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

## TL;DR

This study developed a model to predict falls in older adults with diabetes and neuropathy, highlighting age, balance issues, and neuropathy severity as key factors.

## Contribution

The study introduces a validated logistic regression model for predicting falls in diabetic peripheral neuropathy patients using common clinical variables.

## Key findings

- Age, Michigan Neuropathy Screening Instrument score, and self-reported balance problems were significant predictors of falls.
- A second model identified age, balance problems, and DPN severity as key predictors with good performance metrics.
- The model emphasizes the importance of DPN-related factors over traditional aging-related impairments in predicting falls.

## Abstract

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.

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.

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.

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 balance problems, as these are more relevant in people with diabetes than the traditional physical impairments associated to aging.