AI Article Synopsis

  • Patients with NYHA class I and II heart failure face significant morbidity and mortality, prompting an investigation of a new tissue Doppler index, E/(e' × s'), for predicting long-term cardiac events.
  • A study involving 212 hospitalized heart failure patients monitored cardiac events over three months, revealing that nearly half experienced events such as cardiac death or rehospitalization.
  • The E/(e' × s') > 1.6 at discharge was identified as a strong independent predictor of adverse outcomes, particularly when patients showed further deterioration after three months.

Article Abstract

It has been shown that patients with NYHA class I and II have a high morbidity and mortality burden. We investigated the value of a new tissue Doppler index, E/(e' × s'), to predict cardiac events in the long-term follow-up of patients at an early stage of heart failure (HF). Sequential echocardiography was conducted on a consecutive cohort of 212 hospitalized HF patients, pre-discharged and with three-month follow-up. The primary end point consisted of cardiac death or readmission due to HF worsening. During follow-up, cardiac events occurred in 99 patients (46.7%). The first cardiac event was represented by cardiac death in 8 patients (3.8%) and readmission for HF in 91 patients (42.9%). A Kaplan-Meier analysis did not show a significantly different event-free survival rate between patients with NYHA class I and II. The composite end point was significantly higher in patients with an E/(e' × s') >1.6. The E/(e' × s') at discharge was the best independent predictor of cardiac events. Those exhibiting an E/(e' × s') > 1.6 at discharge, with a subsequent deterioration after three months, displayed the poorest prognosis concerning cardiac events, HF-related rehospitalization, and cardiac mortality (all < 0.05). In early-stage HF patients, an E/(e' × s') > 1.6 emerged as a robust predictor of clinical outcomes, especially when coupled with a deterioration in condition.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10888058PMC
http://dx.doi.org/10.3390/diagnostics14040409DOI Listing

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