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Predictive effects of diabetes-related risk factors for falls in community-dwelling people with diabetic peripheral neuropathy based on a logistic regression model

Title: Predictive effects of diabetes-related risk factors for falls in community-dwelling people with diabetic peripheral neuropathy based on a logistic regression model
Authors: Suda, Eneida Yuri; Sartor, Cristina Dallemole; Passaro, Anice de Campos; Watari, Ricky; Docko, Eunice Young; Sacco, Isabel C. N.
Contributors: mashili, Fredirick Lazaro; Conselho Nacional de Desenvolvimento CientÃfico e Tecnológico
Source: PLOS One ; volume 21, issue 1, page e0340262 ; ISSN 1932-6203
Publisher Information: Public Library of Science (PLoS)
Publication Year: 2026
Collection: PLOS Publications (via CrossRef)
Description: Background This study aimed to identify the predictive effects of different aspects of diabetic peripheral neuropathy (DPN) and other already known risk factors for falls through a comprehensive logistic model within community-dwelling older adults with diabetes and DPN. This paper also provides a model that estimates the probability of a fall occurring in a real-world clinical scenario. Methods This cross-sectional retrospective study analyzed data from subjects that had never fallen (non-fallers, n = 534) and that had fallen at least twice in the previous year (fallers, n = 101). The logistic regression analysis was performed on a training sample randomly extracted from the original sample (non-fallers: n = 85; fallers: n = 81). The model was validated by checking the performance parameters using a test sample comprised of 10% of fallers (n = 16) and a proportionate subsample of non-fallers (n = 85) from the original dataset. Results Three predictive models were developed. The best model (0.762 receiver operating characteristic[ROC] curve area, 60.4% accuracy, 68.8% sensitivity, 58.8% specificity) identified age (odds ratio[OR]=1.06[95%CI: 1.02, 1.10], P = 0.002), Michigan Neuropathy Screening Instrument score (OR=1.23[95%CI: 1.08, 1.40], P = 0.001), and self-reported balance problems (OR=2.65[95%CI: 1.29, 5.45], P = 0.008) as predictors of falls. A second model with good performance parameters (0.750 ROC curve area, 62.4% accuracy, 62.5% sensitivity, 62.4% specificity) showed that age (OR=1.04[95%CI: 1.01, 1.07], P = 0.015), balance problems (OR=3.29[95%CI: 1.64, 6.59], P = 0.001), and DPN severity (OR=1.18[95%CI: 1.03, 1.34], P = 0.018) were predictors of falls. Conclusions We showed the potential of a predictive model for recurrent falls based on commonly evaluated variables in community-dwelling individuals with diabetes for use in clinical practice. Even for individuals who are not at a high risk for falls, it is crucial to assess the combination of DPN signs, symptoms, and severity and the perception of ...
Document Type: article in journal/newspaper
Language: English
DOI: 10.1371/journal.pone.0340262
Availability: https://doi.org/10.1371/journal.pone.0340262; https://dx.plos.org/10.1371/journal.pone.0340262
Rights: http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.8ADCD18E
Database: BASE