Variables Impacting Gfr Estimation Method For Drug Dosing In Ckd: Artificial Neural Network Prediction Model

Objective: This study aimed to measure concordance between different renal function estimates in terms of drug doses and determine the potential significant clinical differences. Methods: Around one hundred and eighty patients (≥ 18 y) with chronic kidney disease (CKD) were eligible for inclusion in this study. A paired-proportion cohort design was utilized using an artificial intelligence model. CKD patients refined into those who have drugs adjusted for renal function. For superiority of Cockcroft-Gault (CG) vs. modified diet in renal disease (MDRD) guided with references for concordance or discordance of the two equations and determined the dosing tiers of each drug. Validated artificial neural networks (ANN) was one outcome of interest. Variable impacts and performed reassignments were compared to evaluate the factors that affect the accuracy in estimating the kidney function for a better drug dosing. Results: The best ANN model classified most cases to CG as the best dosing method (79 vs. 72). The probability was 85% and the top performance was slightly above 93%. Creatinine levels and CKD staging were the most important factors in determining the best dosing method of CG versus MDRD. Ideal and actual body weights were second (24%). Whereas drug class or the specific drug was an important third factor (14%). Conclusion: Among many variables that affect the optimal dosing method, the top three are probably CKD staging, weight, and the drug. The contrasting CKD stages from the different methods can be used to recognize patterns, identify and predict the best dosing tactics in CKD patients.

Studies on serum triglyceride level in patients with myocardial infarction.

Myocardial Infarction (MI) is the most common form of heart disease and the single most important cause of premature death in the developed and developing world. Unfortunately the incidence of the condition is increasing rapidly in many developing countries like Bangladesh. Effort should therefore be taken to minimize the risk factors of MI. Large scale randomized clinical trials have shown that lowering high triglyceride concentration mainly by drugs reduces the risk of cardiac events like MI. So the present work has been designed to see the serum triglyceride levels in normal healthy subjects, to compare serum triglyceride levels in patients with MI and those of healthy subjects and to evaluate the association of serum triglyceride in Bangladeshi MI patients. The present study was carried out in the Department of Biochemistry, BSMMU in collaboration with Department of Cardiology, BSMMU and NICVD, Dhaka during the period of July 2001 to December 2002. A total of 50 subjects were selected, Group A (30 subjects of control ) and Group B (20 subjects of test ). The mean level of serum triglyceride in control subjects were 117.07 +/- 32.41 mg/d1 and in test subjects were 176.87 +/- 37.15 mg/d1. So the present study showed that serum triglyceride level is significantly higher in patients with MI. From the present study, it is difficult to draw any definite conclusion but suggested that high serum triglyceride concentration is a cause of the incidence of MI.