Abstract/Summary

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 on all adult CHD surgical procedures in public hospitals from 2015 to 2022, we developed logistic regression models for mortality at 30 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 using area under the receiver operating characteristic curve and calibration errors for in-sample and cross-validation datasets. RESULTS Average 30-day and 90-day mortality were 1.4% (49/3502) and 1.7% (58/3493). Moderate or severe CHD complexity were strong predictors of 30-day mortality (Odds Ratios (ORs) [95% confidence interval]: 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 (ORs: 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 and 90-day mortality models had median discrimination (inter-quartile range in parenthesis) 0.844 (0.84,0.85) and 0.866 (0.86,0.87), calibration slopes 1.05 (0.60,1.13) and 1.11 (0.61,1.21), and calibration-in-the-large 0.00 (-0.12,0.19) and -0.07 (-0.17,0.30). The 30-day complications model had cross-validation discrimination 0.760 (0.76,0.76), calibration slope 0.93 (0.74,1.18) and calibration-in-the-large -0.07 (-0.13,0.22). CONCLUSIONS The adult CHD risk models perform very 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.