Predictive model to identify the risk of losing protective sensibility of the foot in patients with diabetes mellitus.

Department of Behavioral Sciences and Health, Nursing Area, Faculty of Medicine, University Miguel Hernández, San Juan de Alicante, Spain. Endocrinology and Nutrition, University Hospital San juan de Alicante, Spain. Department of Nursing and Podiatry, Faculty of Health Sciences, University of Malaga, Malaga, Spain. San Blas Health Center, Departament of Physiology, Faculty of Medicine, University Miguel Hernández, San Juan de Alicante, Spain. Department of Nursing, Faculty of Nursing and Podiatry, Frailty Research Organized Group, Universidad de Valencia, Valencia, Spain.

International wound journal. 2020;(1):220-227

Abstract

Diabetic neuropathy is defined as the presence of symptoms and signs of peripheral nerve dysfunction in diabetics. The aim of this study is to develop a predictive logistic model to identify the risk of losing protective sensitivity in the foot. This descriptive cross-sectional study included 111 patients diagnosed with diabetes mellitus. Participants completed a questionnaire designed to evaluate neuropathic symptoms, and multivariate analysis was subsequently performed to identify an optimal predictive model. The explanatory capacity was evaluated by calculating the R2 coefficient of Nagelkerke. Predictive capacity was evaluated by calculating sensitivity, specificity, and estimation of the area under the receiver operational curve. Protective sensitivity loss was detected in 19.1% of participants. Variables associated by multivariate analysis were: educational level (OR: 31.4, 95% CI: 2.5-383.3, P = .007) and two items from the questionnaire: one related to bleeding and wet socks (OR: 28.3, 95% CI: 3.7-215.9, P = .001) and the other related to electrical sensations (OR: 52.9, 95% CI: 4.3-643.9, P = .002), which were both statistically significant. The predictive model included the variables of age, sex, duration of diabetes, and educational level, and it had a sensitivity of 81.3% and a specificity of 95.5%. This model has a high predictive capacity to identify patients at risk of developing sensory neuropathy.

Methodological quality

Publication Type : Observational Study

Metadata