泰国社区居住老年人中 Stopping Elderly Accidents, Deaths & Injuries (STEADI) 计划跌倒风险筛查算法的预测有效性。
Predictive validity of the Stopping Elderly Accidents, Deaths & Injuries (STEADI) program fall risk screening algorithms among community-dwelling Thai elderly.
机构信息
Regional Health Promotion Center 9 Nakhon Ratchasima, Department of Health, 177 Moo.6 Khok Kruat Sub-district, Muang District, Nakhon Ratchasima, 30280, Thailand.
College of Sports Science and Technology, Mahidol University, 999 Phuttamonthon 4 Road, Salaya, Phuttamonthon, Nakhonpathom, 73170, Thailand.
出版信息
BMC Med. 2022 Mar 14;20(1):78. doi: 10.1186/s12916-022-02280-w.
BACKGROUND
Fall risk screening using multiple methods was strongly advised as the initial step for preventing fall. Currently, there is only one such tool which was proposed by the U.S. Centers for Disease Control and Prevention (CDC) for use in its Stopping Elderly Accidents, Death & Injuries (STEADI) program. Its predictive validity outside the US context, however, has never been investigated. The purpose of this study was to determine the predictive validity (area under the receiver operating characteristic curve: AUC), sensitivity, and specificity of the two-step sequential fall-risk screening algorithm of the STEADI program for Thai elderly in the community.
METHODS
A 1-year prospective cohort study was conducted during October 2018-December 2019. Study population consisted of 480 individuals aged 65 years or older living in Nakhon Ratchasima Province, Thailand. The fall risk screening algorithm composed of two serial steps. Step 1 is a screening by the clinician's 3 key questions or the Thai Stay Independent brochure (Thai-SIB) 12 questions. Step 2 is a screening by 3 physical fitness testing tools including Time Up and Go test (TUG), 30-s Chair Stand, and 4-stage balance test. Participants were then followed for their fall incidents. Statistical analyses were conducted by using Cox proportional hazard model. The AUC, sensitivity, specificity, and other relevant predictive validity indices were then estimated.
RESULTS
The average age of the participants was 73.3 ± 6.51 years (range 65-95 years), and 52.5% of them were female. The screening based on the clinician's 3 key questions in Step 1 had a high AUC (0.845), with the sensitivity and specificity of 93.9% (95% CI 88.8, 92.7) and 75.0% (95% CI 70.0, 79.6), respectively. Appropriate risk categorization however differed slightly from the original STEADI program.
CONCLUSIONS
With some modification, the fall risk screening algorithm based on the STEADI program was applicable in Thai context.
背景
美国疾病控制与预防中心（CDC）提出的 STEADI 计划强烈建议使用多种方法进行跌倒风险筛查，作为预防跌倒的初始步骤。目前，仅有一个这样的工具。然而，其在美国以外的环境中的预测有效性从未被研究过。本研究的目的是确定 STEADI 计划两步连续跌倒风险筛查算法在泰国社区老年人中的预测有效性（受试者工作特征曲线下面积：AUC）、灵敏度和特异性。
方法
2018 年 10 月至 2019 年 12 月进行了为期 1 年的前瞻性队列研究。研究人群包括 480 名年龄在 65 岁或以上、居住在泰国那空叻差是玛府的个体。跌倒风险筛查算法由两个连续步骤组成。第 1 步是由临床医生的 3 个关键问题或泰国独立生活手册（泰语-SIB）的 12 个问题进行筛查。第 2 步是通过 3 种体能测试工具进行筛查，包括起身行走测试（TUG）、30 秒坐站测试和 4 阶段平衡测试。然后对参与者进行随访，以了解其跌倒事件。使用 Cox 比例风险模型进行统计分析。然后估计 AUC、灵敏度、特异性和其他相关预测有效性指标。
结果
参与者的平均年龄为 73.3 ± 6.51 岁（范围 65-95 岁），其中 52.5%为女性。第 1 步中基于临床医生的 3 个关键问题的筛查具有较高的 AUC（0.845），其灵敏度和特异性分别为 93.9%（95%CI 88.8，92.7）和 75.0%（95%CI 70.0，79.6）。然而，适当的风险分类与原始 STEADI 计划略有不同。
结论
经过一些修改，基于 STEADI 计划的跌倒风险筛查算法可适用于泰国环境。
Zotero 插件