TableĀ 3

Factors associated with mortality in Cox regression analysis

HR, 95% CIp Value
Liver disease1.95, 1.29 to 2.940.002
Atrial fibrillation1.60, 1.32 to 1.93<0.0001
Presence of new PPM1.38, 1.00 to 1.890.05
Anaemia1.34, 1.09 to 1.640.005
Presence of prior PPM1.31, 1.08 to 1.600.006
Renal disease1.29, 1.04 to 1.610.02
Male sex1.27, 1.06 to 1.530.01
COPD1.21, 1.01 to 1.440.03
STS score1.04, 1.02 to 1.06<0.0001
  • Other variables in the model that did not reach statistical significance included age, CAD, CABG, diabetes, smoking, LV mass index, LV end-diastolic dimension and LVEF.

  • In a sensitivity analysis, when LBBB was considered as a variable, the results were identical (prior PPM, p=0.01) except that presence of new PPM and LBBB did not reach significance as independent predictors of mortality.

  • CABG, coronary artery bypass grafting; CAD, coronary artery disease; COPD, chronic obstructive pulmonary disease; LBBB, left bundle branch block; PPM, permanent pacemaker; STS, Society of Thoracic Surgeons.