Abstract
Objectives:: Risk prediction scores are important for early diagnosis and treatment of diseases. Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes, but the early diagnosis is challenging. This study developed a risk prediction model for DPN based on modifiable risk factors. Materials and Methods:: The study included 315 type 2 diabetes patients with and without DPN. Demographic, biochemical, and diagnostic data were collected. Multinomial logistic regression analysis was used to identify independent risk factors for DPN. Results:: Hemoglobin% and total red blood cells were identified as independent risk factors for DPN, used to develop a risk prediction score. Conclusion:: The risk prediction score developed in this study can be used by physicians to quickly assess a patients risk of DPN and select appropriate therapeutic options. Routine monitoring of modifiable risk factors can improve DPN prognosis. Patients stratified by risk scores can better understand their risk and seek appropriate care.
Copyright
Association for Helping Neurosurgical Sick People. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-Non Derivative-Non Commercial License, permitting copying and reproduction so long as the original work is given appropriate credit.
Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
