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

Total bilirubin-to-albumin ratio and short- and long-term all-cause mortality in acute pancreatitis: Evidence from the MIMIC-IV database

BACKGROUND

The Total Bilirubin-to-Albumin Ratio (TBAR) is widely recognized and applied as a biomarker in the prognostic evaluation of various diseases. However, its role in predicting survival outcomes in patients with acute pancreatitis (AP) remains underexplored. This study aims to investigate the association between TBAR levels and mortality rates in AP patients, thereby providing a novel prognostic indicator for clinical use.

METHODS

This study investigates the association between TBAR and mortality in AP patients. We stratified patient data using X-tile software to analyze intergroup differences. Risk factors significantly associated with mortality were identified through univariate and multivariate regression analyses. Kaplan-Meier (KM) analysis evaluated TBAR's impact on survival, while Receiver Operating Characteristic (ROC) analysis assessed its predictive accuracy, sensitivity, and Area Under the Curve (AUC) for mortality. To ensure robustness, we used Restricted Cubic Spline (RCS) modeling to explore non-linear relationships and performed subgroup analyses to verify the consistency of the TBAR mortality association across patient subgroups.

RESULT

This study included 477 patients. Using X-tile software, we set the optimal TBAR cutoff at 1.33 based on 28-day mortality. Patients were categorized into high-risk (TBAR ≥ 1.33) and low-risk (TBAR < 1.33) groups. Elevated TBAR significantly correlated with increased mortality at multiple time points (7, 14, 21, 28, 90, and 365 days; P < 0.05). KM analysis confirmed lower survival rates in the high-risk group at all time points (P < 0.05). ROC analysis showed TBAR's predictive accuracy for mortality was comparable to the SOFA score and superior to other indicators. RCS modeling revealed a linear TBAR mortality relationship. Subgroup analyses showed no significant interactions between TBAR and most subgroups.

CONCLUSION

The TBAR is strongly correlated with short-term and long-term mortality in patients with acute pancreatitis.

Blood urea nitrogen to albumin ratio as predictor of mortality among acute pancreatitis patients in ICU: A retrospective cohort study

OBJECTIVE

Blood urea nitrogen to albumin ratio (BAR) has served as a predictive marker for patients in the Intensive Care Unit (ICU), and has been studied in patients with sepsis, post-cardiac surgery, severe COVID-19, and acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This objective indicator has demonstrated capability in prognostic prediction.However, research on the prognostic value of BAR in acute pancreatitis (AP) patients are scarce,the goal was to explore the relationship between BAR and total mortality in AP admitted to ICU.

METHODS

A Retrospective analysis was performed utilizing the Medical Information Market for Intensive Care (MIMIC IV) database. Patients with AP admitted to ICU were included and grouped based on BAR. Univariate and multivariate Cox regression analysis were utilized to explore the relationship between BAR and total mortality. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was applied to assess the predictive value of BAR. Cumulative hazard risk accumulation curve verified BAR's predictive capability for short- and long-term mortality. Heterogeneity between different subgroups was excluded by subgroup analysis.

RESULTS

Total 514 AP patients were divided into high-BAR (BAR ≥ 7.62) and low-BAR group (BAR < 7.62). The duration of ICU stay was significantly extended in the high BAR group. In the Cox proportional hazard model, whether adjusting for confounding factors or not, the high BAR was an independent risk factor for total mortality. AUC for BAR was 0.78 (95% C1: 0.72-0.84) at 28 days and 0.70 (95%: Cl: 0.64-0.75) at 360 days.

CONCLUSION

BAR is an objective and independent predictor of both short- and long-term total mortality in AP patients. A prompt, efficient, and uncomplicated assessment of the severity and prognosis, which facilitates ICU doctors to develop treatment plans for poor patient outcomes.

Association Between Lactate-to-Albumin Ratio and 28-Day All-Cause Mortality in Critical Care Patients with COPD: Can Both Arterial and Peripheral Venous Lactate Serve as Predictors?

Background

Lactate-to-albumin ratio (LAR) has been reported as a useful predictor for multiple critical illnesses. However, the association between LAR and mortality in patients with chronic obstructive pulmonary disease (COPD) remains unclear. This study aims to clarify the correlation between LAR and 28-day all-cause mortality in patients with COPD and to investigate whether LAR calculated using arterial lactate (AL) or peripheral venous lactate (PVL) can serve as predictive indicators.

Methods

A total of 1428 patients from the Medical Information Mart for Intensive Care (MIMIC) IV database (version 2.2) and 2467 patients from the eICU Collaborative Research Database (eICU-CRD, version 2.0) were included in this study. Propensity score matching (PSM) method was conducted to control confounders. Cox proportional hazards model, Kaplan-Meier survival method, subgroup analysis and receiver operating characteristic (ROC) analysis were performed to assess the predictive ability of LAR. To verify our hypothesis, data from the two databases were analyzed individually.

Results

After adjusting for covariates, LAR calculated using either AL (MIMIC IV, HR = 1.254, 95% CI, 1.013-1.552, P = 0.038) or PVL (eICU-CRD, HR = 1.442, 95% CI, 1.272-1.634, P < 0.001) was independently associated with 28-day all-cause mortality in COPD patients. Kaplan-Meier analysis showed that patients with higher LAR value had significantly higher all-cause mortality (all P < 0.05). This association was consistent across subgroup analyses. In addition, the ROC analysis suggested that LAR calculated using PVL may have better predictive performance compared to using AL.

Conclusion

LAR calculated using both AL and PVL can independently predict the 28-day all-cause mortality after ICU admission in patients with COPD and higher level of LAR is related to higher mortality risk.

Association of blood urea nitrogen to albumin ratio with mortality in acute pancreatitis

Blood urea nitrogen (BUN) and serum albumin (ALB) are strongly associated with the prognosis in acute pancreatitis (AP). The BUN/ALB ratio (BAR) reflects renal, nutritional, inflammatory, and endothelial functions. In this study, we investigated the association between the BAR and all-cause mortality in critically ill patients with AP. Using data from the Medical Information Market for Intensive Care (MIMIC-IV) database, we conducted a retrospective cohort analysis. The relationship between BAR and mortality was assessed through Kaplan-Meier survival curves, restricted cubic spline models, and multivariable Cox proportional hazards regression. The predictive capacity of BAR for 30-day and 1-year mortality was evaluated using receiver operating characteristic analysis. Our study included 780 participants, with 30-day and 1-year mortality rates of 12.6% and 23.6%, respectively. Higher BAR values were associated with poorer survival outcomes. BAR demonstrated superior predictive performance achieving an area under the curve of 0.74, surpassing BUN, ALB, and SOFA scores. The Cox model indicated a significant independent association between elevated BAR and increased mortality risk, with hazard ratios of 1.43 (95% CI 1.20-1.70) for 30-day mortality and 1.37 (95% CI 1.17-1.60) for 1-year mortality. Stratified and sensitivity analyses confirmed the robustness of these findings. Our results suggest that elevated BAR is associated with poor prognosis in critically ill patients with AP and may serve as a valuable tool for early risk stratification and for assessing both short- and long-term prognosis.

Lactate dehydrogenase to albumin ratio and poor prognosis after thrombolysis in ischemic stroke patients: developing a novel nomogram

BACKGROUND

Ischemic stroke (IS) is associated with high disability and mortality. This study aimed to identify the prognostic predictors and develop a nomogram for a prediction model for ischemic stroke patients after thrombolysis.

METHODS

We retrospectively analyzed data from 359 IS patients who underwent thrombolysis. Clinical characteristics, laboratory parameters, and prognosis data were collected. One-third of the subjects were randomly selected as a validation set (n = 108) for internal validation. Logistic regression analysis was used to derive independent risk indicators. A nomogram was constructed using these indicators, and the performance of the nomogram was assessed by the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC). The agreement of the model predictions with actual observations was assessed via calibration curves, and the clinical utility of the nomogram was assessed via decision curve analysis.

RESULTS

Multivariate logistic regression analysis showed that age, leukocytes, Lactate Dehydrogenase to Albumin Ratio (LAR) and NIHSS were independent predictors of three-month post-thrombolysis prognosis in IS patients. We created a nomogram based on the weighting coefficients of these factors. The AUC curves showed that our model including age, leukocytes, LAR and NIHSS was more accurate in predicting prognosis than a single factor. The calibration curves showed a good fit between actual and predicted probabilities in both the training and validation groups.

CONCLUSION

LAR has a good predictive power for the prognosis of IS patients 3 months after thrombolytic therapy and can be used as a new clinical indicator to establish a practical nomogram.

Nomogram establishment for gastrointestinal bleeding prediction in ICU patients with traumatic brain injury based on the MIMIC-IV database

Objectives

This study aimed to develop a robust nomogram for predicting the occurrence of gastrointestinal bleeding (GIB) in patients with traumatic brain injury (TBI) during their ICU stay, thereby facilitating the optimization of intervention strategies and enabling personalized treatment approaches.

Methods

Patient data were extracted from the publicly available MIMIC-IV (Medical Information Mart for Intensive Care IV) database. In this retrospective cohort study, a total of 2,774 patients with traumatic brain injury (TBI) were included. A 7:3 ratio was applied to allocate patients into the training and validation cohorts. A LASSO logistic regression model was constructed using the training set to identify potential predictors of gastrointestinal bleeding (GIB). The selected features were subsequently utilized to develop a nomogram model. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results

A nomogram model comprising six variables-gender, blood urea nitrogen (BUN), Shock Index (SI), albumin, SOFA score, and diabetes mellitus-was developed. These variables were identified as independent risk factors for gastrointestinal bleeding (GIB) in patients with traumatic brain injury (TBI) (p < 0.05). The area under the receiver operating characteristic curve (AUC) for the derivation cohort and validation cohort was 0.8541 (95% CI: 0.833 to 0.911) and 0.8381 (95% CI: 0.752 to 0.863), respectively. The calibration curve demonstrated good agreement between the predicted probabilities and actual observations, while decision curve analysis (DCA) highlighted the clinical utility of the predictive model.

Conclusion

This study developed a predictive model for GIB in patients with TBI, which may assist clinicians in early identification of high-risk patients and help mitigate the burden of GIB in susceptible populations.

Association between lactate-to-albumin ratio and mortality in hepatic failure: a retrospective cohort study

BACKGROUND

Liver failure has a high mortality rate, and currently, there is no convenient risk predictor. The lactate-to-albumin ratio (LAR) has emerged as a promising predictor in various critical illnesses. However, its potential role in predicting all-cause mortality in patients with liver failure remains unexplored. Therefore, this study aims to investigate the correlation between LAR and all-cause mortality in patients suffering from liver failure.

METHODS

We retrospectively analyzed data from patients with liver failure who were admitted to the intensive care unit (ICU) between 2008 and 2019, which were gathered from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. LAR was calculated from the ratio obtained from the first measurement taken within 24 h of admission. The optimal LAR threshold was determined using the Youden index. With LAR categorized into low, middle, and high groups based on tertiles, Kaplan - Meier analysis was employed to compare mortality risks among three patient groups. Multivariate Cox proportional hazards regression models were utilized to evaluate the association between LAR and all-cause mortality in hepatic failure patients within hospital admission. Additionally, receiver operating characteristic (ROC) and smoothing curve analysis were used to assess the predictive ability, sensitivity, and specificity of LAR for all-cause mortality in patients with liver failure, and the area under the curve (AUC) was calculated. A smooth curve fitting approach and threshold effect analysis were employed to detect the potentially non-linear relationship between the LAR and the risk of all-cause mortality in patients with hepatic failure. Finally, subgroup analyses were performed to assess the relationship between LAR and prognosis across different types of liver failure.

RESULTS

A total of 902 patients with hepatic failure were included in this study. They were divided into survivors group (611 patients) and non-survivors group (291 patients) according to whether they survived during hospitalization, and the mortality rate of patients was 32.26%. The Kaplan-Meier survival curves illustrating patients in hepatic failure with elevated LAR showed a significantly heightened risk of in-hospital mortality (P < 0.001). We identified a non-linear relationship between LAR and the risk of hospital mortality after adjusting for potential confounders and the inflection point of LAR to be 1.33. LAR was shown to be an independent predictor of all-cause mortality within hospitalization in patients with hepatic failure by multivariate COX regression analysis (HR, 1.66; 95% CI, 1.35-2.05; P < 0.0001). The optimal cutoff value for separating the survival and death groups according to ROC was found to be 0.97. The AUC value for LAR was 0.755 (95% CI: 0.721, 0.789), which was higher than that for arterial blood lactate (AUC = 0.725) and serum albumin (AUC = 0.680) alone. It was not inferior even when compared to MELD (AUC = 0.677).

CONCLUSION

LAR has demonstrated good predictive value for all-cause mortality among liver failure patients in our retrospective study.

Association between phosphorus-to-calcium ratio at ICU admission and all-cause mortality in acute pancreatitis: Insights from the MIMIC-IV database

BACKGROUND

Serum phosphorus and serum calcium are important electrolytes in the body. The relationship between them and acute pancreatitis (AP) has been previously discussed. However, the results seem to lack credibility due to the neglect of mutual influence between them. Thus, a comprehensive indicator is needed.

METHODS

In this study, AP patients with intensive care unit (ICU) treatment were extracted from Medical Information Mart for Intensive Care (MIMIC) database. The outcomes included in-hospital mortality and ICU mortality. Kaplan-Meier survival analysis, Cox proportional hazard regression model and restricted cubic spline were employed to investigate the association between the phosphorus-to-calcium ratio (PCR) index and clinical outcomes.

RESULTS

A total of 719 AP patients (57.2% male) were enrolled. The in-hospital and ICU mortality were 11.4% and 7.5%, respectively. After adjusting for confounders, Cox proportional hazard analysis indicated patients with a higher PCR index had a significant association with in-hospital mortality (adjusted hazard ratio, 2.88; 95% confidence interval, 1.34-6.19; p = .007). Restricted cubic splines revealed that a progressively increasing risk of all-cause mortality was associated with an elevated PCR index.

CONCLUSION

The PCR index has a strong correlation with in-hospital and ICU all-cause mortality in AP, which provides a reference for clinical decision-making.

The Prognostic Value of Red Blood Cell Distribution Width-to-Albumin Ratio (RAR) in Predicting Mortality and Severity in Acute Pancreatitis: A Systematic Review and Meta-Analysis

Acute pancreatitis is a potentially life-threatening inflammatory condition with variable clinical presentations. Early risk stratification remains challenging despite existing scoring systems. The red blood cell distribution width-to-albumin ratio (RAR) has emerged as a potential prognostic biomarker in inflammatory conditions. This systematic review and meta-analysis aimed to evaluate the association between admission RAR and outcomes in acute pancreatitis. We conducted a comprehensive literature search and identified five retrospective studies meeting the inclusion criteria. Meta-analysis was performed to assess the relationship between RAR and mortality as well as disease severity in acute pancreatitis patients. Pooled analysis demonstrated that elevated RAR was significantly associated with increased mortality risk (risk ratio (RR): 2.11, 95% confidence interval (95% CI): 1.35-3.30) with moderate heterogeneity (I²: 46%). When comparing disease severity, mean RAR values were significantly lower in mild acute pancreatitis compared to severe cases (mean difference (MD): -1.78, 95% CI: -2.09 to -1.46), also with moderate heterogeneity (I²: 44%). This meta-analysis suggests that RAR, a simple and cost-effective biomarker available from routine blood tests, may serve as a valuable prognostic indicator for mortality and severity in acute pancreatitis. Despite having comparatively lower discriminative ability than conventional scoring systems, RAR offers advantages in terms of rapid assessment and cost efficiency. However, limitations include the small number of included studies, their retrospective nature, and heterogeneity in study settings. Further prospective studies are warranted to validate these findings.

Association between lactate-to-albumin ratio and short-term prognosis of acute-on-chronic liver failure treated with artificial liver support system

BACKGROUND

The impact of lactate-to-albumin ratio (LAR) on the outcome of acute-on-chronic liver failure (ACLF) is scant.

AIMS

To investigate the relationship between LAR and short-term prognosis in patients with COSSH (Chinese Group on the Study of Severe Hepatitis B) ACLF.

METHODS

A retrospective cohort study was conducted in patients with COSSH ACLF treated with an artificial liver support system. Restricted cubic splines, linear regression models, and Cox regression models were used to investigate the relationships of LAR with disease severity and 28-day prognosis.

RESULTS

The 28-day transplant-free and overall survival rates in the 258 eligible patients were 76.4% and 82.2%, respectively. The LAR in 28-day transplant-free survivors was lower than that in transplant or death patients [0.74 (0.58-0.98) vs. 1.03 (0.79-1.35), P <  0.001]. The LAR was positively associated with disease severity, 28-day transplant-free survival [adjusted hazard ratio (HR) (95% confidence interval (CI)) for transplant or death: 2.18 (1.37-3.46), P =  0.001], and overall survival [adjusted HR (95% CI) for death: 2.14 (1.21-3.80), P =  0.009]. Compared with patients with LAR < 1.01, patients with LAR ≥ 1.01 had poor 28-day prognosis [all adjusted HR (95% CI) > 1, P  < 0.05]. Lactate was not a potential modifier of the relationship between LAR and short-term prognosis.

CONCLUSION

LAR was positively associated with disease severity and poor short-term prognosis in patients with COSSH ACLF.

Association between lactate-to-albumin ratio and all-cause mortality in critically ill cirrhotic patients with sepsis: a retrospective analysis of the MIMIC-IV database

BACKGROUND

The impact of lactate-to-albumin ratio (LAR) on mortality of critically ill cirrhotic patients with sepsis is scant.

METHODS

Critically ill cirrhotic patients with sepsis were obtained from the MIMIC-IV database (v3.0). Cox regression models alone and in combination with restricted cubic splines, generalized additive models and smoothed curve fitting were used to investigate the relationship between LAR and all-cause mortality.

RESULTS

A total of 1864 patients were included. The 30-day, 90-day, and 180-day all-cause mortality rates were 38.0%, 46.3%, and 49.5%, respectively. Higher LAR were significantly and nonlinearly associated with higher risks of 30-day, 90-day, and 180-day all-cause mortality (all adjusted HR = 1.17, P < 0.001). L-shaped associations between LAR and 30-day, 90-day, and 180-day all-cause mortality were observed, with an inflection point of 1.05 (P for log-likelihood ratio < 0.01). Compared with patients with LAR < 1.05, patients with LAR ≥ 1.05 had higher risks of 30-day, 90-day, and 180-day all-cause mortality (adjusted HR (95% CI): 1.48 (1.27-1.72), 1.44 (1.25-1.66), and 1.38 (1.21-1.57), respectively). No potential modifiers were found in the relationship between LAR and mortality.

CONCLUSIONS

LAR was positively and nonlinearly associated with all-cause mortality in critically ill cirrhotic patients with sepsis. Thus, it could be used as a prognostic biomarker.

Association between lactate-to-albumin ratio and all-cause mortality in cirrhosis patients: Analysis of the MIMIC-IV database

OBJECTIVE

This study evaluates the predictive value of the lactate/albumin ratio (LAR) for all-cause mortality in cirrhosis patients.

DESIGN

Retrospective observational study.

SETTING

Intensive care unit (ICU).

PATIENTS OR PARTICIPANTS

626 first-time ICU-admitted cirrhosis patients in the USA (MIMIC-IV v2.2).

INTERVENTIONS

None.

MAIN VARIABLES OF INTEREST

LAR index, 28-day, and 90-day all-cause mortality.

RESULTS

Of 626 patients (60.86% male), 27.80% and 39.14% died within 28 and 90 days, respectively. Multivariate Cox analysis showed a significant association between higher LAR and mortality. Adjusted for confounders, elevated LAR increased the 28-day mortality risk [HR: 1.31 (1.21-1.42), P < 0.001]. A restricted cubic spline analysis revealed non-linear relationships between LAR and mortality. For 28-day mortality, the inflection point was 1.583: below this, HR was 2.29 (95% CI: 1.61-3.27, P < 0.001); above, HR was 1.16 (95% CI: 1.02-1.31, P = 0.021; P = 0.002). For 90-day mortality, the inflection point was 1.423: below, HR was 1.60 (95% CI: 1.04-2.47, P = 0.033); above, HR was 0.94 (95% CI: 0.75-1.16, P = 0.542; P = 0.012).

CONCLUSIONS

LAR predicts 28-day and 90-day mortality with a segmented effect. An LAR ≥1.583 signals high 28-day mortality risk, necessitating intensified monitoring and potential ICU admission. For 90-day mortality, LAR near 1.423 serves as an early warning for high-risk patients and guides interventions. Continuous LAR monitoring aids management, but prospective studies are needed to confirm clinical utility.

Association between serum creatinine-to-albumin ratio and 28-day mortality in intensive care unit patients following cardiac surgery: analysis of mimic-iv data

BACKGROUND

Creatinine-to-albumin ratio (CAR) has been recognized as a predictive indicator in the postoperative setting. However, its relationship with outcomes in patients receiving cardiac surgery remains elusive. This study aimed to discuss the link between CAR and 28-day mortality in patients admitted to intensive care unit (ICU) following cardiac surgery, hoping to provide some insights for targeted interventions for improvement of patient outcomes.

METHODS

MIMIC-IV database was searched to obtain data of patients admitted to ICU following cardiac surgery. Retrieved patients were split into three groups based on CAR levels. The 28-day ICU mortality in each group was evaluated and compared using Kaplan-Meier analysis. Subgroup analysis, multivariate Cox regression and restricted cubic spline (RCS) analysis were used to further examine the relationship between CAR and outcomes. Receiver operating characteristic (ROC) curves were used to assess the predictive ability of CAR. Mediation analysis was conducted to investigate the potential mechanism by which CAR affects 28-day ICU mortality.

RESULTS

A total of 5,670 patients were included and divided into three groups. Patients with high CAR values (CAR ≥ 0.31) had a significantly increased rate of 28-day ICU mortality (11.4%), as compared to those with low CAR levels (CAR < 0.23, 1.83%). In addition, patients with high CAR values (CAR ≥ 0.31) had a lowest survival rate than the other two groups (p < 0.0001). ROC curve analysis showed that CAR exhibited a moderate predictive power (AUC = 0.748). Moreover, CAR was identified as a strong risk factor for 28-day ICU mortality, and a significant dose-response association was presented. Further subgroup analysis revealed pronounced mortality risks in females and patients without chronic conditions such as chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Mediation analysis indicated that CAR affected 28-day ICU mortality through biomarkers like chloride (39.8%), glucose (11.8%), potassium (24.4%), and sodium (28.3%).

CONCLUSION

CAR served as a risk factor for 28-day ICU mortality in patients receiving cardiac surgery, and it showed a complex dose-response and subgroup-specific association with 28-day ICU mortality. Additionally, CAR affected 28-day ICU mortality through multiple key biomarkers, providing some insights for targeted interventions.

Lactate-to-albumin ratio as a potential prognostic predictor in patients with cirrhosis and sepsis: a retrospective cohort study

BACKGROUND

Patients with liver cirrhosis face high infection risks due to immune dysfunction and hospital-related factors, increasing mortality rates when sepsis occurs. While various biomarkers predict outcomes in cirrhosis, few are accessible and reliable. This study addresses the gap by evaluating the prognostic potential of the lactate-to-albumin ratio (LAR).

METHODS

We retrospectively analyzed data from patients with cirrhosis and sepsis who were admitted to the intensive care unit at Beth Israel Deaconess Medical Center between 2008 and 2022. LAR was calculated from the ratio obtained from the first measurement taken within 24 h of admission. The optimal LAR threshold was determined using R statistical software. Kaplan-Meier analysis was used to compare mortality risks between two patient groups, while multivariate Cox proportional hazards regression models were used to assess the association between LAR and mortality risk in patients with cirrhosis and concomitant sepsis. A restricted cubic spline (RCS) was used to explore potential dose-response relationships between LAR and mortality. Receiver operating characteristic (ROC) analyses were used to assess the predictive ability, sensitivity, and specificity of LAR for all-cause mortality in patients with cirrhosis and combined sepsis, and the area under the curve (AUC) was calculated. Finally, subgroup analyses were performed to assess the relationship between LAR and prognosis across different populations.

RESULTS

A total of 1731 patients were included in the study. The optimal LAR threshold was identified as 1.0 using R statistical software. Kaplan-Meier analysis indicated that patients with higher LAR levels had a higher risk of 14-day, 28-day, and 90-day all-cause mortality (all log-rank P < 0.001). Multivariate Cox proportional hazards models indicated independent associations between higher LAR levels and all-cause mortality at 14-day, 28-day, and 90-day before and after adjusting for confounders. RCS analysis revealed a nonlinear association between LAR and short- and long-term all-cause mortality in patients with cirrhosis and sepsis. ROC curve analysis showed that although the predictive value of LAR for the prognosis of patients with cirrhosis combined with sepsis was slightly inferior to that of the Model for End-Stage Liver Disease score, it was significantly better than that of lactate, albumin, and the Sequential Organ Failure Assessment. Subgroup analyses showed no significant interactions between LAR and any specific subgroup.

CONCLUSION

LAR has good predictive value for the prognosis of patients with cirrhosis and sepsis.

Association between red cell distribution width to albumin ratio and all-cause mortality in patients with acute pancreatitis admitted to the intensive care unit: a retrospective study based on the MIMIC-IV database

Background

Red blood cell volume distribution width (RDW) and albumin (Alb) have been proved to be predictors of mortality in various diseases, such as acute pancreatitis (AP). However, until now the relationship between RDW to Alb ratio (RAR) and mortality in AP has not been fully elucidated. Therefore, this study aims to evaluate the relationship between RAR and all-cause mortality in AP.

Method

Patients with AP in the Critical Care Medical Information Market (MIMIC-IV) database who met criteria were included in this retrospective study. Associated baseline data was obtained, cleaned and analyzed. Kaplan Meier (K-M) survival curve and Cox proportional hazards regression model were utilized to evaluate the relationship between RAR and all-cause mortality. Restricted Cubic Spline (RCS) was used for exploring how hazard ratio (HR) changes as RAR varied. Additionally, Receiver Operating Characteristic (ROC) analysis and subgroup analysis were conducted to assess the predictive value and to explore the significance of RAR in different populations.

Results

499 patients were included in this study. Survival curve showed that patients with RAR > 5.14 had higher mortality rate at 7-day (d), 14-d, 21-d, 28-d, 90-d, 180-d and 1-year (y). The univariate and multivariate Cox models revealed an independent association between high-level RAR and all-cause mortality at 28-d, 90-d and 1-y. RCS showed that RAR became a risk factor when exceeding 5.14. RAR only had linear relationship with mortality at 1-y after adjusting for the potential confounders. Subgroup analysis suggested that increased RAR caused higher risk of death in male, non-white people or those patients without respiratory failure (RF). ROC analysis indicated that compared with other parameters such as SOFA score, RAR exhibited higher efficiency in predicting in-hospital and all-cause mortality at 14-d, 21-d, 28-d, 90-d. Combined RAR with BISAP, RAR-modified BISAP showed superiority in predicting short-term mortality (28-d).

Conclusion

For patients with AP in ICU, RAR has a strong association with short- and long-term prognosis. Especially, RAR is a promising indicator for short-term all-cause mortality in patients with AP. For males, non-white patients and those without RF, elevated RAR may be a more dangerous signal of mortality.

C-reactive protein to serum calcium ratio as a novel biomarker for predicting severity in acute pancreatitis: a retrospective cross-sectional study

Background

Acute pancreatitis (AP) is a prevalent gastrointestinal emergency with a wide spectrum of clinical outcomes, varying from mild cases to severe forms. The early identification of high-risk patients is essential for improving prognosis. However, the predictive and prognostic potential of the C-reactive protein to serum calcium ratio (CCR) in AP has not been investigated. This study aims to explore the association between CCR and disease severity in patients with AP.

Methods

This retrospective cross-sectional study included 476 AP patients. The CCR was calculated from C-reactive protein and serum calcium levels within the first 24 h of admission. Multivariable logistic regression models were used to evaluate the relationship between CCR and AP severity, with restricted cubic spline analysis and receiver operating characteristic (ROC) analysis to assess dose-response and predictive performance, respectively.

Results

Of the 476 patients, 176 (37%) had mild acute pancreatitis (MAP) and 300 (63%) had moderate to severe AP. The CCR distribution had a median value of 17.5, with an interquartile range (IQR) of 3.0 to 60.2. Each unit increase in CCR was associated with a 7% increase in the risk of developing moderate to severe AP (OR: 1.07; 95% CI: 1.06-1.09). In fully adjusted models, this association remained statistically significant. The area under the curve (AUC) for CCR in predicting moderate to severe AP was 86.9%, with a sensitivity of 73.7% and specificity of 89.2%.

Conclusion

The CCR measured within the first 24 h of admission shows promise as a valuable biomarker for predicting the severity of AP. However, further multicenter prospective cohort studies are needed to confirm its clinical utility and investigate its role in improving treatment strategies and patient management.

Explainable machine learning and online calculators to predict heart failure mortality in intensive care units

AIMS

This study aims to develop explainable machine learning models and clinical tools for predicting mortality in patients in the intensive care unit (ICU) with heart failure (HF).

METHODS

Patients diagnosed with HF who experienced their first ICU stay lasting between 24 h and 28 days were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The primary outcome was all-cause mortality within 28 days. Data analysis was performed using Python and R, with feature selection conducted via least absolute shrinkage and selection operator (LASSO) regression. Fifteen models were evaluated, and the most effective model was rendered explainable through the Shapley additive explanations (SHAP) approach. A nomogram was developed based on logistic regression to facilitate interpretation. For external validation, the eICU database was utilized.

RESULTS

After selection, the study included 2343 records, with 1808 surviving and 535 deceased patients. The median age of the study population was 70.00, with ~3/5 males (60.31%). The median length of stay in the ICU was 6.00 days. The median age of the survival group was younger than the non-survival group (69.00 vs. 73.00), and non-survival patients spent longer time in the ICU. Seventy-five features were initially selected, including basic information, vital signs, laboratory tests, haemodynamics and oxygen status. LASSO regression determined the shrinkage parameter α = 0.020, and 44 features were chosen for model construction. The linear discriminant analysis (LDA) model showed the best performance, and the accuracy reached 0.8354 in the training cohort and 0.8563 in the testing cohort. It showed satisfying area under the curve (AUC), recall, precision, F1 score, Cohen's kappa score and Matthew's correlation coefficient. The concordance index (c-index) reached 0.7972 in the training cohort and 0.8125 in the testing cohort. In external validation, the LDA model achieved approximately 0.9 in accuracy, precision, recall and F1 score, with an AUC of 0.79. Univariable analysis was performed in the training cohort. Features that differed significantly between the survival and non-survival groups were subjected to multiple logistic regression. The nomogram built on multiple logistic regression included 14 features and demonstrated excellent performance. The AUC of the nomogram is 0.852 in the training cohort, 0.855 in the internal validation cohort and 0.770 in the external validation cohort. The calibration curve showed good consistency.

CONCLUSIONS

The study developed an LDA and a nomogram model for predicting mortality in HF patients in the ICU. The SHAP approach was employed to elucidate the LDA model, enhancing its utility for clinicians. These models were made accessible online for clinical application.

Unlocking the Predictive Power of Nutritional Scores in Septic Patients

Background: Sepsis is a critical condition characterized by severe immune dysregulation, ranking among the leading causes of morbidity and mortality in intensive care and internal medicine units. Nutritional status plays a pivotal role in modulating these responses, as when inadequate it can compromise immune defenses, the body's ability to handle stress and inflammation, and the clinical course. Malnutrition is frequently observed in septic patients and is strongly associated with worse clinical outcomes, including increased mortality, prolonged hospital stays, and greater complication rates. In this context, nutritional scoring systems have emerged as valuable tools to evaluate patients' nutritional status and predict clinical trajectories. Objectives: Given the absence of a direct comparison of their performance in an internal medicine setting, this study aimed to assess the effectiveness of various nutritional scores as predictive tools for clinical outcomes in septic patients, emphasizing their application within the field of internal medicine. Methods and Results: A retrospective analysis was conducted on 143 patients diagnosed with sepsis or septic shock who were admitted to an internal medicine unit. Key variables included clinical and laboratory parameters, comorbidities, and nutritional scores at the time of diagnosis. The modified Glasgow Prognostic Score (mGPS), the Prognostic Nutritional Index (PNI), the Controlling Nutritional Status (CONUT) score, the modified Nutrition Risk in Critically Ill (mNUTRIC) score, and the blood urea nitrogen-to-albumin ratio (BAR) were evaluated in forecasting mortality and clinical outcomes in patients with sepsis. Among them, the mNUTRIC score emerged as the strongest independent predictor of in-hospital mortality, with a good performance and a reasonable threshold for risk stratification. Conclusions: The study highlights the mNUTRIC score's practicality and reliability in assessing nutritional and inflammatory risks in septic patients, particularly in non-ICU settings. These findings suggest its potential utility in guiding nutritional interventions and improving clinical outcomes, emphasizing the importance of integrating nutritional assessment into sepsis management.

Association of pre-exiting heart failure with long-term mortality and the recurrence of sepsis

This retrospective cohort study aimed to evaluate the association between pre-existing heart failure and both mortality and the recurrence of sepsis. A total of 16,092 sepsis patients without a history of heart failure and 841 sepsis patients with pre-existing heart failure were identified from the Medical Information Mart for Intensive Care version IV (MIMIC-IV ) database. All patients were adults admitted to intensive care units, and no specific interventions were applied. After matching, Kaplan-Meier survival analysis showed significantly poorer long-term survival rates in patients with heart failure, both in the original (p < 0.0001) and the matched cohort (p = 0.00059). Mortality rates were tracked over different time periods, revealing that the mortality disparity became evident after the first year (p = 0.029). Besides, the cumulative incidence of sepsis recurrence was substantially higher in patients with a history of heart failure (p < 0.001) when deaths without recurrence were treated as competing events. Moreover, there was no statistically significant difference observed in the deaths without recurrence between the two groups (p = 0.251). In conclusion, pre-existing heart failure is associated with an increased risk of long-term mortality, which may be partly explained by a higher incidence of recurrent sepsis in this population.

Large-scale genome-wide association studies identified causal relationship between multiple blood biomarkers and risk of acute pancreatitis

BACKGROUND AND AIM

Observational studies have shown that there is a connection between blood biomarkers and the occurrence of acute pancreatitis (AP). Nevertheless, the causal relationships are still not clear. The purpose of this study was to evaluate causal association between biomarkers and AP.

METHOD(S)

A bidirectional two-sample Mendelian randomization (MR) analysis was applied to investigate the causal association between blood biomarkers and AP. Summary statistics obtained from genome-wide association studies were utilized for this analysis. The primary statistical approach employed was the inverse variance weighted (IVW) method, complemented by sensitivity analyses aimed at assessing heterogeneity and pleiotropy. Furthermore, a multivariable MR (MVMR) analysis was performed to adjust for confounders.

RESULTS

A total of 11 red blood cell (RBC) traits, 6 white blood cell traits, platelet count, and 30 blood biomarkers were analyzed in this study. Genetically predicted RBC count (IVW odds ratio [OR] = 1.144, P = 0.004), the high light scatter reticulocyte count (HLSR) (OR = 1.127, P = 0.022), blood glucose (BG) (OR = 1.480, P = 0.019), and leptin (OR = 1.234, P = 0.050) were suggestively associated with an increased risk of AP. Reverse MR analysis showed no causal effect of AP on RBC, HLSR, BG, and leptin (IVW P > 0.05). Sensitivity analyses and MVMR analysis still supported the earlier causality.

CONCLUSION(S)

Our findings provide evidence of a suggestive association between RBC count, HLSR, BG, and leptin with an increased susceptibility to AP. These findings aid in our comprehension of the cause of AP and may be used as potential prognostic markers or predictors of severity with AP.

Predictive accuracy of lactate albumin ratio for mortality in intensive care units: a nationwide cohort study

BACKGROUND

The lactate albumin ratio (LAR), a simple prognostic marker used in intensive care units (ICUs), combines lactate and serum albumin levels to predict patient outcomes. Despite its potential, the predictive accuracy of the LAR remains insufficiently explored. This study aimed to assess the usefulness of the LAR in predicting mortality among patients in the ICU.

METHODS

This retrospective study conducted a secondary analysis of prospectively obtained clinical data from the Japanese Intensive Care Patient Database. We included all patients admitted to ICUs between 2015 and 2021, excluding those under the age of 16 years. The main outcome was in-hospital mortality. The LAR predictive value for this outcome was assessed by examining the area under the receiver operating characteristic curve and comparing it against prognostic indicators such as age, lactate, albumin and Sequential Organ Failure Assessment score. LAR shape was assessed using unrestricted spline curves, and the optimal cut-off value was identified from sensitivity and negative likelihood ratio. Subgroup analysis was used to evaluate the predictive accuracy of the LAR across different patient attributes and clinical scenarios.

RESULTS

Of 2 34 774 cases analysed, in-hospital mortality was 8.8% (20 723 deaths). The LAR had an area under the curve of 0.761 (95%CI 0.757 to 0.765), indicating a fair predictive performance for in-hospital mortality. Unrestricted spline curves demonstrated that LAR can predict mortality through a monotonic positive dose-response relationship with 0.4 as the optimal cut-off value. In subgroup analysis, areas under the curve were significantly higher in subgroups defined by younger age, female sex, unplanned ICU admission, non-surgical patients, non-infectious patients, non-heart failure patients and lack of end-stage renal disease.

CONCLUSIONS

The LAR might be a useful predictor for screening mortality in ICU patients. However, further research to establish appropriate cut-off values for the LAR and identify the optimal target population is warranted.

Clinical significance of lactate-to-albumin ratio in patients with influenza A virus-induced acute respiratory distress syndrome: a single-center retrospective study

BACKGROUND

The lactate-to-albumin ratio (LAR) is predictive of disease prognosis in some cases. However, the clinical significance of LAR in patients with influenza A virus-induced acute respiratory distress syndrome (ARDS) has yet to be explored. This study aims to investigate whether LAR can be used as a predictor of influenza A virus-induced ARDS.

METHODS

In this single-center retrospective study, we enrolled 105 patients with influenza A virus pneumonia into the study and divided the patients into an ARDS group (74 patients) and a non-ARDS group (31 patients) during hospitalization. Clinical characteristics and laboratory data were collected within 24 h after admission. We explored the risk factors for ARDS using logistic regression analysis. The predictive performance of potential risk factors for ARDS and ARDS-associated complications were evaluated by receiver operating characteristic (ROC) curves, and Pearson's correlation analysis was used to evaluate the correlations between risk factors and clinical and laboratory variables.

RESULTS

LAR was an independent predictor for the development of ARDS in patients with influenza A virus pneumonia and was significantly predictive for ARDS. LAR's area under the curve (AUC) was higher than that of lactate and albumin alone; its AUC was 0.878, with a sensitivity of 71.6% and a specificity of 96.8%. The optimal ROC threshold for distinguishing ARDS from non-ARDS cases was 44.81 × 10- 3. Correlation analysis indicated that LAR was positively associated with duration of invasive ventilation, and APACHE II and SOFA scores in ARDS patients but was negatively associated with PaO2/FiO2 (p < 0.001). Subsequent ROC curve analysis determined that LAR was a robust predictor for the 14-day invasive ventilation (AUC = 0.924), septic shock (AUC = 0.860), and hepatic injury (AUC = 0.905) in hospitalized ARDS patients. It also showed a promising predictive value for 28-day mortality (AUC = 0.881).

CONCLUSION

LAR strongly predicted ARDS development in patients with influenza A virus pneumonia. It showed a significant correlation with disease severity and provided promising predictive efficiency for extrapulmonary complications and 28-day mortality in patients with influenza A virus-induced ARDS.

The endothelial activation and stress index is a potential prognostic indicator for patients with acute pancreatitis managed in the intensive care unit: a retrospective study

Background

The endothelial activation and stress index (EASIX) serves as a dependable and efficient surrogate marker for endothelial dysfunction, which plays an essential role in the pathophysiology of acute pancreatitis (AP). Hence, we investigated the prognostic value of EASIX in AP.

Methods

This was a retrospective study, using patient information obtained from the Medical Information Market for Intensive Care-IV (MIMIC-IV) database. EASIX was calculated using lactate dehydrogenase, serum creatinine, and platelet counts obtained during the first measurement within 24 h of admission. Patients were grouped into three cohorts based on log2-transformed EASIX. The main endpoint of the study was 28-day all-cause mortality (ACM) in AP patients, with the secondary endpoint being 90-day ACM. The relationship between EASIX and prognosis in patients with AP was evaluated using Cox proportional hazards models, Kaplan-Meier curves, restricted cubic spline (RCS) curves, and subgroup analyses. Receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of EASIX compared to other indicators.

Results

The study cohort comprised 620 patients in total. Multivariate Cox proportional hazards analysis indicated that an increased log2 (EASIX) was linked to a higher risk of 28-day ACM in AP patients (HR, 1.32; 95% CI: 1.14-1.52; p < 0.001). The risk of 28-day ACM was higher in Tertiles 2 and 3 compared with Tertile 1 [(HR, 2.80; 95% CI: 1.21-6.45); (HR, 3.50; 95% CI: 1.42-8.66)]. Comparable findings were noted for 90-day ACM. Kaplan-Meier curves demonstrated that patients with elevated log2 (EASIX) had lower 28- and 90-day survival rates. The RCS curves suggested a non-linear relationship between log2 (EASIX) and 28- and 90-day ACM. ROC curves indicated that log2 (EASIX) was not inferior to sequential organ failure assessment and systemic inflammatory response syndrome scores in predicting the prognosis of patients with AP. Subgroup analyses demonstrated no interaction between log2 (EASIX) and any subgroup.

Conclusion

Elevated EASIX levels were significantly correlated with a heightened risk of 28- and 90-day ACM in AP patients.

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.

Association between lactate-to-albumin ratio and short-time mortality in patients with acute respiratory distress syndrome

STUDY OBJECTIVE

The lactate-to-albumin ratio (LAR) has been confirmed to be an effective prognostic marker in sepsis, heart failure, and acute respiratory failure. However, the relationship between LAR and mortality in patients with acute respiratory distress syndrome (ARDS) remains unclear. We aim to evaluate the predictive value of LAR for ARDS patients.

DESIGN

A retrospective cohort study.

SETTING

Medical Information Mart for Intensive Care IV (v2.2) database.

PATIENTS

769 patients with acute respiratory distress syndrome(ARDS).

INTERVENTIONS

We divided the patients into two subgroups according to the primary study endpoint (28-days all-cause mortality): the 28-day survivors and the 28-day non-survivors.

MEASURES

Multivariate Cox Regression, Receiver Operator Characteristic (ROC) and Kaplan-Meier survival analysis were used to investigate the relationship between LAR and short-time mortality in patients with ARDS.

MAIN RESULTS

The 28-day mortality was 38 % in this study. Multivariable Cox regression analysis showed that LAR was an independent predictive factor for 28-day mortality (HR 1.11, 95 %CI: 1.06-1.16, P < 0.001). The area under curve (AUC) of LAR in the ROC was 70.34 % (95 %CI: 66.53 % - 74.15 %) that provided significantly higher discrimination compared with lactate (AUC = 68.00 %, P = 0.0007) or albumin (AUC = 63.17 %, P = 0.002) alone. LAR was also not inferior to SAPSII with the AUC of 73.44 % (95 %CI: 69.84 % - 77.04 %, P = 0.21). Additionally, Kaplan-Meier survival analysis displayed that ARDS patients with high LAR (> the cut-off value 0.9055) had a significantly higher 28-day overall mortality rate (P < 0.001) and in-hospital mortality rate (P < 0.001). However, patients in high LAR group had shorter length of hospital stay (P < 0.001), which might be caused by higher in-hospital mortality.

CONCLUSIONS

We confirmed that there was a positive correlation between LAR and 28-day mortality. This could provide anesthesiologists and critical care physicians with a more convenient tool than SAPSII without being superior for detecting ARDS patients with poor prognosis timely.

The association of serum albumin with 28 day mortality in critically ill patients undergoing dialysis: a secondary analysis based on the eICU collaborative research database

BACKGROUND

The relationship between serum albumin and prognosis in critically ill patients has been studied, however, there is a paucity of exploration into non-linear relationships, particularly in critically ill patients undergoing dialysis. This study intends to investigate the association between serum albumin (ALB) and 28 day mortality in critically ill patients undergoing dialysis.

METHODS

We conducted a multi-center retrospective cohort study of patients undergoing dialysis by utilising data from the eICU Collaborative Research Database from 208 distinct ICUs across the United States between 2014 and 2015. The study focused on mortality within 28 days of ICU admission. We employed univariate analysis, multi-factor logistic regression, subgroup analysis, curve-fitting, and threshold effect analysis to examine the correlation between ALB levels and 28 day mortality.

RESULTS

Among the 2,315 patients with a median age of 63 years, 205 (8.86%) died within 28 days of ICU admission. When ALB level was < 2.7 g/dL, the mortality decreased with an adjusted odds ratio (OR) of 0.34 (95% CI 0.22-0.51, P < 0.0001) for every 1 increment in the ALB. However, no significant mortality changes were observed when ALB levels were at or above this threshold.

CONCLUSION

Our study identifies a nonlinear dose-response relationship between serum ALB levels and 28 day mortality in critically ill patients undergoing dialysis, with a specific turning point observed. This finding underscores a significant negative correlation between ALB levels and mortality risk, with lower ALB levels being associated with higher mortality risk in this particular population.

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

one hundred and seventy-five critically ill cirrhotic patients were assessed 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 (ROC) 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 hour, 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 hour may guide therapeutic interventions and improve patient outcomes. Further prospective studies are warranted to validate these findings and optimize clinical management strategies.

Elevated serum albumin-to-creatinine ratio as a protective factor on clinical outcomes among critically ill patients with sepsis: a retrospective study

Background

The aim of this study was to examine the prognostic significance of serum albumin-to-creatinine ratio (ACR) in critically ill patients with sepsis.

Methods

This retrospective study analyzed sepsis cases admitted to the Affiliated Hospital of Jiangsu University between January 2015 and November 2023. The patients were divided into four groups based on their ACR upon admission to the intensive care unit (ICU). Laboratory data were collected at the time of ICU admission, and the primary outcome measure was in-hospital all-cause mortality. Kaplan-Meier survival curves were generated to illustrate the differences in 30-/60-day mortality among the various groups. Multivariate Cox regression models and restricted cubic splines (RCS) were utilized to explore the association between ACR and all-cause mortality in sepsis patients. Subgroup analyses were conducted to examine the impact of other covariates on the relationship between ACR and all-cause mortality.

Results

A total of 1,123 eligible patients were included in the study, with a median ACR of 0.169. The in-hospital mortality rate was 33.7%, the ICU mortality rate was 31.9%, and the 30-day mortality rate was 28.1%. Kaplan-Meier survival analysis demonstrated that patients with higher ACR had a significantly lower risk of 30-/60-day mortality (log-rank p < 0.001). Multivariable Cox proportional hazards analyses revealed that ACR was an independent predictor of in-hospital death (HR: 0.454, 95% CI 0.271-0.761, p = 0.003), ICU death (HR: 0.498, 95% CI 0.293-0.847, p = 0.010), and 30-day death (HR: 0.399, 95% CI 0.218-0.730, p = 0.003). For each 1-unit increase in ACR, there was a 1.203-fold decrease in the risk of death during the hospital stay. The RCS curve illustrated a non-linear negative correlation between ACR and in-hospital mortality (p for non-linear =0.018), ICU mortality (p for non-linear =0.005), and 30-day mortality (p for non-linear =0.006). Sensitivity analysis indicated consistent effect sizes and directions in different subgroups, confirming the stability of the results.

Conclusion

Low ACR levels were identified as independent risk factors associated with increased in-hospital, ICU, and 30-day mortality in sepsis patients. ACR can serve as a significant predictor of the clinical outcome of sepsis.

The prognostic utility of Lactate/Albumin*Age score in septic patient with normal lactate level

Background

A previous study has shown that the lactate/albumin*age (LAA) score is useful for predicting mortality in patients with sepsis admitted to the ICU. We aimed to evaluate the clinical significance of the LAA score in patients with sepsis who presented to the emergency department (ED).

Methods

This retrospective observational study used data from the Korean Shock Society Registry collected between January 2017 and December 2021. The prognostic performance of the LAA score for predicting the 28-day mortality was evaluated. Lactate and albumin levels were measured immediately after arrival to the ED.

Results

Of the 5346 patients with sepsis, data from 3240 were analyzed. The area under the receiver operating characteristic curve (AUROC) of the LAA score (0.737, 95 % confidence interval (CI) 0.716-0.757), was higher than that of lactate (0.699, 95 % CI 0.677-0.720, p < 0.001), lactate/albumin (LA) ratio (0.730, 95 % CI 0.709-0.751, p = 0.016), and Sequential Organ Failure Assessment (SOFA) score (0.698, 95 % confidence interval 0.676-0.720, p = 0. 004), and Acute Physiology and Chronic Health Evaluation (APACHE) II scores (0.672; 95 % confidence interval 0.649-0.694, p < 0.001). The optimal cut-off value for the LAA score was 119.9. In the Kaplan-Meier analysis according to the optimal cutoff value, the 28-day mortality rates were higher in the high LAA score group (log-rank test, p < 0.001). The LAA score was independently associated with 28-day mortality in the multivariate Cox proportional hazards model (adjusted hazard ratio 2.07, 95 % CI 1.76-2.43, p < 0.001). In the normal (<2 mmol/L) lactate group, the AUROC value for LAA score was higher than LA ratio (normal group 0.674 vs 0.634, p < 0.004). In patients over 65 years old, LAA score (0.731) showed a higher AUROC value than LA ratio (0.725). (p < 0.001).

Conclusion

The LAA score may be used as an independent predictor of mortality in patients with sepsis in the emergency department. Our results show that it performs better than serum lactate alone, LA ratio, and SOFA and APACHE II scores. While this suggests that the LAA could provide clinicians with a useful tool for timely early intervention and care planning in patients with a poor prognosis, further validation in large multicenter prospective studies are necessary to confirm its reliability and practicality as a readily available and objective biomarker.

Kinetics of the Lactate to Albumin Ratio in New Onset Sepsis: Prognostic Implications

The lactate to albumin ratio (LAR) has been associated with the severity and outcome of critical illness and sepsis. However, there are no studies on the kinetics of the LAR during the early phase of sepsis. Therefore, we aimed to investigate the LAR and its kinetics in critically ill patients with new onset sepsis regarding the severity and outcome of sepsis. We prospectively enrolled 102 patients with sepsis or septic shock within 48 h from diagnosis. LARs were recorded at inclusion in the study and one week later. Patients were followed for 28 days. LAR was significantly lower one week after enrollment compared to baseline in all patients (p < 0.001). LARs were significantly higher in patients with septic shock and in nonsurvivors compared to patients with sepsis and survivors, respectively, both at inclusion (p < 0.001, p < 0.001) and at one week later (p < 0.001, p < 0.001). LARs at baseline were positively associated with the severity of sepsis (APACHE II: r = 0.29, p = 0.003; SOFA: r = 0.33, p < 0.001) and inflammatory biomarkers, such as C-reactive protein (r = 0.29, p < 0.1), procalcitonin (r = 0.47, p < 0.001), interleukin 6 (r = 0.28, p = 0.005) interleukin 10 (r = 0.3, p = 0.002) and suPAR (r = 0.28, p = 0.004). In addition, a higher LAR, but not its kinetics, was an independent predictor of 28-day mortality (at inclusion: HR 2.27, 95% C.I. 1.01-5.09, p = 0.04; one week later: HR: 4.29, 95% C.I. 1.71-10.78, p = 0.002). In conclusion, the LAR may be a valuable prognostic indicator in critically ill patients with sepsis at admission and one week later.

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.

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.