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

Xiao Li1, Qingyue Zeng2, Xiaoyu Zhang3

  • 1Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China; Key Laboratory of Internal Medicine of Chinese Medicine, Ministry of Education, Beijing University of Chinese Medicine, Beijing, China.

Life Sciences
|January 6, 2026
PubMed

Insights

Combining stress hyperglycemia ratio (SHR) and neutrophil-to-lymphocyte ratio (NLR) significantly improves all-cause mortality prediction in atherosclerotic cardiovascular disease (ASCVD) patients. This dual-biomarker approach offers superior prognostic stratification compared to individual markers.

Area of Science:

  • Cardiovascular Medicine
  • Biomarker Research
  • Prognostic Studies

Background:

  • Atherosclerotic cardiovascular disease (ASCVD) pathogenesis involves complex metabolic and inflammatory interactions.
  • Stress hyperglycemia ratio (SHR) and neutrophil-to-lymphocyte ratio (NLR) are established biomarkers for metabolic stress and inflammation, respectively.
  • Previous studies indicate the prognostic value of SHR and NLR in ASCVD.

Purpose of the Study:

  • To investigate the combined predictive role of SHR and NLR for all-cause mortality in ASCVD patients.
  • To assess the clinical applicability of this dual-biomarker approach for risk stratification.

Main Methods:

  • Retrospective analysis of ASCVD patients from MIMIC-IV and NHANES databases.
  • Stratification of patients based on SHR and NLR tertiles.
  • Utilization of multivariable Cox regression, restricted cubic splines, time-dependent ROC analysis, and machine learning models to evaluate mortality associations.

Main Results:

  • Elevated SHR and NLR were independently associated with increased all-cause mortality in both NHANES and MIMIC-IV cohorts.
  • The combination of high SHR and NLR demonstrated the most pronounced mortality risk, with hazard ratios significantly higher than individual markers.
  • The combined SHR-NLR assessment significantly improved predictive accuracy for mortality in ASCVD patients.

Conclusions:

  • The combined SHR-NLR assessment effectively quantifies combined metabolic-inflammatory injury in ASCVD.
  • This dual-biomarker approach provides superior prognostic stratification for ASCVD patients compared to individual biomarker evaluation.
  • Further prospective validation is recommended to establish the clinical utility of the combined SHR-NLR approach across diverse populations.
Abstract

Keywords:
Atherosclerotic cardiovascular diseaseCross-cohort observational studyMachine learning algorithmsMortalityNeutrophil-to-lymphocyte ratioStress hyperglycemia ratio

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