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Biomedical subjects

J M Fattu

Publications and source records attributed to J M Fattu.

5 recordsLinked to original sources

A quarter century of drug treatment of dyslipoproteinemia, with a focus on the new HMG-CoA reductase inhibitor fluvastatin.

Disorders associated with the overproduction or delayed clearance of beta-very low density lipoprotein and low density lipoprotein (LDL) are strikingly related to premature coronary artery disease. There are five recognized classes of LDL-lowering drugs, each acting through different basic mechanisms. The increased predictability, safety, and efficacy of newer lipid-lowering agents have allowed controlled clinical trials to demonstrate conclusively that reducing LDL leads to a reduction in coronary artery disease. Fluvastatin, a 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor, is almost completely absorbed, actively targeted to the liver, and secreted in the bile. It has no active circulating metabolites. The safety and efficacy of fluvastatin have been demonstrated in more than 2,500 subjects treated in the United States, Canada, and Europe, and more than 1,000 have been treated for more than 1 year. Combination of fluvastatin with cholestyramine results in additional cholesterol lowering. The Lipoprotein and Coronary Atherosclerosis Study, a randomized, double-blind trial of fluvastatin using quantitative coronary angiography to measure atherosclerotic plaque change and positron emission tomography to evaluate myocardial perfusion (myocardial flow reserve), illustrates the further exploration of lipoproteins and atherogenesis made possible by the availability of this new generation of cholesterol-lowering agents.

Anticholesteremic Agents↗

The use of an expert system in the clinical laboratory as an aid in the diagnosis of anemia.

Experience with an expert system developed for the purpose of classification of anemias is presented. Input for this system consists of limited demographic information on each patient and the results of the complete blood count, with the incorporation of the results of further chemical testing (serum iron/total iron binding capacity/ferritin and serum B12/serum folate/red blood cell folate), if indicated. Performance of this system is demonstrated using data from 84 patients seen in the authors' laboratory selected either because of a request for evaluation by the attending physician or because of significant anemias. Using this limited input, the system was able to accurately classify 74 of 84 (88%) of cases according to previously established criteria. The output from the system is overread by a pathologist. Future directions are also discussed.

Anemia↗

Evaluation of a new classification system for anemias using Consult Learning System.

Since the advent of electronic particle counting, anemias have customarily been classified by evaluating cell size (MCV) and hemoglobin content (MCH). Recently a new parameter estimating red cell size heterogeneity (the 'red cell distribution width' or 'RDW') has been introduced. We have evaluated a proposed classification of anemias based upon this new parameter in a large group of hospitalized patients utilizing an expert system based upon statistical pattern recognition and compared our results to other studies. The potential advantages of using such a system over currently existing uni-dimensional classification systems to evaluate clinical problems are discussed.

Anemia↗

Thyroid disorders: automatic diagnosis in CONSULT I.

Automatic diagnosis of thyroid diseases is implemented on CONSULT I, a microcomputer system based on the Patrick model for computer-assisted diagnosis in medicine. The thyroid 'subsystem' consists of 19 classes (diseases) and 16 features (signs, symptoms, laboratory tests). For 76 test cases obtained from patient records (recognition samples), the 'true' class (disease) is decided in the highest 'probability' number in 89% of cases and in the differential diagnosis in 100% of cases. Performance is compared to physicians. Estimation of class-conditional probability densities utilizing equivalence regions in the feature space is discussed.

Diagnosis, Computer-Assisted↗