AI Summary & Key Takeaways
AI InsightPrimary outcomes focused on factors that had an impact onoverall in-hospital mortality in the elderly population.Results: Our study included 11,430 patients; of this group, 39.9% were elderly, which we defined as 65 years of age or older.
📌 3 Key Takeaways
Abstract
Background/aim: Mortality in the elderly population tends to be higher than in all other age groups; the risk factors that predictmortality among those in this age cohort are not fully understood. This large-scale clinical study aimed to identify effective risk factorsthat predict mortality in the elderly population with a particular focus on age and hospitalization status.Material and methods: We retrospectively analyzed outcomes from patients with clinical follow-up between July 2015 and January2020 at 29 Mayıs State Hospital, Ankara, Turkey. Patient records with missing or ambiguous data were excluded. Age, sex, lengthof hospital stay, comorbidities, consultation requests and diagnoses that include infectious diseases were evaluated for their role inpredicting in-hospital mortality using binary logistic regression analysis. Primary outcomes focused on factors that had an impact onoverall in-hospital mortality in the elderly population.Results: Our study included 11,430 patients; of this group, 39.9% were elderly, which we defined as 65 years of age or older. Risk factorsfor in-hospital mortality in this cohort included consultation requests (AOR = 1.95, CI (1.53–2.49), P < 0.001) and length of hospitalstay of ≥4 days (AOR = 2.49, CI (1.90–3.26), P < 0.001).Conclusion: Elderly patients are at significantly higher risk for in-hospital mortality than are younger patients. Among the factors thatmay be used to predict the risk of in-hospital mortality in the elderly patient cohort, the most important factor is the length of hospitalstay.