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Master Thesis

A personalized algorithm-based discharge checklist in patients with acute heart failure

Abstract : Background. The use of a discharge checklist in patients with acute heart failure (HF) yields a better quality of care, but a single tool may not be suitable in all HF patients. Aims. Evaluate the usefulness of an algorithm-generated personalized discharge checklist (PCL) based on simple baseline characteristics (age, left ventricular ejection fraction (LVEF) and history of HF) on mortality, readmission for HF and quality of care. Methods. We prospectively included 139 patients hospitalized for HF from May 2018 to October 2018. A PCL was created for each patient and had to be fulfilled before discharge. A control cohort of 182 patients was retrospectively included from precedent year. The primary endpoint was mortality and readmission for HF at 6 months. Results. There was no difference among baseline characteristics between PCL and control cohorts regarding mean age and LVEF. During the 6-month follow-up period, 32 patients (23%) died in the PCL cohort vs. 43 patients (23,2%) in the control cohort (p=0.94). 38 patients (27.3%) were hospitalized for HF in the PCL cohort vs. 64 (35.2%) in the control cohort with curves divergence at 2 months (p=0.12). A higher proportion of patients were screened and treated for iron and vitamin D deficiencies as malnutrition supplemented in the PCL group. The post discharge follow-up was better planned in the PCL group were enrolled in a cardiac rehabilitation, telemedicine or PRADO program. Conclusion. There was no difference regarding mortality and HF rehospitalization rate using a PCL in HF patients. However, an improvement in the management of HF comorbidities and a better referral to follow-up programs were observed.
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Master Thesis
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Submitted on : Thursday, February 6, 2020 - 2:48:18 PM
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Florent Allain. A personalized algorithm-based discharge checklist in patients with acute heart failure. Human health and pathology. 2019. ⟨dumas-02469289⟩



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