Eur J Med Res. 2020 Oct 8;25(1):47. doi: 10.1186/s40001-020-00448-9.
AIMS: Heart failure is a syndrome with increasing prevalence in concordance with the aging population and better survival rates from myocardial infarction. Morbidity and mortality are high in chronic heart failure patients, particularly in those with hospital admission for acute decompensation. Several risk stratification tools and score systems have been established to predict mortality in chronic heart failure patients. However, identification of patients at risk with easy obtainable clinical factors that can predict mortality in acute decompensated heart failure (ADHF) are needed to optimize the care-path.
METHODS AND RESULTS: We retrospectively analyzed electronic medical records of 78 patients with HFrEF and HFmrEF who were hospitalized with ADHF in the Heart Center of the University Hospital Cologne in the year 2011 and discharged from the ward after successful treatment. 37.6 ± 16.4 months after index hospitalization 30 (38.5%) patients had died. This mortality rate correlated well with the calculated predicted survival with the Seattle Heart Failure Model (SHFM) for each individual patient. In our cohort, we identified elevated heart rate at discharge as an independent predictor for mortality (p = 0.016). The mean heart rate at discharge was lower in survived patients compared to patients who died (72.5 ± 11.9 vs. 79.1 ± 11.2 bpm. Heart rate of 77 bpm or higher was associated with an almost doubled mortality risk (p = 0.015). Heart rate elevation of 5 bpm was associated with an increase of mortality of 25% (p = 0.022).
CONCLUSIONS: Patients hospitalized for ADHF seem to have a better prognosis, when heart rate at discharge is < 77 bpm. Heart rate at discharge is an easily obtainable biomarker for risk prediction of mortality in HFrEF and HFmrEF patients treated for acute cardiac decompensation. Taking into account this parameter could be useful for guiding treatment strategies in these high-risk patients. Prospective data for validation of this biomarker and specific intervention are needed.
PMID:33032633 | DOI:10.1186/s40001-020-00448-9