A machine learning approach to predict foot care self-management in older adults with diabetes
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
BMC
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
BackgroundFoot care self-management is underutilized in older adults and diabetic foot ulcers are more common in older adults. It is important to identify predictors of foot care self-management in older adults with diabetes in order to identify and support vulnerable groups. This study aimed to identify predictors of foot care self-management in older adults with diabetes using a machine learning approach.MethodThis cross-sectional study was conducted between November 2023 and February 2024. The data were collected in the endocrinology and metabolic diseases departments of three hospitals in Turkey. Patient identification form and the Foot Care Scale for Older Diabetics (FCS-OD) were used for data collection. Gradient boosting algorithms were used to predict the variable importance. Three machine learning algorithms were used in the study: XGBoost, LightGBM and Random Forest. The algorithms were used to predict patients with a score below or above the mean FCS-OD score.ResultsXGBoost had the best performance (AUC: 0.7469). The common predictors of the models were age (0.0534), gender (0.0038), perceived health status (0.0218), and treatment regimen (0.0027). The XGBoost model, which had the highest AUC value, also identified income level (0.0055) and A1c (0.0020) as predictors of the FCS-OD score.ConclusionThe study identified age, gender, perceived health status, treatment regimen, income level and A1c as predictors of foot care self-management in older adults with diabetes. Attention should be given to improving foot care self-management among this vulnerable group.
Açıklama
Anahtar Kelimeler
Foot care, Older adults, Self-management, Machine learning, Diabetes
Kaynak
Diabetology & Metabolic Syndrome
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
16
Sayı
1
Künye
Ozgur, S., Mum, S., Benzer, H., Toran, M. K., & Toygar, I. (2024). A machine learning approach to predict foot care self-management in older adults with diabetes. Diabetology and Metabolic Syndrome, 16(1), 244-9.
