Open AccessPredictive model to identify the risk of losing protective sensibility of the foot in patients with diabetes mellitus
Author(s) -
ChicharroLuna Esther,
PomaresGómez Francisco José,
OrtegaÁvila Ana Belen,
MarchenaRodríguez Ana,
BlanquerGregori José Francisco Javier,
NavarroFlores Emmanuel
Publication year - 2020
Publication title -
international wound journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.867
H-Index - 63
eISSN - 1742-481X
pISSN - 1742-4801
DOI - 10.1111/iwj.13263
Subject(s) - medicine , diabetes mellitus , logistic regression , multivariate analysis , receiver operating characteristic , peripheral neuropathy , positive predicative value , multivariate statistics , risk factor , area under the curve , physical therapy , predictive value , endocrinology , statistics , mathematics
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 R 2 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.