The prognostic impact of inflammation in patients with decompensated acute heart failure, as assessed using the pan-immune inflammation value (PIV)

Abstract

There is increasing evidence that composite scores based on blood counts, which are reflectors of uncontrolled inflammation in the development and progression of heart failure, can be used as prognostic biomarkers in heart failure patients. The prognostic effects of pan-immune inflammation (PIV) as an independent predictor of in-hospital mortality in patients with acute heart failure (AHF) were evaluated based on this evidence. The data of 640 consecutive patients hospitalized for New York Heart Association (NYHA) class 2-3-4 AHF with reduced ejection fraction were analyzed and 565 patients were included after exclusion. The primary outcome was in hospital all-cause death. Secondary outcomes were defined as the following in-hospital events: Acute kidney injury (AKI), malignant arrhythmias, acute renal failure (ARF) and stroke. The PIV was computed using hemogram parameters such as lymphocytes, neutrophils, monocytes and platelets. Patients were categorized as low or high PIV group according to the median value, which was 382.8. A total of 81 (14.3%) in-hospital deaths, 31 (5.4%) AKI, 34 (6%) malignant arrhythmias, 60 (10.6%) ARF and 11 (2%) strokes were reported. Patients with high PIV had a higher in-hospital mortality rate than patients with low PIV (OR: 1.51, 95% CI, 1.26-1.80, p < 0.001). Incorporating PIV into the full model significantly improved model performance (odds ratio X², p < 0.001) compared to the baseline model constructed with other inflammatory markers. PIV is a potent predictor of prognosis with better performance than other well-known inflammatory markers for patients with AHF.

Keywords:

• acute heart failure
• better performance
• in-hospital mortality
• pan-immune inflammation value (PIV)
• prognostic predictor

Author contribution

All authors contributed to: (1) substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, and, (3) final approval of the version to be published.

Disclosure statement

None to declare.