No abstract available.
Malocclusion* ; Overbite*

No abstract available.
Humans ; Kidney Failure, Chronic*

Introduction: Type I diabetes mellitus patients often complain of hunger and suboptimal blood glucose levels. Proper protein distribution might help to improve glucose control and ultimately, carbohydrate distribution. Case presentation: A nine-year-old boy (herein the patient) newly diagnosed with Type I diabetes mellitus with diabetic ketoacidosis, presented nocturia, polydipsia, loss of weight and lethargy. During admission, the patient was dehydrated and had decompensate metabolic acidosis with glycated hemoglobin (HbA1c) 14.5%, random blood sugar 26.2 mmol/dL, and ketone 3.2 mmol/dL. The patient was started on insulin therapy and referred to a dietitian on the 2nd day of admission. Although patient complied with the dietitian's plan, his glucose level remained suboptimal and he complained of hunger immediately after meals. Insulin dose and activity level remained same at this moment. Whilst keeping the protein intake constant, protein exchanges were redistributed into snacks and main meals. The patient felt satiety and his blood glucose started to optimise. Pairing protein-rich foods with carbohydrates can help to slow the rise in blood glucose because protein causes slower stomach emptying and helps prevent sharp spikes in blood glucose and takes the edge off hunger. Conclusion: This reported case showed proper protein distribution with even carbohydrate distribution can help to improve glucose control and satiety in type I diabetic mellitus. It is recommended that further investigations be conducted to provide more concrete evidence on the role of protein distribution in blood glucose control of type I diabetes mellitus.

Purpose To analyze the sources of errors and discuss the techniques to eliminate pitfalls in detecting deep vein thrombosis (DVT) of the proximal lower extremities with color duplex ultrasonography (CDUS). Methods Sixty-eight cases with initial and repeat venous CDUS of the proximal lower extremities were retrospectively reviewed. The repeat was done within 24 hours after initial CDUS scanning. Comparing repeated images to initial ones, the pitfalls and sources of error in CDUS of the proximal lower extremities were discussed. Results In total 68 repeat studies, there were 62 results as same as initials and 4 cases of false negative DVT and 2 cases of false positive DVT. Conclusion Venous CDUS in detecting DVT is observer dependent. Some pitfalls and errors can be eliminated and corrected with proper scan techniques. CDUS is the most valuable imaging modality for assessing suspected DVT in the proximal lower extremities.

No abstract available

A case of neonatal diabetes mellitus is described. The child presented with low birth weight but was normal in appearance. She was acidotic and ketonuria was observed. The HLA typing was DR1 and 3, and insulin autoantibodies were negative. Genetic analysis with polymorphic DNA markers for chromosome 6 indicated biparental inheritance. She required insulin therapy for the control of hyperglycemia, and insulin dependence continues after 8 months of age.
Autoantibodies ; Child ; Chromosomes, Human, Pair 6 ; Diabetes Mellitus* ; Genetic Markers ; Histocompatibility Testing ; Humans ; Hyperglycemia ; Infant, Low Birth Weight ; Infant, Newborn ; Insulin ; Ketosis ; Wills

OBJECTIVES: This study is to see the transition and pattern of the industrial iureal worker, and to develop the prediction model. METHODS: The data of the study are based on the samples from data-warehouse of Occupational Safety & Health Research Institute and are summed monthly from Jan 1986 to Dec 1999. This study data used data mart and Meta data from DW in KOSHA. The prediction model of the injured worker in Industry is designed by using a winters time series method after data preparing (i. e. sample, explore, modify) from DW. RESULTS: Thls predicted model obtained Winters-method multiplicative in exponential smoothing among applied all models, after the tlme series (total 163 months). It showed that the prediction power was 95.5 %. CONCLUSIONS: In the process of exploring the data, totally the rate of industrial injureal workers reduced, and in the yearly circulation, in February and September the number is the lowest but in June, July, October and November the higher. The number of monthly average injureal workers is 8709 (95 % confidence interval 8277, 9140). From the developed prediction model, since Aug 1999 the industrial injureal worker reduced rapidly in Dec 1999 and first period of 2000. But In second period of 2000 the number of the injured workers is increasing. To conclude, as the total economic situation is becoming better in 2000 than In 1999, its is supposed that the injured workers will increase more than the predictive injured workers because of the increase of production rate and labor force.
Academies and Institutes ; Data Mining* ; Employment ; Humans ; Occupational Health

No abstract available.
Adult* ; Humans

No abstract available.
Diagnosis* ; Facial Asymmetry*

No abstract available.
Adult* ; Humans