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1.
Article in English | IMSEAR | ID: sea-44397

ABSTRACT

In the present study we developed and assessed the performance of a simple prediction rule and a neural network model to predict beta-cell reserve in young adults with diabetes. Eighty three young adults with diabetes were included in the study. All were less than 40 years old and without apparent secondary causes of diabetes. The subjects were randomly allocated to 2 groups; group 1 (n = 59) for developing a prediction rule and training a neural network, group 2 (n = 24) for validation purpose. The prediction rule was developed by using stepwise logistic regression. Using stepwise logistic regression and modification of the derived equation, the patient would be insulin deficient if 3(waist circumference in cm) + 4(age at diagnosis) < 340 in the absence of previous diabetic ketoacidosis (DKA) or < 400 in the presence of previous DKA. When tested in the validation set, the prediction rule had positive and negative predictive values of 86.7 per cent and 77.8 per cent respectively with 83.3 per cent accuracy while the ANN model had a positive predictive value of 88.2 per cent and a negative predictive value of 100 per cent with 91.7 per cent accuracy. When testing the performance of the prediction rule and the ANN model compared to the assessment of 23 internists in a subgroup of 9 diabetics whose age at onset was less than 30 years and without a history of DKA, the ANN had the highest ability to predict beta-cell reserve (accuracy = 88.9), followed by the prediction rule (accuracy = 77.8%) and assessments by internists (accuracy = 60.9%). We concluded that beta-cell reserve in young adults with diabetes mellitus could be predicted by a simple prediction rule or a neural network model. The prediction rule and the neural network model can be helpful clinically in patients with mixed clinical features of type 1 and type 2 diabetes.


Subject(s)
Adolescent , Adult , Diabetes Mellitus/diagnosis , Humans , Islets of Langerhans , Logistic Models , Neural Networks, Computer , Predictive Value of Tests
2.
Article in English | IMSEAR | ID: sea-44434

ABSTRACT

A prospective randomized, double-blind, controlled study of cefoperazone/sulbactam (cefoperazone 25 mg/kg/day) + co-trimoxazole (trimethoprim 8 mg/kg/day) vs ceftazidime (100 mg/kg/day) + co-trimoxazole (trimethoprim 8 mg/kg/day) in the treatment of severe melioidosis was conducted at Srinagarind Hospital, Khon Kaen University, Khon Kaen, Thailand, from July 1995 to September 1996. A total of 84 patients were enrolled in the study. Forty of them (48%) had culture-proven melioidosis and were randomly assigned to one of the two treatment groups, each group with 20 patients. Two cases (one in each treatment group) were excluded from the final analysis due to incomplete data. There was no significant difference in the mortality rate between the two groups-16 per cent (3/19) in the cefoperazone/sulbactam group vs 21 per cent (4/19) in the ceftazidime group (p > 0.05). Bacteriological responses of successfully treated patients were similar in both groups, and both treatment regimens were well tolerated. Cefoperazone/sulbactam + co-trimoxazole can therefore be used as an alternative treatment for severe melioidosis. However, to further support this conclusion, a study with a larger patient population is needed.


Subject(s)
Adult , Anti-Bacterial Agents/therapeutic use , Anti-Infective Agents/therapeutic use , Cefoperazone/therapeutic use , Ceftazidime/therapeutic use , Chi-Square Distribution , Double-Blind Method , Drug Therapy, Combination/therapeutic use , Female , Humans , Male , Melioidosis/drug therapy , Middle Aged , Prospective Studies , Statistics, Nonparametric , Sulbactam/therapeutic use , Trimethoprim, Sulfamethoxazole Drug Combination/therapeutic use
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