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New Models for Risk-Adjusted Monitoring of Postsurgical Complications and Mortality in Adult Congenital Heart Disease in England and Wales. | LitMetric

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Article Abstract

Background: Routine monitoring of surgical outcomes can improve service quality. Risk-adjusted monitoring tools for adults with congenital heart disease (CHD) in England and Wales are lacking.

Methods: Using national audit data of all adult CHD surgical procedures in public hospitals from 2015 to 2022, we developed logistic regression models for mortality at 30 days and 90 days and a 30-day complications outcome. Risk factors included patient demographics and categorical derived variables for case complexity and procedure risk. Model performance was assessed by area under the receiver operating characteristic curve and calibration errors for in-sample and cross-validation data sets.

Results: Average 30-day and 90-day mortality were 1.4% (49/3502) and 1.7% (58/3493). Moderate and severe CHD complexity were strong predictors of 30-day mortality (odds ratio [95% CI], 3.5 [0.8-15.8], 8.6 [2.4-30.9]), as was high-risk procedure (OR, 3.6 [2.1-6.0]). Average 30-day complication rate was 7.5% (242/3223). Procedure risk groups (OR, 2.4 [0.9-6.0] to 12.2 [4.0-36.8]) and procedure complexity (OR, 2.5 [1.5-4.3]) were the strongest predictors. In cross-validation, 30-day and 90-day mortality models had median discrimination (interquartile range in parentheses) of 0.844 (0.84-0.85) and 0.866 (0.86-0.87), calibration slopes of 1.05 (0.60-1.13) and 1.11 (0.61-1.21), and calibration-in-the-large of 0.00 (-0.12 to 0.19) and -0.07 (-0.17 to 0.30). The 30-day complications model had cross-validation discrimination of 0.760 (0.76-0.76), calibration slope of 0.93 (0.74-1.18), and calibration-in-the-large of -0.07 (-0.13 to 0.22).

Conclusions: The adult CHD risk models perform well for short-term mortality despite a low number of events. The risk model for 30-day complications showed reduced performance, suggesting that important risk factors are not captured by routinely collected data.

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http://dx.doi.org/10.1016/j.athoracsur.2025.07.030DOI Listing

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