# The Effectiveness of Current Inflammatory Indices and Clinical Scores in Early Diagnosis and Predicting Long-Term Mortality in Patients with Chronic Heart Failure

## TL;DR

This study shows that the Systemic Inflammatory Response Index (SIRI) and Naples Prognostic Score (NPS) are effective for diagnosing heart failure and predicting long-term mortality.

## Contribution

The study demonstrates that SIRI outperforms other inflammatory indices in diagnosing heart failure and predicting mortality.

## Key findings

- SIRI showed superior diagnostic performance with an AUC of 0.893 for heart failure diagnosis.
- SIRI had the highest accuracy (AUC = 0.677) for predicting 24-month mortality in heart failure patients.
- NPS categories correlated with increasing 24-month mortality rates, from 5.9% to 23.0%.

## Abstract

Background: Systemic inflammation through neutrophil-mediated injury, lymphocyte depletion, and monocyte-driven fibrosis plays a central pathophysiological role in heart failure (HF) progression. We investigated the diagnostic and prognostic utility of contemporary inflammatory indices, particularly the Systemic Inflammatory Response Index (SIRI) and Naples Prognostic Score (NPS). Methods: This retrospective cohort study enrolled 926 participants (500 HF patients, 426 controls). Multiple inflammatory indices (e.g., SIRI, Prognostic Nutritional Index (PNI)) and prognostic scores (e.g., NPS) were calculated from routine hematological and biochemical parameters. Primary outcomes were HF diagnosis discrimination and 3-month and 24-month all-cause mortality. Receiver operating characteristic (ROC) curve analysis, Kaplan–Meier survival curves, and Cox proportional hazards regression were performed. Results: HF patients demonstrated significantly elevated inflammatory burden: SIRI (3.26 vs. 1.06, p < 0.001) and NPS (2.00 vs. 1.43, p < 0.001). For HF diagnosis, SIRI exhibited superior discriminative performance (AUC = 0.893; 95% confidence interval (CI): 0.871–0.912), substantially exceeding all other indices (p < 0.001). For long-term mortality prediction, SIRI maintained the highest accuracy (AUC = 0.677), followed by PNI (AUC = 0.639) and NPS (AUC = 0.613). Kaplan–Meier analysis revealed progressive survival deterioration across NPS categories: 24-month mortality increased from 5.9% (NPS = 0) to 23.0% (NPS = 4), p = 0.002. Multivariable Cox regression confirmed independent prognostic value: SIRI >1.86 (HR = 2.232; 95% CI: 1.280–3.892; p = 0.005) and NPS > 2 (HR = 1.403; 95% CI: 1.180–1.668; p < 0.0001). Conclusions: SIRI and NPS represent powerful, readily accessible prognostic tools capturing distinct but complementary pathophysiological domains in HF. These indices offer substantial clinical utility for risk identification and treatment decisions, particularly in resource-limited settings. Future studies should validate these cut-offs and evaluate biomarker-guided therapeutic strategies.