• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.237-245
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• 2010

Nerve conduction studies (NCS) are the most objective measure of nerve function and essential for the diagnosis of sub-clinical neuropathy in diabetes mellitus and diabetic polyneuropathy (DPN). This study evaluates the characteristic of electrophysiological abnormalities in DPN. Electrodiagnostic data from 120 patients with diabetic polyneuropathies and 77 control subjects were reviewed. Motor nerve conduction velocities (MNCV), distal motor latencies (DML), compound muscle action potential (CMAP) amplitudes, No potential frequency and conduction block were analyzed. Data were normalized based on normative reference values, and the proportion of nerves with abnormal values in the lower and upper limbs were evaluated. DPN was systemic demyelinating peripheral polyneuropathy and more severe abnormal nerve conduction was found in lower limbs than in upper limbs. The abnormal degree was more severe in peroneal nerve. It was no statistically significant difference of conduction block in control and DPN group. Our findings suggest that DPN had more common and severe peroneal nerve involvement in the motor nerve conduction studies (MNCS). These findings have important implications for the electrophysiological evaluation of DPN.

• The Monthly Diabetes
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• s.216
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• pp.10-13
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• 2007

요즈음은 인터넷이나 대중매체를 통해 일반인들도 다양한 질병에 대한 많은 정보를 얻을 수 있다. 이에 속하는 것으로 당뇨병은 대표적 만성질환이며 누구나 한번쯤은 들어 본 적이 있는 질환일 것이다. 현대와 같이 고도로 의학이 발달한 상황에서도 만성질환은 완치되는 것이 아니고 평생 관리를 해야하는 질병이기 때문에 많은 환자들이 살아가는 동안 서서히 지치게 되고 관리를 소홀히 하게 됨으로써 당뇨병성 신경병증, 망막증, 신증, 대혈관병증(뇌졸중, 심혈관질환, 말초혈관질환) 등과 같은 합병증의 발생으로 일상생활에 지장을 받게 된다. 따라서 당뇨병환자는 일생 주기적으로 검사와 함께 자신에게 맞는 약을 복용하고 경우에 따라서는 인슐린 주사까지 맞음으로써 지속적인 혈당관리를 하여 합병증의 발생을 최소화 하는 것이 필요하다. 이상에 언급한 다양한 합병증 중 가장 중요한 사망원인은 심혈관질환으로 40세 이후에 발생한 당뇨병환자에서 전체 사망 원인의 50% 이상을 차지한다. 또한 대부분의 당뇨병성 만성합병증이 적극적인 혈당관리로 효과적인 예방이 가능한 반면 심혈관질환과 같은 대혈관합병증은 혈당조절이 잘 되고 있는 환자에서도 당뇨병 발생 기간과 무관하게 발생하고 또 여러 혈관에 걸쳐 다발적이고 광범위하게 발생하므로 원인이 되는 다른 위험요소들에 대한 관리가 함께 이루어져야 한다.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.3
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• pp.155-162
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• 2006

Purpose: Diabetes mellitus (DM) is a critical disease with higher rates of cardiovascular morbidity and mortality due to myocardial ischemia and infarction. There is glowing interest in how to determine high-risk patients who are candidates for screening testing. This study was performed to evaluate the incidence of coronary artery disease (CAD) in diabetic patients detected by Tc-99m MIBI myocardial perfusion SPECT (MPS) and to assess risk factors of CAD and cardiac hard events. Subjects and Methods: 203 diabetic patients (64 male, mean age $64.1{\pm}9.0$ years) who underwent MPS were included between Jan 2000 and July 2004. Cardiac death and nonfatal myocardial infarction (MI) were considered as hard events, and coronary angioplasty and bypass surgery >60 days after testing were considered as soft events. The mean follow-up period was $36{\pm}18$ months. Patients underwent exercise (n=6) or adenosine stress (n=197) myocardial perfusion SPECT. Results: Perfusion defects on MPS were detected in 28.6% (58/203) of the patients. There was no cardiac death but 11 hard events were observed. The annual cardiac hard event rate was 1.1%. In univariate analysis of clinical factors, typical anginal pain, peripheral vascular disease, peripheral polyneuropathy, and resting ECG abnormality were significantly associated with the ocurrence of hard events. Anginal pain, peripheral vascular disease, and resting ECG abnormality remained independent predictors of nonfatal MIs with multivariate analysis. Abnormal SPECT results were significantly associated with high prevalence of hard events but not independent predictors on uni- and multivariate analyses. Conclusion: Patients who were male, had longer diabetes duration (especially over 20 years), peripheral vascular disease, peripheral polyneuropathy, or resting ECG abnormality had higher incidence of CAD. Among clinical factors in diabetic patients, typical angina, peripheral vascular disease, peripheral polyneuropathy, and resting ECG abnormality were strong predictors of hard events.

• 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.