Predictive validity of the Stopping Elderly Accidents, Deaths & Injuries (STEADI) program fall risk screening algorithms among community-dwelling Thai elderly

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Abstract
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.
Funding Information
  • Ratchadapiseksompotch Fund, Faculty of Medicine, Chulalongkorn University, fiscal year 2019 (RA62/024)
  • THE 90th ANNIVERSARY OF CHULALONGKORN UNIVERSITY FUND (GCUGR1125622041D)
  • Department of Health Government Development Fund, fiscal year 2015

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