Akademik Veri Yönetim Sistemi
Arquivos Brasileiros de Cardiologia, cilt.121, sa.6, 2024 (SCI-Expanded)
Background: Although there have been significant improvements in the treatment of heart failure (HF) in recent decades, its prognosis remains poor. Although there are many biomarkers that can help predict the prognosis of patients with HF, there is a need for simpler, cheaper, and more easily available biomarkers. Objective: To evaluate the predictive value of pan-immune-inflammation value (PIV) in patients with acute decompensated HF. Methods: We analyzed 409 patients with HF with reduced ejection fraction who were hospitalized for acute decompensated HF. Patients were divided into 3 groups according to tertiles of PIV: tertile 1 (PIV < 357.25), tertile 2 (PIV ≥ 357.25 and < 834.55), and tertile 3 (PIV ≥ 834.55). P values < 0.05 were considered statistically significant. Kaplan-Meier curves and Cox proportional hazards regression models were used to evaluate the association between PIV and all-cause mortality. The primary outcome was 5-year all-cause mortality, and the secondary outcomes were in-hospital 30 days,, 180-day, and 1-year all-cause mortality. Results: We showed that higher PIV value was associated with both primary and secondary outcomes. The Kaplan-Meier curve showed that patients with higher PIV values had an increased risk of short-and long-term all-cause mortality (log-rank p < 0.001). In the multivariate analysis, PIV was identified as an independent predictor of long-term all-cause mortality in patients with acute decompensated HF, and we observed a 1.96-fold increase in the hazard of an event (odds ratio: 1.96, 95% confidence interval: 1.330 to 2.908, p = 0.001). Conclusions: Our study showed that the novel biomarker PIV can be used as a predictor of prognosis in patients with acute decompensated HF.