Risk stratification using inflammatory and metabolic biomarkers: A multi-cohort predictive study of mortality in atherosclerotic cardiovascular disease.

BACKGROUND The pathological process of atherosclerotic cardiovascular disease (ASCVD) involves complex interactions between metabolic dysregulation and inflammatory responses. The stress hyperglycemia ratio (SHR) and neutrophil-to-lymphocyte ratio (NLR), as biomarkers reflecting metabolic stress and systemic inflammation respectively, have demonstrated significant value in ASCVD prognosis assessment. This study aims to investigate the predictive role of combined SHR and NLR indicators for all-cause mortality in ASCVD patients and their clinical applicability. METHODS ASCVD patients were identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and National Health and Nutrition Examination Survey (NHANES) databases, stratified by SHR/NLR tertiles. Multivariable Cox regression, restricted cubic splines, time-dependent ROC, and machine learning models assessed mortality associations. RESULTS Among 6159 patients, the highest SHR tertile showed increased mortality (NHANES: HR = 1.20, 95 % CI 1.08-1.34; MIMIC-IV: HR = 2.27, 95 % CI 1.44-3.57). The highest NLR tertile showed elevated risk (NHANES: HR = 1.56, 95 % CI 1.39-1.74; MIMIC-IV: HR = 1.61, 95 % CI 1.03-2.52). The combined high SHR/NLR group exhibited the most pronounced risk (NHANES: HR = 1.54, 95 % CI 1.35-1.77; MIMIC-IV: HR = 2.90, 95 % CI 1.70-4.93), with significantly improved predictive accuracy. CONCLUSION The combined SHR-NLR assessment effectively quantifies combined metabolic-inflammatory injury and provides superior prognostic stratification for ASCVD patients compared to individual biomarker evaluation. These findings highlight the clinical potential of this dual-biomarker approach for enhancing risk prediction, though further prospective validation is warranted to establish its predictive utility across various patient populations.

• Publication year

  2026

• Venue

  Life Science

• Publication date

  2026-01-04

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.1016/j.lfs.2025.124182PMID 41494613
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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