Analysis of the Larissa Heart Failure Risk Score: Predictive Value in 9207 Patients Hospitalized for Heart Failure...

Area of Science:

• Cardiology
• Clinical Medicine
• Health Services Research

Background:

• Early risk stratification is crucial for managing hospitalized heart failure (HHF) patients.
• Existing risk models may lack simplicity or broad applicability for HHF.
• The Larissa Heart Failure Risk Score (LHFRS) offers a potentially straightforward approach.

Purpose of the Study:

• To evaluate the predictive accuracy of the Larissa Heart Failure Risk Score (LHFRS) in a large HHF cohort.
• To assess the LHFRS's ability to predict one-year heart failure readmission and all-cause mortality.

Main Methods:

• Retrospective analysis of 13,309 HHF admissions from 9207 unique patients at Cleveland Clinic.
• Utilized the 3-variable LHFRS: hypertension history, myocardial infarction history, and red blood cell distribution width (RDW) ≥ 15%.
• Assessed primary (HF readmission/all-cause mortality) and secondary (all-cause mortality) outcomes at one year.

Main Results:

• All LHFRS components were statistically significant predictors for both outcomes (Log-rank test p < 0.001).
• Higher LHFRS scores demonstrated a strong association with adverse one-year events.
• Logistic regression models showed a C-index of 0.64 for both primary and secondary outcomes.

Conclusions:

• The LHFRS is a simple, validated tool for risk stratification in patients hospitalized for heart failure.
• Its components effectively predict one-year adverse outcomes, including readmission and mortality.
• The LHFRS can serve as a foundation for clinical decision-making and patient management strategies.