Predictive Value of Complete Blood Count Indicators for Short-Term Mortality in Patients with Combined Coronary Artery Disease and Chronic Kidney Disease
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective: Patients with chronic kidney disease (CKD) and coronary artery disease (CAD) had a poor prognosis. Indicators derived from complete blood count (CBC), like neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), Systematic Inflammation Response Index (SIRI), systemic immune-inflammation index (SII) and Pan-Immune-Inflammation Value (PIV) had prognostic significance. But which one performed best in patients with CKD and CAD was still unclear. Methods: CKD Patients with CAD admitted to ICU were retrospectively included. Patients with sepsis, connective tissue disease, tumor and receiving glucocorticoids were excluded. The primary endpoints encompassed in-hospital mortality and 30-day mortality. Results: The study comprised 694 participants, with 60 patients died during hospitalization, and another 15 died in 30-day follow-up period. Both the admission level and maximal level of CBC-derived indicators were higher in the deceased group. ROC curve analysis demonstrated that maximal NLR had the highest AUCs - 0.795 for in-hospital mortality and 0.754 for 30-day mortality prediction. Furthermore, Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) analyses further confirmed that adding maximal NLR to the base model, which included traditional risk factors, significantly improved both NRI and IDI (p < 0.05 for both). Conclusion: The maximum of NLR was with the best predictive value for in-hospital mortality and 30-day mortality in ICU patients with CAD and CKD. Predicting prognosis based on dynamic changes of NLR is more worthy of attention.
Authors: Shuoyan An, Wuqiang Che, Yanxiang Gao, Xiaoyan Duo, Xingliang Li, Jiahui Li
Institution: China-Japan Friendship Hospital
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,320
OpenAlex ID: W4409455402