Cargando…
The correlation between red cell distribution width to albumin ratio and all-cause mortality in critically ill patients with rheumatic diseases: a population-based retrospective study
BACKGROUND: Patients with rheumatic diseases have an increased likelihood of being admitted to the intensive care unit (ICU), highlighting the importance of promptly identifying high-risk individuals to enhance prognosis. This study aimed to assess the correlation of red blood cell distribution widt...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10614050/ https://www.ncbi.nlm.nih.gov/pubmed/37908850 http://dx.doi.org/10.3389/fmed.2023.1199861 |
Sumario: | BACKGROUND: Patients with rheumatic diseases have an increased likelihood of being admitted to the intensive care unit (ICU), highlighting the importance of promptly identifying high-risk individuals to enhance prognosis. This study aimed to assess the correlation of red blood cell distribution width to albumin ratio (RAR) with the 90-days and 360-days survival rates among critically ill rheumatic patients. METHODS: Adult rheumatic patients admitted to the ICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were included. The participants were categorized into two groups, survivors (n = 436) and non-survivors (n = 192), based on their 90-days survival outcome. The population was further classified into tertiles using RAR values, with RAR < 4.63 (n = 208), 4.63–6.07 (n = 211), and > 6.07 (n = 209). Kaplan–Meier curves were utilized to evaluate the cumulative survival rates at 90-days and 360-days. The association between RAR and mortality was assessed using restricted cubic splines (RCS) and multivariate Cox regression analysis. Additional subgroup analyses and sensitivity analyses were conducted to further explore the findings. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive performance of RAR. RESULTS: This study involved 628 critically ill patients with rheumatic diseases, and they had an all-cause mortality of 30.57% at 90-days and 38.69% at 360-days. Kaplan–Meier analysis showed a gradual decrease in both 90-days and 360-days cumulative survival with increasing RAR (χ2 = 24.400, p < 0.001; χ2 = 35.360, p < 0.001). RCS revealed that RAR was linearly related to 90-days and 360-days all-cause mortality risk for critically ill patients with rheumatic diseases (χ2 = 4.360, p = 0.225; χ2 = 1.900, p = 0.594). Cox regression analysis indicated that elevated RAR (> 6.07) was significantly correlated with mortality. The ROC curves demonstrated that an optimal cut-off value of RAR for predicting 90-days mortality was determined to be 5.453, yielding a sensitivity of 61.5% and specificity of 60.3%. CONCLUSION: Elevated RAR (> 6.07) was associated with all-cause mortality at 90-days and 360-days among critically ill patients with rheumatic diseases, serving as an independent risk factor for unfavorable prognosis. |
---|