Table 4.

Logistic regression model for discharge status in acute care facility in patients without NY State post-operative Complication Composite.

Variables	OR	P value	CI
Robotic CABG	0.55	0.032	0.31 - 0.95
Age
2-d quartile	1.26	0.279	0.83 - 1.94
3-d quartile	2.72	< 0.001	1.85 - 4.01
4-th quartile	6.82	< 0.001	4.61 - 10.08
Male gender	0.4	< 0.001	0.30 - 0.52
BMI more than 30.0	1.67	< 0.001	1.27 - 2.20
Dialysis	4.06	< 0.001	2.23 - 7.41
COPD	1.69	0.004	1.18 - 2.42
Cerebrovascular disease	1.73	0.001	1.24 - 2.43
LVEF	0.98	0.004	0.97 - 0.99
Number of diseased coronary arteries
2	0.89	0.824	0.32 - 2.49
3	1.29	0.595	0.50 - 3.33
4	1.43	0.454	0.56 - 3.68
5	1.71	0.293	0.63 - 4.63

Robotic CABG - Robotic coronary artery bypass grafting versus conventional CABG, OR – odd ratio, CI – 95 % confidence interval, BMI – body mass index, LVEF – left ventricular ejection fraction, COPD – chronic obstructive lung disease. The LVEF (p = 0.342) and BMI (p = 0.061 for linearity) met the assumption of linearity in logit by the fractional polynomials test, but we dichotomized BMI to 30 as criteria to obesity, since p value for very close to be significant for none linearity. The fractional polynomials test did not demonstrate that the assumption of linearity in logit met for age (p = 0.037). Thus, age was entered in model in 4 quartiles (29 – 57, 58 – 64, 65 – 72, 73 – 94). The variables included in the full models were age, gender, race (White or not-White), ethnicity (Hispanic vs. not-Hispanic), BMI, history of cerebro-vascular disease, CHF, diabetes, renal failure requiring dialysis, COPD, previous MI within 30 days, LVEF, urgency status (elective vs. urgent), number of diseased coronary arteries, left main coronary artery disease, and intra-aortic balloon pump (IABP). The variables insignificant by the Wald test (p > 0.05) were sequentially removed from the models. The number of diseased coronary arteries was not significant predictor of discharge status but was a confounder and for that reason left in the model.