# Short- and long-term outcomes and 15-year time trends of kidney replacement therapy in critically ill patients with obesity: an observational cohort

Clément Monet, Jawad Bouziane, Joris Pensier, Yassir Aarab, Mathieu Capdevila, Ines Lakbar, Laurent Muller, Claire Roger, Audrey de Jong, Samir Jaber

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Clément Monet, Jawad Bouziane, Joris Pensier, Yassir Aarab, Mathieu Capdevila, et al. Short- and long-term outcomes and 15-year time trends of kidney replacement therapy in critically ill patients with obesity: an observational cohort. Intensive Care Medicine, 2025, 51, pp.1320-1330. 10.1007/s00134-025-07990-2. hal-05138224

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# Short- and long-term outcomes and 15-year time trends of kidney replacement therapy in critically ill patients with Obesity: an observational cohort

Clément Monet¹², Jawad Bouziane<fnref n="3" />, Joris Pensier¹², Yassir Aarab¹², Mathieu Capdevila¹², Ines Lakbar¹², Laurent Muller<fnref n="3" />, Claire Roger<fnref n="3" />, Audrey De Jong¹², Samir Jaber⁴⁵

**Keywords:**

Acute kidney injury; Intensive care; Kidney replacement therapy; Obesity.

**\*Correspondence:**

s-jaber@chu-montpellier.fr

1 Department of Anesthesia and Intensive Care Unit, Regional University Hospital of Montpellier, St-Eloi Hospital, University of Montpellier,

<footnote n="1">¹ of Anesthesia and Intensive Care Unit, Regional University Hospital of Montpellier, St-Eloi Hospital, University of Montpellier, Montpellier, France.</footnote>

<footnote n="2">² PhyMedExp, University of Montpellier, INSERM U1046, CNRS, UMR 9214, Montpellier, France.</footnote>

<footnote n="3">³ Department of Anesthesiology, Emergency and Critical Care Medicine, Intensive Care Unit, Nîmes University Hospital, Nîmes, France.</footnote>

<footnote n="4">⁴ Department of Anesthesia and Intensive Care Unit, Regional University Hospital of Montpellier, St-Eloi Hospital, University of Montpellier, Montpellier, France.
sjaber@chu-montpellier.fr.</footnote>

<footnote n="5">⁵ PhyMedExp, University of Montpellier, INSERM U1046, CNRS, UMR 9214, Montpellier, France.
s-jaber@chu-montpellier.fr.</footnote>
# Abstract

**Purpose:**

Obesity is a public health challenge and a risk factor for chronic and acute kidney injury (AKI). The impact of kidney replacement therapy (KRT) on mortality in this specific population remains unclear. The objectives of this study were to evaluate the association between KRT and short- and long-term outcomes in patients with obesity, and to analyze trends over time in mortality as well as AKI and KRT incidence.

**Methods:**

A 30 retrospective analysis was conducted on all consecutive patients with obesity (body index≥ kg/m²) admitted to a medico-surgical intensive care unit from 2009 to 2024. mass AKI was defined using criteria. The primary outcome was 90-day mortality assessed with Kaplan-Meier KDIGO curves and multivariate Cox analysis. Secondary outcomes included 1-year mortality and time trends assessed on 90-day mortality, AKI, and KRT incidence, as well as SAPS II score.

**Results:**

Among 2,192 patients with obesity included in the study, 295 (13.5%) required KRT. The 90-day mortality was significantly higher in the KRT group compared to the non-KRT group (49.8% (95% CI [44.1-55.5]) vs. 18.9% (95% CI [17.2-20.7]), p < 0.0001). Multivariate analysis confirmed that KRT was independently associated with increased mortality. Over the 15-year period, AKI incidence decreased (p < 0.001).

**Conclusion:**

Among critically ill obese patients, KRT was independently associated with increased 90-day mortality. These results highlight the need for prospective studies to better define optimal management strategies in this high-risk population.
# Introduction

Obesity is a multifactorial disease defined by an excess of fat or adipose tissue that leads to an increase in health risks. In clinical practice, obesity is defined by the World Health Organization (WHO) with a body mass index (BMI) [weight (kg)/height² (m)] greater than or equal to 30 kg/m². It is further classified into “moderate,” “severe,” and “very severe” obesity according to the BMI [1]. In the European region, according to WHO, obesity prevalence has risen from 9.7% to 23% in adults between 1975 and 2016 [2].

Obesity is a well-established risk factor for chronic kidney disease (CKD) with a quicker loss of kidney function over time compared to patients without obesity [3]. Higher BMI is also associated with proteinuria, low glomerular filtration rate (GFR) and end-stage renal disease [4]. Visceral adipose tissue has a predominant impact on kidney function [5], due to its endocrine activity (adiponectin, leptin, etc.) that leads to low-grade chronic inflammation, oxidative stress, activation of the renin–angiotensin–aldosterone system, and insulin resistance [5, 6]. These obesity-associated alterations lead to what is now recognized as “obesity-related glomerulopathy” [7, 8].

Acute kidney injury (AKI) in the intensive care unit (ICU), in unselected patients, is frequent and associated with a poor prognosis [9, 10]. In-hospital mortality associated with AKI is high; depending on the severity of the kidney injury, it ranges from 25 to 40% [9, 11]. In unselected patients with AKI, kidney replacement therapy (KRT) seems to be associated with higher mortality, although results, based on observational study designs, remain conflicting [12–14]. Major studies in the field of KRT in ICU have modified the prescription of KRT in the ICU in the past years, either regarding the timing of initiation [15–19], KRT modality [20, 21], anticoagulation [22–24], or intensity of KRT [25, 26]. Obesity appears to be an independent risk factor for AKI, and the higher the BMI, the higher the incidence of AKI [27–29]. However, studies that focus on AKI and KRT in patients with obesity in ICU are scarce.

The primary objective was to compare, in a population with obesity in the ICU, the 90-day mortality between patients treated with KRT and patients who were not. The secondary objectives were to evaluate the association between KRT and 1-year mortality, to analyze changes over time in mortality in both groups, and to analyze changes over time of AKI and KRT incidence.
# Materials and methods

## Study design and ethics

We conducted a retrospective analysis of prospectively collected data of all patients with obesity consecutively admitted to ICU between June 2009 and November 2024. The study was conducted in a 20-bed adult ICU, a referral center for liver diseases, within a university-affiliated tertiary care hospital. The unit has a balanced case mix, with approximately 50% medical and 50% surgical admissions. We obtained approval from the local research ethics committee (“Institutional Review Board”) of the Montpellier University Hospital (2019_IRB-MTP_05-25).

## Patients and data collection

Patients' actual body weights and heights were measured at the time of ICU admission and used for all analyses as previously described [30–32]. In accordance with WHO recommendation, patients with a body mass index (BMI) ≥ 30 kg/m2 were defined as “with obesity.” Obesity grades were defined as: grade 1 for a BMI between 30 and 34.9 kg/m2, grade 2 between 35 and 39.9 kg/m2, and grade 3 above 40 kg/m2 [1]. All consecutive admissions of patients with obesity hospitalized during the study period were included in the study. Patient data were recorded and included demographics, anthropometrics, clinical and biological data on hospital admission, as well as the Simplified Acute Physiology Score II (SAPS II), ICU admission diagnosis, category of admission (medical or surgical), and comorbidities; the diagnosis of cirrhosis was made as described previously [33]. SAPS II was the severity score routinely used in our ICU during the entire study period (2009–2024). Baseline creatinine was defined either by creatinine level measured prior to ICU admission, if available, or by creatinine level at ICU admission in the absence of AKI at admission. Creatinine and urine output were recorded daily. Diagnosis and staging of acute kidney injury (AKI) were defined according to international guidelines from the Kidney Disease: Improving Global Outcomes (KDIGO) foundation (Electronic Supplementary Table 1) [34]. Although it has not been validated in patients with obesity, this classification is the most recent and is widely used in recent studies; for the purpose of KDIGO classification, urine output was normalized on actual weight. AKI at admission was defined based on the data recorded on the day of admission. AKI during ICU stay was defined by the occurrence of AKI in patients who did not have AKI at admission. To define the maximum KDIGO stage, we used the KDIGO criteria, and only the worst KDIGO stage during the entire ICU stay was retained. Persistent AKI at discharge was defined by non-return to creatinine baseline level (• +/- 10%) at ICU discharge in survivors or on the day of death for the non-survivors, as previously described [35, 36].

In case of kidney replacement therapy, duration (number of days) as well as modality of KRT (either continuous KRT (CKRT) or intermittent hemodialysis (IHD)) were collected. Per local protocol based on international guidelines [34], we aimed to deliver 20–25 mL/kg/h of CKRT dose, or a Kt/V index > 3.9 per week in case of IHD. Per local protocol, CRRT was recommended in cases of hemodynamic instability, while either modality could be used in hemodynamically stable patients at the discretion of the attending physician. CKRT was delivered through Prismaflex or Prismax systems (Baxter, USA) with the ST-150 set. IHD
was delivered through a 5008-therapy system (Fresenius Medical Care, Germany) with FX 80 dialyzers. Dialysis dependency at ICU discharge and at 1 year was also collected.

**Inclusion and exclusion criteria**

All consecutive patients with obesity were included. Exclusion criteria were: (1) end-stage renal disease on dialysis, (2) age less than 18 years, and (3) patient death less than 24 h after admission.

**Outcomes**

The primary outcome was the 90-day mortality. Secondary outcomes included 1-year mortality, the evolution of 90-day mortality over the study period, the evolution of the SAPS II score, AKI and KRT incidence over the study period, persistent AKI at ICU discharge, and dialysis dependency at ICU discharge and at 1 year.

**Statistical analysis**

First, a descriptive analysis was performed overall and in patients treated with KRT (KRT group) and who were not (non-KRT group). Quantitative variables were expressed as mean (• +/- standard deviation (SD)) or median [interquartile range, 25-75%] and compared using the Student-t test or Wilcoxon test as appropriate (Gaussian or non-Gaussian variables). Qualitative variables were expressed as numbers (%) and compared using the uncorrected Chi-square test or Fisher test as appropriate. In case of missing values, the number of missing values was clearly stated for each variable, and no replacement method was used (as shown in Electronic Supplementary Table 2).
<table><caption>Table 2 Patients' characteristics in survivors and non-survivors according to study group</caption><thead><tr><th rowspan="2">Patients' characteristics</th><th colspan="2">KRT group (n = 295)</th><th rowspan="2">p value</th><th colspan="2">Non-KRT group (n = 1807)</th><th rowspan="2">p value</th></tr><tr><th>Survivors (n = 148)</th><th>Non-survivors (n = 147)</th><th>Survivors (n = 1538)</th><th>Non-survivors (n = 359)</th></tr></thead><tbody><tr><td>Age, years</td><td>60 ± 13</td><td>64 ± 10</td><td><strong>0.013</strong></td><td>59 ± 14</td><td>66 ± 12</td><td>&lt;.001</td></tr><tr><td>Female gender</td><td>47 (31.8)</td><td>43 (29.1)</td><td>0.346</td><td>597 (38.8)</td><td>134 (37.3)</td><td>0.642</td></tr><tr><td>Size, cm</td><td>171 ± 9</td><td>169 ± 9</td><td>0.471</td><td>169 ± 10</td><td>168 ± 9</td><td>0.132</td></tr><tr><td>Weight, kg</td><td>106 ± 25</td><td>105 ± 25</td><td>0.575</td><td>107 ± 28</td><td>102 ± 23</td><td>0.002</td></tr><tr><td>Body mass index, kg/m²</td><td>36 ± 8</td><td>37 ± 10</td><td>0.531</td><td>37 ± 9</td><td>36 ± 8</td><td>0.002</td></tr><tr><td>Obesity grade</td><td></td><td></td><td>0.066</td><td></td><td></td><td>0.038</td></tr><tr><td>Grade 1</td><td>81 (55.1)</td><td>80 (54.1)</td><td></td><td>848 (55.1)</td><td>223 (62.1)</td><td></td></tr><tr><td>Grade 2</td><td>48 (32.7)</td><td>37 (25.0)</td><td></td><td>360 (23.4)</td><td>76 (21.2)</td><td></td></tr><tr><td>Grade 3</td><td>18 (12.2)</td><td>31 (20.9)</td><td></td><td>330 (21.5)</td><td>60 (16.7)</td><td></td></tr><tr><td>Past medical history</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Chronic kidney disease</td><td>28 (19.0)</td><td>18 (12.2)</td><td>0.213</td><td>122 (7.9)</td><td>45 (12.5)</td><td>0.008</td></tr><tr><td>Congestive heart failure</td><td>10 (6.8)</td><td>16 (10.8)</td><td>0.333</td><td>121 (7.9)</td><td>44 (12.3)</td><td>0.011</td></tr><tr><td>Hypertension</td><td>53 (36.1)</td><td>58 (39.2)</td><td>0.513</td><td>549 (35.7)</td><td>127 (35.4)</td><td>0.582</td></tr><tr><td>Diabetes</td><td>42 (28.5)</td><td>41 (27.7)</td><td>0.496</td><td>367 (23.9)</td><td>91 (25.3)</td><td>0.937</td></tr><tr><td>Chronic pulmonary disease</td><td>18 (12.2)</td><td>27 (18.2)</td><td>0.068</td><td>263 (17.1)</td><td>67 (18.7)</td><td>0.800</td></tr><tr><td>Cirrhosis</td><td>42 (28.6)</td><td>56 (37.8)</td><td>0.149</td><td>406 (26.4)</td><td>139 (38.7)</td><td>&lt;.001</td></tr><tr><td>Reason for ICU admission</td><td></td><td></td><td>0.166</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>Medical</td><td>83 (56.7)</td><td>92 (64.3)</td><td></td><td>598 (38.9)</td><td>256 (71.3)</td><td></td></tr><tr><td>Surgical</td><td>64 (43.5)</td><td>51 (35.7)</td><td></td><td>940 (61.1)</td><td>103 (28.7)</td><td></td></tr><tr><td>SAPS II</td><td>53 ± 19</td><td>60 ± 19</td><td>0.002</td><td>36 ± 16</td><td>54 ± 20</td><td>&lt;.001</td></tr><tr><td>Vasopressors at ICU admission</td><td>102 (69.4)</td><td>129 (90.2)</td><td>&lt;.001</td><td>552 (35.9)</td><td>234 (65.2)</td><td>&lt;.001</td></tr><tr><td>Mechanical ventilation at ICU admission</td><td>119 (81.0)</td><td>124 (86.7)</td><td>0.420</td><td>990 (64.4)</td><td>243 (67.7)</td><td>0.260</td></tr><tr><td>Serum creatinine at ICU admission, µmol/L</td><td>255 ± 167</td><td>236 ± 128</td><td>0.645</td><td>110.5 ± 83.5</td><td>166.4 ± 115.1</td><td>&lt;.001</td></tr><tr><td>Urine output during first 24 h after ICU admission, mL</td><td>1262 ± 1452</td><td>1187 ± 1467</td><td>0.308</td><td>2201 ± 1291</td><td>1748 ± 1407</td><td>&lt;.001</td></tr><tr><td>Max KDIGO stage during ICU stay</td><td></td><td></td><td>0.816</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>No AKI</td><td>0</td><td>0</td><td></td><td>825 (53.6)</td><td>84 (23.4)</td><td></td></tr><tr><td>1</td><td>7 (4.7)</td><td>5 (3.4)</td><td></td><td>327 (21.3)</td><td>91 (25.3)</td><td></td></tr><tr><td>2</td><td>6 (4.1)</td><td>7 (4.7)</td><td></td><td>255 (16.6)</td><td>87 (24.2)</td><td></td></tr><tr><td>3</td><td>135 (91.2)</td><td>135 (91.8)</td><td></td><td>131 (8.5)</td><td>97 (27.0)</td><td></td></tr></tbody></table>

Values given as mean ± SD or number (%)

KRT kidney replacement therapy, AKI body mass index, SAPS simplified acute physiology score, ICU intensive care unit, KDIGO Kidney Disease: Improving Global Outcomes

Second, survival curves were set up until day 90 using the Kaplan-Meier method and compared with the logrank test. Then, we used a univariate Cox-proportional hazard model to determine whether KRT was associated with 90-day mortality in an unadjusted analysis. Then, we used a multivariate Cox-proportional hazard model to determine whether KRT was independently associated with mortality after adjustment for age, obesity grade, past medical history of chronic kidney disease, reason for admission, SAPS II, and maximum KDIGO stage. Collinearity between variables was tested. No imputation of missing data was made. Third, a univariate logistic regression analysis was done according to 90-day mortality in the KRT group and in the non-KRT group. Then, a multivariate logistic regression was performed to assess the relationship between KRT status (forced variable) and 90-day mortality after ICU admission in the overall population and in the KRT and non-KRT populations. Interactions between variables were tested. Analyses were corrected for the literature-search-based, a priori-selected variables, including demographics, comorbidities, admission characteristics, and pre-KRT variables and treatments, associated with outcomes in AKI requiring KRT. These included gender, age, pre-KRT treatments, and severity at admission characteristics (SAPS II, vasopressors, mechanical ventilation). SAPS II was selected for the final multivariate model to account for overall severity, and a stepwise procedure (with a threshold of *p* < 0.05 to stay in the final model) was used to retain the most relevant variables without collinearity. Odds ratios (OR) were provided for each variable included in the multivariate model.
To assess the potential impact of evolving clinical practices, we conducted a trend analysis across the 15-year period with the Cochran–Armitage test or the Mann–Kendall test when appropriate.

Statistical significance was considered at *p* < 0.05; *p* values were two-tailed. The statistical analysis was performed by the Medical Statistical Department of the Montpellier University Hospital with the help of statistical software (SAS, version 9.4; SAS Institute; Cary, NC).

<figure><img src="image_2.png" /></figure>

# Results

## Patient characteristics

Of the 10,162 patients admitted to the ICU from June 2009 to November 2024, 2224 patients with obesity were identified, of which 2192 were included. Among the 2192 patients, 295 (13.5%) required KRT (KRT group) and 1897 (86.5%) did not (non-KRT group). Within the non-KRT group, 988 (52.1%) had an AKI during the ICU stay and 909 did not (47.9%) (Fig. 1). Among the patients with AKI (n = 1256), 23.5% required KRT. Data for the incidence of AKI are shown in Electronic Supplementary Fig. 1 and Table 3. The proportion of female patients was lower in the KRT group compared to the non-KRT group (30.5% vs. 38.5%, *p* = 0.008) (Table 1). No major difference in obesity grade was found between the groups. Regarding past medical history, patients in the KRT group had a higher rate of chronic kidney disease (15.6% vs. 8.8%, *p* = 0.001). Patients in the KRT group were also more severely ill than patients in the non-KRT group; they had a higher SAPS II score (57 • } 19 vs. 39 • } 18, *p* < 0.001) and a significantly higher incidence of vasopressors and mechanical ventilation at ICU admission. They were also more likely to be admitted for medical reasons (rather than post-surgical) (61% vs. 45%, *p* < 0.001). Median KRT initiation time from admission was 1.0 [0.4–4.0] days after admission. Table 2 presents the main demographic characteristics for survivors and non-survivors, in both the groups (KRT group and non-KRT group).
<table><caption>Table 1 Patients' characteristics from both groups: patients treated with KRT (KRT group) and patients who were not (non-KRT group)</caption><thead><tr><th>Patients' characteristics</th><th>Overall (n = 2192)</th><th>KRT group (n = 295)</th><th>Non-KRT group (n = 1897)</th><th>p value</th></tr></thead><tbody><tr><td>Age, years</td><td>61 ± 14</td><td>62 ± 12</td><td>60 ± 14</td><td>0.193</td></tr><tr><td>Female gender</td><td>821 (37.4)</td><td>90 (30.5)</td><td>731 (38.5)</td><td>0.008</td></tr><tr><td>Size, cm</td><td>169 ± 10</td><td>170 ± 9</td><td>169 ± 10</td><td>0.146</td></tr><tr><td>Weight, kg</td><td>106 ± 27</td><td>105 ± 25</td><td>106 ± 27</td><td>0.578</td></tr><tr><td>Body mass index, kg/m²</td><td>37 ± 9</td><td>36 ± 9</td><td>37 ± 9</td><td>0.329</td></tr><tr><td>Obesity grade</td><td></td><td></td><td></td><td>0.088</td></tr><tr><td>Grade 1</td><td>1232 (56.2)</td><td>161 (54.5)</td><td>1071 (56.5)</td><td></td></tr><tr><td>Grade 2</td><td>529 (24.1)</td><td>85 (28.8)</td><td>444 (23.4)</td><td></td></tr><tr><td>Grade 3</td><td>431 (19.7)</td><td>49 (16.6)</td><td>382 (20.1)</td><td></td></tr><tr><td>Past medical history</td><td></td><td></td><td></td><td></td></tr><tr><td>Chronic kidney disease</td><td>213 (9.7)</td><td>46 (15.6)</td><td>166 (8.8)</td><td>0.001</td></tr><tr><td>Congestive heart failure</td><td>190 (8.7)</td><td>26 (8.8)</td><td>165 (8.7)</td><td>0.948</td></tr><tr><td>Hypertension</td><td>787 (35.9)</td><td>111 (36.0)</td><td>676 (35.6)</td><td>0.507</td></tr><tr><td>Diabetes</td><td>524 (23.9)</td><td>83 (28.1)</td><td>441 (23.2)</td><td>0.067</td></tr><tr><td>Chronic pulmonary disease</td><td>375 (17.1)</td><td>45 (15.3)</td><td>330 (17.4)</td><td>0.364</td></tr><tr><td>Cirrhosis</td><td>644 (29.3)</td><td>98 (35.6)</td><td>546 (29.0)</td><td>0.115</td></tr><tr><td>Reason for ICU admission</td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>Medical</td><td>1034 (47.2)</td><td>180 (61.0)</td><td>854 (45.0)</td><td></td></tr><tr><td>Surgical</td><td>1158 (52.8)</td><td>115 (38.9)</td><td>1043 (54.9)</td><td></td></tr><tr><td>SAPS II</td><td>42 ± 19</td><td>57 ± 19</td><td>39 ± 18</td><td>&lt;0.001</td></tr><tr><td>Vasopressors at ICU admission</td><td>1020 (46.5)</td><td>234 (79.3)</td><td>786 (41.4)</td><td>&lt;0.001</td></tr><tr><td>Mechanical ventilation at ICU admission</td><td>1478 (67.4)</td><td>245 (83.1)</td><td>1233 (65.0)</td><td>&lt;0.001</td></tr><tr><td>Serum creatinine at ICU admission, µmol/L</td><td>138.2 ± 111.8</td><td>248.7 ± 153.1</td><td>121.0 ± 92.8</td><td>&lt;0.001</td></tr><tr><td>Urine output during first 24 h after ICU admission, mL</td><td>1989 ± 1378</td><td>1231 ± 1449</td><td>2113 ± 1326</td><td>&lt;0.001</td></tr><tr><td>Max KDIGO stage during ICU stay</td><td></td><td></td><td></td><td>&lt;0.001</td></tr><tr><td>No AKI</td><td>909 (41.5)</td><td>0</td><td>909 (47.9)</td><td></td></tr><tr><td>1</td><td>430 (19.6)</td><td>12 (4.1)</td><td>418 (22.0)</td><td></td></tr><tr><td>2</td><td>355 (16.2)</td><td>13 (4.4)</td><td>342 (18.0)</td><td></td></tr><tr><td>3</td><td>498 (22.7)</td><td>270 (91.5)</td><td>228 (12.0)</td><td></td></tr></tbody></table>

Values are mean ± SD or number (%)

KRT kidney replacement therapy, BMI body mass index, SAPS simplified acute physiology score, ICU intensive care unit, KDIGO Kidney Disease: Improving Global Outcomes

<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /></figure>

## Primary outcome, 90-day mortality according to KRT status

In the overall population, 90-day mortality was 23.1% (95% CI [21.3–24.8]). In the KRT group, 90-day mortality was 49.8% (95% CI [44.1–55.5]) compared to 18.9% (95% CI [17.2–20.7]) in the non-KRT group, *p* < 0.0001 after univariate logistic regression and by the log-rank test. Kaplan–Meier curves were set up until 90 days after admission in the ICU (Fig. 2). In the multivariate Cox-proportional hazard model, KRT was independently associated with mortality after adjustment for age, cirrhosis, medical admission, SAPS II, and maximum KDIGO stage (adjusted HR = 1.35, 95% CI [1.09–1.68], *p* < 0.01). No collinearity between variables was found (Electronic Supplementary Table 4). In the exploratory analysis using a logistic regression, gender, age, obesity grade, cirrhosis, SAPS II, chronic kidney disease, diabetes, medical admission, and maximum KDIGO stage were selected. After the stepwise procedure, the final multivariate model included age, history of cirrhosis, maximum KDIGO stage, and medical admission. In this model, KRT was independently associated with 90-day mortality (OR 1.61, 95% CI [1.14–2.28], *p* < 0.001). Odds ratios for 90-day mortality after ICU admission are shown in Electronic Supplementary Table 5.

## One-year mortality according to KRT status

In the overall population, 1-year mortality was 28.8% (95% CI [26.7–30.7]). In the KRT group, 1-year mortality was 57.6% (95% CI [52.0–63.3]) compared to 24.4% (95% CI [22.4–26.3]) in the non-KRT group, *p* < 0.0001 after univariate logistic regression and by the log-rank test (Electronic Supplementary Fig. 2).
## Times trends

Over the 15-year study period, there was no significant change in the 90-day mortality in the KRT group (Cochran–Armitage test, *p* = 0.736) nor in the non-KRT group (*p* = 0.073) (Fig. 3A). There was also no trend over time in SAPS II score in the KRT group nor in the non-KRT group (Mann–Kendall test, *p* = 0.095 and *p* = 0.224, respectively)) (Fig. 3B). In the overall population of patients with obesity (*n* = 2192), there was a significant decrease of AKI over time (Cochran–Armitage test, *p* = 0.001); however, there was no significant change over time in KRT occurrence (*p* = 0.451) (Fig. 3C).

## Duration and modality of KRT

Regarding KRT modalities, 152 patients (51.5%) underwent CKRT alone, 32 patients (10.8%) underwent IHD, and 106 (35.9%) patients underwent both modalities. The median duration of KRT was 5.0 [2.0–10.5] days. Data for modality and duration of KRT are shown in Electronic Supplementary Table 6.

## Renal recovery

In the KRT group, persistent AKI at ICU discharge occurred in 35.1% of survivors and in 9.0% of survivors in the non-KRT group (*p* < 0.001) (Electronic Supplementary Table 3). In the KRT group, 18.9% of survivors (32/169) at ICU discharge and 9.6% of survivors (12/125) at 1 year were dialysis-dependent.

## Discussion

This large, single-center cohort of 2192 critically ill obese patients provides novel insights into the relationship between KRT and mortality in this specific population. KRT was independently associated with mortality in this population (adjusted hazard ratio = 1.40, 95% confidence interval [1.13–1.74]). To our knowledge, this is the first study that seeks to assess the relationship between kidney replacement therapy and 90-day mortality after ICU admission, in a population of patients with obesity.

### KRT incidence and mortality

Two large prospective cohorts, the AKI-EPI study and the FINNAKI study, were conducted in unselected patients and aimed to describe the epidemiology of AKI and KRT in ICU patients [9, 11]. In these studies, the percentage of patients who underwent KRT varied from 10 to 15%, and mortality among KRT patients was around 40%. In our study, the incidence of patients with obesity in the ICU who underwent KRT was 13.5%, which is similar to the incidence of KRT in the general population in the ICU. We found a higher 90-day mortality rate in the KRT group than previously described in large cohorts of unselected ICU patients (Electronic Supplementary Table 7 and Fig. 3), although these results are only exploratory. Furthermore, our results support an independent effect of KRT on mortality. In unselected patients, studies on the impact of KRT on mortality yielded conflicting results [12–14].
## KRT and obesity

In the specific population of patients with obesity, data on the impact of KRT are lacking. While several studies investigated the effect of BMI on the risk of AKI and mortality [27–29, 37, 38], there is currently no data available exploring the effect of KRT on outcomes in patients with obesity in the ICU. Druml et al. published a retrospective analysis from a database of 53 Austrian ICUs [27]. The aim of the study was to assess the impact of BMI on outcomes of patients undergoing KRT for AKI. In the entire cohort, 5232 patients were on dialysis for AKI, and among them, 1,130 patients had obesity. After a multivariate analysis, the authors showed a U-shaped pattern mortality curve. The highest mortality was for the underweight group and the group of patients with obesity and a BMI ≥ 35 kg/m2. However, the authors did not explore the effect of KRT on mortality. In addition, three studies on the impact of BMI on the mortality of patients undergoing KRT were carried out in Asian countries [37–39]. While adapted to the population of the study, these results are not applicable to a western population (obesity was defined as a BMI ≥ 25 kg/m2, as defined by the Committee of Clinical Practice Guidelines and Korean Society for the Study of Obesity). Moreover, none of these studies explored a possible independent effect of KRT on mortality.

## Trends over time

Over the 15-year study period, we observed a statistically significant decrease in the incidence of AKI among critically ill obese patients. This trend may be explained by multiple factors, including the implementation of standardized diagnostic criteria (KDIGO), the improvement in sepsis management, and advances in the care of specific high-risk subgroups, notably patients with cirrhosis, who represented approximately a third of our cohort. Despite these changes, the proportion of patients requiring RRT remained stable, suggesting that the threshold for initiating RRT did not substantially evolve in our center during this period. This observation contrasts with studies favoring delayed initiation strategies [15–17, 19] but may reflect the consistency of our local protocols and decision-making practices. Finally, we found no significant change in 90-day mortality or SAPS II scores over time, reinforcing the internal consistency of the cohort and suggesting that the global severity of illness and risk profiles of ICU patients remained stable throughout the study period.

## Dialysis dose

Improvement in prognosis of KRT patients has been made by determining the adequate dialysis dose, which is largely dependent on the patient's weight [25, 26, 34, 40, 41]. Dialysis dosing adequacy in patients with obesity is still subject to debate. Some physicians tend to increase the dialysis dose according to an augmentation of urea distribution volume, mainly by increasing session time and/or frequency [42, 43]. On the contrary, because urea's diffusion in fat tissues seems to be limited, others argue that a calculation of the dose based on total body weight can lead to a relative increase in dialysis dose in patients with obesity [44, 45]. There are currently no data available on KRT doses in patients with obesity in the ICU, and while our study does not include data on KRT dosing, the observed association between KRT and mortality in obese ICU patients highlights the urgent need to explore whether current KRT protocols provide adequate treatment in this population. Future studies should aim to evaluate dose-response relationships and optimize dialysis strategies based on body size and metabolic demand.
Renal recovery

Beyond mortality, renal recovery is a critical outcome in the evaluation of AKI and RRT [46], especially in obese ICU patients who may have complex renal trajectories. In our cohort, we observed that persistent AKI at ICU discharge was significantly more frequent in the KRT group than in the non-KRT group among survivors, suggesting a more prolonged renal insult in patients requiring RRT. Moreover, nearly 10% of patients in the RRT group remained dialysis-dependent at 1 year. These findings highlight the long-term renal burden associated with RRT in this population and suggest the need for ongoing follow-up after ICU discharge.

Limits

Our study bears several limitations. The retrospective, single-center uncontrolled design of the study is intrinsically subject to biases, and the absence of a control group of patients without obesity can limit the external validity of the study. The high incidence of patients with chronic liver disease is a direct consequence of the single- center design and may impact generalizability. Even though weight was determined on the day of admission, we cannot exclude that fluid overload may have affected BMI as well as outcomes. However, data on the general ICU population are numerous, allowing comparison with previous studies. We acknowledge that our analysis of 1-year outcomes was restricted to all-cause mortality and did not account for competing risks, such as non-renal causes of death. Notably, data on active malignancy at ICU admission were not systematically collected, thereby limiting our ability to adjust for this potential confounder.

Finally, although target dialysis doses were defined by local protocol, data on actual delivered doses were not systematically collected. This limits our ability to assess the adequacy of RRT dosing, particularly in the context of obesity. The impact of anticoagulation, a potential issue in patients with obesity, in whom dosing and monitoring can be challenging, was not analyzed in our study and should be addressed in future prospective studies.

Conclusion

This cohort of 2192 patients with obesity highlights a significant and independent association
between KRT and 90-day mortality after ICU admission. Considering the high mortality in
our study, further randomized, controlled trials are needed to better define optimal
management strategies in this high-risk population.

Abbreviations

AKI: Acute kidney Injury; BMI: Body mass index; ICU: Intensive care unit; KRT: Kidney replacement therapy; CKRT: Continuous kidney replacement therapy; UO: Urine output; SCr: Serum creatinine; CI: Confidence interval; OR: Odds ratio.
**Acknowledgements**

Not applicable.

Author contributions

CM had a major role in the acquisition of data as well as writing the manuscript. JB had a major role in the acquisition of data. TR, YA, MC, CL, JP, IL made substantial contributions to the writing of the manuscript. ADJ made substantial contributions to the conception of the work as well as contributions to the draft and revisions of the work. ADJ and JP had a major role in the analysis of the data. YA, MC, JP, IL, LM, and CR made substantial contributions to the conception of the work and interpretation of data. SJ was a substantial contributor to designing the work as well as the interpretation of the data. SJ revised the work in its entirety. All the authors read and approved the final manuscript.

**Funding**

Institutional University Hospital of Montpellier; France.

**Data availability**

The datasets used and/or analyzed during the current study are available from the
corresponding author on reasonable request.

**Declarations**

**Conflicts of interest**

Pr. Jaber is the Editor in Chief for Intensive Care Medicine journal and reports receiving consulting fees from Drager, Medtronic, Mindray, Fresenius, Baxter, and Fisher & Paykel. Pr. De Jong reports receiving remuneration for presentations from Medtronic, Drager, and Fisher & Paykel. Dr. Monet reports receiving remuneration for presentations from Medtronic. The other authors declare that they have no competing interests.

**Ethics approval and consent to participate**

The institutional ethics committee reviewed the retrospective use of anonymous data for scientific purpose and waived the need to obtain informed written consent. The Institutional Review Board (IRB) of Montpellier University Hospital approved the study (2019_IRB-MTP_05-25).

**Consent for publication**

Not applicable.
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