ArticleTherapeutics and clinical risk management2024
Frailty Predicts in-Hospital Death in Traumatic Brain Injury Patients: A Retrospective Cohort Study.
Article in Therapeutics and clinical risk management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background and Aim: Traumatic brain injury (TBI) is a severe public health problem in elderly patients, and frailty is associated with higher mortality rates in older patients. This study aims to assess the prognostic value of frailty in patients with TBI. Methods: Clinical data from 348 TBI patients treated at Affiliated Kunshan Hospital of Jiangsu University and Kunshan Hospital of Traditional Chinese Medicine between December 2018 and December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to determine risk factors affecting in-hospital mortality, and receiver operating characteristic (ROC) curves were plotted to assess the discriminatory power of the frailty index. Frailty was assessed using the FRAIL scale, where FRAIL stands for Fatigue, Resistance, Ambulation, Illness, and Loss of weight, with each item scored as 0 or 1. Results: Using the FRIAL questionnaire, 122 patients had low frailty and 226 had high frailty. Multivariate logistic regression analysis showed that high frailty was a risk factor for in-hospital mortality in TBI patients (P<0.001, OR=2.012 [1.788-2.412]). The proportion of infections occurring in the two groups was statistically different (P=0.015), with severely infected TBI patients being more likely to develop complications. The ROC curve showed an area under the curve for the FRAIL score of 0.845 [0.752-0.938]. Conclusion: Frailty is an important risk factor for in-hospital mortality in elderly TBI patients, and more attention should be paid to patients with high levels of frailty. Clinicians should consider the degree of frailty when assessing TBI and making treatment decisions.
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