Predictive Model of Diabetic Polyneuropathy Severity Based on Vitamin D Level

Area of Science:

• Endocrinology
• Neurology
• Metabolic Diseases

Background:

• Type 2 Diabetes Mellitus (DM) is a global metabolic disease.
• Diabetic neuropathy (DN), particularly diabetic polyneuropathy (DPN), is a common complication.
• Vitamin D influences DN pathogenesis and severity, assessable by nerve conduction studies (NCS).

Purpose of the Study:

• To develop a predictive model for diabetic polyneuropathy (DPN) severity.
• To assess the correlation between vitamin D levels and DPN severity.

Main Methods:

• Prospective cohort study of 50 Type 2 DM patients.
• Measurement of HbA1c and 25(OH)D levels.
• Development of a predictive scoring system using clinical and laboratory variables, including vitamin D.

Main Results:

• A predictive model score > 4 indicated a 2.7 times higher risk of severe DPN.
• The model demonstrated 82.8% sensitivity and 61.9% specificity for predicting DPN severity.
• Most participants had elevated HbA1c (>6.5%) and low vitamin D levels (<20 ng/ml).

Conclusions:

• A predictive model incorporating vitamin D levels effectively identifies severe DPN risk.
• Higher scores on the predictive model correlate with increased risk of severe DPN.
• The developed model shows high sensitivity and specificity for DPN severity prediction.