Effectiveness of the Biothesiometer and the Comprehensive Diabetic Neuropathy Screening Algorithm (CDNSA) in Detecting Diabetic Neuropathy

Abstract

Diabetic neuropathy is a chronic complication of diabetes mellitus that often remains undetected in its early stages and may progress to foot ulcers and amputation. Early detection at the primary healthcare level is essential to prevent further complications. This study aimed to analyze the effectiveness of the Comprehensive Diabetic Neuropathy Screening Algorithm (CDNSA) compared with a biothesiometer as the reference standard in detecting diabetic neuropathy among patients with diabetes mellitus at Soromandi Primary Healthcare Center, Indonesia. This quantitative diagnostic test accuracy study used a cross-sectional approach. A total of 64 patients with diabetes mellitus who met the inclusion and exclusion criteria were recruited using consecutive sampling. Data were collected in 2025 through direct clinical assessments using both the CDNSA and a biothesiometer. The CDNSA assessed large-fiber function using a 10-g monofilament and a 128-Hz tuning fork and small-fiber function using pinprick and cold sensation tests, whereas the biothesiometer measured the Vibration Perception Threshold (VPT). Diagnostic performance was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), overall accuracy, and Receiver Operating Characteristic (ROC) curve analysis. CDNSA demonstrated a sensitivity of 94%, specificity of 100%, PPV of 100%, NPV of 80%, and overall diagnostic accuracy of 100%. The Area Under the Curve (AUC) was 97.1%, indicating excellent discriminatory ability in distinguishing patients with and without diabetic neuropathy. The CDNSA demonstrated excellent diagnostic performance and may serve as a practical and comprehensive screening method for the early detection of diabetic neuropathy in primary healthcare settings.