Abstract
If an important risk factor is missed, multivariate adjustment for an odds ratio of measured outcome can be biased and even a spurious association between the intervention and outcome of interest may be obtained. [...]we argue that not taking the intra-operative and post-operative risk factors into the model would have tampered with the inferences of multivariate logistic regression analysis for risk factors of post-operative short-term mortality and their adjusted odds ratios in this study. [...]post-operative atrial fibrillation is a common, expensive, and potentially morbid complication following cardiac surgery and has been identified as an independent predictor of numerous adverse outcomes after cardiac surgery, including reoperation for bleeding, cardiac arrest, renal or respiratory failure, cerebral complications, need for permanent pacemaker placement, a 2- to 4-fold increased risk of stroke, and a 2-fold increase in all-cause 30-day and 6-month mortality. [1] We have to admit that our risk factors were mostly concentrating on the baseline characteristics of our patients. Since our study included varies types of surgeries, such as mitral valve replacement (MVR), aortic valve replacement (AVR), double valve replacement (DVR), as well as concomitant coronary artery bypass grafting (CABG), as a result, cardiopulmonary bypass (CPB) time could not be a normal distribution.
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