Association Between the Red Blood Cell Distribution Width and 30-Day Mortality in Intensive Care Patients Undergoing Cardiac Surgery: A Retrospective Observational Study Based on the Medical Information Mart for Intensive Care-IV Database.

Background: Millions of patients undergo cardiac surgery each year. The red blood cell distribution width (RDW) could help predict the prognosis of patients who undergo percutaneous coronary intervention or coronary artery bypass surgery. We investigated whether the RDW has robust predictive value for the 30-day mortality among patients in an intensive care unit (ICU) after undergoing cardiac surgery. Methods: Using the Medical Information Mart for Intensive Care-IV Database, we retrieved data for 11,634 patients who underwent cardiac surgery in an ICU. We performed multivariate Cox regression analysis to model the association between the RDW and 30-day mortality and plotted Kaplan-Meier curves. Subgroup analyses were stratified using relevant covariates. Receiver operating characteristic (ROC) curves were used to determine the predictive value of the RDWs. Results: The total 30-day mortality rate was 4.2% (485/11,502). The elevated-RDW group had a higher 30-day mortality rate than the normal-RDW group (P&0.001). The robustness of our data analysis was confirmed by performing subgroup analyses. Each unit increase in the RDW was associated with a 17% increase in 30-day mortality when the RDW was used as a continuous variable (adjusted hazard ratio=1.17, 95% confidence interval, 1.10-1.25). Our ROC results showed the predictive value of the RDW. Conclusions: An elevated RDW was associated with a higher 30-day mortality in patients after undergoing cardiac surgery in an ICU setting. The RDW can serve as an efficient and accessible method for predicting the mortality of patients in ICUs following cardiac surgery.

Association between blood urea nitrogen to serum albumin ratio and in-hospital mortality of patients with sepsis in intensive care: A retrospective analysis of the fourth-generation Medical Information Mart for Intensive Care database.

Background: This study aimed to investigate the relationship between the blood urea nitrogen to serum albumin ratio (BAR) and in-hospital mortality in patients with sepsis. Materials and methods: This is a retrospective cohort study. All septic patient data for the study were obtained from the intensive care unit of Beth Israel Deaconess Medical Center. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using multivariable Cox regression analyses. Survival curves were plotted and subgroup analyses were stratified by relevant covariates. Results: Among 23,901 patients, 13,464 with sepsis were included. The overall in-hospital mortality rate was 18.9% (2550/13464). After adjustment for confounding factors, patients in the highest BAR quartile had an increased risk of sepsis death than those in the lowest BAR quartile (HR: 1.42, 95% CI: 1.3-1.55), using BAR as a categorical variable. When BAR was presented as a continuous variable, the prevalence of in-hospital sepsis-related death increased by 8% (adjusted HR: 1.08, 95% CI: 1.07-1.1, P < 0.001) for each 5-unit increase in BAR, irrespective of confounders. Stratified analyses indicated age interactions (P < 0.001), and the correlation between BAR and the probability of dying due to sepsis was stable. Conclusion: BAR was significantly associated with in-hospital mortality in intensive care patients with sepsis. A higher BAR in patients with sepsis is associated with a worse prognosis in the ICU in the USA. However, further research is required to confirm this finding.

Association between glucose-to-lymphocyte ratio and in-hospital mortality in intensive care patients with sepsis: A retrospective observational study based on Medical Information Mart for Intensive Care IV.

Background: This study aimed to evaluate the association between the glucose-to-lymphocyte ratio (GLR) and in-hospital mortality in intensive care unit (ICUs) patients with sepsis. Methods: This is a retrospective cohort study. Patients with sepsis from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database had their baseline data and in-hospital prognosis retrieved. Multivariable Cox regression analyses were applied to calculate adjusted hazard ratios (HR) with 95% confidence intervals (CI). Survival curves were plotted, and subgroup analyses were stratified by relevant covariates. To address the non-linearity relationship, curve fitting and a threshold effect analysis were performed. Results: Of the 23,901 patients, 10,118 patients with sepsis were included. The overall in-hospital mortality rate was 17.1% (1,726/10,118). Adjusted for confounding factors in the multivariable Cox regression analysis models, when GLR was used as a categorical variable, patients in the highest GLR quartile had increased in-hospital mortality compared to patients in the lowest GLR quartile (HR = 1.26, 95% CI: 1.15-1.38). When GLR was used as a continuous variable, each unit increase in GLR was associated with a 2% increase in the prevalence of in-hospital mortality (adjusted HR = 1.02, 95% CI: 1.01-1.03, p = 0.001). Stratified analyses indicated that the correlation between the GLR and in-hospital mortality was stable. The non-linear relationship between GLR and in-hospital mortality was explored in a dose-dependent manner. In-hospital mortality increased by 67% (aHR = 1.67, 95% CI: 1.45-1.92) for every unit GLR increase. When GLR was beyond 1.68, in-hospital mortality did not significantly change (aHR: 1.04, 95% CI: 0.92-1.18). Conclusion: There is a non-linear relationship between GLR and in-hospital mortality in intensive care patients with sepsis. A higher GLR in ICU patients is associated with in-hospital mortality in the United States. However, further research is needed to confirm the findings.