatient stays, diagnoses, procedures, and length of stay) [40]. However, it does not contain the results of laboratory tests (e.g. blood creatinine). The deterministic record linkage allowed extracting from the SNDS database healthcare data for the 2 years before dialysis start. The 2 years window was chosen and deemed appropriate for studying EDS based on the French CKD management guidelines recommending starting preparation for dialysis at least 1 year before its foreseeable start [41]. For the care trajectories analyses, healthcare data on consultations with all medical specialties, blood creatinine measurements, and hospitalizations were used [42]. REIN registry patients who could not be matched in the SNDS database and patients without information on dialysis start context (emergency or planned) were excluded.

## 2) Ethics statement

The REIN registry was approved by the relevant French committees, the Comité consultatif sur le traitement de l'information en matière de recherche (CCTIRS) and the Commission nationale de l'informatique et des libertés (CNIL N° 903188). Patients are informed about the registration in the REIN registry and their right to not participate (opt out) by the nephrology clinic.

Additionally, the permission to access the raw data used in our study (the SNDS data linked with the REIN registry data) was granted by the French Data Protection Authority (Commission Nationale Informatique et Liberté, CNIL authorization N° 917021). All data used in this study was anonymized before its use. Data was accessed between 10/01/2018 and 12/31/2021. All methods in this study were performed in accordance with relevant guidelines and regulations.

## 3) Analyses

Characteristics at dialysis start were described and compared between men and women. As the study population was not a sample, but the dialysis incident population in 2015, absolute differences and not p-values were used for comparison between groups (i.e. women and men).

Consultations were classified depending on the medical specialty: general practitioner (GP), nephrologist, and all other medical specialties. Hospitalizations were categorized in function of the main medical reason of admission (main diagnosis, International Classification of Diseases-10 codes; S2 Table in S1 File) and duration: a) hospitalizations related to dialysis preparation, b) <24-hour hospitalizations (all diagnoses), c) ≥24-hour hospitalizations related to nephrology, and d) ≥24-hour hospitalizations unrelated to nephrology. To describe the changes in healthcare utilization over time, incidence densities (or monthly consultation and hospitalization incidence rates) were calculated and plotted for the 24 months before dialysis start. Analyses were also stratified by age (<60 and ≥60 years), but no sex difference was observed.
Logistic regression analyses were performed separately in men and women to identify sex-
specific factors associated with EDS. Regression models included the patients' characteristics
at dialysis start (REIN registry) and pre-dialysis healthcare utilization (SNDS). Variables with a
univariate p-value <0.20 were included in the multivariable analysis. A p-value <0.05 was con-
sidered statistically significant. Missing data were considered missing at random and imputed
using the multiple imputation by chained equation procedure with ten iterations resulting in
five imputed datasets [43].

**Results**

1) Patients’ characteristics

In total, 8856 patients were included in the analysis (Fig 1), among whom 3161 (35.7%) were women. Table 1 presents their characteristics at dialysis start. Polycystic kidney disease was more frequent among women, while vascular and hypertensive nephropathies were more frequent in men who also had more cardiovascular diseases (17.8% of men had ≥3 cardiovascular diseases vs 9% of women). Chronic respiratory disease also was more frequent in men (15.6% versus 9.7%). Obesity (body mass index ≥30 kg/m²) was more frequent in women than men (25.5% versus 17.8% in men). The estimated glomerular filtration rate (eGFR) at dialysis start was similar between groups (median value: 8.3 ml/min in men and 7.7 ml/min in women) as well as EDS rate (30.9% in men and 29.1% in women).

<figure><img src="image_5.png" /><figcaption>Fig 1. Flowchart of patient inclusion.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g001
Logistic regression analyses were performed separately in men and women to identify sex-
specific factors associated with EDS. Regression models included the patients' characteristics
at dialysis start (REIN registry) and pre-dialysis healthcare utilization (SNDS). Variables with a
univariate p-value <0.20 were included in the multivariable analysis. A p-value <0.05 was con-
sidered statistically significant. Missing data were considered missing at random and imputed
using the multiple imputation by chained equation procedure with ten iterations resulting in
five imputed datasets [43].

**Results**

1) Patients’ characteristics

In total, 8856 patients were included in the analysis (Fig 1), among whom 3161 (35.7%) were women. Table 1 presents their characteristics at dialysis start. Polycystic kidney disease was more frequent among women, while vascular and hypertensive nephropathies were more frequent in men who also had more cardiovascular diseases (17.8% of men had ≥3 cardiovascular diseases vs 9% of women). Chronic respiratory disease also was more frequent in men (15.6% versus 9.7%). Obesity (body mass index ≥30 kg/m²) was more frequent in women than men (25.5% versus 17.8% in men). The estimated glomerular filtration rate (eGFR) at dialysis start was similar between groups (median value: 8.3 ml/min in men and 7.7 ml/min in women) as well as EDS rate (30.9% in men and 29.1% in women).

<figure><img src="image_4.png" /><figcaption>Fig 1. Flowchart of patient inclusion.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g001
<table><caption>Table 1. Characteristics at dialysis initiation (n = 8856 incident patients in France in 2015).</caption><thead><tr><th></th><th>Men<br>N = 5695<br>(63.4%)</th><th>Women<br>N = 3161<br>(35.7%)</th><th>Absolute difference (Women-Men)</th></tr></thead><tbody><tr><td>Age, median [Q1-Q3]</td><td>71.0 [60.9, 80.0]</td><td>71.3 [59.9, 80.4]</td><td>0.3</td></tr><tr><td>18-45</td><td>467 (8.2%)</td><td>269 (8.5%)</td><td>0.3</td></tr><tr><td>45-60</td><td>865 (15.2%)</td><td>523 (16.5%)</td><td>1.3</td></tr><tr><td>60-75</td><td>2094 (36.8%)</td><td>1064 (33.7%)</td><td>-3.1</td></tr><tr><td>≥ 75</td><td>2269 (39.8%)</td><td>1305 (41.3%)</td><td>1.5</td></tr><tr><td>Initial kidney disease (nephropathy)</td><td></td><td></td><td></td></tr><tr><td>Polycystic</td><td>232 (4.1%)</td><td>220 (7.0%)</td><td>2.9</td></tr><tr><td>Diabetic</td><td>1310 (23.0%)</td><td>754 (23.9%)</td><td>0.9</td></tr><tr><td>Vascular and hypertensive</td><td>1630 (28.6%)</td><td>748 (23.7%)</td><td>-4.9</td></tr><tr><td>Glomerulonephritis</td><td>747 (13.1%)</td><td>334 (10.6%)</td><td>-2.5</td></tr><tr><td>Pyelonephritis</td><td>232 (4.1%)</td><td>135 (4.3%)</td><td>0.2</td></tr><tr><td>Others and unknown</td><td>1544 (27.1%)</td><td>970 (30.7%)</td><td>3.6</td></tr><tr><td>Nephropathy progression type</td><td></td><td></td><td></td></tr><tr><td>Slowly progressive</td><td>3900 (68.5%)</td><td>2063 (65.3%)</td><td>-3.2</td></tr><tr><td>Acute</td><td>641 (11.3%)</td><td>435 (13.8%)</td><td>2.5</td></tr><tr><td>Variable/uncertain</td><td>1154 (20.3%)</td><td>663 (21.0%)</td><td>0.7</td></tr><tr><td>Body mass index (kg/m²)</td><td></td><td></td><td></td></tr><tr><td>&lt; 18.5</td><td>120 (2.1%)</td><td>123 (3.9%)</td><td>1.8</td></tr><tr><td>18.5-23</td><td>1170 (20.5%)</td><td>622 (19.7%)</td><td>-0.8</td></tr><tr><td>23-25</td><td>811 (14.2%)</td><td>341 (10.8%)</td><td>-3.4</td></tr><tr><td>25-30</td><td>1651 (29.0%)</td><td>718 (22.7%)</td><td>-6.3</td></tr><tr><td>≥ 30</td><td>1012 (17.8%)</td><td>807 (25.5%)</td><td>7.7</td></tr><tr><td>Missing</td><td>931 (16.3%)</td><td>550 (17.4%)</td><td>1.1</td></tr><tr><td>Serum albumin (g/L)</td><td></td><td></td><td></td></tr><tr><td>≥ 30</td><td>3985 (70.0%)</td><td>2144 (67.8%)</td><td>-2.2</td></tr><tr><td>&lt; 30</td><td>987 (17.3%)</td><td>570 (18.0%)</td><td>0.7</td></tr><tr><td>Missing</td><td>723 (12.7%)</td><td>447 (14.1%)</td><td>1.4</td></tr><tr><td>Hemoglobin (g/L)</td><td></td><td></td><td></td></tr><tr><td>&lt; 10</td><td>2974 (52.2%)</td><td>1786 (56.5%)</td><td>4.3</td></tr><tr><td>10-12</td><td>1698 (29.8%)</td><td>899 (28.4%)</td><td>-1.4</td></tr><tr><td>≥ 12</td><td>818 (14.4%)</td><td>350 (11.1%)</td><td>-3.3</td></tr><tr><td>Missing</td><td>205 (3.6%)</td><td>126 (4.0%)</td><td>0.4</td></tr><tr><td>Number of cardiovascular diseases*</td><td></td><td></td><td></td></tr><tr><td>0</td><td>2265 (39.8%)</td><td>1678 (53.1%)</td><td>13.3</td></tr><tr><td>1</td><td>1401 (24.6%)</td><td>757 (23.9%)</td><td>-0.7</td></tr><tr><td>2</td><td>1015 (17.8%)</td><td>442 (14.0%)</td><td>-3.8</td></tr><tr><td>≥ 3</td><td>1014 (17.8%)</td><td>284 (9.0%)</td><td>-8.8</td></tr><tr><td>Diabetes</td><td>2585 (45.4%)</td><td>1401 (44.3%)</td><td>-1.1</td></tr><tr><td>Missing</td><td>26 (0.5%)</td><td>14 (0.4%)</td><td>-0.1</td></tr><tr><td>Chronic respiratory disease</td><td>886 (15.6%)</td><td>306 (9.7%)</td><td>-5.9</td></tr><tr><td>Missing</td><td>173 (3.0%)</td><td>87 (2.8%)</td><td>-0.2</td></tr><tr><td>Mobility</td><td></td><td></td><td></td></tr><tr><td>Walk without help</td><td>4438 (77.9%)</td><td>2358 (74.6%)</td><td>-3.3</td></tr><tr><td>Need assistance</td><td>561 (9.9%)</td><td>402 (12.7%)</td><td>2.8</td></tr><tr><td>Totally dependent</td><td>225 (4.0%)</td><td>154 (4.9%)</td><td>0.9</td></tr><tr><td>Missing</td><td>471 (8.3%)</td><td>247 (7.8%)</td><td>-0.5</td></tr></tbody></table>

(Continued)
<table><caption>Table 1. Characteristics at dialysis initiation (n = 8856 incident patients in France in 2015).</caption><thead><tr><th></th><th>Men<br>N = 5695<br>(63.4%)</th><th>Women<br>N = 3161<br>(35.7%)</th><th>Absolute difference (Women-Men)</th></tr></thead><tbody><tr><td>Age, median [Q1-Q3]</td><td>71.0 [60.9, 80.0]</td><td>71.3 [59.9, 80.4]</td><td>0.3</td></tr><tr><td>18-45</td><td>467 (8.2%)</td><td>269 (8.5%)</td><td>0.3</td></tr><tr><td>45-60</td><td>865 (15.2%)</td><td>523 (16.5%)</td><td>1.3</td></tr><tr><td>60-75</td><td>2094 (36.8%)</td><td>1064 (33.7%)</td><td>-3.1</td></tr><tr><td>≥ 75</td><td>2269 (39.8%)</td><td>1305 (41.3%)</td><td>1.5</td></tr><tr><td>Initial kidney disease (nephropathy)</td><td></td><td></td><td></td></tr><tr><td>Polycystic</td><td>232 (4.1%)</td><td>220 (7.0%)</td><td>2.9</td></tr><tr><td>Diabetic</td><td>1310 (23.0%)</td><td>754 (23.9%)</td><td>0.9</td></tr><tr><td>Vascular and hypertensive</td><td>1630 (28.6%)</td><td>748 (23.7%)</td><td>-4.9</td></tr><tr><td>Glomerulonephritis</td><td>747 (13.1%)</td><td>334 (10.6%)</td><td>-2.5</td></tr><tr><td>Pyelonephritis</td><td>232 (4.1%)</td><td>135 (4.3%)</td><td>0.2</td></tr><tr><td>Others and unknown</td><td>1544 (27.1%)</td><td>970 (30.7%)</td><td>3.6</td></tr><tr><td>Nephropathy progression type</td><td></td><td></td><td></td></tr><tr><td>Slowly progressive</td><td>3900 (68.5%)</td><td>2063 (65.3%)</td><td>-3.2</td></tr><tr><td>Acute</td><td>641 (11.3%)</td><td>435 (13.8%)</td><td>2.5</td></tr><tr><td>Variable/uncertain</td><td>1154 (20.3%)</td><td>663 (21.0%)</td><td>0.7</td></tr><tr><td>Body mass index (kg/m²)</td><td></td><td></td><td></td></tr><tr><td>&lt; 18.5</td><td>120 (2.1%)</td><td>123 (3.9%)</td><td>1.8</td></tr><tr><td>18.5-23</td><td>1170 (20.5%)</td><td>622 (19.7%)</td><td>-0.8</td></tr><tr><td>23-25</td><td>811 (14.2%)</td><td>341 (10.8%)</td><td>-3.4</td></tr><tr><td>25-30</td><td>1651 (29.0%)</td><td>718 (22.7%)</td><td>-6.3</td></tr><tr><td>≥ 30</td><td>1012 (17.8%)</td><td>807 (25.5%)</td><td>7.7</td></tr><tr><td>Missing</td><td>931 (16.3%)</td><td>550 (17.4%)</td><td>1.1</td></tr><tr><td>Serum albumin (g/L)</td><td></td><td></td><td></td></tr><tr><td>≥ 30</td><td>3985 (70.0%)</td><td>2144 (67.8%)</td><td>-2.2</td></tr><tr><td>&lt; 30</td><td>987 (17.3%)</td><td>570 (18.0%)</td><td>0.7</td></tr><tr><td>Missing</td><td>723 (12.7%)</td><td>447 (14.1%)</td><td>1.4</td></tr><tr><td>Hemoglobin (g/L)</td><td></td><td></td><td></td></tr><tr><td>&lt; 10</td><td>2974 (52.2%)</td><td>1786 (56.5%)</td><td>4.3</td></tr><tr><td>10-12</td><td>1698 (29.8%)</td><td>899 (28.4%)</td><td>-1.4</td></tr><tr><td>≥ 12</td><td>818 (14.4%)</td><td>350 (11.1%)</td><td>-3.3</td></tr><tr><td>Missing</td><td>205 (3.6%)</td><td>126 (4.0%)</td><td>0.4</td></tr><tr><td>Number of cardiovascular diseases*</td><td></td><td></td><td></td></tr><tr><td>0</td><td>2265 (39.8%)</td><td>1678 (53.1%)</td><td>13.3</td></tr><tr><td>1</td><td>1401 (24.6%)</td><td>757 (23.9%)</td><td>-0.7</td></tr><tr><td>2</td><td>1015 (17.8%)</td><td>442 (14.0%)</td><td>-3.8</td></tr><tr><td>≥ 3</td><td>1014 (17.8%)</td><td>284 (9.0%)</td><td>-8.8</td></tr><tr><td>Diabetes</td><td>2585 (45.4%)</td><td>1401 (44.3%)</td><td>-1.1</td></tr><tr><td>Missing</td><td>26 (0.5%)</td><td>14 (0.4%)</td><td>-0.1</td></tr><tr><td>Chronic respiratory disease</td><td>886 (15.6%)</td><td>306 (9.7%)</td><td>-5.9</td></tr><tr><td>Missing</td><td>173 (3.0%)</td><td>87 (2.8%)</td><td>-0.2</td></tr><tr><td>Mobility</td><td></td><td></td><td></td></tr><tr><td>Walk without help</td><td>4438 (77.9%)</td><td>2358 (74.6%)</td><td>-3.3</td></tr><tr><td>Need assistance</td><td>561 (9.9%)</td><td>402 (12.7%)</td><td>2.8</td></tr><tr><td>Totally dependent</td><td>225 (4.0%)</td><td>154 (4.9%)</td><td>0.9</td></tr><tr><td>Missing</td><td>471 (8.3%)</td><td>247 (7.8%)</td><td>-0.5</td></tr></tbody></table>

(Continued)
<table><caption>**Table 1.** (Continued)</caption><thead><tr><th></th><th>Men<br>N = 5695<br>(63.4%)</th><th>Women<br>N = 3161<br>(35.7%)</th><th>Absolute difference (Women-Men)</th></tr></thead><tbody><tr><td>Emergency dialysis start</td><td>1762 (30.9%)</td><td>919 (29.1%)</td><td>-1.8</td></tr><tr><td>Dialysis modality</td><td></td><td></td><td></td></tr><tr><td>Hemodialysis</td><td>5188 (91.1%)</td><td>2856 (90.4%)</td><td>-0.7</td></tr><tr><td>Peritoneal dialysis</td><td>507 (8.9%)</td><td>305 (9.6%)</td><td>0.7</td></tr><tr><td>eGFR (ml/min per 1.73m², CKD-EPI)<br>Median [Q1, Q3]</td><td>8.3 [6.1, 11.1]</td><td>7.7 [5.7, 10.1]</td><td>-0.6</td></tr><tr><td>Missing</td><td>546 (9.6%)</td><td>321 (10.2%)</td><td>-0.6</td></tr></tbody></table>

## 2) Comparison of the 2-year pre-dialysis care trajectories

During the 2 years before dialysis start, non-hospital care utilization was similar between men and women (Table 2). Specifically, the median number of consultations with a nephrologist was five and the median number of blood creatinine measurements was 24 in both groups. Overall, the percentage of patients with at least one nephrologist consultation increased during the study period from 43% of men and 40.8% of women in the fourth semester to 71.2% of men and 70.5% of women in the last semester before dialysis start. Women and men had a median number of 15 and 14 consultations with a GP, respectively, during the 2 years before dialysis start. Although changes over time were similar between groups, the monthly incidence rates of consultations with a GP (Fig 2) were consistently higher for women than for men (73.8 consultations per patient month versus 65.1).

The monthly incidence rates of consultations with other medical specialists were similar between men and women (Fig 2), but some differences were observed concerning the specialties (Table 3). Psychiatrists represented the sixth specialist consulted by women (6.2% of all consultations versus 2.7% for men). Conversely, urologic surgeons were the third specialist most frequently seen by men (8.9% of consultations) and the tenth by women (4% of consultations). Vascular surgeons and cardiologist also were more frequently consulted by men. The median number of different specialists seen at least once during the 2 years before dialysis start (excluding GP and nephrologist) was 3 in both groups. Detailed results on other specialists are presented in S3 Table in S1 File.

Overall, inpatient care utilization was similar between men and women. In both groups, nephrology-related hospitalizations increased in the last 6 months before dialysis start (reaching 28 hospitalizations per 100 patient-month in the last month). Conversely, hospitalizations unrelated to nephrology (all other causes) remained stable in the 2 years before dialysis start (median of 3.5 hospitalizations per 100 patient-month) (Fig 3). The proportion of patients who had ≥2 hospitalizations related to dialysis preparation was higher in women than men (15.6% versus 11.2%). However, the monthly incidence rate overlapped between groups (Fig 3). The median hospital stay was the same in men and women (6 and 3 days for hospitalizations related and unrelated to nephrology, respectively). Hospitalizations for <24 hours were slightly more frequent in women (Table 2), especially in the last 7 months before dialysis start (median of 9 and 7.5 hospitalizations per 100 patient-month) (Fig 3).

Among the main reasons of nephrology-unrelated hospitalizations, circulatory system diseases and cancer were more frequent among men (29.3% vs 24% and 13.7% vs 10.4% of those hospitalizations for men and women, respectively) (Fig 4). Conversely, injury/poisoning and

<footnote>*Congestive heart failure, coronary disease, arrhythmia, aortic aneurysm, arteritis of lower limbs, stroke, or transient ischemic attack.</footnote>
<table><caption>**Table 1.** (Continued)</caption><thead><tr><th></th><th>Men<br>N = 5695<br>(63.4%)</th><th>Women<br>N = 3161<br>(35.7%)</th><th>Absolute difference (Women-Men)</th></tr></thead><tbody><tr><td>Emergency dialysis start</td><td>1762 (30.9%)</td><td>919 (29.1%)</td><td>-1.8</td></tr><tr><td>Dialysis modality</td><td></td><td></td><td></td></tr><tr><td>Hemodialysis</td><td>5188 (91.1%)</td><td>2856 (90.4%)</td><td>-0.7</td></tr><tr><td>Peritoneal dialysis</td><td>507 (8.9%)</td><td>305 (9.6%)</td><td>0.7</td></tr><tr><td>eGFR (ml/min per 1.73m<sup>2</sup>, CKD-EPI)<br>Median [Q1, Q3]</td><td>8.3 [6.1, 11.1]</td><td>7.7 [5.7, 10.1]</td><td>-0.6</td></tr><tr><td>Missing</td><td>546 (9.6%)</td><td>321 (10.2%)</td><td>-0.6</td></tr></tbody></table>

## 2) Comparison of the 2-year pre-dialysis care trajectories

During the 2 years before dialysis start, non-hospital care utilization was similar between men and women (Table 2). Specifically, the median number of consultations with a nephrologist was five and the median number of blood creatinine measurements was 24 in both groups. Overall, the percentage of patients with at least one nephrologist consultation increased during the study period from 43% of men and 40.8% of women in the fourth semester to 71.2% of men and 70.5% of women in the last semester before dialysis start. Women and men had a median number of 15 and 14 consultations with a GP, respectively, during the 2 years before dialysis start. Although changes over time were similar between groups, the monthly incidence rates of consultations with a GP (Fig 2) were consistently higher for women than for men (73.8 consultations per patient month versus 65.1).

The monthly incidence rates of consultations with other medical specialists were similar between men and women (Fig 2), but some differences were observed concerning the specialties (Table 3). Psychiatrists represented the sixth specialist consulted by women (6.2% of all consultations versus 2.7% for men). Conversely, urologic surgeons were the third specialist most frequently seen by men (8.9% of consultations) and the tenth by women (4% of consultations). Vascular surgeons and cardiologist also were more frequently consulted by men. The median number of different specialists seen at least once during the 2 years before dialysis start (excluding GP and nephrologist) was 3 in both groups. Detailed results on other specialists are presented in S3 Table in S1 File.

Overall, inpatient care utilization was similar between men and women. In both groups, nephrology-related hospitalizations increased in the last 6 months before dialysis start (reaching 28 hospitalizations per 100 patient-month in the last month). Conversely, hospitalizations unrelated to nephrology (all other causes) remained stable in the 2 years before dialysis start (median of 3.5 hospitalizations per 100 patient-month) (Fig 3). The proportion of patients who had ≥2 hospitalizations related to dialysis preparation was higher in women than men (15.6% versus 11.2%). However, the monthly incidence rate overlapped between groups (Fig 3). The median hospital stay was the same in men and women (6 and 3 days for hospitalizations related and unrelated to nephrology, respectively). Hospitalizations for <24 hours were slightly more frequent in women (Table 2), especially in the last 7 months before dialysis start (median of 9 and 7.5 hospitalizations per 100 patient-month) (Fig 3).

Among the main reasons of nephrology-unrelated hospitalizations, circulatory system diseases and cancer were more frequent among men (29.3% vs 24% and 13.7% vs 10.4% of those hospitalizations for men and women, respectively) (Fig 4). Conversely, injury/poisoning and

<footnote>*Congestive heart failure, coronary disease, arrhythmia, aortic aneurysm, arteritis of lower limbs, stroke, or transient ischemic attack.</footnote>
<table><caption>Table 2. Healthcare utilization in the 2 years before dialysis start by sex (n = 8856 patients who started dialysis in France in 2015).</caption><thead><tr><th></th><th>Men<br>(N = 5695)</th><th>Women<br>(N = 3161)</th></tr></thead><tbody><tr><td><strong>General practitioner</strong></td><td></td><td></td></tr><tr><td>Median number of consultations [Q1, Q3]</td><td>14.0 [8, 23]</td><td>15.0 [9, 25]</td></tr><tr><td>No consultation during the last year before dialysis</td><td>421 (7.4%)</td><td>198 (6.3%)</td></tr><tr><td>≥ 1 consultation during the 4<sup>th</sup> semester before dialysis start</td><td>4783 (84.0%)</td><td>2677 (84.7%)</td></tr><tr><td>≥ 1 consultation during the 3<sup>rd</sup> semester before dialysis start</td><td>4814 (84.5%)</td><td>2713 (85.8%)</td></tr><tr><td>≥ 1 consultation during the 2<sup>nd</sup> semester before dialysis start</td><td>4884 (85.8%)</td><td>2727 (86.3%)</td></tr><tr><td>≥ 1 consultation during the 1<sup>st</sup> semester before dialysis start</td><td>5020 (88.1%)</td><td>2825 (89.4%)</td></tr><tr><td><strong>Nephrologist</strong></td><td></td><td></td></tr><tr><td>Median number of consultations [Q1, Q3]</td><td>5.00 [1, 8]</td><td>5.00 [1, 8]</td></tr><tr><td>No consultation during the last year before dialysis</td><td>1387 (24.4%)</td><td>796 (25.2%)</td></tr><tr><td>≥ 1 consultation during the 4<sup>th</sup> semester before dialysis start</td><td>2446 (43.0%)</td><td>1290 (40.8%)</td></tr><tr><td>≥ 1 consultation during the 3<sup>rd</sup> semester before dialysis start</td><td>2780 (48.8%)</td><td>1504 (47.6%)</td></tr><tr><td>≥ 1 consultation during the 2<sup>nd</sup> semester before dialysis start</td><td>3274 (57.5%)</td><td>1783 (56.4%)</td></tr><tr><td>≥ 1 consultation during the 1<sup>st</sup> semester before dialysis start</td><td>4053 (71.2%)</td><td>2228 (70.5%)</td></tr><tr><td><strong>Blood creatinine</strong></td><td></td><td></td></tr><tr><td>Median number of measurements [Q1, Q3]</td><td>24.0 [10, 36]</td><td>24.0 [10, 36]</td></tr><tr><td><strong>Hospitalizations</strong></td><td></td><td></td></tr><tr><td>Number of hospitalizations related to nephrology (≥24 h)</td><td></td><td></td></tr><tr><td>0</td><td>1920 (33.7%)</td><td>1067 (33.8%)</td></tr><tr><td>1</td><td>1136 (19.9%)</td><td>596 (18.9%)</td></tr><tr><td>≥2</td><td>2639 (46.3%)</td><td>1498 (47.4%)</td></tr><tr><td>Median duration in days [Q1, Q3]</td><td>6 [3, 10]</td><td>6 [3, 11]</td></tr><tr><td>Number of hospitalizations unrelated to nephrology (≥24 h)</td><td></td><td></td></tr><tr><td>0</td><td>3703 (65.0%)</td><td>2080 (65.8%)</td></tr><tr><td>1</td><td>949 (16.7%)</td><td>527 (16.7%)</td></tr><tr><td>≥2</td><td>1043 (18.3%)</td><td>554 (17.5%)</td></tr><tr><td>Median duration in days [Q1, Q3]</td><td>3 [1, 7]</td><td>3 [1, 8]</td></tr><tr><td>Number of hospitalizations related to dialysis preparation care</td><td></td><td></td></tr><tr><td>0</td><td>3020 (53.0%)</td><td>1654 (52.3%)</td></tr><tr><td>1</td><td>2040 (35.8%)</td><td>1015 (32.1%)</td></tr><tr><td>≥2</td><td>635 (11.2%)</td><td>492 (15.6%)</td></tr><tr><td>Median duration in days [Q1, Q3]</td><td>2 [0, 2]</td><td>2 [0, 3]</td></tr><tr><td>Number of hospitalizations &lt;24 h</td><td></td><td></td></tr><tr><td>0</td><td>1787 (31.4%)</td><td>992 (31.4%)</td></tr><tr><td>1</td><td>1558 (27.4%)</td><td>770 (24.4%)</td></tr><tr><td>≥2</td><td>2350 (41.3%)</td><td>1399 (44.3%)</td></tr></tbody></table>

https://doi.org/10.1371/journal.pone.0299601.t002

endocrine/nutritional/metabolic diseases were more frequent reasons of hospitalization among women (7.2% vs 4.4% and 7.1% vs 3.9% of hospitalizations for women and men, respectively) (Fig 4).

### 3) Sex-specific factors of emergency dialysis start

The multivariable logistic regressions performed separately for men and women (Table 4) showed that compared with the 18–44 years group, EDS risk was lower in all the other age groups (45–59, 60–74, ≥75 years groups) in men (OR = 0.71, p = 0.01; OR = 0.65, p value;
<table><caption>Table 2. Healthcare utilization in the 2 years before dialysis start by sex (n = 8856 patients who started dialysis in France in 2015).</caption><thead><tr><th></th><th>Men<br>(N = 5695)</th><th>Women<br>(N = 3161)</th></tr></thead><tbody><tr><td><strong>General practitioner</strong></td><td></td><td></td></tr><tr><td>Median number of consultations [Q1, Q3]</td><td>14.0 [8, 23]</td><td>15.0 [9, 25]</td></tr><tr><td>No consultation during the last year before dialysis</td><td>421 (7.4%)</td><td>198 (6.3%)</td></tr><tr><td>≥ 1 consultation during the 4<sup>th</sup> semester before dialysis start</td><td>4783 (84.0%)</td><td>2677 (84.7%)</td></tr><tr><td>≥ 1 consultation during the 3<sup>rd</sup> semester before dialysis start</td><td>4814 (84.5%)</td><td>2713 (85.8%)</td></tr><tr><td>≥ 1 consultation during the 2<sup>nd</sup> semester before dialysis start</td><td>4884 (85.8%)</td><td>2727 (86.3%)</td></tr><tr><td>≥ 1 consultation during the 1<sup>st</sup> semester before dialysis start</td><td>5020 (88.1%)</td><td>2825 (89.4%)</td></tr><tr><td><strong>Nephrologist</strong></td><td></td><td></td></tr><tr><td>Median number of consultations [Q1, Q3]</td><td>5.00 [1, 8]</td><td>5.00 [1, 8]</td></tr><tr><td>No consultation during the last year before dialysis</td><td>1387 (24.4%)</td><td>796 (25.2%)</td></tr><tr><td>≥ 1 consultation during the 4<sup>th</sup> semester before dialysis start</td><td>2446 (43.0%)</td><td>1290 (40.8%)</td></tr><tr><td>≥ 1 consultation during the 3<sup>rd</sup> semester before dialysis start</td><td>2780 (48.8%)</td><td>1504 (47.6%)</td></tr><tr><td>≥ 1 consultation during the 2<sup>nd</sup> semester before dialysis start</td><td>3274 (57.5%)</td><td>1783 (56.4%)</td></tr><tr><td>≥ 1 consultation during the 1<sup>st</sup> semester before dialysis start</td><td>4053 (71.2%)</td><td>2228 (70.5%)</td></tr><tr><td><strong>Blood creatinine</strong></td><td></td><td></td></tr><tr><td>Median number of measurements [Q1, Q3]</td><td>24.0 [10, 36]</td><td>24.0 [10, 36]</td></tr><tr><td><strong>Hospitalizations</strong></td><td></td><td></td></tr><tr><td>Number of hospitalizations related to nephrology (≥24 h)</td><td></td><td></td></tr><tr><td>0</td><td>1920 (33.7%)</td><td>1067 (33.8%)</td></tr><tr><td>1</td><td>1136 (19.9%)</td><td>596 (18.9%)</td></tr><tr><td>≥2</td><td>2639 (46.3%)</td><td>1498 (47.4%)</td></tr><tr><td>Median duration in days [Q1, Q3]</td><td>6 [3, 10]</td><td>6 [3, 11]</td></tr><tr><td>Number of hospitalizations unrelated to nephrology (≥24 h)</td><td></td><td></td></tr><tr><td>0</td><td>3703 (65.0%)</td><td>2080 (65.8%)</td></tr><tr><td>1</td><td>949 (16.7%)</td><td>527 (16.7%)</td></tr><tr><td>≥2</td><td>1043 (18.3%)</td><td>554 (17.5%)</td></tr><tr><td>Median duration in days [Q1, Q3]</td><td>3 [1, 7]</td><td>3 [1, 8]</td></tr><tr><td>Number of hospitalizations related to dialysis preparation care</td><td></td><td></td></tr><tr><td>0</td><td>3020 (53.0%)</td><td>1654 (52.3%)</td></tr><tr><td>1</td><td>2040 (35.8%)</td><td>1015 (32.1%)</td></tr><tr><td>≥2</td><td>635 (11.2%)</td><td>492 (15.6%)</td></tr><tr><td>Median duration in days [Q1, Q3]</td><td>2 [0, 2]</td><td>2 [0, 3]</td></tr><tr><td>Number of hospitalizations &lt;24 h</td><td></td><td></td></tr><tr><td>0</td><td>1787 (31.4%)</td><td>992 (31.4%)</td></tr><tr><td>1</td><td>1558 (27.4%)</td><td>770 (24.4%)</td></tr><tr><td>≥2</td><td>2350 (41.3%)</td><td>1399 (44.3%)</td></tr></tbody></table>

https://doi.org/10.1371/journal.pone.0299601.t002

endocrine/nutritional/metabolic diseases were more frequent reasons of hospitalization among women (7.2% vs 4.4% and 7.1% vs 3.9% of hospitalizations for women and men, respectively) (Fig 4).

### 3) Sex-specific factors of emergency dialysis start

The multivariable logistic regressions performed separately for men and women (Table 4) showed that compared with the 18–44 years group, EDS risk was lower in all the other age groups (45–59, 60–74, ≥75 years groups) in men (OR = 0.71, p = 0.01; OR = 0.65, p value;
<figure><img src="image_6.png" /><figcaption>Fig 2. Incidence rates per patient-month of non-hospital care by sex (N = 5695 men and 3161 women) in the two years before dialysis start.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g002

OR = 0.57, p<0.01, respectively), but only in the ≥75 years group in women (OR = 0.69, p = 0.04). Chronic respiratory disease was associated with a 30% increase in the risk of EDS among men (p<0.01), but not in women (p = 0.84). Needing assistance to walk and being totally dependent were risk factors of EDS in men, but not in women. Conversely, active malignancy was significantly associated with a 36% risk increase of EDS (p = 0.04) in women, but not in men (p = 0.08). Having an acute nephropathy, compared to a slowly progressive nephropathy, was associated with an increased risk of EDS in women (OR = 1.48, p<0.01), but not in men (OR = 1.15, p = 0.18).

Having seen a nephrologist at least three times in the year before dialysis start, compared with once or twice, was associated with a reduced risk of EDS in both men and women (OR = 0.58 and 0.56, p<0.01 respectively). One nephrology-related hospitalization, compared to none, was associated with a decreased risk of EDS only in men (OR = 0.81, p = 0.01). Two or more <24-hour hospitalizations also were associated with a decreased EDS risk in men, but not in women (OR = 0.75, p<0.01, OR = 0.81, p = 0.09).
<figure><img src="image_5.png" /><figcaption>Fig 2. Incidence rates per patient-month of non-hospital care by sex (N = 5695 men and 3161 women) in the two years before dialysis start.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g002

OR = 0.57, p<0.01, respectively), but only in the ≥75 years group in women (OR = 0.69, p = 0.04). Chronic respiratory disease was associated with a 30% increase in the risk of EDS among men (p<0.01), but not in women (p = 0.84). Needing assistance to walk and being totally dependent were risk factors of EDS in men, but not in women. Conversely, active malignancy was significantly associated with a 36% risk increase of EDS (p = 0.04) in women, but not in men (p = 0.08). Having an acute nephropathy, compared to a slowly progressive nephropathy, was associated with an increased risk of EDS in women (OR = 1.48, p<0.01), but not in men (OR = 1.15, p = 0.18).

Having seen a nephrologist at least three times in the year before dialysis start, compared with once or twice, was associated with a reduced risk of EDS in both men and women (OR = 0.58 and 0.56, p<0.01 respectively). One nephrology-related hospitalization, compared to none, was associated with a decreased risk of EDS only in men (OR = 0.81, p = 0.01). Two or more <24-hour hospitalizations also were associated with a decreased EDS risk in men, but not in women (OR = 0.75, p<0.01, OR = 0.81, p = 0.09).
<table><caption>Table 3. Consultations with other medical specialties in the 2 years before dialysis start (top 10 most frequent).</caption><thead><tr><th rowspan="3">Medical specialty</th><th colspan="2">Men (N = 5695)</th><th colspan="2">Women (N = 3161)</th></tr><tr><th colspan="2">Number of consultations (total = 38162)</th><th colspan="2">Number of consultations (total = 21505)</th></tr><tr><th>n</th><th>%</th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Anesthesiology</td><td>3933</td><td>10.3</td><td>2208</td><td>10.3</td></tr><tr><td>Ophthalmology</td><td>3731</td><td>9.8</td><td>2202</td><td>10.2</td></tr><tr><td>Urologic surgery</td><td>3379</td><td>8.9</td><td>1621</td><td>7.5</td></tr><tr><td>Endocrinology</td><td>3081</td><td>8.1</td><td>1480</td><td>6.9</td></tr><tr><td>Vascular surgery</td><td>2965</td><td>7.8</td><td>1382</td><td>6.4</td></tr><tr><td>Cardiology</td><td>2855</td><td>7.5</td><td>1341</td><td>6.2</td></tr><tr><td>General surgery</td><td>2028</td><td>5.3</td><td>1223</td><td>5.7</td></tr><tr><td>Internal Medicine</td><td>1846</td><td>4.8</td><td>1077</td><td>5.0</td></tr><tr><td>Dermatology</td><td>1664</td><td>4.4</td><td>878</td><td>4.1</td></tr><tr><td>Dental surgery</td><td>1468</td><td>3.8</td><td>858</td><td>4.0</td></tr></tbody></table>

The cumulative top 10 most frequent specialties represented 70.6% and 66.4% of the total consultations with other medical specialties for men and women, respectively. Reading example: 10.2% of the total consultations with other medical specialties for women were related to ophthalmology.

https://doi.org/10.1371/journal.pone.0299601.t003

Discussion

In this study, we examined and compared the care trajectories of men and women with CKD who started dialysis in France in 2015. We found that despite clinical characteristic differences at dialysis start, overall healthcare utilization in the previous 2 years was similar between sexes, including outpatient and inpatient care.

First, the temporal trends of pre-dialysis consultations with a GP were similar between sexes, although women had slightly more visits (median consultations: 15 vs 14). Women seeking GPs for reproductive related consultations could explain this slight difference [44]. It should be noted that compared with other studies, our population of patients with pre-dialysis CKD was older (median age: 71 years). This is important because a previous work in the United Kingdom found a gender gap in primary care consultation mainly in the 16 to 60-year-old population (i.e. higher consultation rate by women) that tended to disappear in >60-year-old patients [44].

Second, for nephrology-related care, no difference was observed in temporal trends and number of consultations with a nephrologist, creatinine measurements and hospitalizations for dialysis preparation. This is a positive result in the context of inequalities in access to care, especially when lower awareness of CKD among women has been reported [45]. Our study presents quantitative findings (i.e. rates over time and median number of consultations); however, it did not investigate what happens during these consultations and the resulting therapeutic strategies (i.e. the shared medical decision process). Practices of physicians might differ depending on the patient's gender [46-48]. For example, in a recent qualitative study, nephrologists recognized that they were "more inclined to suggest non-dialytic supportive management" to women deemed "too frail" [49]. Moreover, we found that about 1 in 4 patients (both sexes) did not see a nephrologist in the year before dialysis. This remains an important problem to address and for which the causes might differ between genders.

This overall absence of differences between sexes contrasts with previous studies that reported many differences at various steps of the CKD care trajectories, often unfavorable to women [7]. In the current academic context, studies reporting significant differences are more likely to be published [50]. However, this might lead to a partial view of the problem of sex/gender inequalities, as stressed by Hecking et al. in a recent review on gender and CKD care
<table><caption>Table 3. Consultations with other medical specialties in the 2 years before dialysis start (top 10 most frequent).</caption><thead><tr><th rowspan="3">Medical specialty</th><th colspan="2">Men (N = 5695)</th><th colspan="2">Women (N = 3161)</th></tr><tr><th colspan="2">Number of consultations (total = 38162)</th><th colspan="2">Number of consultations (total = 21505)</th></tr><tr><th>n</th><th>%</th><th>n</th><th>%</th></tr></thead><tbody><tr><td>Anesthesiology</td><td>3933</td><td>10.3</td><td>2208</td><td>10.3</td></tr><tr><td>Ophthalmology</td><td>3731</td><td>9.8</td><td>2202</td><td>10.2</td></tr><tr><td>Urologic surgery</td><td>3379</td><td>8.9</td><td>1621</td><td>7.5</td></tr><tr><td>Endocrinology</td><td>3081</td><td>8.1</td><td>1480</td><td>6.9</td></tr><tr><td>Vascular surgery</td><td>2965</td><td>7.8</td><td>1382</td><td>6.4</td></tr><tr><td>Cardiology</td><td>2855</td><td>7.5</td><td>1341</td><td>6.2</td></tr><tr><td>General surgery</td><td>2028</td><td>5.3</td><td>1223</td><td>5.7</td></tr><tr><td>Internal Medicine</td><td>1846</td><td>4.8</td><td>1077</td><td>5.0</td></tr><tr><td>Dermatology</td><td>1664</td><td>4.4</td><td>878</td><td>4.1</td></tr><tr><td>Dental surgery</td><td>1468</td><td>3.8</td><td>858</td><td>4.0</td></tr></tbody></table>

The cumulative top 10 most frequent specialties represented 70.6% and 66.4% of the total consultations with other medical specialties for men and women, respectively. Reading example: 10.2% of the total consultations with other medical specialties for women were related to ophthalmology.

https://doi.org/10.1371/journal.pone.0299601.t003

Discussion

In this study, we examined and compared the care trajectories of men and women with CKD who started dialysis in France in 2015. We found that despite clinical characteristic differences at dialysis start, overall healthcare utilization in the previous 2 years was similar between sexes, including outpatient and inpatient care.

First, the temporal trends of pre-dialysis consultations with a GP were similar between sexes, although women had slightly more visits (median consultations: 15 vs 14). Women seeking GPs for reproductive related consultations could explain this slight difference [44]. It should be noted that compared with other studies, our population of patients with pre-dialysis CKD was older (median age: 71 years). This is important because a previous work in the United Kingdom found a gender gap in primary care consultation mainly in the 16 to 60-year-old population (i.e. higher consultation rate by women) that tended to disappear in >60-year-old patients [44].

Second, for nephrology-related care, no difference was observed in temporal trends and number of consultations with a nephrologist, creatinine measurements and hospitalizations for dialysis preparation. This is a positive result in the context of inequalities in access to care, especially when lower awareness of CKD among women has been reported [45]. Our study presents quantitative findings (i.e. rates over time and median number of consultations); however, it did not investigate what happens during these consultations and the resulting therapeutic strategies (i.e. the shared medical decision process). Practices of physicians might differ depending on the patient's gender [46-48]. For example, in a recent qualitative study, nephrologists recognized that they were "more inclined to suggest non-dialytic supportive management" to women deemed "too frail" [49]. Moreover, we found that about 1 in 4 patients (both sexes) did not see a nephrologist in the year before dialysis. This remains an important problem to address and for which the causes might differ between genders.

This overall absence of differences between sexes contrasts with previous studies that reported many differences at various steps of the CKD care trajectories, often unfavorable to women [7]. In the current academic context, studies reporting significant differences are more likely to be published [50]. However, this might lead to a partial view of the problem of sex/gender inequalities, as stressed by Hecking et al. in a recent review on gender and CKD care
<figure><img src="image_7.png" /><figcaption>Fig 3. Incidence rates per patient-month of hospitalizations by sex (N = 5695 men and 3161 women) in the two years before dialysis start.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g003

[51]: "less attention is paid to findings in which women are better off or similar to men". Therefore, our results are important and help to better understand the issue of sex/gender and CKD care, especially pre-dialysis care that has not been much investigated yet.

Nevertheless, our study also found some differences in the pre-dialysis care trajectories, particularly the higher number of consultations with a psychiatrist among women. This is consistent with literature data showing that in patients with CKD (pre-dialysis), psychiatric diseases are more frequent in women and depression is diagnosed less often in men [15, 52]. This difference in care utilization might be explained by how men and women react and cope with CKD. Indeed, men might find more difficult to reach out or accept to be referred to mental health specialists due to social pressure and perceived expectations. They may feel that they must display "strength in silence" [49, 53, 54]. Compared with men, women with CKD have lower risks of cardiovascular events and mortality [55]. Biological sex is an important modifier
<figure><img src="image_6.png" /><figcaption>Fig 3. Incidence rates per patient-month of hospitalizations by sex (N = 5695 men and 3161 women) in the two years before dialysis start.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g003

[51]: "less attention is paid to findings in which women are better off or similar to men". Therefore, our results are important and help to better understand the issue of sex/gender and CKD care, especially pre-dialysis care that has not been much investigated yet.

Nevertheless, our study also found some differences in the pre-dialysis care trajectories, particularly the higher number of consultations with a psychiatrist among women. This is consistent with literature data showing that in patients with CKD (pre-dialysis), psychiatric diseases are more frequent in women and depression is diagnosed less often in men [15, 52]. This difference in care utilization might be explained by how men and women react and cope with CKD. Indeed, men might find more difficult to reach out or accept to be referred to mental health specialists due to social pressure and perceived expectations. They may feel that they must display "strength in silence" [49, 53, 54]. Compared with men, women with CKD have lower risks of cardiovascular events and mortality [55]. Biological sex is an important modifier
<figure><img src="image_8.png" /><figcaption>Fig 4. Main medical reasons of nephrology-unrelated hospitalizations (≥24h) in the two years before dialysis start, for men (4058 hospitalizations for n = 1992) and women (2048 hospitalizations for n = 108)*. Adjustment and management of implanted device (e.g. cardiac devices), other surgical follow-up care, examination and observation for other reasons.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g004

of the development of cardiovascular diseases. In particular, estrogen is considered as protective factor [56]. In our study, circulatory system diseases were the most frequent reason for consultation in both sexes, but were a more frequent reason of pre-dialysis hospitalization among men. This was consistent with the higher burden of cardiovascular comorbidities found in men at dialysis start, compared with women (i.e. higher number of cardiovascular diseases and frequency of hypertensive and vascular nephropathy). Nevertheless, the proportion of women and men who started dialysis in emergency (i.e. <24 hours after a nephrologist assessment due to life threatening reasons) was the same (30%). This could be explained by a greater capacity by women to tolerate and cope with CKD consequences, leading to delayed dialysis start compared with men for whom dialysis start might be anticipated due to their greater comorbidity burden. The analysis adjusted for patients' characteristics at dialysis start and pre-dialysis care confirmed that in both groups, lack of nephrological care was an important risk factor of EDS. Among the clinical factors associated with EDS, having an acute nephropathy (e.g. toxic nephropathy, myeloma, extracapillary glomerulonephritis), compared with a slowly progressive nephropathy, significantly increased the risk of EDS in women (+48%, p <0.01), but not in men. The causal relationship with EDS is unclear, but this suggests that in women, acute nephropathies might be more difficult to manage or worsen more rapidly. This should be taken into account by nephrologists and care teams.

## Strengths

This study has several strengths. The first is the exhaustiveness of the population included (i.e. all patients in France who started dialysis) and the quality of the baseline data extracted from the REIN registry [37], a long-established nationwide registry developed and supported by a network of nephrologists and clinical research assistants [38]. Second, the use of the French
<figure><img src="image_7.png" /><figcaption>**Fig 4.** Main medical reasons of nephrology-unrelated hospitalizations (≥24h) in the two years before dialysis start, for men (4058 hospitalizations for n = 1992) and women (2048 hospitalizations for n = 108)*. Adjustment and management of implanted device (e.g. cardiac devices), other surgical follow-up care, examination and observation for other reasons.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0299601.g004

of the development of cardiovascular diseases. In particular, estrogen is considered as protective factor [56]. In our study, circulatory system diseases were the most frequent reason for consultation in both sexes, but were a more frequent reason of pre-dialysis hospitalization among men. This was consistent with the higher burden of cardiovascular comorbidities found in men at dialysis start, compared with women (i.e. higher number of cardiovascular diseases and frequency of hypertensive and vascular nephropathy). Nevertheless, the proportion of women and men who started dialysis in emergency (i.e. <24 hours after a nephrologist assessment due to life threatening reasons) was the same (30%). This could be explained by a greater capacity by women to tolerate and cope with CKD consequences, leading to delayed dialysis start compared with men for whom dialysis start might be anticipated due to their greater comorbidity burden. The analysis adjusted for patients' characteristics at dialysis start and pre-dialysis care confirmed that in both groups, lack of nephrological care was an important risk factor of EDS. Among the clinical factors associated with EDS, having an acute nephropathy (e.g. toxic nephropathy, myeloma, extracapillary glomerulonephritis), compared with a slowly progressive nephropathy, significantly increased the risk of EDS in women (+48%, p <0.01), but not in men. The causal relationship with EDS is unclear, but this suggests that in women, acute nephropathies might be more difficult to manage or worsen more rapidly. This should be taken into account by nephrologists and care teams.

## Strengths

This study has several strengths. The first is the exhaustiveness of the population included (i.e. all patients in France who started dialysis) and the quality of the baseline data extracted from the REIN registry [37], a long-established nationwide registry developed and supported by a network of nephrologists and clinical research assistants [38]. Second, the use of the French
<table><caption>Table 4. Factors associated with EDS in men (N = 5695) and women (N = 3161), multivariable logistic regression.</caption><thead><tr><th rowspan="2">Variable</th><th colspan="2">Men</th><th colspan="2">Women</th></tr><tr><th>Odds Ratio [95% Confidence Interval]</th><th>Odds Ratio [95% Confidence Interval]</th><th>Odds Ratio [95% Confidence Interval]</th><th>Odds Ratio [95% Confidence Interval]</th></tr></thead><tbody><tr><td><strong>Age (vs 18–44 years)</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>45–59 years</td><td>0.71 [0.54, 0.93]</td><td>0.79 [0.55, 1.13]</td><td></td><td></td></tr><tr><td>60–74 years</td><td>0.65 [0.50, 0.84]</td><td>0.71 [0.50, 0.99]</td><td></td><td></td></tr><tr><td>≥ 75 years</td><td>0.57 [0.44, 0.74]</td><td>0.69 [0.49, 0.98]</td><td></td><td></td></tr><tr><td><strong>Nephropathy (vs slowly progressive)</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Acute</td><td>1.15 [0.94, 1.41]</td><td>1.48 [1.14, 1.92]</td><td></td><td></td></tr><tr><td>Uncertain/variable progression</td><td>1.18 [1.01, 1.38]</td><td>1.29 [1.04, 1.59]</td><td></td><td></td></tr><tr><td><strong>Body mass index (kg/m²) (vs 23–25 kg/m²)</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt; 18.5</td><td>1.07 [0.71, 1.63]</td><td>1.11 [0.68, 1.79]</td><td></td><td></td></tr><tr><td>[18.5–23]</td><td>1.29 [1.02, 1.61]</td><td>0.99 [0.69, 1.41]</td><td></td><td></td></tr><tr><td>[25–30]</td><td>0.97 [0.80, 1.18]</td><td>0.96 [0.69, 1.35]</td><td></td><td></td></tr><tr><td>≥ 30</td><td>1.03 [0.82, 1.29]</td><td>0.90 [0.62, 1.30]</td><td></td><td></td></tr><tr><td><strong>Serum albumin &lt; 30g/L (vs ≥30 g/L)</strong></td><td>1.52 [1.26, 1.83]</td><td>1.37 [1.10, 1.71]</td><td></td><td></td></tr><tr><td><strong>Hemoglobin (vs 10–12 g/dL)</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>&lt; 10 g/dL</td><td>1.51 [1.31, 1.75]</td><td>1.59 [1.30, 1.95]</td><td></td><td></td></tr><tr><td>≥ 12 g/dL</td><td>0.86 [0.69, 1.07]</td><td>0.90 [0.64, 1.27]</td><td></td><td></td></tr><tr><td><strong>Cardiovascular diseases* (vs none)</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>1</td><td>1.18 [0.99, 1.40]</td><td>1.31 [1.06, 1.63]</td><td></td><td></td></tr><tr><td>2</td><td>1.53 [1.27, 1.85]</td><td>1.42 [1.09, 1.86]</td><td></td><td></td></tr><tr><td>≥ 3</td><td>1.81 [1.49, 2.20]</td><td>1.99 [1.46, 2.72]</td><td></td><td></td></tr><tr><td><strong>Diabetes</strong></td><td>1.20 [1.05, 1.38]</td><td>1.26 [1.03, 1.53]</td><td></td><td></td></tr><tr><td><strong>Chronic respiratory disease</strong></td><td>1.30 [1.10, 1.55]</td><td>1.03 [0.78, 1.36]</td><td></td><td></td></tr><tr><td><strong>Active malignancy</strong></td><td>1.20 [0.98, 1.46]</td><td>1.36 [1.01, 1.82]</td><td></td><td></td></tr><tr><td><strong>Mobility (vs walk without help)</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Need assistance</td><td>1.45 [1.19, 1.76]</td><td>1.20 [0.92, 1.55]</td><td></td><td></td></tr><tr><td>Totally dependent</td><td>1.65 [1.23, 2.23]</td><td>1.49 [0.99, 2.23]</td><td></td><td></td></tr><tr><td><strong>Consultation with a GP (vs 1–7)**</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>1.09 [0.86, 1.38]</td><td>0.81 [0.57, 1.16]</td><td></td><td></td></tr><tr><td>&gt; 8</td><td>1.03 [0.90, 1.18]</td><td>0.95 [0.79, 1.14]</td><td></td><td></td></tr><tr><td><strong>Consultations with a nephrologist (vs 1–2)**</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>0</td><td>1.47 [1.23, 1.75]</td><td>1.71 [1.35, 2.17]</td><td></td><td></td></tr><tr><td>≥ 3</td><td>0.58 [0.50, 0.68]</td><td>0.56 [0.45, 0.70]</td><td></td><td></td></tr><tr><td><strong>Nephrology-related hospitalizations (vs 0)**</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>1</td><td>0.81 [0.68, 0.96]</td><td>0.88 [0.69, 1.12]</td><td></td><td></td></tr><tr><td>≥ 2</td><td>0.94 [0.81, 1.09]</td><td>0.93 [0.76, 1.14]</td><td></td><td></td></tr><tr><td><strong>Nephrology-unrelated hospitalizations (all other causes) (vs 0)**</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>1</td><td>1.03 [0.86, 1.25]</td><td>1.26 [0.99, 1.61]</td><td></td><td></td></tr><tr><td>≥ 2</td><td>1.04 [0.84, 1.29]</td><td>1.25 [0.94, 1.66]</td><td></td><td></td></tr><tr><td><strong>Preparation to dialysis-related hospitalizations (vs 0)**</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>1</td><td>0.40 [0.34, 0.47]</td><td>0.44 [0.36, 0.55]</td><td></td><td></td></tr><tr><td>≥ 2</td><td>0.36 [0.28, 0.46]</td><td>0.49 [0.37, 0.67]</td><td></td><td></td></tr><tr><td><strong>&lt;24 hours hospitalizations (vs 0)**</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>1</td><td>0.93 [0.79, 1.09]</td><td>1.04 [0.83, 1.31]</td><td></td><td></td></tr></tbody></table>

(Continued)
<table><caption>Table 4. Factors associated with EDS in men (N = 5695) and women (N = 3161), multivariable logistic regression.</caption><thead><tr><th rowspan="2">Variable</th><th>Men</th><th>Women</th></tr><tr><th>Odds Ratio [95% Confidence Interval]</th><th>Odds Ratio [95% Confidence Interval]</th></tr></thead><tbody><tr><td><strong>Age (vs 18–44 years)</strong></td><td></td><td></td></tr><tr><td>45–59 years</td><td>0.71 [0.54, 0.93]</td><td>0.79 [0.55, 1.13]</td></tr><tr><td>60–74 years</td><td>0.65 [0.50, 0.84]</td><td>0.71 [0.50, 0.99]</td></tr><tr><td>≥ 75 years</td><td>0.57 [0.44, 0.74]</td><td>0.69 [0.49, 0.98]</td></tr><tr><td><strong>Nephropathy (vs slowly progressive)</strong></td><td></td><td></td></tr><tr><td>Acute</td><td>1.15 [0.94, 1.41]</td><td>1.48 [1.14, 1.92]</td></tr><tr><td>Uncertain/variable progression</td><td>1.18 [1.01, 1.38]</td><td>1.29 [1.04, 1.59]</td></tr><tr><td><strong>Body mass index (kg/m²) (vs 23–25 kg/m²)</strong></td><td></td><td></td></tr><tr><td>&lt; 18.5</td><td>1.07 [0.71, 1.63]</td><td>1.11 [0.68, 1.79]</td></tr><tr><td>[18.5–23]</td><td>1.29 [1.02, 1.61]</td><td>0.99 [0.69, 1.41]</td></tr><tr><td>[25–30]</td><td>0.97 [0.80, 1.18]</td><td>0.96 [0.69, 1.35]</td></tr><tr><td>≥ 30</td><td>1.03 [0.82, 1.29]</td><td>0.90 [0.62, 1.30]</td></tr><tr><td><strong>Serum albumin &lt; 30g/L (vs ≥30 g/L)</strong></td><td>1.52 [1.26, 1.83]</td><td>1.37 [1.10, 1.71]</td></tr><tr><td><strong>Hemoglobin (vs 10–12 g/dL)</strong></td><td></td><td></td></tr><tr><td>&lt; 10 g/dL</td><td>1.51 [1.31, 1.75]</td><td>1.59 [1.30, 1.95]</td></tr><tr><td>≥ 12 g/dL</td><td>0.86 [0.69, 1.07]</td><td>0.90 [0.64, 1.27]</td></tr><tr><td><strong>Cardiovascular diseases* (vs none)</strong></td><td></td><td></td></tr><tr><td>1</td><td>1.18 [0.99, 1.40]</td><td>1.31 [1.06, 1.63]</td></tr><tr><td>2</td><td>1.53 [1.27, 1.85]</td><td>1.42 [1.09, 1.86]</td></tr><tr><td>≥ 3</td><td>1.81 [1.49, 2.20]</td><td>1.99 [1.46, 2.72]</td></tr><tr><td><strong>Diabetes</strong></td><td>1.20 [1.05, 1.38]</td><td>1.26 [1.03, 1.53]</td></tr><tr><td><strong>Chronic respiratory disease</strong></td><td>1.30 [1.10, 1.55]</td><td>1.03 [0.78, 1.36]</td></tr><tr><td><strong>Active malignancy</strong></td><td>1.20 [0.98, 1.46]</td><td>1.36 [1.01, 1.82]</td></tr><tr><td><strong>Mobility (vs walk without help)</strong></td><td></td><td></td></tr><tr><td>Need assistance</td><td>1.45 [1.19, 1.76]</td><td>1.20 [0.92, 1.55]</td></tr><tr><td>Totally dependent</td><td>1.65 [1.23, 2.23]</td><td>1.49 [0.99, 2.23]</td></tr><tr><td><strong>Consultation with a GP (vs 1–7)**</strong></td><td></td><td></td></tr><tr><td>0</td><td>1.09 [0.86, 1.38]</td><td>0.81 [0.57, 1.16]</td></tr><tr><td>&gt; 8</td><td>1.03 [0.90, 1.18]</td><td>0.95 [0.79, 1.14]</td></tr><tr><td><strong>Consultations with a nephrologist (vs 1–2)**</strong></td><td></td><td></td></tr><tr><td>0</td><td>1.47 [1.23, 1.75]</td><td>1.71 [1.35, 2.17]</td></tr><tr><td>≥ 3</td><td>0.58 [0.50, 0.68]</td><td>0.56 [0.45, 0.70]</td></tr><tr><td><strong>Nephrology-related hospitalizations (vs 0)**</strong></td><td></td><td></td></tr><tr><td>1</td><td>0.81 [0.68, 0.96]</td><td>0.88 [0.69, 1.12]</td></tr><tr><td>≥ 2</td><td>0.94 [0.81, 1.09]</td><td>0.93 [0.76, 1.14]</td></tr><tr><td><strong>Nephrology-unrelated hospitalizations (all other causes) (vs 0)**</strong></td><td></td><td></td></tr><tr><td>1</td><td>1.03 [0.86, 1.25]</td><td>1.26 [0.99, 1.61]</td></tr><tr><td>≥ 2</td><td>1.04 [0.84, 1.29]</td><td>1.25 [0.94, 1.66]</td></tr><tr><td><strong>Preparation to dialysis-related hospitalizations (vs 0)**</strong></td><td></td><td></td></tr><tr><td>1</td><td>0.40 [0.34, 0.47]</td><td>0.44 [0.36, 0.55]</td></tr><tr><td>≥ 2</td><td>0.36 [0.28, 0.46]</td><td>0.49 [0.37, 0.67]</td></tr><tr><td><strong>&lt;24 hours hospitalizations (vs 0)**</strong></td><td></td><td></td></tr><tr><td>1</td><td>0.93 [0.79, 1.09]</td><td>1.04 [0.83, 1.31]</td></tr></tbody></table>

(Continued)
<table><caption>**Table 4.** (Continued)</caption><thead><tr><th rowspan="2">Variable</th><th>Men</th><th>Women</th></tr><tr><th>Odds Ratio<br/>[95% Confidence<br/>Interval]</th><th>Odds Ratio<br/>[95% Confidence<br/>Interval]</th></tr></thead><tbody><tr><td>≥ 2</td><td>0.75 [0.62, 0.90]</td><td>0.81 [0.64, 1.04]</td></tr></tbody></table>

*congestive heart failure, coronary disease, arrhythmia, aortic aneurysm, arteritis of lower limbs, stroke, or transient ischemic attack

https://doi.org/10.1371/journal.pone.0299601.t004

National Health Data System allowed assessing the care trajectories, both non-hospital (e.g. consultations, laboratory tests, and drug deliveries) and hospital care, regardless of the providers' type (public or private sector) and the patients' insurance coverage type.

## Limits

The first and main limitation of this study is that the population studied only included the subset of patients with CKD who initiated dialysis. Sex and gender-based differences in the epidemiology and the care trajectories might exist among those who do not reach or choose renal replacement therapy. For example, evidence suggests that elderly women are more inclined to choose (or been offered) conservative care instead of renal replacement therapy, compared with men [7, 57]. In addition to prospective cohort studies, population-based studies that use healthcare claims databases might provide new insights on sex and gender differences in care trajectories. Indeed, identifying patients with CKD (any stage) through their healthcare utilization would allow including and studying patients unknown to the nephrology services and patients receiving conservative care [58]. Second, we could not assess some socio-economic factors, such as education, marital status and income, that might more strongly affect women than men [49, 59]. Third, as this study took place in France where universal healthcare coverage is offered, the results related to healthcare utilization might not be generalizable to other settings. Finally, although the data used date from 2015, we argue that is still of relevance today. Indeed, the CKD care management guidelines in France were last updated in 2021, with the notable introduction of nurses practitioners. The last previous update dates back from 2012. Although some improvements in CKD care management is reported by the REIN registry [60], some trends in the care of new dialysis patients have remained since 2015. We therefore argue that is unlikely that the main results of this study would be significantly different with more contemporary data.

## Conclusion

This study provides a quantitative description of the pre-dialysis care trajectories of women and men with CKD who started dialysis in France in 2015. Overall, healthcare utilization (GP and nephrological care) was comparable between sexes in the two years before dialysis initiation, despite differences in their clinical profiles at dialysis start. However, sex-specific differences were found for other healthcare areas, particularly higher frequencies of consultations with a psychiatrist among women and more frequent hospitalizations for circulatory system diseases among men. More quantitative and qualitative research is needed to comprehensively understand sex and gender differences in CKD care trajectories, specifically on patients with CKD unknown to nephrology services, on patients receiving conservative care, and on the decision-making processes.
<table><caption>**Table 4.** (Continued)</caption><thead><tr><th rowspan="2">Variable</th><th>Men</th><th>Women</th></tr><tr><th>Odds Ratio<br>[95% Confidence<br>Interval]</th><th>Odds Ratio<br>[95% Confidence<br>Interval]</th></tr></thead><tbody><tr><td>≥ 2</td><td>0.75 [0.62, 0.90]</td><td>0.81 [0.64, 1.04]</td></tr></tbody></table>

*congestive heart failure, coronary disease, arrhythmia, aortic aneurysm, arteritis of lower limbs, stroke, or transient ischemic attack

https://doi.org/10.1371/journal.pone.0299601.t004

National Health Data System allowed assessing the care trajectories, both non-hospital (e.g. consultations, laboratory tests, and drug deliveries) and hospital care, regardless of the providers' type (public or private sector) and the patients' insurance coverage type.

## Limits

The first and main limitation of this study is that the population studied only included the subset of patients with CKD who initiated dialysis. Sex and gender-based differences in the epidemiology and the care trajectories might exist among those who do not reach or choose renal replacement therapy. For example, evidence suggests that elderly women are more inclined to choose (or been offered) conservative care instead of renal replacement therapy, compared with men [7, 57]. In addition to prospective cohort studies, population-based studies that use healthcare claims databases might provide new insights on sex and gender differences in care trajectories. Indeed, identifying patients with CKD (any stage) through their healthcare utilization would allow including and studying patients unknown to the nephrology services and patients receiving conservative care [58]. Second, we could not assess some socio-economic factors, such as education, marital status and income, that might more strongly affect women than men [49, 59]. Third, as this study took place in France where universal healthcare coverage is offered, the results related to healthcare utilization might not be generalizable to other settings. Finally, although the data used date from 2015, we argue that is still of relevance today. Indeed, the CKD care management guidelines in France were last updated in 2021, with the notable introduction of nurses practitioners. The last previous update dates back from 2012. Although some improvements in CKD care management is reported by the REIN registry [60], some trends in the care of new dialysis patients have remained since 2015. We therefore argue that is unlikely that the main results of this study would be significantly different with more contemporary data.

## Conclusion

This study provides a quantitative description of the pre-dialysis care trajectories of women and men with CKD who started dialysis in France in 2015. Overall, healthcare utilization (GP and nephrological care) was comparable between sexes in the two years before dialysis initiation, despite differences in their clinical profiles at dialysis start. However, sex-specific differences were found for other healthcare areas, particularly higher frequencies of consultations with a psychiatrist among women and more frequent hospitalizations for circulatory system diseases among men. More quantitative and qualitative research is needed to comprehensively understand sex and gender differences in CKD care trajectories, specifically on patients with CKD unknown to nephrology services, on patients receiving conservative care, and on the decision-making processes.
**Supporting information**

S1 File.

(PDF)

**Acknowledgments**

The authors thank all REIN registry participants, especially nephrologists and data managers in charge of data collection and quality control: Nadia Honoré, Sabrina Boime, Emilie Gardeur-Algros, Observatoire régional de la santé du Grand Est Dr François Chantrel, Centre hospitalier, Mulhouse Xabina Larre, Dr Karen Leffondré, ISPED Bordeaux Dr Mathilde Reydit, AURAD; Eric Cellarier, Patricia Girault, CHU Clermont-Ferrand Aurélien Tiple, CHU Clermont-Ferrand; Aurélie Caillet, Dr Damiano Ceruasuolo, CHU Caen Dr Clémence Béchade, CHU Caen; Sophie Roche, Dr Anaïs Tendron-Franzin, CHU Dijon Dr Abdelkader Bemrah, Centre hospitalier Châlon/Saône; Muriel Siebert, CHU Rennes, Dr Sahar Bayat, EHESP, Rennes Pr Cécile Vigneau CHU Rennes; Marine Naudin, Dr Jean-Michel Halimi, CHU Tours Dr Bénédicte Sautenet, CHU Tours; Anne-Lise Varnier, Gwendoline Arnoult, Aurore Wolak, CHU Reims Dr Isabelle Kazès, CHU Reims; Ghizlane Izaaryene, Franck Mazoué, Adeline Crémades, Dr Stéphanie Gentile, CHU Marseille Dr Philippe Brunet, APHM Marseille; Caroline Savet, Dr Elisabeth Monnet, CHU Besançon Dr Cécile Courivaud, CHU Besançon; Cécilia Citadelle-Jannetta, Dr Jacqueline Deloumeaux, CHU Point-à-Pitre Dr Valérie Galantine, Clinique de Choisy, Gosier; Devi Rochemont, Mamadou Khali Sow, Pr Mathieu Nacher, Centre hospitalier Cayenne; Blandine Wurtz, Dr Hélène Marini, CHU Rouen Dr Stéphane Edet, CHU Rouen; Evelyne Ducamp, Zoubair Cherquaoui, Hayet Baouche, Houssem Eddine Teb-bakh, Pr Jean-Philippe Jais, LBIM, Necker, APHM Dr Lucile Mercadal, Hôpital de la Pitié Salpétrière, Paris; Mohamed Belkacemi, Yohan Duny, Mélanie Martin, Dr Jean-Pierre Daurès, Université Montpellier Pr Olivier Moranne, CHU Carémeau, Nîmes; Florence Glaudet, Pr Alain Vergnenègre, CHU Limoges Dr Fatouma Touré, CHU Limoges; Marie-Rita Monzel, Véronique Vogel, Marie-Line Erpelding, Philippe Melchior, Amandine Ziegler, CIC 1433 Épیدемиologie Clinique, CHRU Nancy Dr Emmanuelle Laurain, CHRU Nancy; Aurélie Bideau, Natacha Neller, Dr Sylvie Merle, Observatoire régional de la Santé, Fort de France Dr Alex Ranlin, ATIR; Violaine Schmitt, Catherine Marimoutou, CHU de la Réunion Pr Henri Vacher Coponat, CHU de la Réunion; Sophie Lapalu, Ludivine Brun, Dr Benoît Lepage, CHU Toulouse Dr Nathalie Longlune, CHU Rangueil Toulouse; Sébastien Gomis, Carole Foulon, Dr Marc Hazzan, CHU Lille Dr François Glowacki, CHU Lille; Noemie Baroux, RESIR—Réseau de l'insuffisance rénale en Nouvelle-Calédonie, Nouméa Dr Jean-Michel Tivollier, Nouméa; Ghizlane Izaaryene, Franck Mazoué, Adeline Crémades, Pr Stéphanie Gentile, CHU Marseille Pr Philippe Brunet, CHU Marseille; Assia Hami, Jean Xavier Lemauft, Jean-Michel Nguyen, CHU Nantes Pr Maryvonne Hourmant, CHU Nantes; Dr Etienne Bérard, CHU Nice; Amélie Joly, CHU Amiens Dr Ayman Sarraj, Polyclinique Saint Côme, Compiegne; Fabien Duthe, Bénédicte Ayrault, CHU Poitiers Dr Marc Bauwens, CHU Poitiers; Marie Hélène Pierron, Papeete Dr Pascale Testevuide, Papeete; Violaine Schmitt, Catherine Marimoutou, CHU de la Réunion Pr Henri Vacher Coponat, CHU de la Réunion, site Sud; Sylvie Boyer, Agnès Mérono, Marie-Noëlle Guillermin, Hospices Civils de Lyon Dr Roula Galland, Calydial, Irigny; Assia Hami, Jean Xavier Lemauft, Jean-Michel Nguyen, CHU Nantes Dr François Babinet, Echo Le Mans; The REIN registry national coordination can be reached at cecile.couchoud@biomedecine.fr. The dialysis centers participating in the registry are fully listed in the REIN annual report (https://www.agence-biomedecine.fr/Le-programme-REIN). The authors thank Elisabetta Andermarcher for reviewing the English language.
**Supporting information**

S1 File.

(PDF)

**Acknowledgments**

The authors thank all REIN registry participants, especially nephrologists and data managers in charge of data collection and quality control: Nadia Honoré, Sabrina Boime, Emilie Gardeur-Algros, Observatoire régional de la santé du Grand Est Dr François Chantrel, Centre hospitalier, Mulhouse Xabina Larre, Dr Karen Leffondré, ISPED Bordeaux Dr Mathilde Reydit, AURAD; Eric Cellarier, Patricia Girault, CHU Clermont-Ferrand Aurélien Tiple, CHU Clermont-Ferrand; Aurélie Caillet, Dr Damiano Ceruasuolo, CHU Caen Dr Clémence Béchade, CHU Caen; Sophie Roche, Dr Anaïs Tendron-Franzin, CHU Dijon Dr Abdelkader Bemrah, Centre hospitalier Châlon/Saône; Muriel Siebert, CHU Rennes, Dr Sahar Bayat, EHESP, Rennes Pr Cécile Vigneau CHU Rennes; Marine Naudin, Dr Jean-Michel Halimi, CHU Tours Dr Bénédicte Sautenet, CHU Tours; Anne-Lise Varnier, Gwendoline Arnoult, Aurore Wolak, CHU Reims Dr Isabelle Kazès, CHU Reims; Ghizlane Izaaryene, Franck Mazoué, Adeline Crémades, Dr Stéphanie Gentile, CHU Marseille Dr Philippe Brunet, APHM Marseille; Caroline Savet, Dr Elisabeth Monnet, CHU Besançon Dr Cécile Courivaud, CHU Besançon; Cécilia Citadelle-Jannetta, Dr Jacqueline Deloumeaux, CHU Point-à-Pitre Dr Valérie Galantine, Clinique de Choisy, Gosier; Devi Rochemont, Mamadou Khali Sow, Pr Mathieu Nacher, Centre hospitalier Cayenne; Blandine Wurtz, Dr Hélène Marini, CHU Rouen Dr Stéphane Edet, CHU Rouen; Evelyne Ducamp, Zoubair Cherquaoui, Hayet Baouche, Houssem Eddine Teb-bakh, Pr Jean-Philippe Jais, LBIM, Necker, APHM Dr Lucile Mercadal, Hôpital de la Pitié Salpétrière, Paris; Mohamed Belkacemi, Yohan Duny, Mélanie Martin, Dr Jean-Pierre Daurès, Université Montpellier Pr Olivier Moranne, CHU Carémeau, Nîmes; Florence Glaudet, Pr Alain Vergnenègre, CHU Limoges Dr Fatouma Touré, CHU Limoges; Marie-Rita Monzel, Véronique Vogel, Marie-Line Erpelding, Philippe Melchior, Amandine Ziegler, CIC 1433 Épیدемиologie Clinique, CHRU Nancy Dr Emmanuelle Laurain, CHRU Nancy; Aurélie Bideau, Natacha Neller, Dr Sylvie Merle, Observatoire régional de la Santé, Fort de France Dr Alex Ranlin, ATIR; Violaine Schmitt, Catherine Marimoutou, CHU de la Réunion Pr Henri Vacher Coponat, CHU de la Réunion; Sophie Lapalu, Ludivine Brun, Dr Benoît Lepage, CHU Toulouse Dr Nathalie Longlune, CHU Rangueil Toulouse; Sébastien Gomis, Carole Foulon, Dr Marc Hazzan, CHU Lille Dr François Glowacki, CHU Lille; Noemie Baroux, RESIR—Réseau de l'insuffisance rénale en Nouvelle-Calédonie, Nouméa Dr Jean-Michel Tivollier, Nouméa; Ghizlane Izaaryene, Franck Mazoué, Adeline Crémades, Pr Stéphanie Gentile, CHU Marseille Pr Philippe Brunet, CHU Marseille; Assia Hami, Jean Xavier Lemauft, Jean-Michel Nguyen, CHU Nantes Pr Maryvonne Hourmant, CHU Nantes; Dr Etienne Bérard, CHU Nice; Amélie Joly, CHU Amiens Dr Ayman Sarraj, Polyclinique Saint Côme, Compiegne; Fabien Duthe, Bénédicte Ayrault, CHU Poitiers Dr Marc Bauwens, CHU Poitiers; Marie Hélène Pierron, Papeete Dr Pascale Testevuide, Papeete; Violaine Schmitt, Catherine Marimoutou, CHU de la Réunion Pr Henri Vacher Coponat, CHU de la Réunion, site Sud; Sylvie Boyer, Agnès Mérono, Marie-Noëlle Guillermin, Hospices Civils de Lyon Dr Roula Galland, Calydial, Irigny; Assia Hami, Jean Xavier Lemauft, Jean-Michel Nguyen, CHU Nantes Dr François Babinet, Echo Le Mans; The REIN registry national coordination can be reached at cecile.couchoud@biomedecine.fr. The dialysis centers participating in the registry are fully listed in the REIN annual report (https://www.agence-biomedecine.fr/Le-programme-REIN). The authors thank Elisabetta Andermarcher for reviewing the English language.
## Author Contributions

**Conceptualization:** Maxime Raffray, Cécile Vigneau, Sahar Bayat.

**Data curation:** Cécile Couchoud.

**Formal analysis:** Maxime Raffray, Louise Bourasseau.

**Funding acquisition:** Sahar Bayat.

**Investigation:** Maxime Raffray, Louise Bourasseau.

**Methodology:** Maxime Raffray, Cécile Vigneau, Cécile Couchoud, Sahar Bayat.

**Project administration:** Sahar Bayat.

**Supervision:** Cécile Vigneau, Sahar Bayat.

**Validation:** Cécile Vigneau, Cécile Couchoud, Clémence Béchade, François Glowacki, Sahar Bayat.

**Visualization:** Maxime Raffray.

**Writing – original draft:** Maxime Raffray, Louise Bourasseau.

**Writing – review & editing:** Cécile Vigneau, Cécile Couchoud, Clémence Béchade, François Glowacki, Sahar Bayat.

## References

1. Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero JJ, DeMeo DL, et al. Sex and gender: modifiers of health, disease, and medicine. The Lancet. 2020 Aug; 396(10250):565–82. https://doi.org/10.1016/S0140-6736(20)31561-0 PMID: 32828189

2. Cordonnier C, Sprigg N, Sandset EC, Pavlovic A, Sunnerhagen KS, Caso V, et al. Stroke in women— from evidence to inequalities. Nat Rev Neurol. 2017 Sep; 13(9):521–32. https://doi.org/10.1038/nrneurol.2017.95 PMID: 28731036

3. Bertakis KD, Azari R, Helms LJ, Callahan EJ, Robbins JA. Gender Differences in the Utilization of Health Care Services. J Fam Pract. 2000 Feb 1; 49(2):147–147. PMID: 10718692

4. Ladwig KH, Marten-Mittag B, Formanek B, Dammann G. Gender differences of symptom reporting and medical health care utilization in the German population. Eur J Epidemiol. 2000 Jun 1; 16(6):511–8. https://doi.org/10.1023/a:1007629920752 PMID: 11049093

5. Vaidya V, Partha G, Karmakar M. Gender Differences in Utilization of Preventive Care Services in the United States. J Womens Health. 2012 Feb; 21(2):140–5. https://doi.org/10.1089/jwh.2011.2876 PMID: 22081983

6. Moore TJ, Mattison DR. Adult Utilization of Psychiatric Drugs and Differences by Sex, Age, and Race. JAMA Intern Med. 2017 Feb 1; 177(2):274–5. https://doi.org/10.1001/jamainternmed.2016.7507 PMID: 27942726

7. Carrero JJ, Hecking M, Chesnaye NC, Jager KJ. Sex and gender disparities in the epidemiology and outcomes of chronic kidney disease. Nat Rev Nephrol. 2018 Mar; 14(3):151–64. https://doi.org/10.1038/nrneph.2017.181 PMID: 29355169

8. Swartling O, Yang Y, Clase CM, Fu EL, Hecking M, Hödlmoser S, et al. Sex Differences in the Recognition, Monitoring, and Management of CKD in Health Care: An Observational Cohort Study. J Am Soc Nephrol. 2022 Oct 1; 33(10):1903–14. https://doi.org/10.1681/ASN.2022030373 PMID: 35906075

9. Bikbov B, Perico N, Remuzzi G, on behalf of the GBD Genitourinary Diseases Expert Group. Disparities in Chronic Kidney Disease Prevalence among Males and Females in 195 Countries: Analysis of the Global Burden of Disease 2016 Study. Nephron. 2018; 139(4):313–8.

10. Cirillo M, Laurenzi M, Mancini M, Zanchetti A, Lombardi C, De Santo NG. Low glomerular filtration in the population: prevalence, associated disorders, and awareness. Kidney Int. 2006 Aug; 70(4):800–6. https://doi.org/10.1038/sj.ki.5001641 PMID: 16820784

11. Zdrojewski Ł, Zdrojewski T, Rutkowski M, Bandosz P, Król E, Wyrzykowski B, et al. Prevalence of chronic kidney disease in a representative sample of the Polish population: results of the NATPOL 2011
## Author Contributions

**Conceptualization:** Maxime Raffray, Cécile Vigneau, Sahar Bayat.

**Data curation:** Cécile Couchoud.

**Formal analysis:** Maxime Raffray, Louise Bourasseau.

**Funding acquisition:** Sahar Bayat.

**Investigation:** Maxime Raffray, Louise Bourasseau.

**Methodology:** Maxime Raffray, Cécile Vigneau, Cécile Couchoud, Sahar Bayat.

**Project administration:** Sahar Bayat.

**Supervision:** Cécile Vigneau, Sahar Bayat.

**Validation:** Cécile Vigneau, Cécile Couchoud, Clémence Béchade, François Glowacki, Sahar Bayat.

**Visualization:** Maxime Raffray.

**Writing – original draft:** Maxime Raffray, Louise Bourasseau.

**Writing – review & editing:** Cécile Vigneau, Cécile Couchoud, Clémence Béchade, François Glowacki, Sahar Bayat.

## References

1. Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero JJ, DeMeo DL, et al. Sex and gender: modifiers of health, disease, and medicine. The Lancet. 2020 Aug; 396(10250):565–82. https://doi.org/10.1016/S0140-6736(20)31561-0 PMID: 32828189

2. Cordonnier C, Sprigg N, Sandset EC, Pavlovic A, Sunnerhagen KS, Caso V, et al. Stroke in women— from evidence to inequalities. Nat Rev Neurol. 2017 Sep; 13(9):521–32. https://doi.org/10.1038/nrneurol.2017.95 PMID: 28731036

3. Bertakis KD, Azari R, Helms LJ, Callahan EJ, Robbins JA. Gender Differences in the Utilization of Health Care Services. J Fam Pract. 2000 Feb 1; 49(2):147–147. PMID: 10718692

4. Ladwig KH, Marten-Mittag B, Formanek B, Dammann G. Gender differences of symptom reporting and medical health care utilization in the German population. Eur J Epidemiol. 2000 Jun 1; 16(6):511–8. https://doi.org/10.1023/a:1007629920752 PMID: 11049093

5. Vaidya V, Partha G, Karmakar M. Gender Differences in Utilization of Preventive Care Services in the United States. J Womens Health. 2012 Feb; 21(2):140–5. https://doi.org/10.1089/jwh.2011.2876 PMID: 22081983

6. Moore TJ, Mattison DR. Adult Utilization of Psychiatric Drugs and Differences by Sex, Age, and Race. JAMA Intern Med. 2017 Feb 1; 177(2):274–5. https://doi.org/10.1001/jamainternmed.2016.7507 PMID: 27942726

7. Carrero JJ, Hecking M, Chesnaye NC, Jager KJ. Sex and gender disparities in the epidemiology and outcomes of chronic kidney disease. Nat Rev Nephrol. 2018 Mar; 14(3):151–64. https://doi.org/10.1038/nrneph.2017.181 PMID: 29355169

8. Swartling O, Yang Y, Clase CM, Fu EL, Hecking M, Hödlmoser S, et al. Sex Differences in the Recognition, Monitoring, and Management of CKD in Health Care: An Observational Cohort Study. J Am Soc Nephrol. 2022 Oct 1; 33(10):1903–14. https://doi.org/10.1681/ASN.2022030373 PMID: 35906075

9. Bikbov B, Perico N, Remuzzi G, on behalf of the GBD Genitourinary Diseases Expert Group. Disparities in Chronic Kidney Disease Prevalence among Males and Females in 195 Countries: Analysis of the Global Burden of Disease 2016 Study. Nephron. 2018; 139(4):313–8.

10. Cirillo M, Laurenzi M, Mancini M, Zanchetti A, Lombardi C, De Santo NG. Low glomerular filtration in the population: prevalence, associated disorders, and awareness. Kidney Int. 2006 Aug; 70(4):800–6. https://doi.org/10.1038/sj.ki.5001641 PMID: 16820784

11. Zdrojewski Ł, Zdrojewski T, Rutkowski M, Bandosz P, Król E, Wyrzykowski B, et al. Prevalence of chronic kidney disease in a representative sample of the Polish population: results of the NATPOL 2011
survey. Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc—Eur Ren Assoc. 2016 Mar; 31 (3):433–9.

12. Gasparini A, Evans M, Coresh J, Grams ME, Norin O, Qureshi AR, et al. Prevalence and recognition of chronic kidney disease in Stockholm healthcare. Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc—Eur Ren Assoc. 2016 Dec; 31(12):2086–94. https://doi.org/10.1093/ndt/gfw354 PMID: 27738231

13. Arora P, Vasa P, Brenner D, Iglar K, McFarlane P, Morrison H, et al. Prevalence estimates of chronic kidney disease in Canada: results of a nationally representative survey. CMAJ Can Med Assoc J J Assoc Medicale Can. 2013 Jun 11; 185(9):E417–423. https://doi.org/10.1503/cmaj.120833 PMID: 23649413

14. Shin HY, Kang HT. Recent trends in the prevalence of chronic kidney disease in Korean adults: Korean National Health and Nutrition Examination Survey from 1998 to 2013. J Nephrol. 2016 Dec; 29(6):799–807. https://doi.org/10.1007/s40620-016-0280-y PMID: 26943182

15. Hecking M, Bieber BA, Ethier J, Kautzky-Willer A, Sunder-Plassmann G, Säemann MD, et al. Sex-Specific Differences in Hemodialysis Prevalence and Practices and the Male-to-Female Mortality Rate: The Dialysis Outcomes and Practice Patterns Study (DOPPS). PLoS Med. 2014 Oct 28; 11(10):e1001750. https://doi.org/10.1371/journal.pmed.1001750 PMID: 25350533

16. Eriksen BO, Ingebretsen OC. The progression of chronic kidney disease: a 10-year population-based study of the effects of gender and age. Kidney Int. 2006 Jan; 69(2):375–82. https://doi.org/10.1038/sj.ki. 5000058 PMID: 16408129

17. Minutolo R, Gabbai FB, Chiodini P, Provenzano M, Borrelli S, Garofalo C, et al. Sex Differences in the Progression of CKD Among Older Patients: Pooled Analysis of 4 Cohort Studies. Am J Kidney Dis Off J Natl Kidney Found. 2020 Jan; 75(1):30–8. https://doi.org/10.1053/j.ajkd.2019.05.019 PMID: 31409508

18. Swartling O, Rydell H, Stendahl M, Segelmark M, Lagerros YT, Evans M. CKD Progression and Mortality Among Men and Women: A Nationwide Study in Sweden. Am J Kidney Dis. 2021 Aug 1; 78(2):190–199.e1. https://doi.org/10.1053/j.ajkd.2020.11.026 PMID: 33434591

19. Tomlinson LA, Clase CM. Sex and the Incidence and Prevalence of Kidney Disease. Clin J Am Soc Nephrol. 2019 Nov 7; 14(11):1557–9. https://doi.org/10.2215/CJN.11030919 PMID: 31649072

20. Bello AK, Okpechi IG, Osman MA, Cho Y, Htay H, Jha V, et al. Epidemiology of haemodialysis outcomes. Nat Rev Nephrol. 2022 Jun; 18(6):378–95. https://doi.org/10.1038/s41581-022-00542-7 PMID: 35194215

21. Kutner NG, Zhang R, Brogan D. Race, Gender, and Incident Dialysis Patients' Reported Health Status and Quality of Life. J Am Soc Nephrol. 2005 May 1; 16(5):1440–8. https://doi.org/10.1681/ASN. 2004080639 PMID: 15800127

22. Lopes AA, Bragg-Gresham JL, Goodkin DA, Fukuhara S, Mapes DL, Young EW, et al. Factors associated with health-related quality of life among hemodialysis patients in the DOPPS. Qual Life Res. 2007 Feb 8; 16(4):545. https://doi.org/10.1007/s11136-006-9143-7 PMID: 17286199

23. Almutary H, Bonner A. Douglas C. Which Patients with Chronic Kidney Disease Have the Greatest Symptom Burden? A Comparative Study of Advanced Ckd Stage and Dialysis Modality. J Ren Care. 2016; 42(2):73–82. https://doi.org/10.1111/jorc.12152 PMID: 26936486

24. Caplin B, Kumar S, Davenport A. Patients' perspective of haemodialysis-associated symptoms. Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc—Eur Ren Assoc. 2011 Aug; 26(8):2656–63. https://doi.org/10.1093/ndt/gfq763 PMID: 21212166

25. Weisbord SD, Fried LF, Arnold RM, Fine MJ, Levenson DJ, Peterson RA, et al. Prevalence, Severity, and Importance of Physical and Emotional Symptoms in Chronic Hemodialysis Patients. J Am Soc Nephrol. 2005 Aug 1; 16(8):2487–94. https://doi.org/10.1681/ASN.2005020157 PMID: 15975996

26. Adams SV, Rivara M, Streja E, Cheung AK, Arah OA, Kalantar-Zadeh K, et al. Sex Differences in Hospitalizations with Maintenance Hemodialysis. J Am Soc Nephrol. 2017 Sep 1; 28(9):2721–8. https://doi.org/10.1681/ASN.2016090986 PMID: 28432127

27. Chan HW, Clayton PA, McDonald SP, Agar JWM, Jose MD. Risk Factors for Dialysis Withdrawal: An Analysis of the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, 1999–2008. Clin J Am Soc Nephrol. 2012 May 1; 7(5):775–81. https://doi.org/10.2215/CJN.07420711 PMID: 22461540

28. Smothers L, Patzer RE, Pastan SO, DuBay D, Harding JL. Gender Disparities in Kidney Transplantation Referral Vary by Age and Race: A Multiregional Cohort Study in the Southeast United States. Kidney Int Rep. 2022 Jun 1; 7(6):1248–57. https://doi.org/10.1016/j.ekir.2022.03.027 PMID: 35694555

29. Bayat S, Macher MA, Couchoud C, Bayer F, Lassalle M, Villar E, et al. Individual and Regional Factors of Access to the Renal Transplant Waiting List in France in a Cohort of Dialyzed Patients. Am J Transplant. 2015; 15(4):1050–60. https://doi.org/10.1111/ajt.13095 PMID: 25758788
survey. Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc—Eur Ren Assoc. 2016 Mar; 31 (3):433–9.

12. Gasparini A, Evans M, Coresh J, Grams ME, Norin O, Qureshi AR, et al. Prevalence and recognition of chronic kidney disease in Stockholm healthcare. Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc—Eur Ren Assoc. 2016 Dec; 31(12):2086–94. https://doi.org/10.1093/ndt/gfw354 PMID: 27738231

13. Arora P, Vasa P, Brenner D, Iglar K, McFarlane P, Morrison H, et al. Prevalence estimates of chronic kidney disease in Canada: results of a nationally representative survey. CMAJ Can Med Assoc J J Assoc Medicale Can. 2013 Jun 11; 185(9):E417–423. https://doi.org/10.1503/cmaj.120833 PMID: 23649413

14. Shin HY, Kang HT. Recent trends in the prevalence of chronic kidney disease in Korean adults: Korean National Health and Nutrition Examination Survey from 1998 to 2013. J Nephrol. 2016 Dec; 29(6):799–807. https://doi.org/10.1007/s40620-016-0280-y PMID: 26943182

15. Hecking M, Bieber BA, Ethier J, Kautzky-Willer A, Sunder-Plassmann G, Säemann MD, et al. Sex-Specific Differences in Hemodialysis Prevalence and Practices and the Male-to-Female Mortality Rate: The Dialysis Outcomes and Practice Patterns Study (DOPPS). PLoS Med. 2014 Oct 28; 11(10):e1001750. https://doi.org/10.1371/journal.pmed.1001750 PMID: 25350533

16. Eriksen BO, Ingebretsen OC. The progression of chronic kidney disease: a 10-year population-based study of the effects of gender and age. Kidney Int. 2006 Jan; 69(2):375–82. https://doi.org/10.1038/sj.ki. 5000058 PMID: 16408129

17. Minutolo R, Gabbai FB, Chiodini P, Provenzano M, Borrelli S, Garofalo C, et al. Sex Differences in the Progression of CKD Among Older Patients: Pooled Analysis of 4 Cohort Studies. Am J Kidney Dis Off J Natl Kidney Found. 2020 Jan; 75(1):30–8. https://doi.org/10.1053/j.ajkd.2019.05.019 PMID: 31409508

18. Swartling O, Rydell H, Stendahl M, Segelmark M, Lagerros YT, Evans M. CKD Progression and Mortality Among Men and Women: A Nationwide Study in Sweden. Am J Kidney Dis. 2021 Aug 1; 78(2):190–199.e1. https://doi.org/10.1053/j.ajkd.2020.11.026 PMID: 33434591

19. Tomlinson LA, Clase CM. Sex and the Incidence and Prevalence of Kidney Disease. Clin J Am Soc Nephrol. 2019 Nov 7; 14(11):1557–9. https://doi.org/10.2215/CJN.11030919 PMID: 31649072

20. Bello AK, Okpechi IG, Osman MA, Cho Y, Htay H, Jha V, et al. Epidemiology of haemodialysis outcomes. Nat Rev Nephrol. 2022 Jun; 18(6):378–95. https://doi.org/10.1038/s41581-022-00542-7 PMID: 35194215

21. Kutner NG, Zhang R, Brogan D. Race, Gender, and Incident Dialysis Patients' Reported Health Status and Quality of Life. J Am Soc Nephrol. 2005 May 1; 16(5):1440–8. https://doi.org/10.1681/ASN. 2004080639 PMID: 15800127

22. Lopes AA, Bragg-Gresham JL, Goodkin DA, Fukuhara S, Mapes DL, Young EW, et al. Factors associated with health-related quality of life among hemodialysis patients in the DOPPS. Qual Life Res. 2007 Feb 8; 16(4):545. https://doi.org/10.1007/s11136-006-9143-7 PMID: 17286199

23. Almutary H, Bonner A. Douglas C. Which Patients with Chronic Kidney Disease Have the Greatest Symptom Burden? A Comparative Study of Advanced Ckd Stage and Dialysis Modality. J Ren Care. 2016; 42(2):73–82. https://doi.org/10.1111/jorc.12152 PMID: 26936486

24. Caplin B, Kumar S, Davenport A. Patients' perspective of haemodialysis-associated symptoms. Nephrol Dial Transplant Off Publ Eur Dial Transpl Assoc—Eur Ren Assoc. 2011 Aug; 26(8):2656–63. https://doi.org/10.1093/ndt/gfq763 PMID: 21212166

25. Weisbord SD, Fried LF, Arnold RM, Fine MJ, Levenson DJ, Peterson RA, et al. Prevalence, Severity, and Importance of Physical and Emotional Symptoms in Chronic Hemodialysis Patients. J Am Soc Nephrol. 2005 Aug 1; 16(8):2487–94. https://doi.org/10.1681/ASN.2005020157 PMID: 15975996

26. Adams SV, Rivara M, Streja E, Cheung AK, Arah OA, Kalantar-Zadeh K, et al. Sex Differences in Hospitalizations with Maintenance Hemodialysis. J Am Soc Nephrol. 2017 Sep 1; 28(9):2721–8. https://doi.org/10.1681/ASN.2016090986 PMID: 28432127

27. Chan HW, Clayton PA, McDonald SP, Agar JWM, Jose MD. Risk Factors for Dialysis Withdrawal: An Analysis of the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, 1999–2008. Clin J Am Soc Nephrol. 2012 May 1; 7(5):775–81. https://doi.org/10.2215/CJN.07420711 PMID: 22461540

28. Smothers L, Patzer RE, Pastan SO, DuBay D, Harding JL. Gender Disparities in Kidney Transplantation Referral Vary by Age and Race: A Multiregional Cohort Study in the Southeast United States. Kidney Int Rep. 2022 Jun 1; 7(6):1248–57. https://doi.org/10.1016/j.ekir.2022.03.027 PMID: 35694555

29. Bayat S, Macher MA, Couchoud C, Bayer F, Lassalle M, Villar E, et al. Individual and Regional Factors of Access to the Renal Transplant Waiting List in France in a Cohort of Dialyzed Patients. Am J Transplant. 2015; 15(4):1050–60. https://doi.org/10.1111/ajt.13095 PMID: 25758788
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42. Raffray M, Vigneau C, Couchoud C, Bayat S. Predialysis Care Trajectories of Patients With ESKD Starting Dialysis in Emergency in France. Kidney Int Rep. 2021 Jan; 6(1):156-67. https://doi.org/10.1016/j.ekir.2020.10.026 PMID: 33426395

43. Sterne JAC, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009 Jun 29; 338:b2393. https://doi.org/10.1136/bmj.b2393 PMID: 19564179

44. Wang Y, Hunt K, Nazareth I, Freemantle N, Petersen I. Do men consult less than women? An analysis of routinely collected UK general practice data. BMJ Open. 2013 Aug 1; 3(8):e003320. https://doi.org/10.1136/bmjopen-2013-003320 PMID: 23959757

45. Hödlmoser S, Winkelmayer WC, Zee J, Pecoits-Filho R, Pisoni RL, Port FK, et al. Sex differences in chronic kidney disease awareness among US adults, 1999 to 2018. PLOS ONE. 2020 Dec 18; 15(12): e0243431. https://doi.org/10.1371/journal.pone.0243431 PMID: 33338051

46. Hall JA, Irish JT, Roter DL, Ehrlich CM, Miller LH. Gender in medical encounters: an analysis of physician and patient communication in a primary care setting. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 1994 Sep; 13(5):384-92.

47. Hall JA, Roter DL. Patient gender and communication with physicians: results of a community-based study. Womens Health Hillsdale NJ. 1995; 1(1):77-95. PMID: 9373374

48. Chapman KR, Tashkin DP, Pye DJ. Gender bias in the diagnosis of COPD. Chest. 2001 Jun; 119 (6):1691-5. https://doi.org/10.1378/chest.119.6.1691 PMID: 11399692

49. Tong A, Evangelidis N, Kurnikowski A, Lewandowski M, Bretschneider P, Oberbauer R, et al. Nephrologists' Perspectives on Gender Disparities in CKD and Dialysis. Kidney Int Rep. 2022 Mar 1; 7(3):424-35. https://doi.org/10.1016/j.ekir.2021.10.022 PMID: 35257055
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36. Michel A, Pladys A, Bayat S, Couchoud C, Hannedouche T, Vigneau C. Deleterious effects of dialysis emergency start, insights from the French REIN registry. BMC Nephrol. 2018 Sep 17; 19(1):233. https://doi.org/10.1186/s12882-018-1036-9 PMID: 30223784

37. Couchoud C, Stengel B, Landais P, Aldigier JC, de Cornelissen F, Dabot C, et al. The renal epidemiology and information network (REIN): a new registry for end-stage renal disease in France. Nephrol Dial Transplant. 2006 Feb 1; 21(2):411-8. https://doi.org/10.1093/ndt/gfi198 PMID: 16234286

38. Caillet A, Mazoué F, Wurtz B, Larre X, Couchoud C, Lassalle M, et al. Which data in the French registry for advanced chronic kidney disease for public health and patient care? Néphrologie Thérapeutique [Internet]. 2022 Jun 27 [cited 2022 Jul 10]; Available from: https://www.sciencedirect.com/science/article/pii/S176972552200027X https://doi.org/10.1016/j.nephro.2022.01.004 PMID: 35773143

39. Raffray M, Bayat S, Lassalle M, Couchoud C. Linking disease registries and nationwide healthcare administrative databases: the French renal epidemiology and information network (REIN) insight. BMC Nephrol. 2020 Dec; 21(1):25. https://doi.org/10.1186/s12882-020-1692-4 PMID: 31992233

40. Tuppin P, Rudant J, Constantinou P, Gastaldi-Ménager C, Rachas A, de Roquefeuil L, et al. Value of a national administrative database to guide public decisions: From the système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France. Rev DÉpidémiologie Santé Publique. 2017 Oct; 65:S149-67.

41. Haute Autorité de Santé. Guide du parcours de soins—Maladie Rénale Chronique de l'adulte [Internet]. 2012 Feb. Available from: https://www.has-sante.fr/portail/upload/docs/application/pdf/2012-04/guide_parcours_de_seins_mrc_web.pdf

42. Raffray M, Vigneau C, Couchoud C, Bayat S. Predialysis Care Trajectories of Patients With ESKD Starting Dialysis in Emergency in France. Kidney Int Rep. 2021 Jan; 6(1):156-67. https://doi.org/10.1016/j.ekir.2020.10.026 PMID: 33426395

43. Sterne JAC, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009 Jun 29; 338:b2393. https://doi.org/10.1136/bmj.b2393 PMID: 19564179

44. Wang Y, Hunt K, Nazareth I, Freemantle N, Petersen I. Do men consult less than women? An analysis of routinely collected UK general practice data. BMJ Open. 2013 Aug 1; 3(8):e003320. https://doi.org/10.1136/bmjopen-2013-003320 PMID: 23959757

45. Hödlmoser S, Winkelmayer WC, Zee J, Pecoits-Filho R, Pisoni RL, Port FK, et al. Sex differences in chronic kidney disease awareness among US adults, 1999 to 2018. PLOS ONE. 2020 Dec 18; 15(12): e0243431. https://doi.org/10.1371/journal.pone.0243431 PMID: 33338051

46. Hall JA, Irish JT, Roter DL, Ehrlich CM, Miller LH. Gender in medical encounters: an analysis of physician and patient communication in a primary care setting. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 1994 Sep; 13(5):384-92.

47. Hall JA, Roter DL. Patient gender and communication with physicians: results of a community-based study. Womens Health Hillsdale NJ. 1995; 1(1):77-95. PMID: 9373374

48. Chapman KR, Tashkin DP, Pye DJ. Gender bias in the diagnosis of COPD. Chest. 2001 Jun; 119 (6):1691-5. https://doi.org/10.1378/chest.119.6.1691 PMID: 11399692

49. Tong A, Evangelidis N, Kurnikowski A, Lewandowski M, Bretschneider P, Oberbauer R, et al. Nephrologists' Perspectives on Gender Disparities in CKD and Dialysis. Kidney Int Rep. 2022 Mar 1; 7(3):424-35. https://doi.org/10.1016/j.ekir.2021.10.022 PMID: 35257055
50. Canestaro WJ, Hendrix N, Bansal A, Sullivan SD, Devine EB, Carlson JJ. Favorable and publicly funded studies are more likely to be published: a systematic review and meta-analysis. J Clin Epidemiol. 2017 Dec 1; 92:58–68. https://doi.org/10.1016/j.jclinepi.2017.08.004 PMID: 28842289

51. Hecking M, Hödlmoser S, Ahmed SB, Carrero JJ. The Other Way Around: Living With Chronic Kidney Disease From the Perspective of Men. Semin Nephrol. 2022 Mar 1; 42(2):122–8. https://doi.org/10.1016/j.semnephrol.2022.04.003 PMID: 35718360

52. van de Luijtglaarden MWM, Caskey FJ, Wanner C, Chesnaye NC, Postorino M, Janmaat CJ, et al. Uraemic symptom burden and clinical condition in women and men of ≥65 years of age with advanced chronic kidney disease: results from the EQUAL study. Nephrol Dial Transplant. 2019 Jul 1; 34 (7):1189–96.

53. Banks I. No man's land: men, illness, and the NHS. BMJ. 2001 Nov 3; 323(7320):1058–60. https://doi.org/10.1136/bmj.323.7320.1058 PMID: 11691768

54. Barsky AJ, Peekna HM, Borus JF. Somatic Symptom Reporting in Women and Men. J Gen Intern Med. 2001 Apr; 16(4):266–75. https://doi.org/10.1046/j.1525-1497.2001.00229.x PMID: 11318929

55. Toth-Manikowski SM, Yang W, Appel L, Chen J, Deo R, Frydrych A, et al. Sex Differences in Cardiovascular Outcomes in CKD: Findings From the CRIC Study. Am J Kidney Dis. 2021 Aug 1; 78(2):200–209. e1. https://doi.org/10.1053/j.ajkd.2021.01.020 PMID: 33857532

56. Arnold AP, Cassis LA, Eghbali M, Reue K, Sandberg K. Sex Hormones and Sex Chromosomes Cause Sex Differences in the Development of Cardiovascular Diseases. Arterioscler Thromb Vasc Biol. 2017 May; 37(5):746–56. https://doi.org/10.1161/ATVBAHA.116.307301 PMID: 28279969

57. Morton RL, Turner RM, Howard K, Snelling P, Webster AC. Patients who plan for conservative care rather than dialysis: a national observational study in Australia. Am J Kidney Dis Off J Natl Kidney Found. 2012 Mar; 59(3):419–27. https://doi.org/10.1053/j.ajkd.2011.08.024 PMID: 22014401

58. Mansouri I, Raffray M, Lassalle M, de Vathaire F, Fresneau B, Fayech C, et al. An algorithm for identifying chronic kidney disease in the French national health insurance claims database. Néphrologie Thérapeutique [Internet]. 2022 Jun 27 [cited 2022 Jun 28]; Available from: https://www.sciencedirect.com/science/article/pii/S1769725522000864 https://doi.org/10.1016/j.nephro.2022.03.003 PMID: 35773142

59. Neufcourt L, Deguen S, Bayat S, Zins M, Grimaud O. Gender differences in the association between socioeconomic status and hypertension in France: A cross-sectional analysis of the CONSTANCES cohort. PloS One. 2020; 15(4):e0231878. https://doi.org/10.1371/journal.pone.0231878 PMID: 32311000

60. Biomedicine Agency. REIN Registry Annual Report 2021 Data [Internet]. France; 2023. Available from: https://www.agence-biomedecine.fr/IMG/pdf/rapport_rein_2021_2023-06-26.pdf
50. Canestaro WJ, Hendrix N, Bansal A, Sullivan SD, Devine EB, Carlson JJ. Favorable and publicly funded studies are more likely to be published: a systematic review and meta-analysis. J Clin Epidemiol. 2017 Dec 1; 92:58–68. https://doi.org/10.1016/j.jclinepi.2017.08.004 PMID: 28842289

51. Hecking M, Hödlmoser S, Ahmed SB, Carrero JJ. The Other Way Around: Living With Chronic Kidney Disease From the Perspective of Men. Semin Nephrol. 2022 Mar 1; 42(2):122–8. https://doi.org/10.1016/j.semnephrol.2022.04.003 PMID: 35718360

52. van de Luijtaarden MWM, Caskey FJ, Wanner C, Chesnaye NC, Postorino M, Janmaat CJ, et al. Uraemic symptom burden and clinical condition in women and men of ≥65 years of age with advanced chronic kidney disease: results from the EQUAL study. Nephrol Dial Transplant. 2019 Jul 1; 34 (7):1189–96.

53. Banks I. No man's land: men, illness, and the NHS. BMJ. 2001 Nov 3; 323(7320):1058–60. https://doi.org/10.1136/bmj.323.7320.1058 PMID: 11691768

54. Barsky AJ, Peekna HM, Borus JF. Somatic Symptom Reporting in Women and Men. J Gen Intern Med. 2001 Apr; 16(4):266–75. https://doi.org/10.1046/j.1525-1497.2001.00229.x PMID: 11318929

55. Toth-Manikowski SM, Yang W, Appel L, Chen J, Deo R, Frydrych A, et al. Sex Differences in Cardiovascular Outcomes in CKD: Findings From the CRIC Study. Am J Kidney Dis. 2021 Aug 1; 78(2):200–209. e1. https://doi.org/10.1053/j.ajkd.2021.01.020 PMID: 33857532

56. Arnold AP, Cassis LA, Eghbali M, Reue K, Sandberg K. Sex Hormones and Sex Chromosomes Cause Sex Differences in the Development of Cardiovascular Diseases. Arterioscler Thromb Vasc Biol. 2017 May; 37(5):746–56. https://doi.org/10.1161/ATVBAHA.116.307301 PMID: 28279969

57. Morton RL, Turner RM, Howard K, Snelling P, Webster AC. Patients who plan for conservative care rather than dialysis: a national observational study in Australia. Am J Kidney Dis Off J Natl Kidney Found. 2012 Mar; 59(3):419–27. https://doi.org/10.1053/j.ajkd.2011.08.024 PMID: 22014401

58. Mansouri I, Raffray M, Lassalle M, de Vathaire F, Fresneau B, Fayech C, et al. An algorithm for identifying chronic kidney disease in the French national health insurance claims database. Néphrologie Thérapeutique [Internet]. 2022 Jun 27 [cited 2022 Jun 28]; Available from: https://www.sciencedirect.com/science/article/pii/S1769725522000864 https://doi.org/10.1016/j.nephro.2022.03.003 PMID: 35773142

59. Neufcourt L, Deguen S, Bayat S, Zins M, Grimaud O. Gender differences in the association between socioeconomic status and hypertension in France: A cross-sectional analysis of the CONSTANCES cohort. PloS One. 2020; 15(4):e0231878. https://doi.org/10.1371/journal.pone.0231878 PMID: 32311000

60. Biomedicine Agency. REIN Registry Annual Report 2021 Data [Internet]. France; 2023. Available from: https://www.agence-biomedecine.fr/IMG/pdf/rapport_rein_2021_2023-06-26.pdf