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Incremental value of C-reactive protein to the MEESSI acute heart failure risk score
Desiree Wussler1,2, Maria Belkin1,2, Samyut Shrestha1,2
1Cardiovascular Research Institute Basel (CRIB) and Department of Cardiology, University Hospital Basel, University of Basel, Basel, Switzerland.
Insights
Adding C-reactive protein (CRP) to the MEESSI score improves acute heart failure (AHF) risk stratification. This enhanced model better predicts 30-day mortality and identifies more low-risk patients.
Area of Science:
- Cardiology
- Clinical Risk Stratification
- Inflammation Biomarkers
Background:
- Acute heart failure (AHF) poses significant mortality risks.
- Current risk stratification models, like the MEESSI-AHF score, are crucial for patient management.
- The role of systemic inflammation in AHF prognosis requires further investigation.
Purpose of the Study:
- To enhance the MEESSI-AHF risk score by incorporating C-reactive protein (CRP) levels.
- To evaluate the incremental value of CRP in predicting 30-day mortality in AHF patients.
- To assess the impact of CRP addition on risk stratification accuracy and clinical usefulness.
Main Methods:
- Prospective multicentre diagnostic study (BASEL V) with central adjudication of AHF cases.
- Calculation of the established MEESSI-AHF risk score using 12 independent risk factors.
- Logistic regression model extension by adding CRP to assess 30-day mortality, with validation in an independent cohort.
Main Results:
- The extended MEESSI model incorporating CRP showed significantly higher prognostic accuracy (c-statistic 0.83) compared to the original model (c-statistic 0.79).
- The enhanced model stratified a greater percentage of patients into the lowest risk group (33.1% vs. 20.3%).
- Excellent and improved calibration was demonstrated, with results confirmed in an independent validation cohort.
Conclusions:
- Quantifying systemic inflammation via CRP concentration offers incremental value to the MEESSI model for AHF risk stratification.
- The addition of CRP improves the accuracy and clinical utility of risk assessment in AHF patients.
- The findings support the integration of inflammatory markers into existing AHF risk prediction tools.
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.
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