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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