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Diabetic polyneuropathy (DPN) can be classified based on fiber diameter into three subtypes: small fiber neuropathy (SFN), large fiber neuropathy (LFN), and mixed fiber neuropathy (MFN). We examined the effect of different diagnostic models on the frequency of polyneuropathy subtypes in type 2 diabetes patients with DPN. This study was based on patients from the Danish Center for Strategic Research in Type 2 Diabetes cohort. We defined DPN as probable or definite DPN according to the Toronto Consensus Criteria. DPN was then subtyped according to four distinct diagnostic models. A total of 277 diabetes patients (214 with DPN and 63 with no DPN) were included in the study. We found a considerable variation in polyneuropathy subtypes by applying different diagnostic models independent of the degree of certainty of DPN diagnosis. For probable and definite DPN, the frequency of subtypes across diagnostic models varied from: 1.4% to 13.1% for SFN, 9.3% to 21.5% for LFN, 51.4% to 83.2% for MFN, and 0.5% to 14.5% for non-classifiable neuropathy (NCN). For the definite DPN group, the frequency of subtypes varied from: 1.6% to 13.5% for SFN, 5.6% to 20.6% for LFN, 61.9% to 89.7% for MFN, and 0.0% to 6.3% for NCN. The frequency of polyneuropathy subtypes depends on the type and number of criteria applied in a diagnostic model. Future consensus criteria should clearly define sensory functions to be tested, methods of testing, and how findings should be interpreted for both clinical practice and research purpose.
Itani et al. (Thu,) studied this question.