Clinical Scorecard: Creation and assessment of a nomogram for forecasting cardiac autonomic neuropathy in individuals with diabetes

At a Glance

Key Highlights

• Prevalence of DCAN in the study population was 45.0%.
• Seven independent predictors identified: history of diabetic retinopathy or kidney disease, diabetes duration, age, heart rate, fasting plasma glucose, and HbA1c.
• Logistic Regression model showed the highest sensitivity (77.0%) and was selected as the optimal prediction tool.
• A nomogram was developed for individualized risk assessment.
• The model demonstrated good calibration and potential clinical utility.

Guideline-Based Recommendations

Diagnosis

• Use cardiovascular autonomic reflex tests (CARTs) for diagnosing DCAN.

Management

• Implement early risk assessment and personalized clinical management based on the nomogram.

Monitoring & Follow-up

• Regularly assess patients with diabetes for signs of DCAN using the predictive model.

Risks

• Patients with DCAN have a significantly higher 5-year mortality risk compared to those without autonomic dysfunction.

Patient & Prescribing Data

453 patients with type 1 or type 2 diabetes.

The nomogram can facilitate early identification and management of patients at risk for DCAN.

Clinical Best Practices

• Utilize the developed nomogram for screening patients with diabetes for DCAN.
• Incorporate routine assessment of identified predictors in clinical practice.

Related Resources & Content

• Study on DCAN prevalence and outcomes