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Table 1 Baseline Characteristics for Included Study Cohort

From: Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project

Characteristic Data (n = 34,212)
Age (years)a 54 ± 13
Maleb 18,703 (55)
Raceb
 White 23,801 (70)
 Black 9768 (29)
 Others 643 (1)
Body Mass Index (kg/m2)a 29.3 ± 5.8
Reason for Testb
 Chest Pain 17,547 (51)
 Shortness of Breath 3307 (10)
 Pre-Operation 781 (2)
 Rule out Ischemia 3884 (11)
Stress Variablesa
 Peak METS 9.2 ± 3.1
 Resting Systolic Blood Pressure (mmHg) 132 ± 19
 Resting Diastolic Blood Pressure (mmHg) 82 ± 11
 Resting Heart rate (bpm) 74 ± 13
 Peak Systolic Blood Pressure (mmHg) 183 ± 27
 Peak Diastolic Blood Pressure (mmHg) 86 ± 14
 Peak Heart Rate (bpm) 151 ± 21
Chronotropic incompetenceb 6957 (23.3)
Past Medical Historyb
 Diabetes 5907(17)
 Hypertension 20,534 (60)
 Smoking 15,249 (43)
 Family History of CAD 18,299 (51)
Medications Usedb
 Diuretic Use 5743 (16)
 Hypertensive medications 14,905 (42)
 Diabetes medications 2432 (7)
 Statin 4524 (13.2)
 Aspirin 5752 (16.8)
 Beta Blockers 5434 (15.9)
 Calcium Channel Blockers 4638 (13.5)
  1. mmHg millimeter mercury, bpm beat per minute, CAD coronary artery disease
  2. All the data are presented as:
  3. aMean and standard deviation and
  4. bfrequencies and percentages