Kidney Res Clin Pract > Epub ahead of print
Kim, Ye, Kim, Lee, and Lee: Sarcopenia is independently associated with mortality and recovery from dialysis in critically ill patients with sepsis-induced acute kidney injury receiving continuous renal replacement therapy

Abstract

Background

Sarcopenia upon admission to the intensive care unit (ICU) consistently correlates with adverse outcomes, including heightened mortality, in critically ill patients. This study aims to investigate the independent association of sarcopenia with both mortality and recovery from dialysis in critically ill patients with sepsis-induced acute kidney injury (SIAKI) undergoing continuous renal replacement therapy (CRRT).

Methods

This retrospective study included 618 patients with SIAKI who underwent CRRT in our ICU. All patients had abdominal computed tomography (CT) scans within 3 days preceding ICU admission. The cross-sectional area of skeletal muscles at the third lumbar vertebra was quantified, and the skeletal muscle index (SMI), a normalized measure of skeletal muscle mass, was computed. Using Korean-specific SMI cutoffs, patients were categorized into sarcopenic and non-sarcopenic groups.

Results

Among the 618 patients, 301 expired within 28 days of ICU admission. Multivariable Cox regression analysis revealed that sarcopenia independently predicted 28-day mortality. Among survivors, sarcopenia was independently associated with recovery from dialysis within 28 days after ICU admission. Kaplan-Meier analysis illustrated that sarcopenic patients had a higher mortality rate and a lower rate of recovery from dialysis within 28 days after ICU admission compared to non-sarcopenic patients.

Conclusion

This study underscores the independent association of sarcopenia, assessed via CT-derived SMI, with both mortality and recovery from dialysis in critically ill patients with SIAKI undergoing CRRT. The inclusion of sarcopenia assessment could serve as a valuable tool for physicians in effectively stratifying the risk of adverse outcomes in these patients.

Introduction

Acute kidney injury (AKI) is a prevalent and severe complication observed in over half of critically ill patients [1]. Mortality rates among critically ill patients with AKI are documented to exceed 50%, reaching as high as 80% in cases necessitating renal replacement therapy (RRT) [2]. Sepsis stands as the primary instigator of AKI in intensive care unit (ICU)-admitted patients, contributing to roughly 40% to 50% of all AKI instances [3]. For critically ill patients experiencing hemodynamic instability, continuous RRT (CRRT) stands out as the primary method for dialysis. Despite advances in intensive care, such as CRRT, the mortality rate for critically ill patients with sepsis-induced AKI (SIAKI) undergoing CRRT remains at 50% to 60% [4]. Furthermore, a significant proportion of these patients continue to depend on dialysis upon hospital discharge [5].
Various methods for risk assessment, including disease severity scores and a range of biomarkers, have been integrated into the management of patients with AKI. These tools assess the likelihood of mortality and recovery from dialysis, offering essential insights for clinical decision-making [6]. Nevertheless, widely used prognostic instruments like Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) are criticized for their lack of accuracy and considerable variability in AKI patients [7]. Therefore, there is a need for disease-specific risk stratification tools to predict clinical outcomes, such as mortality and recovery from dialysis, in AKI patients, including critically ill individuals with SIAKI undergoing CRRT.
Sarcopenia, characterized by diminishing muscle mass, strength, and physical function, manifests with a nearly 20% reduction in skeletal muscle mass during the initial 10 days of ICU admission [8]. This loss of muscle mass is linked to prolonged mechanical ventilation and increased mortality [8]. Notably, a substantial number of patients already present with sarcopenia upon ICU admission, and its presence is significantly associated with higher mortality [812]. Despite numerous studies exploring the impact of sarcopenia on adverse outcomes in ICU patients, research specifically focused on those with AKI, particularly those undergoing CRRT, is limited. Additionally, investigations into the influence of sarcopenia on recovery from dialysis in AKI patients are scarce. Therefore, in light of the absence of risk stratification tools for assessing outcomes in AKI patients, our aim was to investigate whether the presence of sarcopenia at ICU admission holds prognostic value in predicting mortality and recovery from dialysis in patients with SIAKI undergoing CRRT.

Methods

All aspects of research and data collection adhered to the principles of the Declaration of Helsinki and prevailing ethical guidelines, receiving approval from the Institutional Review Board (IRB) of the Pusan National University Yangsan Hospital (No. 05-2022-091). Due to the retrospective nature of the analysis, utilizing de-identified information from medical charts and records, the requirement for informed consent was waived by the IRB.

Study population and data

Our study focused exclusively on patients admitted to the ICU at Pusan National University Yangsan Hospital between 2013 and 2022, employing a retrospective cohort design. Initially, we enrolled a total of 885 adult patients (aged ≥18 years) who experienced sepsis and AKI and underwent CRRT. Exclusion criteria comprised individuals with (a) end-stage renal disease on chronic dialysis or a history of kidney transplantation, (b) incomplete data pertaining to the skeletal muscle mass, and (c) death or discharge within 72 hours of CRRT initiation. As a result, 618 patients formed the basis for our analysis (Fig. 1).
Electronic medical records were scrutinized, and demographic and clinical data were collected upon ICU admission. This encompassed details such as age, sex, body weight, comorbidities (chronic kidney disease [CKD], hypertension, diabetes mellitus, chronic obstructive pulmonary disease [COPD], liver cirrhosis, congestive heart failure, solid cancer, and hematologic cancer), infection source (respiratory, gastrointestinal, urinary tract, and soft tissue), severity of illness (SOFA score, APACHE II, vasopressor use, and ventilator dependency), mean arterial pressure, fever, heart rate, and oliguria (<0.5 mL/kg/hr for 6 hours before CRRT initiation). Blood examinations, encompassing creatinine, blood urea nitrogen, potassium, sodium, leukocyte count, hemoglobin, platelet count, total bilirubin, albumin, prothrombin time/international normalized ratio (PT/INR), C-reactive protein, and lactate levels, were conducted upon CRRT initiation. Additionally, we explored the time intervals between AKI diagnosis and CRRT initiation, CRRT duration, and the prescribed CRRT dose.

Computed tomography image analysis

We assessed the cross-sectional area of skeletal muscle (SMA, cm2) by conducting single-slice abdominal computed tomography (CT) scans at the third lumbar vertebra (L3), a selected landmark known for its established correlation with overall muscle mass [13,14]. The measured SMA included the psoas, erector spinae, quadratus lumborum, transverse abdominal, internal and external obliques, and rectus abdominis (Fig. 2A).
CT scans, obtained within 3 days before or after ICU admission for diagnostic purposes, were retrieved from the hospital’s radiology system and stored for subsequent analysis. We included only patients who underwent non-enhanced CT to exclude the effect of radiocontrast agent on the kidneys. Utilizing open-source software (ImageJ) and trained personnel, we outlined the outer and inner perimeters of the abdominal muscles, along with the outer perimeter of the L3 vertebra. The SMA was then calculated by applying a muscle-specific threshold (–29 to +150) in Hounsfield units, following the approach outlined by Gomez-Perez et al. [15] (Fig. 2BD). The skeletal muscle index (SMI) was derived by adjusting for body size (SMA [cm2]/height [m2]). Using the SMI, patients were classified as either having sarcopenia or not, based on Korean-specific SMI thresholds: less than 39.33 cm2/m2 for males and less than 27.77 cm2/m2 [16]. Those falling below these thresholds were categorized as having sarcopenia.

Continuous renal replacement therapy protocol

CRRT protocol is summarized in Supplementary Methods (available online).

Definition and study outcome

Definitions of sepsis and AKI are provided in Supplementary Methods (available online). The primary outcome of the study was mortality within 28 days following admission to the ICU. Another outcome involved assessing recovery from dialysis among survivors, defined as the absence of any form of renal replacement therapy, including CRRT and intermittent hemodialysis, within 28 days after ICU admission.

Statistical analysis

Continuous variables were represented by medians and interquartile ranges (IQRs), and their comparison utilized the Mann-Whitney test. Categorical variables were conveyed as numbers and percentages, and their comparison employed the chi-square test. To ascertain independent predictors for mortality and recovery from dialysis within the initial 28 days of ICU admission, both univariable and multivariable Cox proportional hazards analyses were utilized. The outcomes were presented as hazard ratios (HRs) along with corresponding 95% confidence intervals (CIs). Significant variables were identified through univariable analysis (p < 0.1), with consideration of clinically important variables in the multivariable analysis. Variables present in the SOFA or APACHE II scores, such as mean arterial pressure, platelet count, pH, and serum creatinine, which demonstrated significance in the univariable analysis, were excluded from the multivariable analysis to prevent redundancy. Instead, the SOFA and APACHE II scores for these variables were factored into the final multivariable analysis. Additionally, a Kaplan-Meier analysis and log-rank test were executed to compare mortality and recovery from dialysis among groups, stratified by the presence of sarcopenia. Statistical significance was established at p < 0.05, and all analyses were conducted using IBM SPSS version 27.0 (IBM Corp.).

Results

Baseline characteristics at intensive care unit admission stratified by 28-day mortality after intensive care unit admission

CRRT was administered to 618 patients diagnosed with SIAKI. Among this cohort, 298 individuals (48.2%) met the criteria for sarcopenia based on specific SMI thresholds tailored for the Korean population. Within this subset, 301 patients succumbed to mortality within 28 days of their admission to the ICU. Table 1 elucidates the baseline characteristics of the study subjects, stratified according to their 28-day mortality status post-ICU admission. Concerning demographic factors, non-survivors exhibited an advanced age compared to survivors, with no statistically significant differences noted in terms of sex or body weight between the two cohorts. Regarding comorbidities, non-survivors presented a higher prevalence of COPD, liver cirrhosis, congestive heart failure, and solid cancer compared to survivors. There were no significant variations in the sources of infection between the two cohorts. In relation to the severity of illness, non-survivors manifested higher SOFA and APACHE II scores, along with an elevated incidence of vasopressor use and ventilator dependency, in contrast to survivors. Upon admission to the ICU, non-survivors exhibited lower mean arterial pressure, platelet count, and pH levels compared to survivors. Additionally, non-survivors demonstrated a higher prevalence of oliguria, elevated prothrombin time, and increased lactate levels. The time interval between the diagnosis of AKI and the initiation of CRRT was significantly longer in non-survivors than in survivors. There were no notable differences in the prescribed CRRT doses between the two cohorts. Regarding SMI, non-survivors displayed lower SMI levels at ICU admission compared to survivors (median, 28.7 [IQR, 23.8–36.4] vs. 38.9 [IQR, 32.8–44.6], p < 0.001). In terms of sarcopenia, non-survivors exhibited a higher prevalence of sarcopenia compared to survivors (66.1% vs. 31.2%, p < 0.001).

Baseline characteristics at intensive care unit admission stratified by 28-day recovery from dialysis among survivors

Out of the 317 individuals who survived, 136 patients achieved successful recovery from dialysis within the initial 28 days of their ICU admission. The fundamental characteristics, organized based on the recovery from dialysis within the first 28 days of initiating CRRT, are intricately delineated in Table 2. Those who attained recovery from dialysis showcased a lower incidence of CKD compared to those who persisted in requiring dialysis. Regarding the severity of their condition upon ICU admission, individuals who experienced recovery from dialysis demonstrated lower SOFA and APACHE II scores, coupled with a decreased need for vasopressors and ventilator support, in contrast to their dialysis-dependent counterparts. This subset of patients who recovered from dialysis exhibited a reduced occurrence of oliguria and lower levels of serum creatinine and lactate compared to their counterparts dependent on dialysis. In relation to SMI, those who successfully recovered from dialysis presented higher SMI levels at ICU admission than individuals dependent on dialysis (median, 43.1 [IQR, 37.3–54.2] vs. 35.9 [IQR, 27.8–42.2], p < 0.001). Regarding the presence of sarcopenia, patients who achieved recovery from dialysis demonstrated a decreased prevalence of sarcopenia compared to their dialysis-dependent counterparts (14.7% vs. 17.0%, p < 0.001).

Association between sarcopenia and 28-day mortality after intensive care unit admission

The Kaplan-Meier curve depicted a significantly elevated mortality rate among patients diagnosed with sarcopenia compared to those without sarcopenia (28-day mortality: 31.9% vs. 66.8%, p < 0.001) (Fig. 3A). Table 3 provides an overview of the variables demonstrating associations with 28-day mortality in the univariable Cox regression analysis. Sarcopenia emerged as a noteworthy predictor of 28-day mortality (compared to non-sarcopenia: HR, 2.66; 95% CI, 2.09–3.38; p < 0.001). Additionally, age, COPD, liver cirrhosis, congestive heart failure, solid cancer, SOFA score, APACHE II score, vasopressor use, ventilator use, mean arterial pressure, oliguria, platelet count, pH, lactate, and time from AKI diagnosis to CRRT initiation were also identified as substantial predictors of 28-day mortality. In the multivariable Cox regression analysis, sarcopenia maintained its status as an independent predictor of 28-day mortality (compared to non-sarcopenia: HR, 1.83; 95% CI, 1.42–2.38; p < 0.001). Furthermore, congestive heart failure, SOFA score, APACHE II score, oliguria, lactate, and the time interval from AKI diagnosis to CRRT initiation were recognized as independent predictors of 28-day mortality.
Following this, an investigation was carried out to probe the connection between sarcopenia and 28-day mortality in subgroups categorized by age, sex, CKD, SOFA score, and the time from AKI diagnosis to the initiation of CRRT (Fig. 4A). By utilizing the median SOFA score and time from AKI diagnosis to CRRT initiation as benchmarks, all participants in the study were sorted into either the high SOFA group (>14 points) or the low SOFA group (≤14 points), and the late CRRT group (>1.0 day) or the early CRRT group (≤1.0 day). The results of the multivariable Cox regression analysis disclosed sarcopenia as an independent predictor of 28-day mortality across predefined subgroups, encompassing age categories (>65 or ≤65 years), sex (male or female), presence or absence of CKD, severity of illness (high SOFA or low SOFA), and timing of CRRT initiation (early or late).

Association between sarcopenia and 28-day recovery from dialysis after intensive care unit admission

The Kaplan-Meier curve demonstrated a significantly lower rate of recovery from dialysis in patients with sarcopenia compared to those without sarcopenia (28-day recovery rate from dialysis: 20.2% vs. 53.2%, p < 0.001) (Fig. 3B). Table 4 offers a comprehensive summary of the variables linked to the 28-day recovery from dialysis post-ICU admission among survivors. Univariate Cox regression analysis revealed sarcopenia as a predictor for recovery from dialysis (compared to non-sarcopenia: HR, 0.30; 95% CI, 0.19–0.49; p < 0.001). Moreover, CKD, SOFA and APACHE II scores, vasopressor and ventilator use, and oliguria were independently associated with recovery from dialysis. The multivariate Cox regression analysis confirmed sarcopenia’s independent predictor status for recovery from dialysis (compared to non-sarcopenia: HR, 0.42; 95% CI, 0.26–0.68; p < 0.001). Additionally, oliguria, SOFA score, and APACHE II score retained independent associations with recovery from dialysis. Furthermore, sarcopenia remained an independent predictor of dialysis recovery within 28 days after ICU admission across the subgroups (Fig. 4B).

Discussion

In the present study, we discovered that 48.5% of critically ill patients with SIAKI undergoing CRRT were sarcopenic, confirming the high prevalence of sarcopenia in this population. Notably, individuals with sarcopenia upon ICU admission experienced significantly higher mortality and a lower rate of recovery from dialysis compared to those without sarcopenia. Furthermore, sarcopenia was found to be an independent predictor for mortality and recovery from dialysis at 28 days for these patients. Importantly, this observation held true independently of other well-known prognostic factors for these patients, including SOFA and APACHE II scores.
This research focused on assessing sarcopenia by measuring skeletal muscle mass using a single cross-sectional CT image at the L3 vertebra. CT imaging is widely acknowledged as the gold standard for evaluating body composition, and assessing cross-sectional muscle areas at specific anatomical sites provides a convenient approach for estimating skeletal muscle mass with CT imaging [16]. The quantitative evaluation of cross-sectional SMA using CT imaging is typically carried out at the L3 level, showing a substantial correlation with overall body muscle mass [14,16,17].
One of the pivotal findings of the current study is that sarcopenia at ICU admission independently predicts mortality at 28 days in critically ill patients with SIAKI undergoing CRRT. Consistent with our findings, previous studies have demonstrated that sarcopenia at ICU admission is independently associated with adverse outcomes, including higher mortality and fewer ventilator-free and ICU-free days [812,18]. In the context of critically ill patients with sepsis, a few studies have been reported. Oh et al. [18] found that sarcopenia was associated with both short-term and long-term mortality in 905 patients with septic shock. Lee et al. [19] showed that muscle mass depletion was associated with mortality in 274 patients with sepsis. Regarding patients with AKI, only one study has been reported. Jung et al. [12] demonstrated that muscle mass could be a determining factor for mortality in 2,200 patients with AKI undergoing CRRT. Taken together, our study has demonstrated that sarcopenia is an independent predictor of mortality in a specific group of critically ill patients, namely those with SIAKI undergoing CRRT, contributing to the growing body of research supporting the independent association between sarcopenia and mortality in critically ill patients.
While sarcopenia demonstrates an independent association with mortality in our study subjects, the underlying mechanisms governing these associations remain unclear. In numerous instances, malnutrition and the depletion of muscle mass manifest concomitantly, marked by a reduction in nutrient intake, body weight, and physical activity [18]. These factors collectively contribute to a decline in muscle mass, strength, and physical function. The depletion of muscle mass emerges as a primary factor suppressing amino acid and protein synthesis in response to biological changes in the immune system [18]. This suggests that sarcopenic patients may exhibit heightened vulnerability to newly developed infections and a worsening of existing infection status due to an impaired immune system compared to non-sarcopenic patients [18]. Furthermore, individuals with low muscle mass experience a state of chronic inflammatory conditions, and the promotion of a catabolic state through this chronic inflammation further deteriorates organ functions, including the kidneys. Lastly, hormonal dysregulation observed in AKI patients, including altered levels of growth hormone, testosterone, thyroid hormone, and insulin-like growth factor-1, contributes to a poor clinical outcome by increasing protein degradation and suppressing protein synthesis [12]. The mechanism underlying the causal relationship between sarcopenia and mortality in patients with SIAKI receiving CRRT should be clarified in future clinical and experimental studies.
Another principal finding of our current study is that sarcopenia at ICU admission independently predicts recovery from dialysis at 28 days in critically ill patients with SIAKI undergoing CRRT. To our knowledge, our study is the first to establish the independent relationship between sarcopenia and recovery from dialysis in AKI patients receiving CRRT. Moreover, our results reveal that CKD, SOFA scores, APACHE II scores, and oliguria—previously identified as predictors of recovery from dialysis in CRRT patients—also independently predict recovery from dialysis in SIAKI patients undergoing CRRT. These findings suggest that, beyond traditional predictors, sarcopenia is a predictive factor for recovery from dialysis in SIAKI patients receiving CRRT. The underlying mechanism for the relationship between sarcopenia and recovery from dialysis in our study remains unclear. While the pathophysiology of SIAKI involves tubular necrosis, tubular apoptosis, and endothelial damage, the systemic inflammatory response during sepsis emerges as a key factor in SIAKI development [3]. Therefore, it can be hypothesized that factors worsening inflammation in SIAKI interfere with renal recovery. As mentioned earlier, patients with sarcopenia are in a state of chronic inflammation and may experience an augmented inflammatory reaction during SIAKI [12]. Consequently, this heightened inflammatory response may contribute to a lower likelihood of recovery from dialysis in these patients. We believe that further experimental and clinical research is warranted to explore and elucidate these associations.
Our study has some limitations. Firstly, due to its retrospective design, establishing a causal relationship between sarcopenia and mortality or recovery from dialysis proved challenging, making it difficult to draw definitive conclusions regarding the clinical effects of sarcopenia in our study subjects. Furthermore, while we endeavored to conduct the analysis by incorporating as many variables as possible known to influence study outcomes, data on other potential factors such as nutritional status, pre- and post-SIAKI physical activity levels, and specific treatment modalities that could impact outcomes were not obtained due to the retrospective nature of this study. We believe that future studies including these variables could consolidate the results of our study. Secondly, our study focused on a specific subset of critically ill patients, namely those with SIAKI who underwent CRRT. This introduces a potential selection bias, limiting the generalizability of our findings to other populations of critically ill patients with AKI. Additionally, CT scans were conducted based on clinical indications rather than a standardized study protocol. Consequently, patients with SIAKI who did not undergo CT scans were excluded, creating another source of selection bias. Thirdly, we defined sarcopenia using CT scan-derived skeletal muscle area. While previous studies support the utility of CT scan-derived skeletal muscle area in predicting adverse outcomes in critically ill patients [812,18], and its correlation with total muscle mass in healthy subjects [14] and cancer patients [17], this validation was not conducted within our study population. Furthermore, the Asian Working Group for Sarcopenia recommends using dual-energy X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) to measure appendicular muscle mass for assessing sarcopenia [20], suggesting the need for future studies using alternative methods like DXA or BIA to validate our results. Lastly, our study focused exclusively on Korean patients, utilizing Korean-specific SMI thresholds to define sarcopenia. Therefore, caution is warranted when extrapolating our findings to other ethnic groups.
Despite these limitations, our study has several strengths. Firstly, it is the first investigation to date exploring the association between sarcopenia and recovery from dialysis, in addition to mortality, in patients with AKI undergoing CRRT. Secondly, our study included a relatively large cohort of patients (n = 618), comparable to previous studies examining the prognostic value of sarcopenia in critically ill patients. Thirdly, our multivariable analysis spanned various subgroups, incorporating adjustments for significant confounding variables known to impact mortality and recovery from dialysis in AKI patients undergoing CRRT, such as CKD, oliguria, SOFA scores, APACHE II scores, and the interval time from AKI diagnosis to CRRT initiation. Collectively, these findings contribute robust evidence supporting the association between sarcopenia and mortality or recovery from dialysis in patients with SIAKI undergoing CRRT.
In conclusion, the presence of sarcopenia upon ICU admission, assessed by skeletal muscle mass on CT scans, was found to be a predictor of mortality and recovery from dialysis at 28 days in patients with SIAKI undergoing CRRT. Importantly, this association remains independent of commonly used risk factors for adverse outcomes in this population. We suggest that the inclusion of sarcopenia, along with traditional prognostic factors, could assist physicians in risk stratification for adverse outcomes, enabling timely interventions in patients with SIAKI undergoing CRRT. Furthermore, we advocate for future prospective studies to investigate whether interventions targeting the improvement of sarcopenia could influence patient outcomes in this specific patient population.

Supplementary Materials

Supplementary data are available at Kidney Research and Clinical Practice online (https://doi.org/10.23876/j.krcp.24.015).

Notes

Conflicts of interest

All authors have no conflicts of interest to declare.

Funding

This work was supported by a 2-Year Research Grant of Pusan National University.

Data sharing statement

The data presented in this study are available upon reasonable request to the corresponding author.

Authors’ contributions

Conceptualization: IYK, SBL

Data curation: All authors

Formal analysis: All authors

Funding acquisition: SBL

Investigation: IYK, BMY, SRK, DWL

Writing–original draft: IYK

Writing–review & editing: IYK, SBL

All authors read and approved the final manuscript.

Figure 1.

Flow diagram of the study population.

CRRT, continuous renal replacement therapy; SIAKI, sepsis-induced acute kidney injury.
j-krcp-24-015f1.jpg
Figure 2.

Example of computed tomography scan analysis.

(A) The skeletal muscle area at the third lumbar vertebra. (B–D) The skeletal muscle tissues quantified are highlighted in red. Measurement technique using ImageJ. After adjusting the threshold between –250 and +1,000, we traced the outer muscle perimeter (yellow contour in B), the outer muscle perimeter (yellow contour in C), and the vertebral body perimeter (yellow contour in D), respectively, with the freehand selection tool. These measurements were obtained after adjusting the threshold between –29 and +150. The skeletal muscle area can be calculated by subtraction (A–B–C).
j-krcp-24-015f2.jpg
Figure 3.

Outcomes according to the presence of sarcopenia at ICU admission in patients with sepsis-induced acute kidney injury receiving continuous renal replacement therapy.

(A) Probability of survival and (B) recovery from dialysis. Among all participants (n = 618), individuals with sarcopenia exhibited a notable elevation in mortality compared to those without sarcopenia (28-day mortality: 31.9% vs. 66.8%, p < 0.001). In the subset of survivors (n = 317), those with sarcopenia demonstrated a significantly reduced likelihood of recovering from dialysis compared to those without sarcopenia (28-day recovery rate from dialysis: 20.2% vs. 53.2%, p < 0.001).
ICU, intensive care unit.
j-krcp-24-015f3.jpg
Figure 4.

Hazard ratio plots of sarcopenia for mortality (A) and recovery from dialysis (B) in predefined subgroups.

Among all study participants (n = 618), the multivariable Cox regression analysis indicated that sarcopenia independently predicted 28-day mortality in predefined subgroups, including age >65 or ≤65 years, male or female sex, high SOFA group or low SOFA group, and early CRRT group or late CRRT group. In survivors (n = 317), sarcopenia independently predicted 28-day recovery from dialysis across predefined subgroups.
AKI, acute kidney injury; CI, confidence interval; CKD, chronic kidney disease; CRRT, continuous renal replacement therapy; SOFA, Sequential Organ Failure Assessment.
j-krcp-24-015f4.jpg
Table 1.
Baseline characteristics stratified 28-day mortality after ICU admission (n = 618)
Characteristic Survivor Non-survivor p-value
Demographics
 No. of subjects 317 301
 Age (yr) 69 (58–77) 72 (62–80) 0.004
 Male sex 190 (59.9) 178 (59.1) 0.84
 Body mass index (kg/m2) 23.9 (21.8–25.5) 23.3 (21.8–25.2) 0.27
Comorbid disease
 Chronic kidney disease 69 (21.8) 79 (26.2) 0.19
 Hypertension 161 (50.8) 172 (57.1) 0.11
 Diabetes mellitus 111 (35.0) 118 (39.2) 0.28
 COPD 29 (9.1) 54 (17.9) 0.001
 Liver cirrhosis 35 (11.0) 65 (21.6) <0.001
 Congestive heart failure 34 (10.7) 58 (19.3) 0.003
 Solid cancer 53 (16.7) 72 (23.9) 0.03
 Hematologic cancer 19 (6.0) 21 (7.0) 0.62
Infection source
 Respiratory 113 (35.6) 111 (36.9) 0.75
 Gastrointestinal 95 (30.0) 101 (33.6) 0.34
 Urinary tract 90 (28.4) 69 (22.9) 0.12
 Soft tissue 9 (2.8) 13 (4.3) 0.32
 Unknown 10 (3.2) 7 (2.3) 0.53
Severity of illness at ICU admission
 SOFA score 11 (6–15) 17 (13–20) <0.001
 APACHE II score 24 (21–30) 32 (28–35) <0.001
 Vasopressors use 109 (34.4) 207 (68.8) <0.001
 Ventilator dependency 91 (28.7) 225 (74.8) <0.001
Findings at ICU admission
 Mean arterial pressure (mmHg) 80 (70–93) 66 (55–82) <0.001
 Fever or hypothermia 119 (37.5) 112 (37.2) 0.93
 Heart rate (beat/min) 97 (79–115) 99 (82–115) 0.45
 Oliguria for 6 hours before CRRT (<0.5 mL/kg/hr) 88 (27.8) 202 (67.1) <0.001
 Creatinine (mg/dL) 2.6 (2.3–3.4) 2.7 (2.4–4.0) 0.12
 Blood urea nitrogen (mg/dL) 50.0 (41.4–69.9) 51.6 (41.0–70.2) 0.87
 Sodium (meq/L) 136 (130–141) 135 (130–141) 0.96
 Potassium (meq/L) 4.5 (4.0–5.1) 4.7 (4.0–5.3) 0.18
 Leukocyte count (1,000/mm3) 12.9 (10.1–18.9) 13.4 (9.7–19.3) 0.67
 Hemoglobin (g/dL) 9.1 (7.9–10.8) 9.4 (7.7–11.0) 0.84
 Platelet count (1,000/mm3) 115 (71–161) 80 (53–118) <0.001
 Total bilirubin (mg/dL) 1.8 (0.8–4.0) 1.9 (0.5–4.2) 0.81
 Albumin (g/dL) 2.7 (2.3–3.1) 2.6 (2.3–3.1) 0.26
 PT/INR 1.6 (1.3–1.9) 1.7 (1.5–2.0) 0.003
 C-reactive protein (mg/dL) 11.3 (6.8–25.4) 14.0 (7.7–26.2) 0.12
 pH 7.28 (7.23–7.35) 7.22 (7.16–7.31) <0.001
 Lactate (mmol/L) 2.8 (1.9–6.8) 7.5 (4.3–11.6) <0.001
CRRT
 Interval time from AKI diagnosis to CRRT initiation (day) 0.3 (0.3–1.4) 1.6 (0.9–2.4) <0.001
 Prescribed CRRT dose (mL/kg/hr) 37.6 (35.4–39.9) 37.5 (35.1–40.0) 0.71
Skeletal muscle index (cm2/m2) 38.9 (32.8–44.6) 28.7 (23.8–36.4) <0.001
Sarcopenia 99 (31.2) 199 (66.1) <0.001

Values are expressed as number only, median (interquartile range), or number (%).

AKI, acute kidney injury; APACHE II, Acute Physiology and Chronic Health Evaluation II; COPD, chronic obstructive pulmonary disease; CRRT, continuous renal replacement therapy; ICU, intensive care unit; PT/INR, prothrombin time/international normalized ratio; SOFA, Sequential Organ Failure Assessment.

Table 2.
Baseline characteristics stratified by 28-day recovery from dialysis after ICU admission among the survivors (n = 317)
Characteristic Dialysis dependence Recovery from dialysis p-value
Demographics
 No. of subjects 181 136
 Age (yr) 69 (59–79) 68 (58–75) 0.07
 Male sex 102 (56.4) 88 (64.7) 0.13
 Body mass index (kg/m2) 23.0 (21.8–25.4) 23.9 (21.7–25.7) 0.76
Comorbid disease
 Chronic kidney disease 60 (33.1) 9 (6.6) <0.001
 Hypertension 97 (53.6) 64 (47.1) 0.25
 Diabetes mellitus 66 (36.5) 45 (33.1) 0.53
 COPD 22 (12.2) 7 (5.1) 0.03
 Liver cirrhosis 20 (11.0) 15 (11.0) 0.995
 Congestive heart failure 23 (12.7) 11 (8.1) 0.19
 Solid cancer 31 (17.1) 22 (16.2) 0.82
 Hematologic cancer 12 (6.6) 7 (5.1) 0.58
Infection source
 Respiratory 70 (38.7) 43 (31.6) 0.19
 Gastrointestinal 54 (29.8) 41 (30.1) 0.95
 Urinary tract 45 (24.9) 45 (33.1) 0.11
 Soft tissue 7 (3.9) 2 (1.5) 0.20
 Unknown 5 (2.8) 5 (3.7) 0.65
Severity of illness at ICU admission
 SOFA score 13 (9–16) 8 (4–12) <0.001
 APACHE II score 26 (22–32) 23 (20–27) <0.001
 Vasopressors use 76 (42.0) 33 (24.3) 0.001
 Ventilator dependency 66 (36.5) 25 (18.4) <0.001
Findings at CRRT initiation
 Mean arterial pressure (mmHg) 79 (69–93) 84 (70–90) 0.47
 Fever or hypothermia 69 (38.1) 50 (36.8) 0.81
 Heart rate (beat/min) 97 (80–113) 97 (78–122) 0.78
 Oliguria for 6 hr before CRRT, <0.5 mL/kg/hr 74 (40.9) 14 (10.3) <0.001
 Creatinine (mg/dL) 2.7 (2.5–3.4) 2.5 (2.2–3.2) <0.001
 Blood urea nitrogen (mg/dL) 51.3 (41.3–68.5) 48.9 (42.4–70.0) 0.80
 Sodium (meq/L) 136 (130–141) 135 (130–141) 0.58
 Potassium (meq/L) 4.5 (4.0–5.2) 4.5 (4.1–5.1) 0.61
 Leukocyte count (×1,000/mm3) 12.6 (9.5–18.6) 13.8 (10.6–20.1) 0.17
 Hemoglobin (g/dL) 9.0 (7.9–10.7) 9.5 (7.8–11.1) 0.36
 Platelet count (×1,000/mm3) 115 (67–161) 122 (76–162) 0.68
 Total bilirubin (mg/dL) 1.8 (0.8–4.2) 1.9 (0.3–3.6) 0.13
 Albumin (g/dL) 2.7 (2.3–3.1) 2.7 (2.4–3.1) 0.59
 PT/INR 1.6 (1.4–1.9) 1.7 (1.3–1.9) 0.38
 C-reactive protein (mg/dL) 13.0 (7.5–26.4) 10.1 (5.8–24.4) 0.07
 pH 7.27 (7.23–7.33) 7.29 (7.20–7.37) 0.31
 Lactate (mmol/L) 3.3 (1.9–7.1) 2.5 (1.8–6.6) 0.04
CRRT
 Interval time from AKI diagnosis to CRRT initiation (day) 0.4 (0.3–1.4) 0.3 (0.3–1.2) 0.18
 Prescribed CRRT dose (mL/kg/hr) 37.6 (35.2–39.9) 37.6 (35.6–39.8) 0.56
Skeletal muscle index (cm2/m2) 35.9 (27.8–42.2) 43.1 (37.3–54.2) <0.001
Sarcopenia 79 (43.6) 20 (14.7) <0.001

Values are expressed as median (interquartile range) or number (%).

AKI, acute kidney injury; APACHE II, Acute Physiology and Chronic Health Evaluation II; COPD, chronic obstructive pulmonary disease; CRRT, continuous renal replacement therapy; ICU, intensive care unit; PT/INR, prothrombin time/international normalized ratio; SOFA, Sequential Organ Failure Assessment.

Table 3.
Univariable and multivariable Cox regression analyses for 28-day mortality after ICU admission (n = 618)
Variable Univariable
Multivariable
HR (95% CI) p-value HR (95% CI) p-value
Demographics
 Age, per 1 year increase 1.01 (1.00–1.02) 0.006 1.00 (0.99–1.00) 0.25
 Male sex 0.96 (0.77–1.21) 0.75 0.78 (0.60–1.00) 0.06
 Body mass index, per 1.0 kg/m2 increase 0.98 (0.94–1.03) 0.43
Comorbid disease
 Chronic kidney disease 1.15 (0.89–1.49) 0.28
 Hypertension 1.14 (0.90–1.43) 0.27
 Diabetes mellitus 1.11 (0.88–1.40) 0.38
 COPD 1.64 (1.22–2.20) 0.001 1.16 (0.85–1.57) 0.35
 Liver cirrhosis 1.55 (1.17–2.03) 0.002 1.21 (0.91–1.60) 0.20
 Congestive heart failure 1.52 (1.14–2.02) 0.004 1.52 (1.13–2.05) 0.006
 Solid cancer 1.30 (1.00–1.70) 0.049 1.24 (0.94–1.64) 0.13
 Hematologic cancer 1.16 (0.74–1.80) 0.52
Infection source
 Respiratory 1.06 (0.84–1.34) 0.61
 Gastrointestinal 1.11 (0.87–1.41) 0.40
 Urinary tract 0.81 (0.62–1.06) 0.12
 Soft tissue 1.35 (0.77–2.35) 0.30
 Unknown 0.76 (0.36–1.61) 0.47
Severity of illness
 SOFA score, per 1 point increase 1.15 (1.12–1.18) <0.001 1.11 (1.08–1.14) <0.001
 APACHE II score, per 1 point increase 1.12 (1.10–1.14) <0.001 1.05 (1.03–1.08) <0.001
 Vasopressors use 2.75 (2.15–3.52) <0.001
 Ventilator dependency 4.26 (3.28–5.53) <0.001
Findings at ICU admission
 Mean arterial pressure, per 1.0 mmHg increase 0.97 (0.96–0.97) <0.001
 Fever or hypothermia 0.99 (0.79–1.26) 0.96
 Heart rate, per 1.0 beat/min increase 1.00 (1.00–1.01) 0.45
 Oliguria for 6 hr before CRRT, <0.5 mL/kg/hr 3.21 (2.53–4.10) <0.001 1.63 (1.25–2.13) 0.001
 Serum creatinine, per 1.0 mg/dL increase 1.11 (1.01–1.21) 0.46
 Serum blood urea nitrogen, per 1.0 mg/dL increase 1.00 (1.00–1.00) 0.56
 Sodium, per 1.0 meq/L increase 1.00 (0.99–1.02) 0.78
 Potassium, per 1.0 meq/L increase 1.06 (0.95–1.19) 0.32
 Leukocyte count, per 1,000/mm3 increase 1.00 (0.99–1.02) 0.51
 Hemoglobin, per 1.0 g/dL increase 0.99 (0.94–1.04) 0.64
 Platelet count, per 1,000/mm3 increase 0.99 (0.99–1.00) <0.001
 Total bilirubin, per 1.0 mg/dL increase 1.01 (0.96–1.06) 0.69
 Albumin, per 1.0 g/dL increase 0.90 (0.72–1.11) 0.31
 PT/INR, per 1.0 increase 1.19 (0.99–1.43) 0.06 0.83 (0.67–1.03) 0.09
 C-reactive protein, per 1.0 mg/dL increase 1.00 (1.00–1.01) 0.34
 pH, per 0.1 increase 0.77 (0.71–0.84) <0.001
 Lactate, per 1.0 mmol/L increase 1.13 (1.10–1.15) <0.001 1.05 (1.02–1.08) 0.001
Interval time from AKI diagnosis to CRRT initiation, per 1 day increase 1.49 (1.38–1.62) <0.001 1.12 (1.01–1.25) 0.03
Prescribed CRRT dose, per 1 mL/kg/hr increase 0.99 (0.96–1.04)
Sarcopenia, vs. non-sarcopenia 2.66 (2.09–3.38) <0.001 1.83 (1.42–2.38) <0.001

AKI, acute kidney injury; APACHE II, Acute Physiology and Chronic Health Evaluation II; CI, confidence interval; COPD, chronic obstructive pulmonary disease; CRRT, continuous renal replacement therapy; HR, hazard ratio; ICU, intensive care unit; PT/INR, prothrombin time/international normalized ratio; SOFA, Sequential Organ Failure Assessment.

Table 4.
Univariable and multivariable Cox regression analyses for 28-day recovery from dialysis after ICU admission among the survivors (n = 317)
Variable Univariable
Multivariable
HR (95% CI) p-value HR (95% CI) p-value
Demographics
 Age, per 1 year increase 0.52 (0.99–1.00) 0.049 1.00 (0.98–1.01) 0.41
 Male sex 1.25 (0.88–1.78) 0.22 1.24 (0.81–1.79) 0.24
 Body mass index, per 1.0 kg/m2 increase 1.01 (0.95–1.09) 0.71
Comorbid disease
 Chronic kidney disease 0.20 (0.10–0.40) <0.001 0.34 (0.17–0.68) 0.002
 Hypertension 0.80 (0.57–1.12) 0.20
 Diabetes mellitus 0.87 (0.61–1.24) 0.43
 COPD 0.49 (0.23–1.05) 0.07 0.80 (0.37–1.74) 0.57
 Liver cirrhosis 0.95 (0.56–1.63) 0.85
 Congestive heart failure 0.68 (0.37–1.27) 0.23
 Solid cancer 0.87 (0.55–1.38) 0.57
 Hematologic cancer 0.89 (0.42–1.91) 0.77
Infection source
 Respiratory 0.79 (0.55–1.14) 0.20
 Gastrointestinal 1.04 (0.72–1.50) 0.83
 Urinary tract 1.28 (0.90–1.83) 0.17
 Soft tissue 0.46 (0.11–1.87) 0.28
 Unknown 1.31 (0.54–3.20) 0.55
Severity of illness
 SOFA score, per 1 point increase 0.90 (0.87–0.93) <0.001 0.93 (0.90–0.96) <0.001
 APACHE II score, per 1 point increase 0.91 (0.88–0.94) <0.001 0.93 (0.90–0.97) <0.001
 Vasopressors use 0.54 (0.37–0.81) 0.002
 Ventilator dependency 0.50 (0.30–0.77) 0.002
Findings at CRRT initiation
 Mean arterial pressure, per 1.0 mmHg increase 1.00 (0.99–1.01) 0.65
 Fever or hypothermia 0.99 (0.70–1.41) 0.98
 Heart rate, per 1.0 beat/min increase 1.00 (0.99–1.01) 0.83
 Oliguria for 6 hr before CRRT, <0.5 mL/kg/hr 0.23 (0.13–0.41) <0.001 0.38 (0.22–0.67) 0.001
 Serum creatinine, per 1.0 mg/dL increase 0.85 (0.71–1.02) 0.08
 Serum blood urea nitrogen, per 1.0 mg/dL increase 1.00 (1.00–1.01) 0.90
 Sodium, per 1.0 meq/L increase 0.99 (0.97–1.01) 0.42
 Potassium, per 1.0 meq/L increase 0.88 (0.74–1.05) 0.17
 Leukocyte count, per 1,000/mm3 increase 1.01 (0.99–1.03) 0.23
 Hemoglobin, per 1.0 g/dL increase 1.06 (0.98–1.15) 0.12
 Platelet count, per 1,000/mm3 increase 1.00 (1.00–1.00) 0.75
 Total bilirubin, per 1.0 mg/dL increase 1.00 (0.92–1.07) 0.91
 Albumin, per 1.0 g/dL increase 1.16 (0.85–1.60) 0.35
 PT/INR, per 1.0 increase 0.95 (0.71–1.27) 0.75
 C-reactive protein, per 1.0 mg/dL increase 0.99 (0.98–1.00) 0.18
 pH, per 0.1 increase 1.02 (0.85–1.22) 0.82
 Lactate, per 1.0 mmol/L increase 0.96 (0.92–1.01) 0.14
Interval time from AKI diagnosis to CRRT initiation, per 1 day increase 0.94 (0.78–1.13) 0.48
Prescribed CRRT dose, per 1 mL/kg/hr increase 1.01 (0.94–1.07) 0.86
Sarcopenia, vs. non-sarcopenia 0.30 (0.19–0.49) <0.001 0.42 (0.26–0.68) <0.001

AKI, acute kidney injury; APACHE II, Acute Physiology and Chronic Health Evaluation II; CI, confidence interval; COPD, chronic obstructive pulmonary disease; CRRT, continuous renal replacement therapy; HR, hazard ratio; ICU, intensive care unit; PT/INR, prothrombin time/international normalized ratio; SOFA, Sequential Organ Failure Assessment.

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