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Gender Differences in Predictive Factors of Older Adults’ IADL Recovery Following Hip Fracture

机译:髋关节骨折后老年人IADL恢复预测因素的性别差异

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Abstract After hip fracture, older adults experience poor functional outcomes including a lack of IADL recovery. Gender differences exist in risk, incidence, mortality, and complication rates; yet, analyses of predictive factors of IADL especially by gender are often not conducted. The purpose of this study was to investigate gender differences in predictive factors of IADL recovery for older adults at two and six months following hip fracture. This secondary analysis used data (n=326 with IADL of n=399) the Baltimore Hip Studies (BHS-7 cohort). Participants were 65 years of age and community-dwelling. Men were sequentially enrolled; women were frequency-matched. Data analysis required building a shared parameter model was built that incorporated an ordinal logistic regression within a generalized linear mixed-effects model, in conjunction with a time-to-event hazards regression model for the time to death or withdrawal. Predictive factors included: age, race, marital status, and comorbidities; physical function; cognitive status (3MS); and psychosocial function (depression [CES-D], resilience, fear of falling, social participation, and perceived health status. Results indicated that higher age (OR 1.1 95% CI 1.05, 1.15, p .01), greater comorbidity burden (OR 1.31 95% CI 1.08, 1.6, p .01), poorer baseline Lower Physical ADL ( OR 1.8 95% CI 1.54, 2.15, p .01), better cognitive function (OR 0.95 95% CI 0.9, 1; p= 0.047) and poorer LPADL recovery (OR 1.27 95% CI 1.07, 1.5, p .05) significantly impacted IADL recovery. The stratified (by gender) model was not as strong as the full model, but did indicate some gender differences may exist.
机译:摘要髋部骨折后,老年人经历了缺乏的功能结果,包括缺乏IADL恢复。性别差异存在风险,发病率,死亡率和并发症率;然而,通常没有进行IADL预测因素的分析通常不会进行。本研究的目的是调查臀部骨折后两年和六个月的老年成人的IADL恢复预测因素的性别差异。这种二级分析使用数据(n = 326,N = 399的IADL)BALTIMORE HIP研究(BHS-7 COSHORT)。参与者> 65岁和社区住宅。男人被依次注册;女性频率匹配。建立建立共享参数模型所需的数据分析,其在广义线性混合效果模型中结合了一个序数逻辑回归,与死亡或退出的时间结合在一起的时间危害回归模型。预测因素包括:年龄,种族,婚姻状况和合并症;物理功能;认知状态(3ms);和心理社会功能(抑郁症[CES-D],弹性,害怕下降,社会参与和感知健康状况。结果表明,较高的年龄(或1.1 95%CI 1.05,1.15,P <.01),更大的合并症负担(或1.31 95%CI 1.08,1.6,P <.01),基线较差的基线低物理ADL(或1.8 95%CI 1.54,2.15,P <.01),更好的认知功能(或0.95 95%CI 0.9,1; P. = 0.047)和较差的LPADL恢复(或1.27 95%CI 1.07,1.5,1.5,P <.05)显着影响了IADL恢复。分层(按性别)模型并不像完整模型那么强大,但确实表明了一些性别差异可能存在。

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