Incremental value of C‐reactive protein to the MEESSI acute heart failure risk score.

Aims: We hypothesized that the current gold standard for risk stratification of patients with acute heart failure (AHF), the Multiple Estimation of risk based on the Emergency department Spanish Score In patients with AHF (MEESSI‐AHF) risk score, can be further improved by adding systemic inflammation as quantified by C‐reactive protein (CRP). Methods and results: In a prospective multicentre diagnostic study (BASEL V), AHF was centrally adjudicated by two independent cardiologists. The MEESSI‐AHF risk score was calculated using an established reduced and recalibrated model containing 12 independent risk factors. Model extension was performed by refitting and adding CRP in the logistic regression model with 30‐day mortality as binary outcome. Discrimination, calibration and clinical usefulness were used to assess the performance of the extended Multiple Estimation of risk based on the Emergency department Spanish Score In patients (MEESSI) model. Validation was performed in an independent, retrospective and single‐centre AHF cohort. Among 1208 AHF patients with complete data allowing calculation of the recalibrated MEESSI and the extended MEESSI models, the prognostic accuracy for 30‐day mortality of the extended MEESSI model (c‐statistic 0.83, 95% confidence interval [CI] 0.79–0.87) was significantly higher compared to the recalibrated model (c‐statistic 0.79, 95% CI 0.75–0.83, p = 0.013). The extended model allowed to stratify a higher percentage of patients into the lowest risk group compared to the recalibrated model (33.1% vs. 20.3%). Demonstrating a calibration plot's slope of 1.00 (95% CI 0.81–1.19) and an intercept of 0.0 (95% CI −0.22 to 0.22), the extended MEESSI model achieved excellent and improved calibration. Results were confirmed in the independent validation cohort (n = 575). Conclusions: Quantifying inflammation using CRP concentration provided incremental value in AHF risk stratification using the established MEESSI model. [ABSTRACT FROM AUTHOR]