BACKGROUND: To evaluate the prevalence of diabetic polyneuropathy (DPN) and develop a simple and accurate method for the evaluation of DPN risk in primary care settings. MATERIALS AND METHODS: Cross-sectional descriptive study in a random sample (N = 307) of type 2 diabetes mellitus participants. DPN was diagnosed by both clinical neurological examination and simplified DPN Selection Method in each patient. Correlation between the two methods was obtained. RESULTS: Prevalence of DPN was 23.13% (confidence interval,18.38-27.87) according to clinical neurological examination. Noteworthy, clinical neurological evaluation scores were related to nerve conduction studies (r = 0.882; P < 0.0005). DPN presence was positively related to age, metabolic control (HbA1c levels), known duration of diabetes, diabetic retinopathy, cardiovascular disease, peripheral ischemia and systolic and diastolic blood pressure, but was negatively related to current high-density lipoprotein cholesterol (HDL-C) levels (P < 0.0001). The sensitivity and specificity of our DPN Selection Method (using four clinical parameters: age, retinopathy, HbA1c and HDL-C plasma levels) for diagnosis of DPN was 74.20% and 74.90%, respectively. CONCLUSIONS: The expected prevalence of DPN was observed. The sensitivity of the DPN Selection Method correlated well with formal clinical neurological exam in detection of the condition. We therefore conclude the DPN Selection Method is a useful tool in primary care settings in the evaluation and diagnosis of DPN.
BACKGROUND: To evaluate the prevalence of diabetic polyneuropathy (DPN) and develop a simple and accurate method for the evaluation of DPN risk in primary care settings. MATERIALS AND METHODS: Cross-sectional descriptive study in a random sample (N = 307) of type 2 diabetes mellitusparticipants. DPN was diagnosed by both clinical neurological examination and simplified DPN Selection Method in each patient. Correlation between the two methods was obtained. RESULTS: Prevalence of DPN was 23.13% (confidence interval,18.38-27.87) according to clinical neurological examination. Noteworthy, clinical neurological evaluation scores were related to nerve conduction studies (r = 0.882; P < 0.0005). DPN presence was positively related to age, metabolic control (HbA1c levels), known duration of diabetes, diabetic retinopathy, cardiovascular disease, peripheral ischemia and systolic and diastolic blood pressure, but was negatively related to current high-density lipoprotein cholesterol (HDL-C) levels (P < 0.0001). The sensitivity and specificity of our DPN Selection Method (using four clinical parameters: age, retinopathy, HbA1c and HDL-C plasma levels) for diagnosis of DPN was 74.20% and 74.90%, respectively. CONCLUSIONS: The expected prevalence of DPN was observed. The sensitivity of the DPN Selection Method correlated well with formal clinical neurological exam in detection of the condition. We therefore conclude the DPN Selection Method is a useful tool in primary care settings in the evaluation and diagnosis of DPN.