AUTHOR=Shao Zhuce , Wang Zilong , Bi Shuxiong , Zhang Jianguo 

TITLE=Establishment and validation of a nomogram for progression to diabetic foot ulcers in elderly diabetic patients

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1107830

DOI=10.3389/fendo.2023.1107830

ISSN=1664-2392

ABSTRACT=Many diabetic patients develop and progress to diabetic foot ulcers, which seriously affect health and quality of life and cause great economic and psychological stress, especially in elderly diabetic patients who often have various underlying diseases, and the consequences of their progression to diabetic foot ulcers are more serious and seriously affect elderly patients in surgery. Therefore, the column line graph prediction model is drawn based on regression analysis to derive the influencing factors of the progression of elderly diabetic patients to diabetic foot, and the total score derived from the combination of various influencing factors can visually calculate the probability of the progression of elderly diabetic patients to diabetic foot.
LASSO regression analysis yielded a more significant significance on risk factors for progression to diabetic foot in elderly diabetic patients, such as age, presence of peripheral neuropathy, history of smoking, duration of disease, serum lactate dehydrogenase, and high-density cholesterol; (2) Based on the influencing factors and existing theories, a column line graph prediction model for progression to diabetic foot in elderly diabetic patients was constructed. The working characteristic curves of subjects in the training group and their area under the curve (area under the curve = 0.870) were also analyzed simultaneously with the working characteristic curves of subjects in the external validation population and their area under the curve (area under the curve = 0.910), which finally showed that the model was effective in predicting column line graphs; (iii) the C index in the modeled cohort was 0.870 (95% CI: 0.799- 0.931) and the C-index in the validation cohort was 0.910 (95% CI: 0.837-0.951), indicating that the model had good predictive accuracy; the calibration curve fit was good; (iv) the results of the decision curve analysis showed that the model would have good results in clinical use; (v) it indicated that the established predictive model for predicting progression to diabetic foot in elderly diabetic patients had good test efficacy and helped clinically screen the possibility of progression to diabetic foot in elderly diabetic patients and give personalized interventions to different patients in time.