Selection of risk and diagnosis in diabetic polyneuropathy. Validation of method of new systems

Introduction. In a previous study we developed a specific algorithm, the polyneuropathy selection method (PSM) with 4 parameters (age, HDL-C, HbA 1c, and retinopathy), to select patients at risk of diabetic polyneuropathy (DPN). We also developed a simplified method for DPN diagnosis: outpatient polyneuropathy diagnosis (OPD), with 4 variables (symptoms and 3 objective tests). Objectives. To confirm the validity of conventional tests for DPN diagnosis; to validate the discriminatory power of the PSM and the diagnostic value of OPD by evaluating their relationship to electrodiagnosis studies and objective clinical neurological assessment; and to evaluate the correlation of DPN and pro-inflammatory status. Design. Cross-sectional, crossed association for PSM validation. Paired samples for OPD validation. Setting. Primary care in 3 counties. Participants. Random sample of 75 subjects from the type-2 diabetes census for PSM evaluation. Thirty DPN patients and 30 non-DPN patients (from 2 DM2 sub-groups in our earlier study) for OPD evaluation. Methods. The gold standard for DPN diagnosis will be studied by means of a clinical neurological study (symptoms, physical examination, and sensitivity tests) and electrodiagnosis studies (sensitivity and motor EMG). Risks of neuropathy, macroangiopathy and pro-inflammatory status (PCR, TNF soluble fraction and total TGF-β1) will be studied in every subject. Expected results. Electrodiagnosis studies should confirm the validity of conventional tests for DPN diagnosis. PSM and OPD will be valid methods for selecting patients at risk and diagnosing DPN. There will be a significant relationship between DPN and pro-inflammatory tests.