DOI: 10.5061/dryad.sqv9s4nht
title: 90-day mortality in AKI-D and CKD5-D patients admitted to the ICU

description: Acute kidney injury (AKI) and chronic kidney disease (CKD)
 are related conditions commonly encountered in intensive care.
 While both may require renal replacement therapy (RRT), critically ill
 patients with dialysis-requiring AKI have significantly higher mortality
 and poor clinical outcomes than those with end-stage CKD. To compare
 90-day mortality between patients with KDIGO stage 3 dialysis-requiring
 AKI (AKI-D) and those with stage 5 dialysis-dependent CKD (CKD5-D)
 admitted to the ICU. Secondary objectives were to identify independent
 predictors of increased 90-day mortality among AKI-D and CKD5-D patients,
 and to identify independent predictors of RRT at 90 days among patients
 who experienced an episode of AKI-D. This retrospective, single-center
 cohort study included adult patients with AKI-D or CKD5-D admitted to the
 ICU of a private quaternary hospital in São Paulo, Brazil. The study was
 approved by the Research Ethics Committee (CEP) of the Federal University
 of São Paulo, with a waiver of informed consent. The primary outcome was
 90-day mortality. Multivariable logistic regression was used to identify
 independent predictors of mortality and dialysis dependence. A total of
 2,377 patients were included: 1,878 (79%) with AKI-D and 499 (21%) with
 CKD5-D. The overall 90-day mortality was 42.5%, significantly higher in
 the AKI-D (50.3% vs. 13.2%; p &lt;0.001) compared to CKD5-D group.
 Independent predictors of 90-day mortality among AKI-D and CKD5-D patients
 included older age, the need for vasoactive drugs, mechanical ventilation
 and diagnosis of sepsis. Among 731 AKI-D survivors assessed at 90 days,
 175 (23.9%) remained dialysis-dependent. Risk factors for persistent
 dialysis dependence included older age, coronary artery disease, clinical
 (non-surgical) admission, and higher baseline creatinine. The risk of
 death in critically ill patients with AKI-D was more than three times
 higher than in individuals with CKD5-D. Although both AKI-D and CKD5-D
 patients experience loss of renal function, the factors correctable by
 dialysis alone do not account for the mortality difference between these
 groups. Rather, the severity of the acute illness, reflected by the need
 for invasive mechanical ventilation and vasoactive drugs, emerged as key
 determinants of short-term outcomes in this cohort.
description: <strong>Study Design</strong> This
 was a retrospective, single-center cohort study approved by the Research
 Ethics Committee (CEP) of the Federal University of São Paulo – UNIFESP
 (CAAE: 27698819300005505), with a waiver of informed consent. This study
 is reported in accordance with the Strengthening the Reporting of
 Observational studies in Epidemiology (STROBE) statement.
 <strong>Setting</strong> The study
 was conducted in the Adult Intensive Care Unit (ICU) of Einstein Hospital
 Israelita, a private quaternary care hospital located in São Paulo,
 Brazil. At the time of the study, the general ICU had 41 beds and provided
 care to both clinical and surgical patients. Through a partnership with
 the Brazilian Ministry of Health (Sistema Único de Saúde [SUS]), the ICU
 also managed patients involved in solid organ transplantation programs,
 including transplant candidates, those on waiting lists, and recipients of
 kidney, liver, lung, heart, pancreas, and multivisceral
 transplantation. <strong>Study
 participants</strong> Adult patients who
 underwent dialysis during their ICU stay between January 1, 1999, and
 December 31, 2015, were eligible for inclusion. Exclusion criteria
 included patients younger than 18 years of age, those receiving
 extracorporeal therapy for exogenous intoxication, patients whose initial
 dialysis modality was peritoneal dialysis, those transferred to other
 facilities, or those with incomplete data. For patients with multiple ICU
 admissions, only the first ICU stay was included in the analysis
 <strong>Data collection and study
 variables</strong> Data were obtained from the
 Epimed Monitor System® (Epimed Solutions, Rio de Janeiro, Brazil), an
 electronic structured case report form in which trained ICU case managers
 entered patient data prospectively and a nephrology-specific database
 developed by the hospital’s multidisciplinary team. All data were
 anonymized prior to analysis. Collected variables
 included demographic characteristics, comorbidities, and history of solid
 organ transplantation, presence of sepsis, reason for ICU admission,
 baseline renal function, initial RRT modality, severity scores at ICU
 admission, including the Acute Physiology and Chronic Health Evaluation II
 (APACHE II) and the Simplified Acute Physiology Score 3 (SAPS 3). APACHE
 II data were available from 1999 to 2012, and SAPS 3 was adopted from 2013
 onward following the implementation of the Epimed® system. Additionally,
 information was collected on the ICU and hospital length of stay (LOS),
 use of vasoactive drugs and need for mechanical ventilation during the ICU
 stay, and mortality (ICU, in-hospital, and 90-day post-ICU
 admission). <strong>Definitions and RRT
 modalities</strong> Patients were divided into
 two groups (AKI-D and CKD5-D) according to the type of kidney failure.
 Patients with pre-existing CKD5-D were defined as those with documented
 CKD and on regular RRT for at least three months prior to ICU
 admission. Baseline renal function was defined using
 the most recent serum creatinine values available prior to
 hospitalization. When such values were unavailable, the first creatinine
 measurement upon admission was used. Baseline glomerular filtration rate
 was estimated using the Chronic Kidney Disease Epidemiology Collaboration
 (CKD-EPI) 2021 equation. Recovery of renal function was defined as
 independence from RRT. Two primary RRT modalities were
 used: intermittent hemodialysis (IHD) and continuous venovenous
 hemodiafiltration (CVVHDF). CVVHDF was directed at patients with
 hemodynamic instability, severe neurological injury, and/or intracranial
 hypertension, requiring strict metabolic and volume control. The Prisma®
 or Prismaflex® (Gambro Lundia AB, Lund, Sweden) systems were used, with
 M100 or M150 filters (AN69 dialyzer membrane) and a blood flow rate of 100
 to 120 mL/min. Beginning in 1999, regional citrate anticoagulation was
 employed, with citrate infusion limited to 2.5 mmol/L in cases of liver
 dysfunction (INR ≥ 2.5). The minimum prescribed continuous dialysis dose
 was 25 mL/kg/h. For IHD, the Fresenius 4008
 hemodialysis machine (Fresenius Medical Care AG, Bad Homburg, Germany) was
 used, with a blood flow of 300–400 mL/min and dialysate flow of 500–800
 mL/min. When feasible, the dialysis target was a urea reduction ratio ≥ 65
 % and Kt/V ≥ 1.2 per session. Anticoagulation was not routinely used
 during IHD; only priming with 100 mL of 0.9 % NaCl every 15 minutes was
 performed.
 <strong>Outcomes</strong> Our
 primary outcome of interest was 90-day mortality.
 <strong>Statistical Analysis</strong>
 Categorical variables were expressed as absolute and relative
 frequencies, while continuous variables were presented as median and
 interquartile range (IQR). Comparisons were performed between AKI-D and
 CKD5-D groups. Categorical variables were compared with chi-square test or
 Fisher's exact test as appropriate. Continuous variables were
 compared using an independent t-test or Mann-Whitney U test in cases of
 non-normal distribution. Normality was assessed using the Shapiro-Wilk
 test. To identify independent predictors of 90-day
 mortality, analyses were conducted in the AKI-D and CKD5-D groups
 separately. Variables with a p-value &lt; 0.20 in the univariate
 analysis were included in the multivariate analysis, which used a multiple
 logistic regression model to estimate odds ratios (OR) and 95% confidence
 intervals (95 % CI). Multicollinearity was assessed using the variance
 inflation factor (VIF), with values &gt; 5 indicating significant
 collinearity. The linearity assumption for continuous variables included
 in the model was evaluated both graphically and using the likelihood ratio
 test. Variable selection was performed using the stepwise method, and
 model fit was assessed using the Hosmer-Lemeshow goodness-of-fit test. The
 analysis of predictors of dialysis dependence at 90 days was restricted to
 patients with AKI-D who survived, had not undergone isolated or combined
 kidney transplantation, and had available renal function data at 90 days
 post-ICU admission. This analysis followed the same methodology used for
 the 90-day mortality outcome. Statistical significance
 was set at p &lt; 0.05. All analyses were performed using R software,
 version 4.3.4 (www.r-project.org).
description: # 90-day mortality in AKI-D and CKD5-D patients admitted to the ICU
 Dataset DOI:
 [10.5061/dryad.sqv9s4nht](https://doi.org/10.5061/dryad.sqv9s4nht) ##
 Description of the data and file structure **90-DAY MORTALITY IN AKI-D AND
 CKD 5-D PATIENTS ADMITTED TO THE ICU** **File structure** The
 de-identified data bank presented here has been used for the analyses
 reported in the manuscript "90-day mortality in AKI-D and CKD 5-D
 patients admitted to the ICU." The file contains baseline
 characteristics (age, gender, race), comorbidities, rrt characteristics,
 and ICU and hospital stay characteristics. To maintain data anonymization,
 time-related variables (namely, ICU length of stay and hospital length of
 stay) have been modified using random noise to reduce their
 identifiability while preserving their analytical utility. Additionally,
 to mask the identification of patients, their age has been categorized
 according to the interquartile range. Some data points may be missing due
 to incomplete patient records or unavailable information in the electronic
 health record system. Missing data have been left as empty cells. **Data
 description** ·      age (categorical): patient age at hospital admission
 (years) categorized according to quartiles; 1 (age &lt; 51); 2 (51 ≤ age
 &lt; 63); 3 (63 ≤ age &lt; 76); 4 (age ≥ 76) ·      gender
 (categorical): 1 (female); 2 (male) ·      race (categorical): 1
 (asian_descent); 2 (black); 3 (mixed); 4 (white); ·      diabetes_mellitus
 (categorical): 0 (no); 1 (yes) ·      systemic \_arterial_hypertension
 (categorical): 0 (no); 1 (yes) ·      hepatic_disease (categorical): 0
 (no); 1 (yes) ·      cardiac_insufficiency (categorical): 0 (no); 1 (yes)
 ·      coronary_insufficiency (categorical): 0 (no); 1 (yes) ·     
 chronic_pneumopathy (categorical): 0 (no); 1 (yes) ·      neoplasia
 (categorical): 0 (no); 1 (yes) ·      malignant_hematologic_disease
 (categorical): 0 (no); 1 (yes) ·      bone_marrow_transplant
 (categorical): 0 (no); 1 (yes) ·      solid_organ_transplant
 (categorical): 0 (no); 1 (yes) ·      type_organ_transplant (categorical):
 1 (kidney); 2 (liver); 3 (heart); 4 (pancreas and kidney); 5 (lung); 6
 (not applicable ); 7 (liver and kidney ); 8 (multivisceral); 9 (heart and
 kidney); 10 (pancreas)  ·      apacheII: (numerical): APACHE II score at
 ICU admission – it was available until 2012; ·      saps3 (numerical):
 SAPS 3 score at ICU admission – it was implemented from 2013 onward ·     
 vasoactive_drug (categorical): 0 (no); 1(yes) – during ICU stay ·     
 mechanical_ventilation (categorical): 0 (no); 1(yes) – during ICU stay
 ·      cause_icu_admission (categorical): 1 (infection); 2 (cardiovascular
 disease); 3 (pancreatitis); 4 (bleeding); 5 (drug toxicity); 6 (urgent
 surgery); 7 (trauma); 8 (major burn); 9 (elective surgery ); 10
 (transplant); 11 (neurologic disease/alteration); 12 (respiratory failure
 ); 13 (metabolic disfunction); 14 (liver failure) ·      type_patient
 (categorical): 1 (clinical); 2 (surgical) ·      first_rrt (first renal
 replacement therapy modality) (categorical): 1 (CVVHDF: continuous
 venovenous hemodiafiltration; 2 (IHD: intermittent hemodialysis) ·     
 los_icu (numerical): ICU length of stay, in days; ·      los_hosp
 (numerical): hospital length of stay, in days ·      discharge_without_rrt
 (categorical): 0 (no); 1(yes) ·      without_rrt_90d (categorical): 0
 (no); 1(yes) ·      icu_outcome (categorical): 1 (death); 2 (dialiysis
 dependent at icu discharge); 3 (renal recovery = dialysis independent)
 ·      hospital_outcome (categorical): 1 (death); 2 (dialiysis dependent
 at hospital discharge); 3 (renal recovery = dialysis independent) ·     
 death_90d (primary outcome) (categorical): 0 (no); 1(yes) – not alive 90
 days after icu admission ·      type_renal_failure (categorical): 1 (Acute
 Kidney Injury (AKI-D)); 3 (Chronic Kidney Disease (CKD5-D)) ·     
 baseline_creatinine (numerical): baseline creatinine in mg/dl ·     
 creatinine_hospital (numerical): first creatinine value available at
 hospital, mg/dl ·      rrt_90d (secondary outcome) (categorical): 0 (no);
 1(yes) - dialysis dependent 90 days after icu admission ·      sepsis
 (categorical): 0 (no); 1(yes) ·      sepsis_sources (categorical): 1
 (urinary tract); 2 (skin/soft tissue); 3 (abdominal); 4 (cadiovascular
 system); 5 (central nervous system); 6 (unknown source); 7 (respiratory);
 8 (not applicable ); 9 (bloodstream infection) ·      baseline_gfr_value
 (numerical): baseline glomerular filtration rate in ml/min; ·     
 baseline_gfr_stage (numerical): 1 (≥ 90 mL/min); 2 (89-60 mL/min); 3a
 (59-45 mL/min); 3b (44-30 mL/min); 4 (29-15 mL/min); 5 (&lt; 15 mL/min) -
 baseline glomerular filtration rate categorized **Code/software** R
 softaware (R Core Team (2024). R: A Language and Environment for
 Statistical Computing. R Foundation for Statistical Computing, Vienna,
 Austria. [https://www.R-project.org/](https://www.R-project.org/)) was
 used in all statistical analyses. ### Files and variables #### File:
 Raw_data_-*Dryad*.xls **Description:**  ##### Variables * ·      age
 (categorical): patient age at hospital admission (years) categorized
 according to quartiles; 1 (age &lt; 51); 2 (51 ≤ age &lt; 63); 3 (63 ≤ age
 &lt; 76); 4 (age ≥ 76) ·      gender (categorical): 1 (female); 2 (male)
 ·      race (categorical): 1 (asian_descent); 2 (black); 3 (mixed); 4
 (white) ·      diabetes_mellitus (categorical): 0 (no); 1 (yes) ·     
 systemic \_arterial_hypertension (categorical): 0 (no); 1 (yes) ·     
 hepatic_disease (categorical): 0 (no); 1 (yes) ·     
 cardiac_insufficiency (categorical): 0 (no); 1 (yes) ·     
 coronary_insufficiency (categorical): 0 (no); 1 (yes) ·     
 chronic_pneumopathy (categorical): 0 (no); 1 (yes) ·      neoplasia
 (categorical): 0 (no); 1 (yes) ·      malignant_hematologic_disease
 (categorical): 0 (no); 1 (yes) ·      bone_marrow_transplant
 (categorical): 0 (no); 1 (yes) ·      solid_organ_transplant
 (categorical): 0 (no); 1 (yes) ·      type_organ_transplant (categorical):
 1 (kidney); 2 (liver); 3 (heart); 4 (pancreas and kidney); 5 (lung); 6
 (not applicable ); 7 (liver and kidney ); 8 (multivisceral); 9 (heart and
 kidney); 10 (pancreas)  ·      apacheII: (numerical): APACHE II score at
 ICU admission – it was available until 2012 ·      saps3 (numerical): SAPS
 3 score at ICU admission – it was implemented from 2013 onward ·     
 vasoactive_drug (categorical): 0 (no); 1(yes) – during ICU stay ·     
 mechanical_ventilation (categorical): 0 (no); 1(yes) – during ICU stay
 ·      cause_icu_admission (categorical): 1 (infection); 2 (cardiovascular
 disease); 3 (pancreatitis); 4 (bleeding); 5 (drug toxicity); 6 (urgent
 surgery); 7 (trauma); 8 (major burn); 9 (elective surgery ); 10
 (transplant); 11 (neurologic disease/alteration); 12 (respiratory failure
 ); 13 (metabolic disfunction); 14 (liver failure); ·      type_patient
 (categorical): 1 (clinical); 2 (surgical) ·      first_rrt (first renal
 replacement therapy modality) (categorical): 1 (CVVHDF: continuous
 venovenous hemodiafiltration; 2 (IHD: intermittent hemodialysis) ·     
 los_icu (numerical): ICU length of stay, in days ·      los_hosp
 (numerical): hospital length of stay, in days ·      discharge_without_rrt
 (categorical): 0 (no); 1(yes) ·      without_rrt_90d (categorical): 0
 (no); 1(yes) ·      icu_outcome (categorical): 1 (death); 2 (dialiysis
 dependent at icu discharge); 3 (renal recovery = dialysis independent)
 ·      hospital_outcome (categorical): 1 (death); 2 (dialiysis dependent
 at hospital discharge); 3 (renal recovery = dialysis independent) ·     
 death_90d (primary outcome) (categorical): 0 (no); 1(yes) – not alive 90
 days after icu admission ·      type_renal_failure (categorical): 1 (Acute
 Kidney Injury (AKI-D)); 3 (Chronic Kidney Disease (CKD5-D)); ·     
 baseline_creatinine (numerical): baseline creatinine in mg/dl ·     
 creatinine_hospital (numerical): first creatinine value available at
 hospital, mg/dl ·      rrt_90d (secondary outcome) (categorical): 0 (no);
 1(yes) - dialysis dependent 90 days after icu admission ·      sepsis
 (categorical): 0 (no); 1(yes) ·      sepsis_sources (categorical): 1
 (urinary tract); 2 (skin/soft tissue); 3 (abdominal); 4 (cadiovascular
 system); 5 (central nervous system); 6 (unknown source); 7 (respiratory);
 8 (not applicable ); 9 (bloodstream infection0 ·      baseline_gfr_value
 (numerical): baseline glomerular filtration rate in ml/min; ·     
 baseline_gfr_stage (numerical): 1 (≥ 90 mL/min); 2 (89-60 mL/min); 3a
 (59-45 mL/min); 3b (44-30 mL/min); 4 (29-15 mL/min); 5 (&lt; 15 mL/min) -
 baseline glomerular filtration rate categorized ## Code/software R
 softaware (R Core Team (2024). R: A Language and Environment for
 Statistical Computing. R Foundation for Statistical Computing, Vienna,
 Austria. [https://www.R-project.org/](https://www.R-project.org/)) was
 used in all statistical analyses. ## Access information Other publicly
 accessible locations of the data: * None Data was derived from the
 following sources: * Epimed  * Specific data bank ## Human subjects data
 The study was approved by the Research Ethics Committee (CEP) of the
 Federal University of São Paulo, with a waiver of informed consent. Our
 research was conducted on human data in compliance with the Helsinki
 Declaration.