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Table 2. Logistic regression variable parameters

From: Development, validation, and proof-of-concept implementation of a two-year risk prediction model for undiagnosed atrial fibrillation using common electronic health data (UNAFIED)

Parametera,b Description Estimatec Odds ratio (95% confidence interval)
Intercept   0.4063  
Age (years) 40 ≤ Age < 56 − 0.9741 0.38 (0.36, 0.4)
  67 ≤ Age < 77 0.7216 2.06 (1.94, 2.19)
  Age ≥ 77 1.5844 4.88 (4.54, 5.23)
Heart disease (derived) Present 0.5053 1.66 (1.55, 1.77)
Albumin (g/dL) Albumin < 3.5 0.7438 2.1 (1.93, 2.3)
BMI (kg/m2) Missing 0.0884 1.09 (0.99, 1.21)
  BMI < 18.5 0.6086 1.84 (1.26, 2.69)
  24.9 ≤ BMI ≤ 29.9 0.0384 1.04 (0.92, 1.17)
  BMI > 29.9 0.3723 1.45 (1.3, 1.62)
COPD diagnosis Present 0.5259 1.69 (1.57, 1.82)
Gender Female − 0.6226 0.54 (0.51, 0.56)
Heart failure diagnosis Present 1.0609 2.89 (2.53, 3.31)
Insurance Commercial − 0.4111 0.66 (0.62, 0.71)
  Medicaid 0.0378 1.04 (0.95, 1.13)
  Other/unknown − 0.8584 0.42 (0.39, 0.46)
Kidney disease (derived) Present 0.58 1.79 (1.59, 2.01)
Shock diagnosis Present 0.6219 1.86 (1.67, 2.08)
  1. aSee Additional file 1, for codes and logic used for extraction and derivation of parameters
  2. bReference parameters: Age 56–66 years (inclusive), no calculated heart disease, albumin ≥ 3.5 (or missing value), normal BMI (19.5–24.9), no COPD, male, no heart failure, Medicare insurance, no calculated kidney disease, and no shock.
  3. cEach eligible patient had a risk score of exp(raw score)/(1 + exp(raw score)), where the raw score was the sum of the intercept and parameter estimates corresponding to the patients characteristics in each parameter.