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Table 1 UCHealth Population by MI diagnosis

From: Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data

 

No MI

6-month Incident MI

Number (%)

2.25 million(%)

20,591 (%)

Age (Mean ± SD)

43.32 ± 22.56

70.36 ± 14.02

Female sex (%)

1,228,689 (54.5%)

7880 (37.7%)

Hypertension (%)

376,371 (16.72%)

12,314 (59.8%)

Coronary artery disease (%)

59,199 (2.63%)

6700 (32.53%)

Mitral valve disease (%)

30,251 (1.34%)

1668 (8.1%)

Heart failure (%)

44,999 (2%)

3038 (14.75)

Diabetes mellitus (%)

131,059 (5.82%)

5432 (26.38%)

Obesity (%)

127,575 (5.67%)

2343 (11.37%)

Chronic kidney disease (%)

42,759 (1.9%)

2128 (10.33%)

  1. Legend: Baseline demographics and relative frequency of typical MI risk factors. Diagnoses based on presence of diagnosis code (ICD-10; ICD-9) for each. Hypertension: I10x; 401.x, Coronary artery disease: I25.1; 414.01, Mitral Valve disease: I34.2, I34.0, 394.0, 424.0, Heart failure: I50.9, 428.0, Type II Diabetes Mellitus: E11.9, 250.00, Obesity: E66.9, 278.0, Chronic kidney disease: N18.9, 585.9
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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