Key result
A preoperative risk model for postoperative cardiac dysfunction achieved an AUC of 0.838 (95% CI 0.812-0.864), performing significantly better than five previously published scores (P<0.0002).
Why the study?
Does a newly developed preoperative risk prediction model improve the prediction of postoperative cardiac dysfunction compared to existing risk scores in patients undergoing open heart surgery?
Cohort (n=4,989)
No
Does a newly developed preoperative risk prediction model improve the prediction of postoperative cardiac dysfunction compared to existing risk scores in patients undergoing open heart surgery?
Effect estimate: AUC 0.838 (95% CI 0.812-0.864)
p-value: p=<0.0002
A novel preoperative risk prediction model using routine clinical variables accurately predicts postoperative cardiac dysfunction and outperforms existing risk scores.
No takes yet. Share an insight, caveat, or question.
May aid preoperative risk stratification in open heart surgery; extends prior scores but requires prospective validation before practice change.
Widyastuti et al. (2012) conducted a cohort in open cardiac surgery (n=4,989). Preoperative risk prediction model vs. Previously published risk scores was evaluated on postoperative cardiac dysfunction (AUC 0.838, 95% CI 0.812-0.864, p=<0.0002). A preoperative risk model for postoperative cardiac dysfunction achieved an AUC of 0.838 (95% CI 0.812-0.864), performing significantly better than five previously published scores (P<0.0002).
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