Prognostic value of red blood cell distribution width in sepsis induced cardiomyopathy patients

The potential association between red blood cell distribution width (RDW) at admission and prognosis in patients with sepsis-induced cardiomyopathy(SIC) remains uncertain. The purpose of this study was to explore the prognostic value of RDW on mortality in patients with SIC. Data for this retrospective study were obtained from the MIMIC IV2.2 database. We used propensity score matching (PSM) and Cox proportional hazards regression analysis to evaluate the main risk factors associated with mortality in SIC patients. This analysis was utilized to develop a predictive nomogram. To assess the predictive accuracy and clinical usefulness of the model, we employed the concordance index (C-index) and decision curve analysis. To define the high- and low-RDW groups among patients with SIC, we determined the optimal cut-off value by maximizing the Youden index. According to the screening criteria, we identified a cohort of 1051 patients diagnosed with SIC. When comparing the high-RDW group to the low-RDW group, it was found that the high-RDW group exhibited longer Los_ICU(4.5 days vs.3.8 days, respectively, P = 0.009) and higher mortality rates at 28 days (33.8% vs. 7.8%, respectively, P < 0.001). A nomogram model was created using matched patients which included various factors such as Age, RDW, LDH, CKMB, creatinine and the administration of β-blocker. The C-index predicting 28-day survival probability was 0.846. Decision curves analysis demonstrated that the inclusion of RDW in the model provided a greater net benefit compared to excluding RDW. The prognosis of patients with SIC can be predicted by the RDW value. The nomogram model provides a useful tool in identifying and managing SIC patients.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-10-18
DOI
https://doi.org/10.1038/s41598-024-75480-4
Citations
6
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
1.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prognostic value of red blood cell distribution width in sepsis induced cardiomyopathy patients

Jian Liao, Dingyu Lu, Maojuan Wang, Lian Zhang
6 citations
Scientific Reports
Inflammatory Biomarkers in Disease Prognosis
1.70
article

Prognostic value of red blood cell distribution width in sepsis induced cardiomyopathy patients

Jian Liao, Dingyu Lu, Maojuan Wang, Lian Zhang
article en
6 citations

Abstract

The potential association between red blood cell distribution width (RDW) at admission and prognosis in patients with sepsis-induced cardiomyopathy(SIC) remains uncertain. The purpose of this study was to explore the prognostic value of RDW on mortality in patients with SIC. Data for this retrospective study were obtained from the MIMIC IV2.2 database. We used propensity score matching (PSM) and Cox proportional hazards regression analysis to evaluate the main risk factors associated with mortality in SIC patients. This analysis was utilized to develop a predictive nomogram. To assess the predictive accuracy and clinical usefulness of the model, we employed the concordance index (C-index) and decision curve analysis. To define the high- and low-RDW groups among patients with SIC, we determined the optimal cut-off value by maximizing the Youden index. According to the screening criteria, we identified a cohort of 1051 patients diagnosed with SIC. When comparing the high-RDW group to the low-RDW group, it was found that the high-RDW group exhibited longer Los_ICU(4.5 days vs.3.8 days, respectively, P = 0.009) and higher mortality rates at 28 days (33.8% vs. 7.8%, respectively, P < 0.001). A nomogram model was created using matched patients which included various factors such as Age, RDW, LDH, CKMB, creatinine and the administration of β-blocker. The C-index predicting 28-day survival probability was 0.846. Decision curves analysis demonstrated that the inclusion of RDW in the model provided a greater net benefit compared to excluding RDW. The prognosis of patients with SIC can be predicted by the RDW value. The nomogram model provides a useful tool in identifying and managing SIC patients.

Scientific ReportsVol. 14(1)
Deyang Stomatological Hospital (CN)
Openalex Percentile: Top 13%
Inflammatory Biomarkers in Disease Prognosis
1.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.