• Annals of Clinical Neurophysiology
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• v.21 no.1
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• pp.36-43
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• 2019

Background: Diabetic peripheral polyneuropathy (DPN) is associated with a variety of symptoms. Nerve conduction studies (NCSs) are considered to be the gold standard of nerve damage assessments, but these studies are often dissociated from the subjective symptoms observed in DPN patients. Thus, the aim of the present study was to investigate the correlations between NCS parameters and neuropathic symptoms quantified using the Michigan Neuropathy Screening Instrument (MNSI). Methods: Patients with type 2 diabetes mellitus (T2DM) with or without symptoms of neuropathy were retrospectively enrolled. Demographic data, clinical laboratory data, MNSI score, and NCS results were collected for analysis; DPN was diagnosed based on the MNSI score (${\geq}3.0$) and abnormal NCS results. Pearson's correlation coefficients were used to evaluate the relationships between MNSI score and NCS variables. Results: The final analyses included 198 patients (115 men and 83 women) with a mean age of $62.6{\pm}12.7$ years and a mean duration of diabetes of $12.7{\pm}8.4$ years. The mean MNSI score was 2.8 (range, 0.0-9.0), and 69 patients (34.8%) were diagnosed with DPN. The MNSI score was positively correlated with the median motor nerve latency and negatively correlated with the median motor, ulnar sensory, peroneal, tibial, and sural nerve conduction velocities (NCVs). When the patients were categorized into quartiles according to MNSI score, peroneal nerve conduction velocity was significantly lower in the second MNSI quartile than in the first MNSI quartile (p = 0.001). A multivariate analysis revealed that the peroneal NCV was independently associated with MNSI score after adjusting for age, sex, and glycosylated hemoglobin A1c (HbA1c) levels. Conclusions: The present results indicate that a decrease in peroneal NCV was responsible for early sensory deficits in T2DM patients.

• Journal of Haehwa Medicine
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• v.13 no.1
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• pp.47-59
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• 2004

Objectives & Methods: We investigated 28 books to study etiology and pathology of Son-Bal Jeorim. Result and Conclusion 1. The eiology of Son-Bal Jeorim is same as it of Bee Jeung(痺症). 2. Generally speaking, the cause of Bee Jeung was distributed Wind(風), Coldness(寒), Wetness (濕) of meridian. Bee Jeung can be devided into SilBi(實痺) and HeoBi(虛痺). In SilBi(實痺) there are PungHanSeupBi(風寒濕痺) and YeolBi(熱痺). In HeoBi(虛痺), there are GiHyeolHeoBi(氣血虛痺), EumheoBi(陰虛痺) and YangHeoBi(陽虛痺). 3. Son-Bal Jeorim belong to peripheral neuropathy in western medicine. 4. Syndrome of acute motor paralysis with variable disturbance of sensory and autonomic function, subacute sensorymotor paralysis, syndrome of chronic sensorimotor polyneuropathy, neuropathy with mitochondrial disease, syndrome of mononeuropathy or nerve plexusopathy. 5. Peripheral neuropathy is caused by carpal tunnel syndrome, diabetic neuropathy, uremic neuropathy, hepatic neuropathy, hypothyroid neuropathy, hyperthyroid neuropathy, neuropathy due to malnutrition, neuropathy due to toxic material, neuropathy due to drug, paraneoplastic neuropathy, hereditary neuropathy, etc. 6. Cerebral apoplexy, myelopathy, peripheral circulatory disturbance, anxiety syndrome cause symptoms of peripheral neuropathy

• Journal of the Korean Society of Radiology
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• v.9 no.5
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• pp.315-322
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• 2015

The purposes of this study were to compare the sensitivities of two tests, QST(quantitative sensory test)and PPG(photoplethysmography) in normal adults. We evaluated the sensory thresholds of QST and PPG and diabetes mellitus test in 17 normal adults. The finding of this study can be summarized as follow :The diagnostic sensitivities of QST was similar to PPG. There is a direct correlation between the amount of Blood sugar and parasympathetic nerve in ANS. Concluded that the QST might be complement to NCS for early of diabetic polyneuropathy. A new diagnostic approach, QST was introduced and exploited for diagnosis. This study provides support for PPG performed a ANS analysis.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.309-319
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• 2016

There is a need to develop a data quality management algorithm in order to improve the quality of health care data. In this study, we developed a data quality control algorithms associated diseases related to diabetes in patients with hypertension. To make a data quality algorithm, we extracted hypertension patients from 2011 and 2012 discharge damage survey data. As the result of developing Data quality management algorithm, significant factors in hypertension patients with diabetes are gender, age, Glomerular disorders in diabetes mellitus, Diabetic retinopathy, Diabetic polyneuropathy, Closed [percutaneous] [needle] biopsy of kidney. Depending on the decision tree results, we defined Outlier which was probability values associated with a patient having diabetes corporal with hypertension or more than 80%, or not more than 20%, and found six groups with extreme values for diabetes accompanying hypertension patients. Thus there is a need to check the actual data contained in the Outlier(extreme value) groups to improve the quality of the data.