Functional dependence predicts adverse outcomes among geriatric otolaryngology patients better than more complex risk scales: a multivariate analysis of hospitalization risks on elderly group

功能依赖性比更复杂的风险评估量表更能预测老年耳鼻喉科患者的不良预后:一项针对老年人群住院风险的多变量分析

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Abstract

INTRODUCTION: As the population of adults aged 80 years and older continues to grow, otorhinolaryngology departments face increasing demands to manage complex and vulnerable older patients. Identifying reliable predictors of adverse outcomes in this population is essential for optimizing care. METHODS: In this multicenter retrospective study, data from 426 hospitalized patients aged ≥ 80 years were collected across eight university hospitals. The study investigated three clinical outcomes: prolonged hospitalization, 30-days serious complications, and 90-days functional decline. Explanatory variables included, inter alia, functional status measures and traditional risk assessment tools such as the ASA score, Caprini score, and Charlson Comorbidity Index (CCI). Potential predictors of adverse outcomes were examined using univariate tests, as well as multivariate logistic regression modeling. RESULTS: Physical inactivity (p < 0.012), dependence in daily functioning (p < 0.009), and impaired food intake (p < 0.003) consistently predicted prolonged hospitalization, serious complications, and functional decline. The three variables describing functional status proved to be the most significant predictors of adverse outcomes among the variables included in the study. Most of the traditional assessment tools-including the ASA and Caprini scales-showed limited predictive value compared to the functional status variables, whereas CCI provided additional prognostic information. DISCUSSION: Functional status indicators, particularly mobility, dependence in activities of daily living, and food intake, emerged as strong and consistent predictors of major adverse outcomes in geriatric otorhinolaryngology inpatients. These findings support the integration of functional measures into routine risk stratification to better identify high-risk older adults and guide more individualized clinical management strategies.

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