Association between lactate-to-albumin ratio and 28-days all-cause mortality in patients with acute pancreatitis: A retrospective analysis of the MIMIC-IV database

Clinical significance of the lactate-to-albumin ratio on prognosis in critically ill patients with acute kidney injury

OBJECTIVE

To explore the relationship between lactate-to-albumin ratio (LAR) at ICU admission and prognosis in critically ill patients with acute kidney injury (AKI).

METHODS

A retrospective analysis was conducted. Patients were divided into low (<0.659) LAR and high LAR (≥0.659) groups. Least absolute shrinkage and selection operator regression analysis was conducted to select variables associated with the 30-day prognosis. Cox regression analyses were performed to assess the association between LAR and mortality. Kaplan-Meier curves were plotted to compare cumulative survival rates between high and low LAR groups. Subgroup analysis was employed to assess the stability of the results. ROC curve was used to determine the diagnostic efficacy of LAR on prognosis.

RESULTS

A nonlinear relationship was observed between LAR and the risk of 30-day and 360-day all-cause mortality in AKI patients (p < 0.001). Cox regulation showed that high LAR (≥ 0.659) was an independent risk factor for 30-day and 360-day all-cause mortality in patients with AKI (p < 0.001). The Kaplan-Meier survival curves demonstrated a noteworthy decrease in cumulative survival rates at both 30 and 360 days for the high LAR group in comparison to the low LAR group (p < 0.001). Subgroup analyses demonstrated the stability of the results. ROC curves showed that LAR had a diagnostic advantage when compared with lactate or albumin alone (p < 0.001).

CONCLUSION

High LAR (≥0.659) at ICU admission was an independent risk factor for both short-term (30-day) and long-term (360-day) all-cause mortality in patients with AKI.

The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study

BACKGROUND

There is no evidence to determine the association between the lactate dehydrogenase to albumin ratio (LAR) and the development of sepsis-associated acute kidney injury (SAKI). We aimed to investigate the predictive impact of LAR for SAKI in patients with sepsis.

METHODS

A total of 4,087 patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC IV) database were included. Logistic regression analysis was used to identify the association between LAR and the risk of developing SAKI, and the relationship was visualized using restricted cubic spline (RCS). The clinical predictive value of LAR was evaluated by ROC curve analysis. Subgroup analysis was used to search for interactive factors.

RESULTS

The LAR level was markedly increased in the SAKI group (p < 0.001). There was a positive linear association between LAR and the risk of developing SAKI (p for nonlinearity = 0.867). Logistic regression analysis showed an independent predictive value of LAR for developing SAKI. The LAR had moderate clinical value, with an AUC of 0.644. Chronic kidney disease (CKD) was identified as an independent interactive factor. The predictive value of LAR for the development of SAKI disappeared in those with a history of CKD but remained in those without CKD.

CONCLUSIONS

Elevated LAR 12 h before and after the diagnosis of sepsis is an independent risk factor for the development of SAKI in patients with sepsis. Chronic comorbidities, especially the history of CKD, should be taken into account when using LAR to predict the development of AKI in patients with sepsis.

Comparison of lactate/albumin ratio and established scoring systems for predicting mortality in critically ill cirrhotic patients

BACKGROUND

Critically ill cirrhotic patients may present a serious clinical condition defined as acute-on-chronic liver failure with high mortality. While established scoring systems like Child-Pugh and Model for End-stage Liver Disease (MELD) offer prognostic insights, their limitations warrant exploration of alternative markers. The lactate/albumin ratio (LAR) serves as a potential prognostic indicator in critical care settings, yet its utility in cirrhotic patients remains underexplored.

METHODS

We assessed 175 critically ill cirrhotic patients in this retrospective cohort study. Clinical severity scores, including Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Failure Assessment (SOFA), and chronic liver failure-organ failure score (CLIF-OF), were compared with LAR along with traditional liver failure scoring systems. Logistic regression and receiver operating characteristic curve analysis were used to evaluate prognostic performance.

RESULTS

Intensive care unit (ICU) nonsurvivors had significantly higher scores in all liver failure and clinical severity scores compared to survivors (p<0.001). Median LAR was significantly higher in nonsurvivors (p<0.001). ROC analysis revealed comparable prognostic accuracy between LAR, APACHE II, SOFA, and CLIF-OF scores in predicting ICU mortality. Logistic regression identified SOFA score at 48th hours, LAR, and requirement of mechanical ventilation as independent predictors of ICU mortality.

CONCLUSION

LAR demonstrates promising prognostic utility in predicting ICU mortality among critically ill cirrhotic patients, complementing established scoring systems. Early reassessment using SOFA score at 48th hours may guide therapeutic interventions and improve patient outcomes. Further prospective studies are warranted to validate these findings and optimize clinical management strategies.

Lactate-to-albumin ratio: A promising predictor of 28-day all-cause mortality in critically Ill patients with acute ischemic stroke

INTRODUCTION

Numerous diseases have been found to be associated with the lactate-to-albumin ratio (LAR), as confirmed by existing research. This study aims to investigate the relationship between LAR within 24 hours of admission and a 28-day mortality rate in patients manifesting ischemic stroke.

METHODS

This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.1) database. We included adult patients with acute ischemic stroke (AIS) who were admitted to the intensive care unit. The primary outcome entailed evaluating the ability of LAR to predict death at 28-day of hospital admission in patients with AIS.

RESULTS

A total of 502 patients with ischemic stroke were enrolled in the study, of which 185 (36.9 %) died within 28 days after hospital admission. We identified a linear association between LAR and mortality risk. Compared with the reference group (first LAR tertile), the 28-day mortality was increased in the highest tertile; the fully adjusted HR value was 1.21 (1.08 to 1.40). the Area Under the Curve (AUC) value for LAR was 58.26 % (95 % CI: 53.05 % - 63.46 %), which was higher than that for arterial blood lactate (AUC = 56.88 %) and serum albumin (AUC = 55.29 %) alone. It was not inferior even when compared to SOFA (AUC = 56.28 %). The final subgroup analysis exhibited no significant interaction of LAR with each subgroup (P for interaction: 0.079 - 0.848).

CONCLUSION

In our study, LAR emerged as a promising predictor of all-cause mortality in acute ischemic stroke patients within 28 days of admission.

C-reactive protein/lymphocyte ratio as a prognostic biomarker in acute pancreatitis: a cross-sectional study assessing disease severity

BACKGROUND

The C-reactive protein/lymphocyte ratio (CLR) is a prognostic biomarker of various diseases. However, its significance in acute pancreatitis (AP) remains unknown. The main aim of this study was to investigate the association between the CLR and disease severity in patients with AP.

METHODS

This cross-sectional study included 476 AP patients [mild acute pancreatitis (MAP), n =176; moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP), n =300]. The primary exposure of interest was the baseline CLR. The primary outcome was the incidence of moderate to severe AP. Multivariate logistic regression and restricted cubic spline analyses were performed to evaluate the association between the CLR and the incidence of moderate to severe AP. Receiver operating characteristic (ROC) analysis was conducted to assess the predictive efficacy, sensitivity, and specificity of CLR in predicting the incidence of moderate to severe AP.

RESULTS

The mean age of the patients was 44±13.2 years, and 76.5% were male. The distribution of CLR was 31.6 (interquartile range, 4.5, 101.7). Moderate to severe AP occurred in 300 cases (63.0%). After multiple adjustments, CLR was independently associated with the incidence of moderate to severe AP (odds ratio, 1.04; 95% CI: 1.03-1.05; P < 0.001). A nonlinear relationship was found between CLR and the incidence of moderate to severe AP, with a threshold of approximately 45. The effect size and CI below and above the threshold value were 1.061 (1.033-1.089) and 1.014 (0.997-1.031), respectively. The area under the curve (AUC) for CLR was 87.577% (95% CI: 84.443- 90.710%) with an optimal cut-off value of 30.835, resulting in a sensitivity of 73.7% and a specificity of 88.6%.

CONCLUSIONS

There was a nonlinear relationship with a saturation effect between the CLR and the incidence of moderate to severe AP. The CLR measured within 24 h of admission may serve as a promising biomarker for predicting the emergence of moderate to severe AP, thereby providing a more scientifically grounded basis for preventing such cases. Nonetheless, further research is warranted to validate and strengthen these findings.

Association between serum creatinine to albumin ratio and short- and long-term all-cause mortality in patients with acute pancreatitis admitted to the intensive care unit: a retrospective analysis based on the MIMIC-IV database

Background

Serum creatinine (Cr) and albumin (Alb) are important predictors of mortality in individuals with various diseases, including acute pancreatitis (AP). However, most previous studies have only examined the relationship between single Cr or Alb levels and the prognosis of patients with AP. To our knowledge, the association between short- and long-term all-cause mortality in patients with AP and the blood creatinine to albumin ratio (CAR) has not been investigated. Therefore, this study aimed to evaluate the short- and long-term relationships between CAR and all-cause mortality in patients with AP.

Methods

We conducted a retrospective study utilizing data from the Medical Information Market for Intensive Care (MIMIC-IV) database. The study involved analyzing various mortality variables and obtaining CAR values at the time of admission. The X-tile software was used to determine the optimal threshold for the CAR. Kaplan-Meier (K-M) survival curves and multivariate Cox proportional hazards regression models were used to assess the relationship between CAR and both short- and long-term all-cause mortality. The predictive power, sensitivity, specificity, and area under the curve (AUC) of CAR for short- and long-term mortality in patients with AP after hospital admission were investigated using Receiver Operating Characteristic analysis. Additionally, subgroup analyses were conducted.

Results

A total of 520 participants were included in this study. The CAR ideal threshold, determined by X-tile software, was 0.446. The Cox proportional hazards model revealed an independent association between CAR≥0.446 and all-cause mortality at 7-day (d), 14-d, 21-d, 28-d, 90-d, and 1-year (y) before and after adjustment for confounders. K-M survival curves showed that patients with CAR≥0.446 had lower survival rates at 7-d, 14-d, 21-d, 28-d, 90-d, and 1-y. Additionally, CAR demonstrated superior performance, with higher AUC values than Cr, Alb, serum total calcium, Glasgow Coma Scale, Systemic Inflammatory Response Syndrome score, and Sepsis-related Organ Failure Assessment score at 7-d, 14-d, 21-d, 28-d, 90-d, and 1-y intervals. Subgroup analyses showed that CAR did not interact with a majority of subgroups.

Conclusion

The CAR can serve as an independent predictor for short- and long-term all-cause mortality in patients with AP. This study enhances our understanding of the association between serum-based biomarkers and the prognosis of patients with AP.

Blood urea nitrogen to serum albumin ratio: a novel mortality indicator in intensive care unit patients with coronary heart disease

The blood urea nitrogen to albumin ratio (BAR) has been demonstrated as a prognostic factor in sepsis and respiratory diseases, yet its role in severe coronary heart disease (CHD) remains unexplored. This retrospective study, utilizing data from the Medical Information Mart for Intensive Care-IV database, included 4254 CHD patients, predominantly male (63.54%), with a median age of 74 years (IQR 64-83). Primary outcomes included in-hospital, 28-day and 1-year all-cause mortality after ICU admission. The Kaplan-Meier curves, Cox regression analysis, multivariable restricted cubic spline regression were employed to assess association between BAR index and mortality. In-hospital, within 28-day and 1-year mortality rates were 16.93%, 20.76% and 38.11%, respectively. Multivariable Cox proportional hazards analysis revealed associations between the increased BAR index and higher in-hospital mortality (HR 1.11, 95% CI 1.02-1.21), 28-day mortality (HR 1.17, 95% CI 1.08-1.27) and 1-year mortality (HR 1.23, 95% CI 1.16-1.31). Non-linear relationships were observed for 28-day and 1-year mortality with increasing BAR index (both P for non-linearity < 0.05). Elevated BAR index was a predictor for mortality in ICU patients with CHD, offering potential value for early high-risk patient identification and proactive management by clinicians.

Association between glycemic variability and short-term mortality in patients with acute kidney injury: a retrospective cohort study of the MIMIC-IV database

Acute kidney injury (AKI) represents a significant challenge to global public health problem and is associated with poor outcomes. There is still considerable debate about the effect of mean blood glucose (MBG) and coefficient of variation (CV) of blood glucose on the short-term mortality of AKI patients. This retrospective cohort study aimed to explore the association between glycemic variability and short-term mortality in patients with AKI. Data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analyzed, including 6,777 adult AKI patients. MBG and CV on the first day of ICU admission were calculated to represent the overall glycemic status and variability during the ICU stay in AKI patients. The primary outcome indicator was ICU 30-day mortality of AKI patients. Multivariate Cox regression analysis and smoothed curve fitting were used to assess the relationship between blood glucose levels and mortality. Eventually, the ICU 30-day mortality rate of AKI patients was 23.5%. The increased MBG and CV were significantly correlated with ICU 30-day mortality (hazards ratio (HR) = 1.20, 95% confidence interval (CI) 1.14-1.27; HR = 1.08, 95% CI 1.03-1.13). The smoothed curve fitting showed a U-shaped relationship between MBG on the first day of ICU admission and ICU 30-day mortality (inflection point = 111.3 mg/dl), while CV had a linear relationship with 30-day ICU mortality. Thus, we conclude that MBG and CV were significantly associated with short-term mortality in intensive care patients with AKI. Tighter glycemic control may be an effective measure to improve the prognosis of patients with AKI.

Association between red cell distribution width-to-albumin ratio and prognostic outcomes in pediatric intensive care unit patients: a retrospective cohort study

Objective

This study aimed to assess the association between Red Cell Distribution Width-to-Albumin Ratio (RAR) and the clinical outcomes in Pediatric Intensive Care Unit (PICU) patients.

Design

This is a retrospective cohort study.

Methods

We conducted a retrospective cohort study based on the Pediatric Intensive Care database. The primary outcome was the 28-day mortality rate. Secondary outcomes included the 90-day mortality rate, in-hospital mortality rate, and length of hospital stay. We explored the relationship between RAR and the prognosis of patients in the PICU using multivariate regression and subgroup analysis.

Results

A total of 7,075 participants were included in this study. The mean age of the participants was 3.4 ± 3.8 years. Kaplan-Meier survival curves demonstrated that patients with a higher RAR had a higher mortality rate. After adjusting for potential confounding factors, we found that for each unit increase in RAR, the 28-day mortality rate increased by 6% (HR = 1.06, 95% CI: 1.01-1.11, P = 0.015). The high-RAR group (RAR ≥ 4.0) had a significantly increased 28-day mortality rate compared to the low-RAR group (RAR ≤ 3.36) (HR = 1.7, 95% CI: 1.23-2.37, P < 0.001). Similar results were observed for the 90-day and in-hospital mortality rate. No significant interactions were observed in the subgroup analysis.

Conclusion

Our study suggests a significant association between RAR and adverse outcomes in PICU patients. A higher RAR is associated with higher 28-day, 90-day, and in-hospital mortality rates.

The role of lactate-to-albumin ratio to predict 30-day risk of death in patients with sepsis in the emergency department: a decision tree analysis

BACKGROUND

Accurately estimating the prognosis of septic patients on arrival in the emergency department (ED) is clinically challenging. The lactate-to-albumin ratio (LAR) has recently been proposed to improve the predictive performance of septic patients admitted to the ICU.

OBJECTIVES

This study aims to assess whether the LAR could be used as an early prognostic marker of 30-day mortality in patients with sepsis in the ED.

METHODS

A prospective observational study was conducted in the ED of the Hospital of Merano. All patients with a diagnosis of sepsis were considered. The LAR was recorded on arrival in the ED. The primary outcome measure was mortality at 30 days. The predictive role of the LAR for mortality was evaluated with the area under the ROC curve, logistic regression adjusted for the Charlson Comorbidity Index value, National Early Warning Score, and Sequential Organ Failure score, and with decision tree analysis.

RESULTS

459 patients were enrolled, of whom 17% (78/459) died at 30 days. The median LAR of the patients who died at 30 days (0.78 [0.45-1.19]) was significantly higher than the median LAR of survivors (0.42 [0.27-0.65]) (p < 0.001). The discriminatory ability of the LAR for death at 30 days was 0.738, higher than that of lactate alone (0.692), and slightly lower than that of albumin alone (0.753). The decision trees confirmed the role of the LAR as an independent risk factor for mortality.

CONCLUSION

The LAR can be used as an index to better predict the 30-day risk of death in septic patients.

Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization

BACKGROUND

To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods.

METHODS

In total, 5757 CAD patients receiving coronary revascularization admitted to ICU in Medical Information Mart for Intensive Care IV (MIMIC-IV) were included in this cohort study. All the data were randomly split into the training set (n = 4029) and testing set (n = 1728) at 7:3. Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression model were applied for feature screening. Variables with Pearson correlation coefficient<9 were included, and the regression coefficients were set to 0. Features more closely related to the outcome were selected from the 10-fold cross-validation, and features with non-0 Coefficent were retained and included in the final model. The predictive values of the models were evaluated by sensitivity, specificity, area under the curve (AUC), accuracy, and 95% confidence interval (CI).

RESULTS

The Catboost model presented the best predictive performance with the AUC of 0.831 (95%CI: 0.811-0.851) in the training set, and 0.760 (95%CI: 0.722-0.798) in the testing set. The AUC of the logistic regression model was 0.789 (95%CI: 0.764-0.814) in the training set and 0.731 (95%CI: 0.686-0.776) in the testing set. The results of Delong test revealed that the predictive value of the Catboost model was significantly higher than the logistic regression model (P<0.05). Charlson Comorbidity Index (CCI) was the most important variable associated with the risk of stroke in CAD patients receiving coronary revascularization.

CONCLUSION

The Catboost model was the optimal model for predicting the risk of stroke in CAD patients receiving coronary revascularization, which might provide a tool to quickly identify CAD patients who were at high risk of postoperative stroke.

A nomogram for predicting in-hospital overall survival of hypertriglyceridemia-induced severe acute pancreatitis: A single center, cross-sectional study

Background

Hypertriglyceridemia-induced severe acute pancreatitis (HTG-SAP) is a type of pancreatitis characterized by an abnormal elevation of plasma triglyceride. HTG-SAP has been associated with various complications and a high mortality rate. In this study, we established a nomogram for predicting the overall survival (OS) of HTG-SAP patients during hospitalization.

Methods

128 HTG-SAP cases hospitalized at the Affiliated Huadu Hospital, Southern Medical University, from 2019 to 2022 were analyzed retrospectively. A nomogram including prognostic factors correlated with OS during hospitalization was established by multivariate Cox regression analysis. We internally validated the nomogram using time-dependent (at 1-, 2-, and 3- months) survival receiver operating characteristic (SROC) and calibration curve with 500 iterations of bootstrap resampling. Time-dependent decision curve analysis (DCA) was employed to validate the clinical value of the nomogram.

Results

Multivariate Cox regression indicated that serum triglyceride, red blood cell distribution width (RDW), lactic acid, and interleukin-6 (IL6) were independent prognostic factors for OS of HTG-SAP patients during hospitalization and were used to construct a nomogram. The time-dependent area under the curve (AUC) values at 1-, 2-, and 3- months were 0.946, 0.913, and 0.929, respectively, and the Concordance index (C-index) of the nomogram was 0.916 (95%CI 0.871-0.961). The time-dependent calibration curves indicated good consistency between the observed and predicted outcomes. The time-dependent DCAs also revealed that the nomogram yielded a high clinical net benefit. After stratifying the included cases into two risk groups based on the risk score obtained from the nomogram, the high-risk group exhibited a significantly inferior overall survival (OS) compared to the low-risk group (p < 0.0001).

Conclusions

Our nomogram exhibited good performance in predicting the overall survival of HTG-SAP patients during hospitalization.

Development and validation of a novel combinatorial nomogram model to predict in-hospital deaths in heart failure patients

BACKGROUND

The purpose of this study was to develop a Nomogram model to identify the risk of all-cause mortality during hospitalization in patients with heart failure (HF).

METHODS

HF patients who had been registered in the Medical Information Mart for Intensive Care (MIMIC) III and IV databases were included. The primary outcome was the occurrence of all-cause mortality during hospitalization. Two Logistic Regression models (LR1 and LR2) were developed to predict in-hospital death for HF patients from the MIMIC-IV database. The MIMIC-III database were used for model validation. The area under the receiver operating characteristic curve (AUC) was used to compare the discrimination of each model. Calibration curve was used to assess the fit of each developed models. Decision curve analysis (DCA) was used to estimate the net benefit of the predictive model.

RESULTS

A total of 16,908 HF patients were finally enrolled through screening, of whom 2,283 (13.5%) presented with in-hospital death. Totally, 48 variables were included and analyzed in the univariate and multifactorial regression analysis. The AUCs for the LR1 and LR2 models in the test cohort were 0.751 (95% CI: 0.735∼0.767) and 0.766 (95% CI: 0.751-0.781), respectively. Both LR models performed well in the calibration curve and DCA process. Nomogram and online risk assessment system were used as visualization of predictive models.

CONCLUSION

A new risk prediction tool and an online risk assessment system were developed to predict mortality in HF patients, which performed well and might be used to guide clinical practice.

Association between lactate/albumin ratio and 28-day all-cause mortality in ischemic stroke patients without reperfusion therapy: a retrospective analysis of the MIMIC-IV database

Objective

The lactate/albumin ratio (LAR) has been used as a novel prognostic indicator for aneurysmal subarachnoid hemorrhage, traumatic brain injury, sepsis, heart failure, and acute respiratory failure. However, its potential in predicting all-cause mortality in patients with ischemic stroke (IS) has not been evaluated. Therefore, this study aimed to elucidate the correlation between LAR and 28-day all-cause mortality in IS patients without reperfusion therapy.

Methods

This retrospective cohort study used data from the Medical Information Mart for Intensive Care (MIMIC-IV) (v2.0) database. It included 568 IS adult patients admitted to the intensive care unit (ICU). The correlation between LAR and ICU 28-day all-cause mortality rate was analyzed using multiple COX regression analysis and Kaplan-Meier survival analysis. Restricted cubic spline (RCS) curves were used to assess the relationship between LAR and 28-day mortality. In addition, a subgroup analysis was performed to investigate the impact of other influencing factors on outcomes. The primary outcome was the ability of LAR to predict 28-day mortality in IS patients.

Results

Among the 568 patients with IS, 370 survived (survival group) and 198 died (non-survival group) within 28 days of admission (mortality rate: 34.9%). A multivariate COX regression analysis indicated that LAR was an independent predictor of all-cause mortality within 28 days after admission for patients with IS (hazard ratio: 1.32; 95% confidence interval: 1.03-1.68; P = 0.025). We constructed a model that included LAR, age, race, sex, white blood cell count, Sequential Organ Failure Assessment (SOFA) score, and anion gap (AG) and established a prediction model with an area under the curve (AUC) value of 71.5% (95% confidence interval: 67.1%-75.8%). The optimal cutoff value of LAR that separated the survival group and the non-survival group based on the Youden index was 0.55. The Kaplan-Meier survival curves plotted using this critical value showed that patients with LAR ≥ 0.55 had a significantly higher 28-day all-cause mortality rate than patients with LAR < 0.55 (P = 0.0083).

Conclusion

LAR can serve as an independent predictor of all-cause mortality within 28 days after admission for patients with IS.

Association of lactate/albumin ratio with in-hospital mortality in ICU patients with acute respiratory failure: A retrospective analysis based on MIMIC-IV database

We aimed to investigate the association between the lactate/albumin ratio (LAR), and in-hospital mortality in critically ill patients with acute respiratory failure. This retrospective cohort study was conducted based on the medical information mart for intensive care-IV database, which included critically ill adult patients with acute respiratory failure whose primary endpoint was in-hospital death. The analyses included curve fitting, a logistic multivariate regression model, and subgroup analysis. In this study, 6028 intensive care unit patients with acute respiratory failure were analyzed. Of these, 1843 (30.57%) died. After adjusting for confounding factors, a nonlinear relationship between LAR and in-hospital mortality was observed, and the risk of death was found to decrease by 81% with a reduction of 1 unit of LAR when it was < 4.46. The association between LAR and in-hospital mortality was not statistically significant when LAR was > 4.46. Hence, the relationship between LAR and in-hospital mortality could only be observed when the LAR was < 4.46. There is a nonlinear relationship between LAR and the risk of in-hospital death in intensive care unit patients with acute respiratory failure, and there is a saturation effect.

Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit

Purpose

The aim of this study is to develop and validate a predictive model for the prediction of in-hospital mortality in patients with acute pancreatitis (AP) based on the intensive care database.

Patients and Methods

We analyzed the data of patients with AP in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). Then, patients from MIMIC-IV were divided into a development group and a validation group according to the ratio of 8:2, and eICU-CRD was assigned as an external validation group. Univariate logistic regression and least absolute shrinkage and selection operator regression were used for screening the best predictors, and multivariate logistic regression was used to establish a dynamic nomogram. We evaluated the discrimination, calibration, and clinical efficacy of the nomogram, and compared the performance of the nomogram with Acute Physiology and Chronic Health Evaluation II (APACHE-II) score and Bedside Index of Severity in AP (BISAP) score.

Results

A total of 1030 and 514 patients with AP in MIMIC-IV database and eICU-CRD were included in the study. After stepwise analysis, 8 out of a total of 37 variables were selected to construct the nomogram. The dynamic nomogram can be obtained by visiting https://model.sci-inn.com/KangZou/. The area under receiver operating characteristic curve (AUC) of the nomogram was 0.859, 0.871, and 0.847 in the development, internal, and external validation set respectively. The nomogram had a similar performance with APACHE-II (AUC = 0.841, p = 0.537) but performed better than BISAP (AUC = 0.690, p = 0.001) score in the validation group. Moreover, the calibration curve presented a satisfactory predictive accuracy, and the decision curve analysis suggested great clinical application value of the nomogram.

Conclusion

Based on the results of internal and external validation, the nomogram showed favorable discrimination, calibration, and clinical practicability in predicting the in-hospital mortality of patients with AP.