A combination of SOFA score and biomarkers gives a better prediction of septic AKI and in-hospital mortality in critically ill surgical patients: a pilot study

Mortality prediction model from combined serial lactate, procalcitonin and calprotectin levels in critically ill patients with sepsis: A retrospective study according to Sepsis-3 definition

OBJECTIVE

1) To evaluate the ability of baseline and on 24 h serum calprotectin, in comparison to canonical biomarkers (lactate and procalcitonin), for prognosis of 28-day mortality in critically ill septic patients; and 2) To develop a predictive model combining the three biomarkers.

DESIGN

A single-center, retrospective study.

SETTING

Intensive Care Unit of a university hospital.

PATIENTS OR PARTICIPANTS

One hundred and seventy three septic pacientes were included.

INTERVENTIONS

Measurement of baseline lactate, procalcitonin and calprotectin level and procalcitonin and calprotectin levels on 24 h.

MAIN VARIABLES OF INTEREST

Demographics and comorbidities, SOFA score on ICU admission, baseline lactate, procalcitonin and calprotectin on admission and on 24 h and 28-day mortality.

RESULTS

1) On ICU admission, lactate was the only biomarker achieving a significant accuracy (AUC: 0.698); 2) On 24 h, no differences were found on procalcitonin and calprotectin levels. Procalcitonin and calprotectin clearances were significantly lower in non-survivors and both achieved a moderate performance (AUCs: 0.668 and 0.664, respectively); 3) A biomarker based-model achieved a significant accuracy (AUC: 0.766), trending to increase (AUC: 0.829) to SOFA score alone; y 4) Baseline lactate levels and procalcitonin and calprotectin clearance were independent predictors for the outcome.

CONCLUSIONS

1) Baseline and on 24 h calprotectina and procalcitonin levels lacked ability in predicting 28-day mortality; 2) Accuracy of clearance of both biomarkers was moderate; and 3) Combination of SOFA score and the predictive biomarker based-model showed a high prognostic accuracy.

The Sepsis Score Dilemma: Balancing Precision and Utility

How to cite this article: Pande R, Pandey M. The Sepsis Score Dilemma: Balancing Precision and Utility. Indian J Crit Care Med 2024;28(10):906-907.

Diagnostic and Prognostic Utilities of Pancreatic Stone Protein in Patients with Suspected Sepsis

Background/Objectives: Pancreatic stone protein (PSP) is an emerging biomarker of sepsis that is secreted from pancreas sensing remote organ damages. We explored the diagnostic and prognostic utilities of PSP in patients with suspected sepsis. Methods: In a total of 285 patients (suspected sepsis, n = 148; sepsis, n = 137), we compared PSP with procalcitonin (PCT) and sequential organ failure assessment (SOFA) score. Sepsis diagnoses were explored using receiver operating characteristic curve analyses with area under the curves (AUCs). Clinical outcomes (in-hospital mortality, 30-day mortality, and kidney replacement therapy [KRT]) were explored using the Kaplan-Meier method and a multivariate analysis with hazard ratio (HR). Results: PCT and PSP were comparable for sepsis diagnosis (AUC = 0.71-0.72, p < 0.001). The sepsis proportion was significantly higher when both biomarkers increased than when either one or both biomarkers did not increase (89.0% vs. 21.3-47.7%, p < 0.001). Each biomarker quartile (Q1-Q4) differed significantly according to their SOFA score (all p < 0.001). Compared with Q1, the Q2-Q4 groups showed worse clinical outcomes (p = 0.002-0.041). Both biomarkers added to the SOFA score showed higher HRs than the SOFA score alone (3.3-9.6 vs. 2.8-4.2, p < 0.001-0.011), with nearly 2.5-fold higher HR (9.6 vs. 4.2) for predicting KRT. Conclusions: Although PCT and PSP did not independently predict clinical outcomes in the multivariate analysis, PSP demonstrated diagnostic and prognostic utilities in patients with suspected sepsis, especially for predicting kidney dysfunction. PSP, alone or in combination with PCT, would be a valuable tool that can be added to clinical assessments.

Development and validation of a nomogram to predict the risk of vancomycin-related acute kidney injury in critical care patients

Background

Vancomycin-associated acute kidney injury (AKI) leads to underestimated morbidity in the intensive care unit (ICU). It is significantly important to predict its occurrence in advance. However, risk factors and nomograms to predict this AKI are limited.

Methods

This was a retrospective analysis of two databases. A total of 1,959 patients diagnosed with AKI and treated with vancomycin were enrolled from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. According to the 7:3 ratio, the training set (n = 1,372) and the internal validation set (n = 587) were randomly allocated. The external validation set included 211 patients from the eICU Collaborative Research Database (eICU). Next, to screen potential variables, the least absolute shrinkage and selection operator (LASSO) regression was utilized. Subsequently, the nomogram was developed by the variables of the selected results in the multivariable logistic regression. Finally, discrimination, calibration, and clinical utility were evaluated to validate the nomogram.

Results

The constructed nomogram showed fine discrimination in the training set (area under the receiver operator characteristic curve [AUC] = 0.791; 95% confidence interval [CI]: 0.758-0.823), internal validation set (AUC = 0.793; 95% CI: 0.742-0.844), and external validation set (AUC = 0.755; 95% CI: 0.663-0.847). Moreover, it also well demonstrated calibration and clinical utility. The significant improvement (P < 0.001) in net reclassification improvement (NRI) and integrated differentiation improvement (IDI) confirmed that the predictive model outperformed others.

Conclusion

This established nomogram indicated promising performance in determining individual AKI risk of vancomycin-treated critical care patients, which will be beneficial in making clinical decisions.

Urinary cystatin-C and urinary NGAL associated with sepsis predicts longer hospital stay in premature newborns

Aim: To evaluate the urinary biomarkers related to sepsis in preterm newborns (NBs) and to investigate the predictive capacity of these biomarkers for a longer hospital stay.Methods: Serum and urine were collected from 27 healthy NBs, 24 NBs with neonatal infection without sepsis and 11 NBs with sepsis for the measurement of sindecan-1, lipocalin associated with urinary neutrophil gelatinase (uNGAL), urinary cystatin-C (uCysC) and urinary kidney injury molecule-1.Results: Levels of uNGAL and urinary cystatin-C were elevated in NBs with sepsis and neonatal infection, and uNGAL was significant predictor of hospital stay longer than 30 days (odds ratio: 1.052; 95% CI: 1.012-1.093; p = 0.01).Conclusion: uNGAL was associated with sepsis in preterm NBs and was useful to predict extended hospital stay.

A two-tier feature selection method for predicting mortality risk in ICU patients with acute kidney injury

Acute kidney injury (AKI) is one of the most important lethal factors for patients admitted to intensive care units (ICUs), and timely high-risk prognostic assessment and intervention are essential to improving patient prognosis. In this study, a stacking model using the MIMIC-III dataset with a two-tier feature selection approach was developed to predict the risk of in-hospital mortality in ICU patients admitted for AKI. External validation was performed using separate MIMIC-IV and eICU-CRD. The area under the curve (AUC) was calculated using the stacking model, and features were selected using the Boruta and XGBoost feature selection methods. This study compares the performance of a stacking model using two-tier feature selection with a model using single-tier feature selection (XGBoost: 85; Boruta: 83; two-tier: 0.91). The predictive effectiveness of the stacking model was further validated by using different datasets (Validation 1: 0.83; Validation 2: 0.85) and comparing it with a simpler model and traditional clinical scores (SOFA: 0.65; APACH IV: 0.61). In addition, this study combined interpretable techniques and causal inference to analyze the causal relationship between features and predicted outcomes.

A point-of-care electrochemical biosensor for the rapid and sensitive detection of biomarkers in murine models with LPS-induced sepsis

Sepsis is a life-threatening condition, which is irreversible if diagnosis and intervention are delayed. The response of the immune cells towards an infection triggers widespread inflammation through the production of cytokines, which may result in multiple organ dysfunction and eventual death. Conventional detection techniques fail to provide a rapid diagnosis because of their limited sensitivity and tedious protocol. This study proposes a point-of-care (POC) electrochemical biosensor that overcomes the limitations of current biosensing technologies in the clinical setting by its integration with electrokinetics, enhancing the sensitivity to picogram level compared with the nanogram limit of current diagnostic technologies. This biosensor promotes the use of a microelectrode strip to address the limitations of conventional photolithographic fabrication methods. Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and microRNA-155 (miR-155) were monitored in a lipopolysaccharide (LPS)-induced septic mouse model. The optimum target hybridization time in a high conductivity medium was observed to be 60 s leading to the completion of the whole operation within 5 min compared with the 4-h detection time of the traditional enzyme-linked immunosorbent assay (ELISA). The limit of detection (LOD) was calculated to be 0.84, 0.18, and 0.0014 pg mL-1, respectively. This novel sensor may have potential for the early diagnosis of sepsis in the clinical setting.

Renal arterial resistive index versus novel biomarkers for the early prediction of sepsis-associated acute kidney injury

Acute kidney injury (AKI) is a critical complication of sepsis. There is a continuous need to identify and validate biomarkers for early detection. Serum and urinary biomarkers have been investigated, such as neutrophil gelatinase associated lipocalin (NGAL) and cystatin C (Cys C), but their reliability in the intensive care unit (ICU) remains unknown. Renal hemodynamics can be investigated by measuring the renal resistive index (RRI). This study aimed to compare the performance of RRI, serum NGAL (sNGAL), urinary NGAL (uNGAL), and serum Cys C levels as early predictors of the diagnosis and persistence of sepsis-associated AKI. A total of 166 adult patients with sepsis syndrome were enrolled immediately after ICU admission. Biomarkers were measured directly (T1) and on day 3 (T3). RRI was measured directly (T1) and 24 h later (T2). Patients were categorized (according to the occurrence and persistence of AKI within the first 7 days) into three groups: no AKI, transient AKI, and persistent AKI. The incidence rate of sepsis-associated AKI was 60.2%. Sixty-six patients were categorized as in the no AKI group, while another 61 were in transient AKI and only 39 were in persistent AKI. The RRI value (T1 ≥ 0.72) was the best tool for predicting AKI diagnosis (area under the receiver operating characteristic curve, AUROC = 0.905). Cys C (T1 ≥ 15.1 mg/l) was the best tool to predict the persistence of AKI (AUROC = 0.977). RRI (T1) was the best predictive tool for sepsis-associated AKI, while Cys C was the best predictor of its persistence and 28-day mortality.

Assessment of Nutritional Risk Scores (the Nutritional Risk Screening 2002 and Modified Nutrition Risk in Critically Ill Scores) as Predictors of Mortality in Critically Ill Patients on Extracorporeal Membrane Oxygenation

Nutritional risk is associated with intensive care unit (ICU) stay and mortality, the Nutritional Risk Screening 2002 (NRS 2002) and the modified Nutritional Risk in the Critically Ill (mNUTRIC) score are assessment instruments and useful in predicting the risk regarding mortality in ICU patients. Our aim was to assess the effects of mNUTRIC and NRS 2002 on mortality in patients on extracorporeal membrane oxygenation (ECMO). A retrospective cohort study was performed and 78 patients were included for final analysis. In the current study, the NRS 2002 and the mNUTRIC score within 24 hours before starting ECMO were applied to assess patients' nutritional status on ECMO and explore the relationship between nutritional status and patient outcomes. This study suggests that both mNUTRIC and NRS 2002 scores were found to be significant independent risk and prognostic factors for in-hospital and 90 day morality among ECMO patients based on multivariable logistic regression analysis ( p < 0.05), with those in the high-risk group having higher in-hospital and 90 day mortality rates than those identified as being at low risk ( p < 0.001). In comparison to the NRS 2002 score, the mNUTRIC score demonstrated a superior prognostic ability in ECMO patients.

Plasma proenkephalin and neutrophil gelatinase-associated lipocalin predict mortality in ICU patients with acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is a common complication in patients admitted to intensive care unit (ICU) and mortality rates for this condition are high. To reduce the high incidence of short-term mortality, reliable prognostic indicators are required to facilitate early diagnosis and treatment of AKI. We assessed the ability of plasma proenkephalin (p‑PENK) and plasma neutrophil gelatinase-associated lipocalin (p‑NGAL) to predict 28-day mortality in AKI patients in intensive care.

METHODS

This prospective study, carried out between January 2019 and December 2019, comprised 150 patients (100 male) diagnosed with AKI after excluding 20 patients discharged within 24 h and those with missing hospitalization data. Blood samples were collected to determine admission p-PENK and p-NGAL levels. The study outcome was 28‑day mortality.

RESULTS

The mean patient age was 68 years (female, 33%). The average P‑PENK and p‑NGAL levels were 0.24 ng/µL and 223.70 ng/mL, respectively. P‑PENK levels >0.36 ng/µL and p‑NGAL levels >230.30 ng/mL were used as critical values to reliably indicate 28‑day mortality for patients with AKI (adjusted hazard ratios 0.785 [95% confidence interval 0.706-0.865, P<0.001] and 0.700 [95% confidence interval 0.611-0.789, P<0.001], respectively). This association was significant for mortality in patients in intensive care with AKI. Baseline p-PENK (0.36 ng/µL) and p-NGAL (230.30 ng/mL) levels and their respective cut-off values showed clinical value in predicting 28-day mortality.

CONCLUSION

Serum PENK and NGAL levels, when used in conjunction, improved the accuracy of predicting 28-day mortality in patients with AKI while retaining sensitivity and specificity.

Combination of Urinary Neutrophil Gelatinase-associated Lipocalin, Kidney Injury Molecular-1, and Angiotensinogen for the Early Diagnosis and Mortality Prediction of Septic Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is one of the most severe complications of sepsis. This study was conducted to analyze the role of urinary neutrophil gelatinase-associated lipocalin (uNGAL), urinary kidney injury molecular-1 (uKIM-1), and urinary angiotensinogen (uAGT) in the early diagnosis and mortality prediction of septic AKI.

METHODS

The prospective study enrolled 80 sepsis patients in the ICU and 100 healthy individuals and divided patients into an AKI group and a non-AKI group. uNGAL, uKIM-1, uAGT, serum creatinine/procalcitonin/C-reaction protein, and other indicators were determined, and clinical prediction scores were recorded. The sensitivity and specificity of uNGAL, uKIM-1, and uAGT in diagnosis and mortality prediction were analyzed by the receiver operator characteristic (ROC) curve and the area under the curve (AUC).

RESULTS

uNGAL, uKIM-1, and uAGT levels were higher in sepsis patients than healthy controls, higher in AKI patients than non-AKI patients, and higher in AKI-2 and AKI-3 patients than AKI-1 patients. At 0 h after admission, the combined efficacy of three indicators in septic AKI diagnosis (ROC-AUC: 0.770; sensitivity: 82.5%; specificity: 70.0%) was better than a single indicator. At 24 h, uNGAL, uKIM-1, and uAGT levels were higher in sepsis non-survivals than survivals and higher in septic AKI non-survivals than septic AKI survivals. The combined efficacy of three indicators in the prediction of sepsis/septic AKI mortality (ROC-AUC: 0.828/0.847; sensitivity: 71.4%/100.0%; specificity: 82.7%/66.7%) was better than a single indicator.

CONCLUSION

uNGAL, uKIM-1, and uAGT levels were increased in septic AKI, and their combination helped the early diagnosis and mortality prediction.

S100A8/A9: An emerging player in sepsis and sepsis-induced organ injury

Sepsis, the foremost contributor to mortality in intensive care unit patients, arises from an uncontrolled systemic response to invading infections, resulting in extensive harm across multiple organs and systems. Recently, S100A8/A9 has emerged as a promising biomarker for sepsis and sepsis-induced organ injury, and targeting S100A8/A9 appeared to ameliorate inflammation-induced tissue damage and improve adverse outcomes. S100A8/A9, a calcium-binding heterodimer mainly found in neutrophils and monocytes, serves as a causative molecule with pro-inflammatory and immunosuppressive properties, which are vital in the pathogenesis of sepsis. Therefore, improving our comprehension of how S100A8/A9 acts as a pathological player in the development of sepsis is imperative for advancing research on sepsis. Our review is the first-to the best of our knowledge-to discuss the biology of S100A8/A9 and its release mechanisms, summarize recent advances concerning the vital roles of S100A8/A9 in sepsis and the consequential organ damage, and underscore its potential as a promising diagnostic biomarker and therapeutic target for sepsis.

Construction and validation of a risk assessment model for acute kidney injury in patients with acute pancreatitis in the intensive care unit

BACKGROUND

To construct and validate a risk assessment model for acute kidney injury (AKI) in patients with acute pancreatitis (AP) in the intensive care unit (ICU).

METHODS

A total of 963 patients diagnosed with acute pancreatitis (AP) from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database was included. These patients were randomly divided into training set (N = 674) and validation set (N = 289) at a ratio of 7:3. Clinical characteristics were utilized to establish a nomogram for the prediction of AKI during ICU stay. These variables were selected by the least absolute shrinkage and selection operation (LASSO) regression and included in multivariate logistic regression analysis. Variables with P-values less than 0.05 were included in the final model. A nomogram was constructed based on the final model. The predicted accuracy of the nomogram was assessed by calculating the receiver operating characteristic curve (ROC) and the area under the curve (AUC). Moreover, calibration curves and Hosmer-Lemeshow goodness-of-fit test (HL test) were performed to evaluate model performance. Decision curve analysis (DCA) evaluated the clinical net benefit of the model.

RESULTS

A multivariable model that included 6 variables: weight, SOFA score, white blood cell count, albumin, chronic heart failure, and sepsis. The C-index of the nomogram was 0.82, and the area under the receiver operating characteristic curve (AUC) of the training set and validation set were 0.82 (95% confidence interval:0.79-0.86) and 0.76 (95% confidence interval: 0.70-0.82), respectively. Calibration plots showed good consistency between predicted and observed outcomes in both the training and validation sets. DCA confirmed the clinical value of the model and its good impact on actual decision-making.

CONCLUSION

We identified risk factors associated with the development of AKI in patients with AP. A risk prediction model for AKI in ICU patients with AP was constructed, and improving the treatment strategy of relevant factors in the model can reduce the risk of AKI in AP patients.

Diagnostic Accuracy of Plasma Cystatin C and Renal Resistive Index for Acute Kidney Injury in Critically Ill Patients: A Prospective Observational Study

Background

Acute kidney injury (AKI) is a quite common problem in critically ill patients. Serum cystatin C has emerged as a marker of AKI. This study was aimed to evaluate the diagnostic ability of serum Cystatin-C and Renal Resistive Index in prediction of AKI among critically ill patients.

Methodology

This prospective observational study was carried out in the department of Medicine, over a period of one year. After informed consent and ethical clearance total 120 critically ill patients suffering from sepsis were enrolled, out of which 70 patients developed AKI while 50 did not develop AKI during treatment in Intensive care unit (ICU). Serum cystatin C was measured on day 1 by particle-enhanced immune nephelometric assay, Renal resistive index (RRI) calculated by ratio of the velocities of arterial perfusion throughout the cardiac phase and glomerular filtration rate was measured on days 1, 3, and 7 respectively.

Results

S. cystatin C value was significantly higher(>3times) in AKI patients (14.07±4.8 mcg/ml) as compared to those who did not develop AKI (4.28±3.27 mcg/ml) (p<0.001). After ROC analysis it was found that day1, S. cystatin C, at cut off value of ≥9.29 mcg/ml had diagnostic accuracy 90% with sensitivity 91%, specificity89% and PPV 95.5%. While RRI value on day 7, at cut-off value of ≥0.72, had diagnostic accuracy 98%, sensitivity (98.6%) and specificity (96.7%) for AKI with 98.6% PPV, 96.7% NPV.

Conclusion

Serum cystatin C appears to be a promising bio- markers for early diagnosis of AKI in critically ill patients. Whereas, RRI although non-invasive had good diagnostic accuracy but it diagnosed AKI after few days thus diagnosis of kidney injury delayed.

Soluble Urokinase-Type Plasminogen Activator Receptor as a Prognostic Marker of Ugandan Children at Risk of Severe and Fatal Malaria

BACKGROUND

Current malaria diagnostic tests do not reliably identify children at risk of severe and fatal infection. Host immune and endothelial activation contribute to malaria pathogenesis. Soluble urokinase-type plasminogen activator receptor (suPAR) is a marker of these pathways. We hypothesized that measuring suPAR at presentation could risk-stratify children with malaria.

METHODS

Plasma suPAR levels were determined in consecutive febrile children with malaria at presentation to hospital in Jinja, Uganda. We evaluated the accuracy of suPAR in predicting in-hospital mortality, and whether suPAR could improve a validated clinical scoring system (Lambaréné Organ Dysfunction Score [LODS]).

RESULTS

Of the 1226 children with malaria, 39 (3.2%) died. suPAR concentrations at presentation were significantly higher in children who went on to die than in those who survived (P < .0001). suPAR levels were associated with disease severity (LODS: 0 vs 1, P = .001; 1 vs 2, P < .001; 2 vs 3, 0 vs 2, 1 vs 3, and 0 vs 3, P < .0001). suPAR concentrations were excellent predictors of in-hospital mortality (area under the receiver operating characteristic curve [AUROC], 0.92 [95% confidence interval {CI}, .91-.94]). The prognostic accuracy of LODS (AUROC, 0.93 [95% CI, .91-.94]) was improved when suPAR was added (AUROC, 0.97 [95% CI, .96-.98]; P < .0001).

CONCLUSIONS

Measuring suPAR at presentation can identify children at risk of severe and fatal malaria. Adding suPAR to clinical scores could improve the recognition and triage of children at risk of death. suPAR can be detected with a point-of-care test and can now be evaluated in prospective trials.

Spectrum, Outcomes, and Mortality Predictors of Acute Kidney Injury among Non-COVID-19 Patients during COVID-19 Pandemic: Data from Four Intensive Care Units

Introduction

The data of acute kidney injury (AKI), that is, community-acquired AKI (CA-AKI) and hospital-acquired AKI (HA-AKI) among non-COVID patients from intensive care units (ICU) during the coronavirus disease-2019 (COVID-19) pandemic are scarce. We planned to study the change in the profile of such patients compared to the pre-pandemic era.

Materials and methods

This prospective observational study was conducted at four ICUs dealing with non-COVID patients at a government hospital in North India, and was aimed at assessing outcomes, and mortality predictors of AKI among non-COVID patients during the COVID-19 pandemic. Renal and patient survival at ICU transfer-out and hospital discharge, ICU and hospital stay duration, mortality predictors, and dialysis requirement at discharge were evaluated. The current or previous COVID-19 infection, previous AKI or chronic kidney disease (CKD), organ donors, and organ transplant patients were excluded.

Results

Among the 200 non-COVID-19 AKI patients, diabetes mellitus (DM), primary hypertension, and cardiovascular diseases were the predominant comorbidities in descending order. The commonest cause of AKI was severe sepsis, followed by systemic infections and post-surgery patients. Dialysis requirements at ICU admission during ICU stay and above 30 days were seen in 20.5, 47.5, and 6.5% of patients, respectively. Incidence of CA-AKI and HA-AKI was 1.24:1, whereas dialysis requirement above 30 days was 0.85:1, respectively. The 30-day mortality was 42%. Hepatic dysfunction [hazard ratio (HR): 3.471], septicemia (HR: 3.342), age above 60 years (HR: 4.000), higher sequential organ failure assessment (SOFA) score (HR: 1.107; p = 0.001), anemia (p = 0.003), and low serum iron (p = 0.001) were important mortality predictors in AKI.

Conclusion

Compared to the pre-COVID era, CA-AKI was more common than HA-AKI due to restricted elective surgeries during the COVID-19 pandemic. Acute kidney injury with multiorgan involvement and hepatic dysfunction, elderly age with higher SOFA score and sepsis were predictors of adverse renal and patient outcomes.

How to cite this article

Singh B, Dogra PM, Sood V, Singh V, Katyal A, Dhawan M, et al. Spectrum, Outcomes, and Mortality Predictors of Acute Kidney Injury among Non-COVID-19 Patients during COVID-19 Pandemic: Data from Four Intensive Care Units. Indian J Crit Care Med 2023;27(2):119-126.

Using a machine learning model to predict the development of acute kidney injury in patients with heart failure

Background

Heart failure (HF) is a life-threatening complication of cardiovascular disease. HF patients are more likely to progress to acute kidney injury (AKI) with a poor prognosis. However, it is difficult for doctors to distinguish which patients will develop AKI accurately. This study aimed to construct a machine learning (ML) model to predict AKI occurrence in HF patients.

Materials and methods

The data of HF patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was retrospectively analyzed. A ML model was established to predict AKI development using decision tree, random forest (RF), support vector machine (SVM), K-nearest neighbor (KNN), and logistic regression (LR) algorithms. Thirty-nine demographic, clinical, and treatment features were used for model establishment. Accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the ML algorithms.

Results

A total of 2,678 HF patients were engaged in this study, of whom 919 developed AKI. Among 5 ML algorithms, the RF algorithm exhibited the highest performance with the AUROC of 0.96. In addition, the Gini index showed that the sequential organ function assessment (SOFA) score, partial pressure of oxygen (PaO₂), and estimated glomerular filtration rate (eGFR) were highly relevant to AKI development. Finally, to facilitate clinical application, a simple model was constructed using the 10 features screened by the Gini index. The RF algorithm also exhibited the highest performance with the AUROC of 0.95.

Conclusion

Using the ML model could accurately predict the development of AKI in HF patients.

Development and Validation of a Prognostic Nomogram to Predict 30-Day Mortality Risk in Patients with Sepsis-Induced Cardiorenal Syndrome

INTRODUCTION

Sepsis-induced cardiorenal syndrome (sepsis-induced CRS) is a devastating medical condition that is frequently associated with a high fatality rate. In this study, we aimed to develop an individualized nomogram that may help clinicians assess 30-day mortality risk in patients diagnosed with sepsis-induced CRS.

METHODS

A total of 340 patients with sepsis-induced CRS admitted from January 2015 to May 2019 in Shanghai Tongji Hospital were used as a training cohort to develop a nomogram prognostic model. The model was constructed using multivariable logistic analyses and was then externally validated by an independent cohort of 103 patients diagnosed with sepsis-induced CRS from June 2019 to December 2020. The prognostic ability of the nomogram was assessed through discrimination, calibration, and accuracy.

RESULTS

Five prognostic factors were determined and included in the nomogram: age, Sequential (sepsis-related) Organ Failure Assessment (SOFA) score, vasopressors, baseline serum creatinine, and the rate of change in myoglobin. Our prognostic nomogram showed well-fitted calibration curves and yielded strong discrimination power with the area under the curve of 0.879 and 0.912 in model development and validation, respectively. In addition, the nomogram prognostic model exhibited an evidently higher predictive accuracy than the SOFA score.

CONCLUSIONS

We developed a prognostic nomogram model for patients with sepsis-induced CRS and externally validated the model in another independent cohort. The nomogram exhibited greater strength in predicting 30-day mortality risk than the SOFA score, which may help clinicians estimate short-term prognosis and modulate therapeutic strategies.

Development and External Validation of a Nomogram for Predicting Acute Kidney Injury in Cardiogenic Shock Patients in Intensive Care Unit

Background

The aim of this study was to construct and external validate a nomogram for predicting cardiogenic shock acute kidney injury (CS-AKI) in patients in intensive care unit (ICU).

Methods

All patients diagnosed with CS from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) were included in this study. Least absolute shrinkage and selection operator (LASSO) regression and recursive feature elimination for support vector machine (SVM-RFE) were used to determine the overlapping clinical features associated with CS-AKI. The predictive nomogram was established based on the significant clinical parameters and externally verified in this study.

Results

LASSO regression and SVM-RFE demonstrated that Charlson Comorbidity Index (CCI), usage of mechanical ventilation, SOFA score, white blood cell, albumin, eGFR, anion gap, and positive fluid balance were closely associated with CS-AKI in the training cohort. The predictive nomogram based on the eight parameters showed good predictive performance as calculated by C-index were 0.823 (95% confidence index, 95% CI 0.798-0.849), 0.819 (95% CI 0.769-0.849), and 0.733 (95% CI 0.704-0.763) in the training set, in the internal validation set and in the external validation sets, respectively. Moreover, the nomogram exhibited not only encouraging calibration ability but also great clinical utility in the training set and in the validation sets.

Conclusion

CCI, usage of mechanical ventilation, SOFA score, white blood cell, albumin, eGFR, anion gap, and positive fluid balance were closely associated with CS-AKI. The predictive nomogram for CS-AKI manifested well-predictive ability for the identification of ICU patients with CS-AKI.

Serum Neutrophil Gelatinase-Associated Lipocalin (NGAL) Could Provide Better Accuracy Than Creatinine in Predicting Acute Kidney Injury Development in Critically Ill Patients

Acute kidney injury (AKI) is one of the most common complications in critically ill patients. In recent years, studies have focused on exploring new biomarkers for the early diagnosis and prognosis of AKI. The aim of this study was to investigate serum prognostic biomarkers (neutrophil gelatinase-associated lipocalin, NGAL, and creatinine) of AKI in critically ill patients. The study included 266 critically ill, initially nonseptic, patients admitted to a multidisciplinary ICU. Serum levels of NGAL and creatinine were measured at ICU admission. ROC curves were generated to estimate the prognostic value of the biomarkers, while a logistic regression analysis was performed to assess their association with an increased AKI risk. Patients were divided in two groups based on the development (n = 98) or not (n = 168) of AKI during their ICU stay. Serum NGAL levels at ICU admission were significantly higher in those who subsequently developed AKI compared to those who did not (p < 0.0001). NGAL was shown to be more accurate in predicting AKI development than creatinine; furthermore, NGAL levels were associated with an increased risk of AKI development (1.005 (1.002–1.008), p < 0.0001). In the present study, we were able to demonstrate that increased serum NGAL levels at ICU admission might be predictive of AKI development during ICU hospitalization. Further studies are needed to support NGAL as a prognostic marker of acute kidney injury.

Accuracy of the WSES classification system for pelvic ring disruptions: an international validation study

Background

In 2017, a novel classification for pelvic injuries was established by the World Society of Emergency Surgery (WSES). We validated its effectiveness using nationwide real-world data. The roles of associated vascular injury and open fracture in this system were also evaluated.

Methods

Patients with pelvic fractures in the National Trauma Data Bank 2015 dataset were retrospectively studied. First, the mortality rates were compared by WSES classification. Second, independent predictors of mortality were evaluated using a multivariate logistic regression model. Patients with and without associated vascular injuries and the same hemodynamic and pelvic ring stability statuses were compared. Patients with associated vascular injuries were compared to the proportion of nonsurvivors and survivors with unstable pelvic ring injuries. Third, the outcomes were compared between patients with open pelvic fracture and closed pelvic fracture in the mild, moderate and severe WSES classes.

Results

During the 12-month study period, 44,163 blunt pelvic fracture patients were included. The mortality rates were 1.8%, 3.8% and 10.6% for the mild, moderate and severe WSES classes, respectively (p < 0.001). MLR analysis showed that unstable pelvic ring injury did not significantly affect mortality (p = 0.549), whereas open pelvic fracture and associated vascular injury were independent predictors of mortality (odds of mortality: open pelvic fracture 1.630, p < 0.001; associated vascular injury 1.602, p < 0.001). Patients with associated vascular injuries showed that there was no significant difference in the proportion of patients with unstable pelvic ring injuries between survivors and nonsurvivors (37.2% vs. 32.7%, p = 0.323). In all three classes, patients with open pelvic fractures had significantly higher mortality rates and infection rates than patients with closed fractures (mortality rates: minor 3.5% vs. 1.8%, p = 0.009, moderate 11.2% vs. 3.3%, p < 0.001, severe 23.8% vs. 9.8%, p < 0.001; infection rates: minor 3.3% vs. 0.7%, p < 0.001, moderate 6.7% vs. 2.1%, p < 0.001, severe 7.9% vs. 2.8%, p < 0.001).

Conclusions

Based on this nationwide study, the WSES guideline provides an accurate and reproducible classification of pelvic fractures. It is recommended that open/closed fractures and associated vascular injuries be evaluated as supplements of the WSES classification.

Mortality Prediction in Patients with Severe Acute Kidney Injury Requiring Renal Replacement Therapy

Background and Objective: Acute kidney injury (AKI) remains a serious health condition around the world, and is related to high morbidity, mortality, longer hospitalization duration and worse long-term outcomes. The aim of our study was to estimate the significant related factors for poor outcomes of patients with severe AKI requiring renal replacement therapy (RRT). Materials and Methods: We retrospectively analyzed data from patients (n = 573) with severe AKI requiring RRT within a 5-year period and analyzed the outcomes on discharge from the hospital. We also compared the clinical data of the surviving and non-surviving patients and examined possible related factors for poor patient outcomes. Logistic regression was used to analyze the odds ratio for patient mortality and its related factors. Results: In 32.5% (n = 186) of the patients, the renal function improved and RRT was stopped, 51.7% (n = 296) of the patients died, and 15.9% (n = 91) of the patients remained dialysis-dependent on the day of discharge from the hospital. During the period of 5 years, the outcomes of the investigated patients did not change statistically significantly. Administration of vasopressors, aminoglycosides, sepsis, pulmonary edema, oliguria, artificial pulmonary ventilation (APV), patient age ≥ 65 y, renal cause of AKI, AKI after cardiac surgery, a combination of two or more RRT methods, dysfunction of three or more organs, systolic blood pressure (BP) ≤ 120 mmHg, diastolic BP ≤ 65 mmHg, and Sequential Organ Failure Assessment (SOFA) score on the day of the first RRT procedure ≥ 7.5 were related factors for lethal patient outcome. Conclusions: The mortality rate among patients with severe AKI requiring RRT is very high—52%. Patient death was significantly predicted by the causes of AKI (sepsis, cardiac surgery), clinical course (oliguria, pulmonary edema, hypotension, acidosis, lesion of other organs) and the need for a continuous renal replacement therapy.

The Clinical Value of GDF15 and Its Prospective Mechanism in Sepsis

Growth differentiation factor 15 (GDF15) is involved in the occurrence and development of many diseases, and there are few studies on its relationship with sepsis. This article aims to explore the clinical value of GDF15 in sepsis and to preliminarily explore its prospective regulatory effect on macrophage inflammation and its functions. We recruited 320 subjects (132 cases in sepsis group, 93 cases in nonsepsis group, and 95 cases in control group), then detected the serum GDF15 levels and laboratory indicators, and further investigated the correlation between GDF15 and laboratory indicators, and also analyzed the clinical value of GDF15 in sepsis diagnosis, severity assessment, and prognosis. In vitro, we used LPS to stimulate THP-1 and RAW264.7 cells to establish the inflammatory model, and detected the expression of GDF15 in the culture medium and cells under the inflammatory state. After that, we added GDF15 recombinant protein (rGDF15) pretreatment to explore its prospective regulatory effect on macrophage inflammation and its functions. The results showed that the serum GDF15 levels were significantly increased in the sepsis group, which was correlated with laboratory indexes of organ damage, coagulation indexes, inflammatory factors, and SOFA score. GDF15 also has a high AUC in the diagnosis of sepsis, which can be further improved by combining with other indicators. The dynamic monitoring of GDF15 levels can play an important role in the judgment and prognosis of sepsis. In the inflammatory state, the expression of intracellular and extracellular GDF15 increased. GDF15 can reduce the levels of cytokines, inhibit M1 polarization induced by LPS, and promote M2 polarization. Moreover, GDF15 also enhances the phagocytosis and bactericidal function of macrophages. Finally, we observed a decreased level of the phosphorylation of JAK1/STAT3 signaling pathway and the nuclear translocation of NF-κB p65 with the pretreatment of rGDF15. In summary, our study found that GDF15 has good clinical application value in sepsis and plays a protective role in the development of sepsis by regulating the functions of macrophages and inhibiting the activation of JAK1/STAT3 pathway and nuclear translocation of NF-κB p65.

Plasma calprotectin in the emergency department: a potential clinical biomarker for patients with infectious diseases

Increased levels of plasma calprotectin are reported in patients with infectious diseases. However, the clinical usefulness of calprotectin as a biomarker to identify patients with infectious diseases in the emergency department (ED) setting has not been investigated. To study the ability of calprotectin to discriminate patients with acute infectious diseases and dyspnea from patients with other causes of acute dyspnea in the ED setting. Patients aged ≥18 years seeking ED during daytime on weekdays between March 2013 and July 2018, with acute dyspnea, were included. Participants (n = 1287) were triaged according to Medical Emergency Triage and Treatment System-Adult score (METTS-A) or Rapid Emergency Triage and Treatment System (RETTS), and blood samples were collected. The association between calprotectin and other markers of infectious diseases, i.e. biomarkers (CRP, leucocytes) and body temperature, was studied. The predictive value of calprotectin for the outcome of acute infection was evaluated with receiver operating characteristic (ROC) analysis. Univariate cross-sectional regression showed significant associations between calprotectin and leucocytes, CRP and body temperature. Patients with severe infections including pneumonia (n = 119) had significantly higher concentrations of calprotectin compared to patients with heart failure (n = 162) or chronic obstructive pulmonary disease (n = 183). When tested for the outcome of acute infection (n = 109), the area under the ROC curve (AUROC) was for CRP 0.83 and for calprotectin 0.78. Plasma calprotectin identifies infectious diseases in ED patients with acute dyspnea, and the clinical usefulness of Calprotectin in the ED has to be further studied.

A Model-Based Approach to Assess Unstable Creatinine Clearance in Critically Ill Patients

Creatinine clearance is an important tool to describe the renal elimination of drugs in pharmacokinetic (PK) evaluations and clinical practice. In critically ill patients, unstable kidney function invalidates the steady-state assumption underlying equations, such as Cockcroft-Gault. Although measured creatinine clearance (mCrCL) is often used in nonsteady-state situations, it assumes that observed data are error-free, neglecting frequently occurring errors in urine collection. In contrast, compartmental nonlinear mixed effects models of creatinine allow to describe dynamic changes in kidney function while explicitly accounting for a residual error associated with observations. Based on 530 serum and 373 urine creatinine observations from 138 critically ill patients, a one-compartment creatinine model with zero-order creatinine generation rate (CGR) and first-order CrCL was evaluated. An autoregressive approach for interoccasion variability provided a distinct model improvement compared to a classical approach (Δ Akaike information criterion (AIC) -49.0). Fat-free mass, plasma urea concentration, age, and liver transplantation were significantly related to CrCL, whereas weight and sex were linked to CGR. The model-based CrCL estimates were superior to standard approaches to estimate CrCL (or glomerular filtration rate) including Cockcroft-Gault, mCrCL, four-variable modification of diet in renal disease (MDRD), six-variable MDRD, and chronic kidney disease epidemiology collaboration as a covariate to describe cefepime and meropenem PKs in terms of objective function value. In conclusion, a dynamic model of creatinine kinetics provides the means to estimate actual CrCL despite dynamic changes in kidney function, and it can easily be incorporated into population PK evaluations.

Sarcopenia as a predictor of mortality among the critically ill in an intensive care unit: a systematic review and meta-analysis

BACKGROUND

The evidence of sarcopenia based on CT-scan as an important prognostic factor for critically ill patients has not seen consistent results. To determine the impact of sarcopenia on mortality in critically ill patients, we performed a systematic review and meta-analysis to quantify the association between sarcopenia and mortality.

METHODS

We searched studies from the literature of PubMed, EMBASE, and Cochrane Library from database inception to June 15, 2020. All observational studies exploring the relationship between sarcopenia based on CT-scan and mortality in critically ill patients were included. The search and data analysis were independently conducted by two investigators. A meta-analysis was performed using STATA Version 14.0 software using a fixed-effects model.

RESULTS

Fourteen studies with a total of 3,249 participants were included in our meta-analysis. The pooled prevalence of sarcopenia among critically ill patients was 41 % (95 % CI:33-49 %). Critically ill patients with sarcopenia in the intensive care unit have an increased risk of mortality compared to critically ill patients without sarcopenia (OR = 2.28, 95 %CI: 1.83-2.83; P < 0.001; I² = 22.1 %). In addition, a subgroup analysis found that sarcopenia was associated with high risk of mortality when defining sarcopenia by total psoas muscle area (TPA, OR = 3.12,95 %CI:1.71-5.70), skeletal muscle index (SMI, OR = 2.16,95 %CI:1.60-2.90), skeletal muscle area (SMA, OR = 2.29, 95 %CI:1.37-3.83), and masseter muscle(OR = 2.08, 95 %CI:1.15-3.77). Furthermore, critically ill patients with sarcopenia have an increased risk of mortality regardless of mortality types such as in-hospital mortality (OR = 1.99, 95 %CI:1.45-2.73), 30-day mortality(OR = 2.08, 95 %CI:1.36-3.19), and 1-year mortality (OR = 3.23, 95 %CI:2.08 -5.00).

CONCLUSIONS

Sarcopenia increases the risk of mortality in critical illness. Identifying the risk factors of sarcopenia should be routine in clinical assessments and offering corresponding interventions may help medical staff achieve good patient outcomes in ICU departments.

MBD2 mediates renal cell apoptosis via activation of Tox4 during rhabdomyolysis-induced acute kidney injury

Our study investigated the role of Methyl‐CpG–binding domain protein 2 (MBD2) in RM‐induced acute kidney injury (AKI) both in vitro and in vivo. MBD2 was induced by myoglobin in BUMPT cells and by glycerol in mice. MBD2 inhibition via MBD2 small interfering RNA and MBD2‐knockout (KO) attenuated RM‐induced AKI and renal cell apoptosis. The expression of TOX high mobility group box family member 4 (Tox4) induced by myoglobin was markedly reduced in MBD2‐KO mice. Chromatin immunoprecipitation analysis indicated that MBD2 directly bound to CpG islands in the Tox4 promoter region, thus preventing promoter methylation. Furthermore, siRNA inhibition of Tox4 attenuated myoglobin‐induced apoptosis in BUMPT cells. Finally, MBD2‐KO mice exhibited glycerol‐induced renal cell apoptosis by inactivation of Tox4. Altogether, our results suggested that MBD2 plays a role in RM‐induced AKI via the activation of Tox4 and represents a potential target for treatment of RM‐associated AKI.

Risk Factors of Acute Kidney Injury in ECMO Patients: A Systematic Review and Meta-Analysis

PURPOSE

Acute kidney injury (AKI) is one of the most common complications in patients receiving extracorporeal membrane oxygenation (ECMO), but there is no systematic analysis regarding its risk factors. This meta-analysis aims to determine the risk factors of AKI in adult patients with ECMO treatment.

METHODS

Two authors independently carried out a systemic literature search using PubMed, Web of Science, and Embase until April 20, 2020 (inclusive) to enroll 12 studies reporting the necessary clinical characteristics. The Gender (male), age, APACHE II score, SOFA score, cancer, diabetes mellitus (DM), intra-aortic balloon pump (IABP), postcardiotomy, and ECMO supporting duration were pooled for further analysis by STATA.

RESULTS

Adult patients receiving ECMO who develop AKI and severe AKI incidents are usually older or have a higher APACHE II scores; in addition, severe AKI is related to higher SOFA scores, DM, and longer duration of ECMO support.

CONCLUSIONS

Patients with these clinical characteristics should be paid more attention during ECMO. There remains a need for additional studies to validate these conclusions and to detect additional AKI risk factors for ECMO patients.

Mortality prediction of serum neutrophil gelatinase-associated lipocalin in patients requiring continuous renal replacement therapy

BACKGROUND/AIMS

We investigated whether serum neutrophil gelatinase-associated lipocalin (NGAL) can predict mortality in patients with acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT).

METHODS

This study enrolled 169 patients who underwent serum NGAL testing at CRRT initiation from June 2017 to January 2019. The predictive power of serum NGAL level for 28-day mortality was compared to the Acute Physiology and Chronic Health Evaluation-II (APACHE-II) score and Sequential Organ Failure Assessment (SOFA) score via area under the receiver operating characteristic curve (AuROC) value.

RESULTS

There were 55 survivors and 114 non-survivors at 28 days post-CRRT initiation. Median serum NGAL level was significantly higher in the non-survivor group than in the survivor group (743.0 ng/mL vs. 504.0 ng/mL, p = 0.003). The AuROC value of serum NGAL level was 0.640, which was lower than APACHEII score and SOFA score values (0.767 and 0.715, respectively). However, in the low APACHE-II score group (< 27.5), AuROC value of serum NGAL was significantly increased (0.698), and it was an independent risk factor for 28 day-mortality (hazard ratio, 2.405; 95% confidence interval, 1.209 to 4.783; p = 0.012).

CONCLUSION

In patients with AKI requiring CRRT, serum NGAL levels may be useful for predicting short-term mortality in those with low APACHE-II scores.

The Protective Effects of Protease Inhibitor MG-132 on Sepsis-Induced Acute Kidney Injury and Its Mechanisms

MG-132 is an aldehyde peptide proteasome inhibitor, which reduces the inflammatory response and exerts a protective effect on severe acute pancreatitis and associated lung injury of rats. However, the involvement of MG-132 in sepsis-induced acute kidney injury (AKI) and the underlying mechanisms remain unknow. In this study, SD rats were employed to induce sepsis by cecal ligation and puncture (CLP) method and then divided into control, sham, CLP, and CLP + MG-132. Histopathology observation was detected by hematoxylin and eosin staining. The levels of biomarkers representing renal function such as serum creatinine (Scr), blood urea nitrogen (BUN), serum cystatin C (Scys C), and indicators of AKI such as Kim-1, IL-18, α glutathione S-traferase (α-GST) and albumin were measured by ELISA. Western blot and immunohistochemistry were performed to measure Testican-1. In order to assess the role of Testican-1, the expression of β-catenin, c-myc and cyclinD1 were evaluated by western blot. The results indicated that the levels of SCr, BUN, Scys C, KIM-1, IL-18, GST-α and albumin were decreased after MG-132 treatment compared with CLP group. And both pathological injury and W/D ratio were obviously improved in the CLP + MG- 132 group. Furthermore, the level of Testican-1 increased in the CLP group while a decreased presented in the CLP + MG-132 group. The expression of β-catenin, c-myc and cyclinD1 were downregulated in the CLP + MG-132 group compared to the CLP group. Our findings suggested that MG-132 can protect against AKI via inhibiting Testican-1 through the Wnt/β-catenin pathway MG-132 served as a novel biomarker and therapeutic regimen for sepsis-induced AKI.

Association of Serum Calprotectin Concentrations with Mortality in Critically Ill and Septic Patients

Background: Calprotectin is present in the cytosol of neutrophil granulocytes and released upon activation. Fecal calprotectin is applied in the clinical management of inflammatory bowel disease whereas serum calprotectin has been discussed as a biomarker in inflammatory disorders. However, its long-term prognostic relevance in critical illness remains unclear. Our aim was to investigate serum calprotectin concentrations as a prognostic biomarker in critically ill and septic patients. Methods: Serum calprotectin concentrations were analyzed in 165 critically ill patients (108 with sepsis, 57 without sepsis) included in our observational study. Patients were enrolled upon admission to the medical intensive care unit (ICU) of the RWTH Aachen University Hospital. Calprotectin concentrations were compared to 24 healthy controls and correlated with clinical parameters, therapeutic interventions, and survival. Results: Serum calprotectin concentrations were significantly increased in ICU patients as well as in septic patients compared to respective controls (p < 0.001 for ICU patients and p = 0.001 for septic patients). Lower calprotectin concentrations were measured in patients with comorbidities i.e., coronary artery disease. Calprotectin concentrations strongly correlated with the C-reactive protein (p < 0.001) and were closely associated to parameters of mechanical ventilation (i.a. inspiratory oxygen fraction, FiO2; p < 0.001). The overall survival was significantly impaired in septic patients with high baseline calprotectin concentrations (p = 0.036). However, patients with increasing calprotectin serum concentrations within the first week of ICU admission showed an improved overall survival (p = 0.009). Conclusions: In summary, serum calprotectin concentrations are significantly increased in critically ill patients with sepsis. High calprotectin concentrations at ICU admission predict long-term mortality risk, whereas increasing calprotectin concentrations are associated with a favorable long-term outcome.

Calprotectin and Neutrophil Gelatinase-Associated Lipocalin As Biomarkers of Acute Kidney Injury in Acute Coronary Syndrome

BACKGROUND

Acute kidney injury (AKI) is increasingly being seen in patients with acute coronary syndromes (ACS) and it is associated with higher short-term and long-term morbidity and mortality. Therefore, it is of paramount importance to identify those ACS patients at risk for the development of AKI. The objective of this study was to evaluate two different plasma biomarkers calprotectin and neutrophil gelatinase-associated lipocalin (NGAL) in early detecting the development of AKI in ACS patients.

METHODS

172 ACS patients admitted to the Coronary Care Unit in Yantai Yuhuangding Hospital were prospectively enrolled. Their blood samples were obtained on admission and subjected to enzyme-linked immunosorbent assay to determine the levels of novel biomarkers. The clinical data and biomarkers were recorded and analyzed.

RESULTS

In this study, 23 (13.4%) patients had a diagnosis of AKI. Statistical analysis demonstrated that in ACS patients with AKI, the following two biomarkers were significantly higher than these without AKI: plasma calprotectin (5942.26 ± 1955.88 ng/mL vs. 3210.29 ± 1833.60 ng/mL, p < 0.001) and plasma NGAL (164.91 ± 43.63 ng/mL vs. 122.48 ± 27.33 ng/mL, p < 0.001). Plasma calprotectin and NGAL could discriminate the development of AKI respectively with an area under the ROC curve (AUC) of 0.864 and 0.850. A combination of the two plasma biomarkers calprotectin and NGAL could early discriminate AKI in ACS patients with an AUC of 0.898.

CONCLUSIONS

This study demonstrated a promising panel of plasma calprotectin and NGAL as early diagnostic biomarkers for AKI in ACS patients.

PERSEVERE Biomarkers Predict Severe Acute Kidney Injury and Renal Recovery in Pediatric Septic Shock

Rationale: Acute kidney injury (AKI), a common complication of sepsis, is associated with substantial morbidity and mortality and lacks definitive disease-modifying therapy. Early, reliable identification of at-risk patients is important for targeted implementation of renal protective measures. The updated Pediatric Sepsis Biomarker Risk Model (PERSEVERE-II) is a validated, multibiomarker prognostic enrichment strategy to estimate baseline mortality risk in pediatric septic shock.Objectives: To assess the association between PERSEVERE-II mortality probability and the development of severe, sepsis-associated AKI on Day 3 (D3 SA-AKI) in pediatric septic shock.Methods: We performed secondary analysis of a prospective observational study of children with septic shock in whom the PERSEVERE biomarkers were measured to assign a PERSEVERE-II baseline mortality risk.Measurements and Main Results: Among 379 patients, 65 (17%) developed severe D3 SA-AKI. The proportion of patients developing severe D3 SA-AKI increased directly with increasing PERSEVERE-II risk category, and increasing PERSEVERE-II mortality probability was independently associated with increased odds of severe D3 SA-AKI after adjustment for age and illness severity (odds ratio, 1.4; 95% confidence interval, 1.2-1.7; P < 0.001). Similar associations were found between increasing PERSEVERE-II mortality probability and the need for renal replacement therapy. Lower PERSEVERE-II mortality probability was independently associated with increased odds of renal recovery among patients with early AKI. A newly derived model incorporating the PERSEVERE biomarkers and Day 1 AKI status predicted severe D3 SA-AKI with an area under the received operating characteristic curve of 0.95 (95% confidence interval, 0.92-0.98).Conclusions: Among children with septic shock, the PERSEVERE biomarkers predict severe D3 SA-AKI and identify patients with early AKI who are likely to recover.

Prognostic and predictive enrichment in sepsis

Sepsis is a heterogeneous disease state that is both common and consequential in critically ill patients. Unfortunately, the heterogeneity of sepsis at the individual patient level has hindered advances in the field beyond the current therapeutic standards, which consist of supportive care and antibiotics. This complexity has prompted attempts to develop a precision medicine approach, with research aimed towards stratifying patients into more homogeneous cohorts with shared biological features, potentially facilitating the identification of new therapies. Several investigators have successfully utilized leukocyte-derived mRNA and discovery-based approaches to subgroup patients on the basis of biological similarities defined by transcriptomic signatures. A critical next step is to develop a consensus sepsis subclassification system, which includes transcriptomic signatures as well as other biological and clinical data. This goal will require collaboration among various investigative groups, and validation in both existing data sets and prospective studies. Such studies are required to bring precision medicine to the bedside of critically ill patients with sepsis.

Potential Prognostic Markers of Acute Kidney Injury in the Early Phase of Acute Pancreatitis

Acute kidney injury (AKI) is a serious complication of acute pancreatitis (AP), which occurs in up to 70% of patients with severe AP and significantly increases the risk of mortality. At present, AKI is diagnosed based on dynamic increase in serum creatinine and decreased urine output; however, there is a need for earlier and more accurate biomarkers. The aim of the study was to review current evidence on the laboratory tests that were studied as the potential biomarkers of AKI in AP. We also briefly summarized the knowledge coming from the studies including sepsis or ICU patients since severe acute pancreatitis is associated with systemic inflammation and organ failure. Serum cystatin C and serum or urine NGAL have been shown to predict or diagnose AKI in AP; however, this evidence come from the single center studies of low number of patients. Other markers, such as urinary kidney injury molecule-1, cell cycle arrest biomarkers (tissue inhibitor metalloproteinase-2 and urine insulin-like growth factor-binding protein 7), interleukin-18, liver-type fatty acid-binding protein, or calprotectin have been studied in other populations suffering from systemic inflammatory states. In AP, the potential markers of AKI may be significantly influenced by either dehydration or inflammation, and the impact of these factors may be difficult to distinguish from kidney injury. The subject of AKI complicating AP is understudied. More studies are needed, for both exploratory (to choose the best markers) and clinical (to evaluate the diagnostic accuracy of the chosen markers in real clinical settings).