Developing a prediction rule from automated clinical databases to identify high-risk patients in a large population with diabetes

Diabetes Care

Volumn 24, Issue 9, 2001, Pages 1547-1555

  Selby, Joe V ^a   Karter, Andrew J ^a   Ackerson, Lynn M ^a   Ferrara, Assiamira ^a   Liu, Jennifer ^a  

^a DIVISION OF RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GLYCOSYLATED HEMOGLOBIN;

ADULT; AGED; ARTICLE; COHORT ANALYSIS; DIABETES MELLITUS; DIABETIC ANGIOPATHY; EDUCATIONAL STATUS; FACTUAL DATABASE; FEMALE; HEALTH MAINTENANCE ORGANIZATION; HUMAN; INFECTION; MALE; MEDICAL RECORD; MIDDLE AGED; OBESITY; PREDICTION AND FORECASTING; REGISTER; REPRODUCIBILITY; RETROSPECTIVE STUDY; RISK ASSESSMENT; RISK FACTOR; UNITED STATES;

ADULT; AGED; AGED, 80 AND OVER; CALIFORNIA; COHORT STUDIES; DATABASES, FACTUAL; DIABETES COMPLICATIONS; DIABETES MELLITUS; DIABETIC ANGIOPATHIES; EDUCATIONAL STATUS; FEMALE; HEALTH MAINTENANCE ORGANIZATIONS; HEMOGLOBIN A, GLYCOSYLATED; HUMANS; INFECTION; MALE; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; MIDDLE AGED; OBESITY; PREDICTIVE VALUE OF TESTS; REGISTRIES; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; RISK ASSESSMENT; RISK FACTORS;

EID: 0035461407     PISSN: 01495992     EISSN: None     Source Type: Journal    
DOI: 10.2337/diacare.24.9.1547     Document Type: Article

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