TY - JOUR
T1 - A Prediction Model for Falls in Community-Dwelling Older Adults in Podiatry Practices
AU - van Gulick, Danique J. J.
AU - Perry, Sander I. B.
AU - van der Leeden, Marike
AU - van Beek, Jolan G. M.
AU - Lucas, Cees
AU - Stuiver, Martijn M.
N1 - Funding Information: This work was funded (50%) by the Dutch association of podiatrists (NVvP: Nederlandse Vereniging van Podotherapeuten). The funder had no influence on study design, recruitment, data collection, analysis, and writing of the article. Publisher Copyright: © 2022 S. Karger AG, Basel. All rights reserved.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Introduction: Falls are a worldwide health problem among community-dwelling older adults. Emerging evidence suggests that foot problems increase the risk of falling, so the podiatrist may be crucial in detecting foot-related fall risk. However, there is no screening tool available which can be used in podiatry practice. The predictive value of existing tools is limited, and the implementation is poor. The development of risk models for specific clinical populations might increase the prediction accuracy and implementation. Therefore, the aim of this study was to develop and internally validate an easily applicable clinical prediction model (CPM) that can be used in podiatry practice to predict falls in community-dwelling older adults with foot (-related) problems. Methods: This was a prospective study including community-dwelling older adults (≥65 years) visiting podiatry practices. General fall-risk variables, and foot-related and function-related variables were considered as predictors for the occurrence of falls during the 12-month follow-up. Logistic regression analysis was used for model building, and internal validation was done by bootstrap resampling. Results: 407 participants were analyzed; the event rate was 33.4%. The final model included fall history in the previous year, unsteady while standing and walking, plantarflexor strength of the lesser toes, and gait speed. The area under the receiver operating characteristic curve was 0.71 (95% CI: 0.66-0.76) in the sample and estimated as 0.65 after shrinkage. Conclusion: A CPM based on fall history in the previous year, feeling unsteady while standing and walking, decreased plantarflexor strength of the lesser toes, and reduced gait speed has acceptable accuracy to predict falls in our sample of podiatry community-dwelling older adults and is easily applicable in this setting. The accuracy of the model in clinical practice should be demonstrated through external validation of the model in a next study.
AB - Introduction: Falls are a worldwide health problem among community-dwelling older adults. Emerging evidence suggests that foot problems increase the risk of falling, so the podiatrist may be crucial in detecting foot-related fall risk. However, there is no screening tool available which can be used in podiatry practice. The predictive value of existing tools is limited, and the implementation is poor. The development of risk models for specific clinical populations might increase the prediction accuracy and implementation. Therefore, the aim of this study was to develop and internally validate an easily applicable clinical prediction model (CPM) that can be used in podiatry practice to predict falls in community-dwelling older adults with foot (-related) problems. Methods: This was a prospective study including community-dwelling older adults (≥65 years) visiting podiatry practices. General fall-risk variables, and foot-related and function-related variables were considered as predictors for the occurrence of falls during the 12-month follow-up. Logistic regression analysis was used for model building, and internal validation was done by bootstrap resampling. Results: 407 participants were analyzed; the event rate was 33.4%. The final model included fall history in the previous year, unsteady while standing and walking, plantarflexor strength of the lesser toes, and gait speed. The area under the receiver operating characteristic curve was 0.71 (95% CI: 0.66-0.76) in the sample and estimated as 0.65 after shrinkage. Conclusion: A CPM based on fall history in the previous year, feeling unsteady while standing and walking, decreased plantarflexor strength of the lesser toes, and reduced gait speed has acceptable accuracy to predict falls in our sample of podiatry community-dwelling older adults and is easily applicable in this setting. The accuracy of the model in clinical practice should be demonstrated through external validation of the model in a next study.
KW - Assessment tool
KW - Fall risk
KW - Foot
KW - Podiatrist
UR - http://www.scopus.com/inward/record.url?scp=85123512671&partnerID=8YFLogxK
U2 - https://doi.org/10.1159/000520962
DO - https://doi.org/10.1159/000520962
M3 - Article
C2 - 34979512
SN - 0304-324X
VL - 68
SP - 1214
EP - 1223
JO - Gerontology
JF - Gerontology
IS - 11
ER -