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Multicenter Study Comparative Study
A comparison of four risk models for the prediction of cardiovascular complications in patients with a history of atrial fibrillation undergoing non-cardiac surgery.
- F A McAlister, E Youngson, M Jacka, M Graham, D Conen, M Chan, W Szczeklik, P Alonso-Coello, P J Devereaux, and vascular events in non-cardiac surgery patIents cohort evaluation (VISION) investigators.
- Alberta SPOR Support Unit, University of Alberta, Edmonton, AB, Canada.
- Anaesthesia. 2020 Jan 1; 75 (1): 27-36.
AbstractIt is unclear how best to predict peri-operative cardiovascular risk in patients with atrial fibrillation undergoing non-cardiac surgery. This study examined the accuracy of the revised cardiac risk index and three atrial fibrillation thrombo-embolic risk models for predicting 30-day cardiovascular events after non-cardiac surgery in patients with a pre-operative history of atrial fibrillation. We conducted a prospective cohort study in 28 centres from 2007 to 2013 of 40,004 patients ≥ 45 years of age undergoing inpatient non-cardiac surgery who were followed until 30 days after surgery for cardiovascular events (defined as myocardial injury, heart failure, stroke, resuscitated cardiac arrest or cardiovascular death). The 2088 patients with a pre-operative history of atrial fibrillation were at higher risk of peri-operative cardiovascular events compared with the 34,830 patients without a history of atrial fibrillation (29% vs. 13%, respectively, adjusted odds ratio 1.30 (95%CI 1.17-1.45). Compared with the revised cardiac risk index (c-index 0.60), all atrial fibrillation thrombo-embolic risk scores were significantly better at predicting peri-operative cardiovascular events: CHADS2 (c-index 0.62); CHA2 DS2 -VASc (c-index 0.63); and R2 CHADS2 (c-index 0.65), respectively. Although the three thrombo-embolic risk prediction models were significantly better than the revised cardiac risk index for prediction of peri-operative cardiovascular events, none of the four models exhibited strong discrimination metrics. There remains a need to develop a better peri-operative risk prediction model.© 2019 Association of Anaesthetists.
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