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坦桑尼亚老年内科住院患者谵妄的危险因素

Risk Factors for Delirium in Older Medical Inpatients in Tanzania.

作者信息

Lewis Emma Grace, Banks Jessica, Paddick Stella-Maria, Duinmaijer Ashanti, Tucker Laura, Kisoli Aloyce, Cletus Jane, Lissu Carolyn, Kilonzo Kajiru, Cosker Glynis, Mukaetova-Ladinska Elizabeta Blagoja, Dotchin Catherine, Gray William, Walker Richard, Urasa Sarah

机构信息

Institute of Tropical Medicine and International Health, Charité-Universitätsmedizin, Berlin, Germany.

出版信息

Dement Geriatr Cogn Disord. 2017;44(3-4):160-170. doi: 10.1159/000479058. Epub 2017 Sep 5.

DOI:10.1159/000479058
PMID:28869952
Abstract

BACKGROUND

The risk factors for prevalent delirium in older hospitalised adults in Sub-Saharan Africa (SSA) remain poorly characterised.

METHODS

A total of 510 consecutive admissions of adults aged ≥60 years to acute medical wards of Kilimanjaro Christian Medical Centre in northern Tanzania were recruited. Patients were assessed within 24 h of admission with a risk factor questionnaire, physiological observations, neurocognitive assessment, and informant interview. Delirium and dementia diagnoses were made according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM V) and DSM IV respectively, by an expert panel.

RESULTS

Being male, current alcohol use, dementia, and physiological markers of illness severity were significant independent risk factors for delirium on multivariable analysis.

CONCLUSIONS

The risk factors for prevalent delirium in older medical inpatients in SSA include pre-existing dementia, and are similar to those identified in high-income countries. Our data could help inform the development of a delirium risk stratification tool for older adults in SSA.

摘要

背景

撒哈拉以南非洲(SSA)地区老年住院成年人中现患谵妄的危险因素仍未得到充分描述。

方法

连续招募了坦桑尼亚北部乞力马扎罗基督教医疗中心急性内科病房510例年龄≥60岁的成年住院患者。患者在入院24小时内接受危险因素问卷调查、生理指标观察、神经认知评估和 informant 访谈。谵妄和痴呆诊断分别由一个专家小组根据《精神疾病诊断与统计手册》第5版(DSM V)和 DSM IV 做出。

结果

在多变量分析中,男性、当前饮酒、痴呆以及疾病严重程度的生理指标是谵妄的显著独立危险因素。

结论

SSA地区老年内科住院患者中现患谵妄的危险因素包括既往存在的痴呆,且与高收入国家所确定的危险因素相似。我们的数据有助于为SSA地区老年人开发谵妄风险分层工具提供信息。

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