Abstract: Objective To construct a nomogram based on systemic inflammation markers for assessing the risk of adverse outcomes in patients with heart failure (HF). Methods We retrospectively collected the clinical data from 430 patients with HF hospitalized in our hospital from June, 2017 to June, 2019. The patients were randomized into derivation group (n=286) and validation group (n=144) at a 7∶3 ratio using R software. The risk factors for adverse prognosis of HF were screened using COX regression analysis to establish the nomogram. The predictive accuracy of the nomogram was assessed using calibration curves. Decision curve analysis (DCA) and Kaplan-Meier curves were used to evaluate the clinical utility of the nomogram. Results The results of COX multivariate regression analysis showed that age (P=0.030), body mass index (BMI, P=0.002), New York Heart Association classification (NYHA, P<0.001), hypertension (P=0.004), lymphocyte count (P<0.001), platelet-to-lymphocyte ratio (PLR, P=0.007), neutrophil-to-lymphocyte ratio (NLR, P<0.001) and system inflammation response index (SIRI, P<0.001) were prognostic factors for HF patients. The nomogram was constructed using these prognostic factors. The C-indexes of the derivation and validation cohorts were 0.719 (95% CI: 0.680-0.758) and 0.732 (95% CI: 0.693-0.771), respectively. The calibration curves showed a good concordance of the nomogram for predicting adverse outcomes in patients with HF. Conclusion The nomogram constructed based on the systemic inflammation markers and the conventional risk factors can predict adverse outcomes (mortality and readmission) in patients with HF.

Key words: heart failure; prognosis; systemic inflammation markers; nomogram