Life Expectancy Exploration of Heart Failure Patients Presenting with Diabetes
Keywords:
Diabetes mellitus (DM), Heart failure (HF), Prognosis, Survival rate, Proportional hazard modelAbstract
Background: Diabetes is a condition marked by high blood sugar levels, that could lead to complications in organs such as the kidneys, liver, and heart. Previous research has identified diabetes as a primary risk factor for congestive heart failure (CHF), a condition where stiffened heart muscles hinder oxygenated blood circulation. Despite its severity, few studies have examined CHF prognosis in diabetic patients. This study aimed to provide survival estimates and provide their comparisons among predictors, assess mortality risks based on specific variables, and reveal patient outcome patterns. Methods: We analyzed data from a 2015 study at Faisalabad Institute of Cardiology and Allied Hospital (FICAH), Pakistan, focusing on diabetic patients with Class III or IV heart failure and left ventricular systolic dysfunction. Kaplan-Meier estimates provided survival rates, log-rank tests compared survival across variables, Cox regression models estimated hazard ratios, and cluster analysis grouped patients by characteristics and survival rates. Results: The study examined 125 diabetic heart failure patients. Of these, 40 (32%) were censored and the remaining 85 (68%) died. The total follow-up period was 278 days, on the 120th day, 0.752 [95% CI = 0.678 to 0.883] of the patients survived after initial diagnosis. Cox regression showed a decrement of 60% in the risk of death for females compared to males and identified age (HR = 1.065, p= 0.0006), smoking (HR = 2.228, p= 0.0669) and hypertension (HR = 1.663, p= 0.1639) as major mortality risk factors. Cluster analysis revealed the risk factors associated with middle aged and the older patients. Conclusion: The overall prognosis of heart failure patients with diabetes was poor, with high mortality rates, implying effective treatment and management.
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Copyright (c) 2024 Prosper NARH, Michael Asante OFOSU, Elliot Owusu ADDO, Daniel Wiafe PREKO, Grace Aba BART-PLANGE, Roselyn Oforiwaa ACQUAH
This work is licensed under a Creative Commons Attribution 4.0 International License.
All papers published in Applied Medical Informatics are licensed under a Creative Commons Attribution (CC BY 4.0) International License.