Albumin levels predict mortality in sepsis patients with acute kidney injury undergoing continuous renal replacement therapy: a secondary analysis based on a retrospective cohort study

DEVELOPMENT AND VALIDATION OF A NOMOGRAM FOR PREDICTING 28-DAY IN-HOSPITAL MORTALITY IN SEPSIS PATIENTS BASED ON AN OPTIMIZED ACUTE PHYSIOLOGY AND CHRONIC HEALTH EVALUATION II SCORE

ABSTRACT

Purpose : The objective of this study is to establish a nomogram that correlates optimized Acute Physiology and Chronic Health Evaluation II (APACHE II) score with sepsis-related indicators, aiming to provide a robust model for early prediction of sepsis prognosis in clinical practice and serve as a valuable reference for improved diagnosis and treatment strategies. Methods : This retrospective study extracted sepsis patients meeting the inclusion criteria from the MIMIC-IV database to form the training group. An optimized APACHE II score integrated with relevant indicators was developed using a nomogram for predicting the prognosis of sepsis patients. External validation was conducted using data from the intensive care unit at Lanzhou University Second Hospital. Results : The study enrolled 1805 patients in the training cohort and 203 patients in the validation cohort. A multifactor analysis was conducted to identify factors affecting patient mortality within 28 days, resulting in the development of an optimized score by simplifying evaluation indicators from APACHE II score. The results showed that the optimized score (area under the ROC curve [AUC] = 0.715) had a higher area under receiver operating characteristic curve than Sequential Organ Failure Assessment score (AUC = 0.637) but slightly lower than APACHE II score (AUC = 0.720). Significant indicators identified through multifactor analysis included platelet count, total bilirubin level, albumin level, prothrombin time, activated partial thromboplastin time, mechanical ventilation use and renal replacement therapy use. These seven indicators were combined with optimized score to construct a nomogram based on these seven indicators. The nomogram demonstrated good clinical predictive value in both training cohort (AUC = 0.803) and validation cohort (AUC = 0.750). Calibration curves and decision curve analyses also confirmed its good predictive ability, surpassing the APACHE II score and Sequential Organ Failure Assessment score in identifying high-risk patients. Conclusions : The nomogram was established in this study using the MIMIC-IV database and validated with external data, demonstrating its robust discriminability, calibration, and clinical practicability for predicting 28-day mortality in sepsis patients. These findings aim to provide substantial support for clinicians' decision making.

The relationship between lactate dehydrogenase to albumin ratio and all-cause mortality during ICU stays in patients with sepsis: A retrospective cohort study with propensity score matching

Background

Sepsis is a prevalent and severe medical condition which is frequently observed in the intensive care unit (ICU). Although numerous biomarkers have been identified to predict the prognosis of sepsis, the lactate dehydrogenase to albumin ratio (LDH/ALB ratio) has not been extensively investigated. The principal objective of this study is to assess the relationship between LDH/ALB ratio and all-cause mortality in patients with sepsis.

Methods

This study included all adult critically ill patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.0) database. Propensity score matching (PSM) analysis was conducted to mitigate bias, and Kaplan-Meier curves were performed to evaluate the cumulative survival across different groups. The association between the LDH/ALB ratio and mortality was examined through restricted cubic spline (RCS) analysis and Cox regression analysis. The robustness of the findings was confirmed through subgroup analyses. Additionally, the prognostic capability of the LDH/ALB ratio was further evaluated using receiver operating characteristic (ROC) curve analysis.

Results

There were 6059 adult patients with sepsis enrolled in the final analysis. RCS revealed a non-linear relationship between the LDH/ALB ratio and an increased risk of ICU all-cause mortality (χ2 = 46.900, P < 0.001). Following PSM analysis, 1553 matched pairs were obtained. As comparison to the low LDH/ALB ratio group, the mortality rate in the high LDH/ALB ratio group was significantly higher (P < 0.001). Kaplan-Meier curves, both before and after PSM, revealed that the ICU cumulative survival rate for patients with sepsis was significantly lower in the high LDH/ALB ratio group compared to the low LDH/ALB ratio group (χ2 = 93.360, P < 0.001; χ2 = 14.400, P < 0.001). Even after adjusting for a range of potential confounders, multivariate Cox regression analysis indicated that an elevated LDH/ALB ratio was a significant predictor of all-cause mortality in these patients. ROC curve analysis demonstrated that the LDH/ALB ratio had an area under the ROC curve (AUC) of 0.688 for predicting ICU mortality, with a sensitivity of 69.2% and a specificity of 58.6%.

Conclusions

An elevated LDH/ALB ratio (≥10.57) was associated with all-cause mortality in critically ill patients with sepsis, and it might serve as a prognostic marker. Clinicians should pay closer attention to sepsis patients presenting with an LDH/ALB ratio of 10.57 or higher.

Serum total protein-to-albumin ratio predicts risk of death in septic acute kidney injury patients: A cohort study

OBJECTIVE

Sepsis is the leading cause of acute kidney injury (AKI). Increasing evidence shows that serum total protein-to-albumin ratio (TAR) could serve as an inflammation- and nutrition-based prognostic marker in various diseases. The purpose of this study was to assess the prognostic value of TAR in predicting the clinical outcomes of septic AKI patients.

METHODS

We retrospectively enrolled septic AKI patients between August 2015 and August 2022 at West China Hospital of Sichuan University. Patients admitted between August 2015 and August 2021 were defined as the original cohort. The primary outcomes were 30-day and 90-day all-cause mortality of septic AKI patients. The secondary outcomes were septic shock, transfer to the intensive care unit, mechanical ventilation, requirement for renal replacement therapy, and stage 3 AKI. The utility of TAR was further verified in a validation cohort of septic AKI patients admitted between September 2021 and August 2022.

RESULTS

In the original cohort, a total of 309 eligible patients with a median age of 58 years were enrolled, of which 70.2 % were males. In multivariate Cox analysis, after adjustments for age, sex, and other confounding factors, higher TAR at admission was associated with an increased risk of 30-day and 90-day all-cause mortality in septic AKI patients (HR 1.91, 95 % CI 1.18-3.09, P = 0.008; HR 1.54, 95 % CI 1.01-2.34, P = 0.043, respectively). Subgroup analysis revealed no significant interactions in most strata. TAR at AKI diagnosis or discharge was not significantly related to 30-day (P = 0.120 and 0.153, respectively) or 90-day mortality (P = 0.147 and 0.124, respectively). We found no relationship between baseline TAR and septic shock, transfer to the intensive care unit, mechanical ventilation, requirement for renal replacement therapy, or stage 3 AKI (all P > 0.05). In the validation cohort of 81 septic AKI patients, TAR at admission remained a significant prognosticator for 30-day and 90-day mortality (HR 4.367, 95 % CI 1.20-15.87, P = 0.025; HR 4.237, 95 % CI 1.59-11.27, P = 0.004).

CONCLUSIONS

TAR at admission is an independent risk factor for 30-day and 90-day mortality in septic AKI patients and could be used as a convenient and economic septic AKI prognostic indicator.

Association between albumin corrected anion gap and all-cause mortality in critically ill patients with acute kidney injury: a retrospective study based on MIMIC-IV database

BACKGROUND

The early identification of patients at high risk for acute kidney injury (AKI) with a poor prognosis is crucial to prevent complications and minimize mortality. This study sought to investigate the association between albumin-corrected anion gap (ACAG) and all-cause mortality among critically ill patients with AKI.

METHODS

All eligible AKI patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV version 2.0) database were considered for participation in this study. We employed Kaplan-Meier curves to assess the 30-d and 360-d cumulative survival rates among various groups. Flexibly visualizing the connection between ACAG and mortality, we utilize restricted cubic splines (RCS) and multivariate Cox regression models. Result robustness underwent assessment through subgroup analyses and sensitivity analyses. Receiver-operating characteristic (ROC) curves were generated to evaluate the predictive performance of ACAG.

RESULTS

The study included 9625 AKI participants, of whom 58.60% were male, and the 360-d all-cause mortality rate was 39.89%. According to Kaplan-Meier analysis, the 30-d and 360-d cumulative survival rates for AKI patients were significantly lower in the high ACAG group than in the normal ACAG group. RCS analysis indicated that ACAG levels had a non-linear correlation with the risk of 30-d and 360-d mortality for AKI patients. Cox regression analysis demonstrated that ACAG is an independent risk indicator for 30-d and 360-d prognosis in AKI patients in the ICU.

CONCLUSIONS

Elevated ACAG levels (> 20 mmol/L) at ICU admission were associated with 30-d and 360-d all-cause mortality in critically ill patients with AKI.

Association of Hypoalbuminemia With Clinical Outcomes in Patients Admitted With Acute Heart Failure

Albumin is a protein produced by the liver essential for maintaining blood volume and regulating fluid balance. Hypoalbuminemia is characterized by low levels of albumin in the blood. It is also a marker of malnutrition-inflammatory syndrome. Several studies have demonstrated its prognostic role in patients with chronic heart failure; however, data regarding hypoalbuminemia in acute heart failure admissions are scarce. This study aims to analyze the relationship between hypoalbuminemia and heart failure. We used a retrospective cohort study surveying data from the 2016-2018 combined National Inpatient Sample (NIS) database. Adult hospitalizations for heart failure patients were identified using the ICD-10 codes, stratified into cohorts with and without hypoalbuminemia. Primary outcomes were (1) in-patient mortality, (2) length of stay, and total hospital charge. We also reclassified the HF admissions with hypoalbuminemia to those with systolic or diastolic heart failure to compare any differences in mortality and other in-patient complications. Multivariate linear and logistic regression were used to adjust for confounders and to analyze the outcomes. There were 1,365,529 adult hospitalizations for Congestive Heart Failure (CHF), and among them 1,205,990 (88 %) had secondary diagnoses of hypoalbuminemia. Patients with comorbid hypoalbuminemia were, on average, 8 years older (P < 0.001), predominantly white race, and males (P-value <0.001). HF hospitalizations with hypoalbuminemia had double in-hospital mortality than those without (4.8% vs 2.7%, P < 0.001). However, there was no difference in mortality between patients with Systolic heart failure and Diastolic heart failure with concomitant low albumin levels (from 4.9 % vs 4.7%, P 0.13). We found that patients admitted with HF and concomitant Hypoalbuminemia (HA) had nearly twice the odds of in-patient mortality than those with normal albumin levels. The Length of Stay (LOS) was higher between comparison groups. THC remained statistically indifferent in patients regardless of albumin levels but was greater in hypoalbuminemic patients with Systolic heart failure than Diastolic heart failure ones.

Fibrinogen-to-Albumin Ratio in Neonatal Sepsis

Background

Previous studies have established an association between fibrinogen-to-albumin ratio (FAR) and cancer, cardiovascular disease, and coronavirus disease 2019. However, no studies have investigated the relationship between FAR and neonatal sepsis. This study aims to evaluate the association of fibrinogen-to-albumin ratio with the presence and severity of sepsis in neonates.

Methods

A total of 1292 neonates with suspected sepsis were enrolled in this study. Clinical and laboratory data were collected from electronic medical records. Neonates with final diagnosis with sepsis were divided into the sepsis group, The remaining neonates were divided into the control group. Neonates with sepsis were further categorized into mild (n = 312) and severe (n = 425) groups based on the severity of their condition. FAR was determined by dividing the plasma fibrinogen concentration (g/L) by the serum albumin concentration (g/L). The statistical analyses were conducted using the SPSS 26.0 statistical software package, as deemed appropriate.

Results

FAR levels were significantly higher in neonates with sepsis compared to the control group. Additionally, a significant gradual increase in FAR was observed in the control, mild sepsis, and severe sepsis groups (P < 0.001). Correlation analysis showed that FAR had a positive correlation with PCT, CRP, and the length of hospital stay. Multiple logistic regression analysis showed that FAR was independently associated with the presence and severity of neonatal sepsis. Specifically, FAR was identified as an independent risk factor for both the presence of sepsis (OR = 8.641, 95% CI 5.708-13.080, P < 0.001) and severe sepsis (OR = 2.817, 95% CI 1.701-4.666, P < 0.001).

Conclusion

FAR is significantly increased in neonates with sepsis and had a correlation with the severity of sepsis. Increased FAR was an independent predictor for the presence and severity of neonatal sepsis.

Diagnostic and Prognostic Roles of C-Reactive Protein, Procalcitonin, and Presepsin in Acute Kidney Injury Patients Initiating Continuous Renal Replacement Therapy

For reducing the high mortality rate of severe acute kidney injury (AKI) patients initiating continuous renal replacement therapy (CRRT), diagnosing sepsis and predicting prognosis are essential. However, with reduced renal function, biomarkers for diagnosing sepsis and predicting prognosis are unclear. This study aimed to assess whether C-reactive protein (CRP), procalcitonin, and presepsin could be used to diagnose sepsis and predict mortality in patients with impaired renal function initiating CRRT. This was a single-center, retrospective study involving 127 patients who initiated CRRT. Patients were divided into sepsis and non-sepsis groups according to the SEPSIS-3 criteria. Of the 127 patients, 90 were in the sepsis group and 37 were in the non-sepsis group. Cox regression analysis was performed to determine the association between the biomarkers (CRP, procalcitonin, and presepsin) and survival. CRP and procalcitonin were superior to presepsin for diagnosing sepsis. Presepsin was closely related to the estimated glomerular filtration rate (eGFR) (r = -0.251, p = 0.004). These biomarkers were also evaluated as prognostic markers. Procalcitonin levels ≥3 ng/mL and CRP levels ≥31 mg/L were associated with higher all-cause mortality using Kaplan-Meier curve analysis. (log-rank test p = 0.017 and p = 0.014, respectively). In addition, procalcitonin levels ≥3 ng/mL and CRP levels ≥31 mg/L were associated with higher mortality in univariate Cox proportional hazards model analysis. In conclusion, a higher lactic acid, sequential organ failure assessment score, eGFR, and a lower albumin level have prognostic value to predict mortality in patients with sepsis initiating CRRT. Moreover, among these biomarkers, procalcitonin and CRP are significant factors for predicting the survival of AKI patients with sepsis-initiating CRRT.

Albumin Level is Associated with Short-Term and Long-Term Outcomes in Sepsis Patients Admitted in the ICU: A Large Public Database Retrospective Research

Objective

This study aimed to explore the relationship between albumin level with short- and long-term outcomes in sepsis patients admitted in the intensive care unit (ICU) based on a large public database to provide clinical evidence for physicians to make individualized plans of albumin supplementation.

Methods

Sepsis patients admitted in the ICU in MIMIC-IV were included. Different models were performed to investigate the relationships between albumin and mortalities of 28-day, 60-day, 180-day and 1-year. Smooth fitting curves were performed.

Results

A total of 5357 sepsis patients were included. Mortalities of 28-day, 60-day, 180-day and 1-year were 29.29% (n = 1569), 33.92% (n = 1817), 36.70% (n = 1966) and 37.71% (n = 2020). In the fully adjusted model (adjusted for all potential confounders), with each 1g/dL increment in albumin level, the risk of mortality in 28-day, 60-day, 180-day and 1-year decreased by 39% (OR = 0.61, 95% CI: 0.54-0.69), 34% (OR = 0.66, 95% CI: 0.59-0.73), 33% (OR = 0.67, 95% CI: 0.60-0.75), and 32% (OR = 0.68, 95% CI: 0.61-0.76), respectively. The non-linear negative relationships between albumin and clinical outcomes were confirmed by smooth fitting curves. The turning point of albumin level was 2.6g/dL for short- and long-term clinical outcomes. When albumin level ≤2.6g/dL, with each 1g/dL increment in albumin level, the risk of mortality in 28-day, 60-day, 180-day and 1-year decreased by 59% (OR = 0.41, 95% CI: 0.32-0.52), 62% (OR = 0.38, 95% CI: 0.30-0.48), 65% (OR = 0.35, 95% CI: 0.28-0.45), and 62% (OR = 0.38, 95% CI: 0.29-0.48), respectively.

Conclusion

Albumin level was associated with short- and long-term outcomes in sepsis. Albumin supplementation might be beneficial for septic patients with serum albumin<2.6g/dL.

The correlation study between blood urea nitrogen to serum albumin ratio and prognosis of patients with sepsis during hospitalization

BACKGROUND

Sepsis is a common critical illness in intensive care unit (ICU) and seriously threatens the life of patients. Therefore, to identify a simple and effective clinical indicator to determine prognosis is essential for the management of sepsis patients. This study was mainly based on blood urea nitrogen to albumin ratio (B/A), a comprehensive index, to explore its correlation with the prognosis of sepsis patients during hospitalization.

METHODS

Totally, adult patients in ICU who were diagnosed with sepsis in Medical Information Mart for Intensive Care IV(MIMIC-IV) database from 2008 to 2019 were involved in this study. The study population were divided into survivors group and non-survivors group based on the prognosis during hospitalization. Restricted cubic spline (RCS) was utilized to analyze the association between B/A level and the risk of ICU all-cause mortality in patients with sepsis and determine the optimal cut-off value of B/A. The study population was divided into low B/A group and high B/A group based on the optimal cut-off value. The survival curve of ICU cumulative survival rate was draw through Kaplan-Meier method. The correlation between B/A and the prognosis of patients was conducted by multivariate Cox regression analysis. Furthermore, we performed sensitivity analyses to assess the robustness of the results.

RESULTS

A total of 10,578 patients with sepsis were enrolled, and the ICU all-cause mortality was 15.89%. The patients in the non-survivors group had higher B/A values and more comorbidities than those in the survivors group. RCS showed that the risk of ICU all-cause mortality increased with the B/A level, showing a non-linear trend (χ2 = 66.82, p < 0.001). The mortality rate in the high B/A group was significantly higher than that in the low B/A group (p < 0.001). Kaplan-Meier curves revealed that compared with the low B/A group, the ICU cumulative survival rate of patients with sepsis was significantly lower in the high B/A group (log-rank test, χ2 = 148.620, p < 0.001). Further analysis of multivariate Cox proportional hazards regression showed that an elevated B/A (≥ 7.93) was an independent factor associated with ICU mortality among patients with sepsis.

CONCLUSIONS

An elevated B/A might be a useful prognostic indicator in patients with sepsis. This study could offer a deeper insight into treating sepsis.

Construction and validation of an early warning model for predicting the acute kidney injury in elderly patients with sepsis

BACKGROUND

Sepsis-induced acute kidney injury (S-AKI) is a significant complication and is associated with an increased risk of mortality, especially in elderly patients with sepsis. However, there are no reliable and robust predictive models to identify high-risk patients likely to develop S-AKI. We aimed to develop a nomogram to predict S-AKI in elderly sepsis patients and help physicians make personalized management within 24 h of admission.

METHODS

A total of 849 elderly sepsis patients from the First Affiliated Hospital of Xi'an Jiaotong University were identified and randomly divided into a training set (75%, n = 637) and a validation set (25%, n = 212). Univariate and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The corresponding nomogram was constructed based on those predictors. The calibration curve, receiver operating characteristics (ROC)curve, and decision curve analysis were performed to evaluate the nomogram. The secondary outcome was 30-day mortality and major adverse kidney events within 30 days (MAKE30). MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD).

RESULTS

The independent predictors for nomogram construction were mean arterial pressure (MAP), serum procalcitonin (PCT), and platelet (PLT), prothrombin time activity (PTA), albumin globulin ratio (AGR), and creatinine (Cr). The predictive model had satisfactory discrimination with an area under the curve (AUC) of 0.852-0.858 in the training and validation cohorts, respectively. The nomogram showed good calibration and clinical application according to the calibration curve and decision curve analysis. Furthermore, the prediction model had perfect predictive power for predicting 30-day mortality (AUC = 0.813) and MAKE30 (AUC = 0.823) in elderly sepsis patients.

CONCLUSION

The proposed nomogram can quickly and effectively predict S-AKI risk in elderly sepsis patients within 24 h after admission, providing information for clinicians to make personalized interventions.

Explainable Machine Learning-Based Risk Prediction Model for In-Hospital Mortality after Continuous Renal Replacement Therapy Initiation

In this study, we established an explainable and personalized risk prediction model for in-hospital mortality after continuous renal replacement therapy (CRRT) initiation. This retrospective cohort study was conducted at Changhua Christian Hospital (CCH). A total of 2932 consecutive intensive care unit patients receiving CRRT between 1 January 2010, and 30 April 2021, were identified from the CCH Clinical Research Database and were included in this study. The recursive feature elimination method with 10-fold cross-validation was used and repeated five times to select the optimal subset of features for the development of machine learning (ML) models to predict in-hospital mortality after CRRT initiation. An explainable approach based on ML and the SHapley Additive exPlanation (SHAP) and a local explanation method were used to evaluate the risk of in-hospital mortality and help clinicians understand the results of ML models. The extreme gradient boosting and gradient boosting machine models exhibited a higher discrimination ability (area under curve [AUC] = 0.806, 95% CI = 0.770-0.843 and AUC = 0.823, 95% CI = 0.788-0.858, respectively). The SHAP model revealed that the Acute Physiology and Chronic Health Evaluation II score, albumin level, and the timing of CRRT initiation were the most crucial features, followed by age, potassium and creatinine levels, SPO2, mean arterial pressure, international normalized ratio, and vasopressor support use. ML models combined with SHAP and local interpretation can provide the visual interpretation of individual risk predictions, which can help clinicians understand the effect of critical features and make informed decisions for preventing in-hospital deaths.