Classification and Regression Tree Analysis in Adult Hemophagocytic Syndrome: Identifying Acute Heart Failure...

Area of Science:

• Cardiology
• Hematology
• Critical Care Medicine

Background:

• Hemophagocytic syndrome (HPS) is a rare, life-threatening condition.
• Heart failure (HF) is a common and serious complication of HPS.

Purpose of the Study:

• To identify predictors of acute heart failure (HF) in patients diagnosed with Hemophagocytic Syndrome (HPS).
• To utilize Classification and Regression Tree (CART) analysis for developing predictive models.

Main Methods:

• Retrospective analysis of 146 HPS patients without prior HF diagnosis.
• Inclusion of variables: age, cardiothoracic ratio (CTR), etiology, NT-proBNP, CRP, ferritin, triglyceride, and LDH.
• CART analysis to predict HF status, with evaluation of model performance (sensitivity, specificity, accuracy).

Main Results:

• Cardiothoracic ratio (CTR) was the most significant predictor of HF in HPS.
• Elevated NT-proBNP and CRP levels indicated cardiac stress and inflammation, also predicting HF.
• Older age and rheumatological etiology increased susceptibility to HF in HPS patients.

Conclusions:

• Key predictors for acute HF in HPS include CTR, NT-proBNP, CRP, age, and etiology.
• Early identification of these predictors can lead to timely interventions and improved patient outcomes.
• Findings offer valuable clinical insights for managing HF in HPS and guide future research.