FreshRSS

🔒
❌ Acerca de FreshRSS
Hay nuevos artículos disponibles. Pincha para refrescar la página.
AnteayerTus fuentes RSS

Construction of an instrument to enable the assessment of the risk of falls in older outpatients: A quantitative methodological study

Abstract

Objectives

To develop an instrument to facilitate the risk assessment of falls in older outpatients.

Design

A quantitative methodological study using the cross-sectional data.

Methods

This study enrolled 1988 older participants who underwent comprehensive geriatric assessment (CGA) in an outpatient clinic from May 2020 to November 2022. The history of any falls (≥1 falls in a year) and recurrent falls (≥2 falls in a year) were investigated. Potential risk factors of falls were selected by stepwise logistic regression, and a screening tool was constructed based on nomogram. The tool performance was compared with two reference tools (Fried Frailty Phenotype; CGA with 10 items, CGA-10) by using receiver operating curves, sensitivity (Sen), specificity (Spe), and area under the curve (AUC).

Results

Age, unintentional weight loss, depression measured by the Patient Health Questionnaire-2, muscle strength measured by the five times sit-to-stand test, and stand balance measured by semi- and full-tandem standing were the most important risk factors for falls. A fall risk screening tool was constructed with the six measurements (FRST-6). FRST-6 showed the best AUC (Sen, Spe) of 0.75 (Sen = 0.72, Spe = 0.69) for recurrent falls and 0.65 (Sen = 0.74, Spe = 0.48) for any falls. FRST-6 was comparable to CGA-10 and outperformed FFP in performance.

Conclusions

Age, depression, weight loss, gait, and balance were important risk factors of falls. The FRST-6 tool based on these factors showed acceptable performance in risk stratification.

Impact

Performing a multifactorial assessment in primary care clinics is urgent for falls prevention. The FRST-6 provides a simple and practical way for falls risk screening. With this tool, healthcare professionals can efficiently identify patients at risk of falling and make appropriate recommendations in resource-limited settings.

Patient or Public Contribution

No patient or public contribution was received, due to our study design.

❌