Diabetes Mellitus, Type 2 ; complications ; diagnosis ; therapy ; Humans ; Liver Diseases ; complications ; diagnosis ; therapy

Glucokinase maturity-onset diabetes of the young (GCK-MODY) represents a distinct subgroup of MODY that does not require hyperglycemia-lowering treatment and has very few diabetes-related complications. Three patients from two families who presented with clinical signs of GCK-MODY were evaluated. Whole-exome sequencing was performed and the effects of the identified mutations were assessed using bioinformatics tools, such as PolyPhen-2, SIFT, and in silico modeling. We identified two mutations: p.Leu30Pro and p.Ser383Leu. In silico analyses predicted that these mutations result in structural conformational changes, protein destabilization, and thermal instability. Our findings may inform future GCK-MODY diagnosis; furthermore, the two mutations detected in two Korean families with GCK-MODY improve our understanding of the genetic basis of the disease.
Computational Biology ; Computer Simulation ; Diabetes Complications ; Diabetes Mellitus, Type 2* ; Diagnosis ; Glucokinase* ; Humans

BACKGROUND: This study was aimed to investigate the diagnosis-related characteristics of the microvascular complications among patients with type 2 diabetes mellitus and to identify the relationship ship between regular check-up and detection of complications of diabetes. METHODS: The study subjects were 63 patients with diabetic microvascular complications. The data were collected with self-administered questionnaire and analyzed with descriptive statistics. RESULTS: The main motive to identify retinopathy was through 'visiting hospital after having symptoms (58.9%)', and not through regular checkup. The most common symptom of retinopathy was dim dye (84.3%) and the mean duration after diabetes mellitus diagnosis was 6.8 years. The main motive to identify renal complications was through 'visiting hospital after having symptoms and checking for other complications (28.0%)'. The most common symptom of renal complications was edema of face and hands (72.0%) and the mean duration following diabetes mellitus diagnosis was 8.4 years. The main motive to identify neuropathy was through 'visiting hospital after having symptoms (34.8%)', and not regular checkup. The most common symptom of neuropathy was tingling sensation of feet (100.0%) and the mean duration following diabetes mellitus diagnosis was 7.4 years. CONCLUSION: Based on the results, we suggest that diabetes complications check-up should be performed simultaneously to make the diagnosis of diabetes mellitus, and that the health care providers could provide them with more opportunities to have such check-ups with standardized complications care guidelines.
Diabetes Complications ; Diabetes Mellitus ; Diabetes Mellitus, Type 2* ; Diagnosis ; Edema ; Foot ; Hand ; Health Personnel ; Humans ; Sensation ; Ships ; Surveys and Questionnaires

INTRODUCTIONTo review the definitions of the metabolic syndrome according to various expert groups and assess their relevance to clinical practice.

MATERIALS AND METHODSMedline searches were conducted to identify studies which addressed: (i) the utility of the metabolic syndrome compared to multivariable predictive functions for the identification of individuals at high risk of type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD), (ii) the importance and definition of obesity in the definition of the metabolic syndrome and (iii) the impact of lifestyle and pharmacological interventions designed to reduce the risk of cardiovascular disease in those with and without the metabolic syndrome.

RESULTSAlthough inferior to multivariable risk scores in predicting T2DM and CVD, the metabolic syndrome represents a simple clinical tool, particularly for the prediction of T2DM. Obesity is not a critical component of the metabolic syndrome for identifying those at increased risk of CVD but may be important for predicting T2DM. If anything, pharmacological therapy, especially lipid lowering is as, if not more, effective in those with the metabolic syndrome than in those without.

CONCLUSIONSAlthough the metabolic syndrome appears to have limited utility for the identification of individuals at increased risk of T2DM or CVD, the diagnosis of the metabolic syndrome presents an opportunity to rationalise health services to deliver coordinated care to those with metabolic syndrome.

Cardiovascular Diseases ; etiology ; Diabetes Mellitus, Type 2 ; etiology ; Humans ; Metabolic Syndrome ; complications ; diagnosis ; Obesity ; complications

Although isolated cranial nerve palsies are common in diabetic patients, multiple, simultaneous cranial neuropathies are rare. We describe the second case of a complete superior orbital fissure syndrome including the optic nerve in a middle-aged Papuan man with newly diagnosed diabetes mellitus. The differential diagnosis included septic cavernous sinus thrombosis and Tolosa Hunt syndrome, and management was initially directed at excluding these serious, treatable conditions.
Cavernous Sinus Thrombosis - diagnosis ; Diabetes Mellitus, Type 2 - complications ; Diabetes Mellitus, Type 2 - diagnosis ; New Guinea ; Oculomotor Nerve Diseases - diagnosis ; Oculomotor Nerve Diseases - etiology ; Tolosa-Hunt Syndrome - diagnosis

<0.05). PP2h, fasting C-peptide and ratio of fasting insulin/C-peptide tend to be higher in hepatogenous DM than those of controls, but which were not statistically significant. CONCLUSIONS: The ratio of PP2h/FPG and fasting plasma insulin differentiated hepatogenous DM from the other type 2 DM. Insulin resistance in liver cirrhosis was higher than the other type 2 DM, and impaired hepatic insulin degradation might be an important mechanism of hyperinsulinemia in liver cirrhosis.
Adult ; Aged ; Blood Glucose/analysis ; Diabetes Mellitus/*diagnosis/*etiology ; Diabetes Mellitus, Type 2/*diagnosis ; Diagnosis, Differential ; Female ; Humans ; Insulin/blood ; Liver Cirrhosis/*complications ; Male ; Middle Aged

OBJECTIVETo investigate the diagnostic value of serum islet autoantibody-glutamic acid decarboxylase antibody (GADA) and islet cell antibody (ICA) in patients with hepatogenic diabetes.

METHODSSerum GADA and ICA were measured with enzyme-linked immunosorbent assay (ELISA) in 217 patients with chronic hepatitis B (CH) or liver cirrhosis (LC). The positivity rate of GADA and ICA in different phases of CH and LC and their relations with diabetes mellitus were analyzed.

RESULTSThe positivity rate of the islet autoantibody in the circulation was 72% in CH and LC patients with diabetes mellitus and 30% in patients with normal glucose level, showing significant difference between the two patient groups (Chi2=36.620, P=0.000). CH patients with diabetes had much higher positivity rate for the antibody [52% than type 2 diabetic patients with liver dysfunction [8%, P<0.05]. The positivity rate was also much higher in CH and LC patients with lowered C peptide level [70%] than in those with normal C peptide level [40%, P<0.005].

CONCLUSIONBoth GADA and ICA have important value in the diagnosis of hepatogenic diabetes and may serve as indexed in laboratory test for distinguishing hepatogenic diabetes from type 2 diabetes.

Adult ; Autoantibodies ; blood ; Diabetes Mellitus, Type 1 ; complications ; diagnosis ; immunology ; Diabetes Mellitus, Type 2 ; complications ; diagnosis ; immunology ; Diagnosis, Differential ; Female ; Glutamate Decarboxylase ; immunology ; Hepatitis B, Chronic ; complications ; Humans ; Islets of Langerhans ; immunology ; Liver Cirrhosis ; complications ; Male ; Middle Aged ; Predictive Value of Tests

No abstract available.
Abscess/complications/*diagnosis ; Adenocarcinoma/complications/*diagnosis ; Adult ; Diabetes Mellitus, Type 2/complications ; Diabetic Ketoacidosis/*etiology ; Fatal Outcome ; Female ; Humans ; Pancreatic Neoplasms/complications/*diagnosis

BACKGROUNDVarious methods can be applied to build predictive models for the clinical data with binary outcome variable. This research aims to explore the process of constructing common predictive models, Logistic regression (LR), decision tree (DT) and multilayer perceptron (MLP), as well as focus on specific details when applying the methods mentioned above: what preconditions should be satisfied, how to set parameters of the model, how to screen variables and build accuracy models quickly and efficiently, and how to assess the generalization ability (that is, prediction performance) reliably by Monte Carlo method in the case of small sample size.

METHODSAll the 274 patients (include 137 type 2 diabetes mellitus with diabetic peripheral neuropathy and 137 type 2 diabetes mellitus without diabetic peripheral neuropathy) from the Metabolic Disease Hospital in Tianjin participated in the study. There were 30 variables such as sex, age, glycosylated hemoglobin, etc. On account of small sample size, the classification and regression tree (CART) with the chi-squared automatic interaction detector tree (CHAID) were combined by means of the 100 times 5-7 fold stratified cross-validation to build DT. The MLP was constructed by Schwarz Bayes Criterion to choose the number of hidden layers and hidden layer units, alone with levenberg-marquardt (L-M) optimization algorithm, weight decay and preliminary training method. Subsequently, LR was applied by the best subset method with the Akaike Information Criterion (AIC) to make the best used of information and avoid overfitting. Eventually, a 10 to 100 times 3-10 fold stratified cross-validation method was used to compare the generalization ability of DT, MLP and LR in view of the areas under the receiver operating characteristic (ROC) curves (AUC).

RESULTSThe AUC of DT, MLP and LR were 0.8863, 0.8536 and 0.8802, respectively. As the larger the AUC of a specific prediction model is, the higher diagnostic ability presents, MLP performed optimally, and then followed by LR and DT in terms of 10-100 times 2-10 fold stratified cross-validation in our study. Neural network model is a preferred option for the data. However, the best subset of multiple LR would be a better choice in view of efficiency and accuracy.

CONCLUSIONWhen dealing with data from small size sample, multiple independent variables and a dichotomous outcome variable, more strategies and statistical techniques (such as AIC criteria, L-M optimization algorithm, the best subset, etc.) should be considered to build a forecast model and some available methods (such as cross-validation, AUC, etc.) could be used for evaluation.

Case-Control Studies ; Decision Trees ; Diabetes Mellitus, Type 2 ; complications ; Diabetic Neuropathies ; diagnosis ; etiology ; Humans ; Logistic Models

OBJECTIVE: To evaluate the application value of Toronto clinical scoring system (TCSS) and its grading of neuropathy for diabetic peripheral neuropathy (DPN), and to explore the relationship between TCSS grading of neuropathy and the grading of diabetic nephropathy and diabetic retinopathy. METHODS: A total of 209 patients of Type 2 diabtes (T2DM) underwent TCSS. Taking electrophysiological examination as a gold standard for diagnosing DPN, We compared the results of TCSS score > or = 6 with electrophysiological examination, and tried to select the optimal cut-off points of TCSS. RESULTS: The corresponding accuracy, sensitivity, and specificity of TCSS score > or = 6 were 76.6%, 77.2%, and 75.6%, respectively.The Youden index and Kappa were 0.53 and 0.52, which implied TCSS score > or = 6 had a moderate consistency with electrophysiological examination. There was a linear positive correlation between TCSS grading of neuropathy and the grading of diabetic nephropathy and diabetic retinopathy (P<0.05). The optimal cut-off point was 5 or 6 among these patients. CONCLUSION TCSS is reliable in diagnosing DPN and its grading of neuropathy has clinical value.
Adult ; Aged ; Diabetes Mellitus, Type 2 ; complications ; Diabetic Neuropathies ; diagnosis ; physiopathology ; Electrophysiology ; Female ; Humans ; Male ; Middle Aged ; Neurologic Examination ; methods