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Backgrounds: Risk stratification systems have been important in reducing morbidity and mortality among congenital heart disease (CHD) patients requiring cardiac surgery. Multiple risk stratification scoring systems have been developed, including Aristotle Basic Complexity Score (ABC), Aristotle Comprehensive Complexity Score (ACC), Society of Thoracic Surgeons and European Association for Cardiothoracic Surgery (STS-EACTS), and Risk Adjustment in Congenital Heart Surgery (RACHS-1). This study aims to access the superior risk stratification scoring system model in predicting mortality and morbidity. Methods: The authors used Embase, PubMed, Scopus, and ProQuest as the primary databases for searching and included studies from hand searching. The area under the receiver operating characteristic curve was compared. Results: A total of 11 articles were included in this review. The AUC of ABC for predicting mortality ranges from 0.59 to 0.71, and morbidity ranges from 0.673 to 0.743. The AUC of ACC score for predicting mortality ranges from 0.704 to 0.87, and a study revealed the AUC of morbidity is 0.730. The AUC of RACHS-1 for predicting mortality ranges from 0.68 to 0.782. The AUC of STS-EACTS for predicting mortality ranges from 0.739 to 0.8 and 0.732 for predicting morbidity. Conclusion: ABC, ACC, RACHS-1, and STS-EACTS have acceptable to excellent discriminatory ability in predicting mortality and morbidity among CHD patients requiring cardiac surgery. [ABSTRACT FROM AUTHOR]

Backgrounds : Risk stratification systems have been important in reducing morbidity and mortality among congenital heart disease (CHD) patients requiring cardiac surgery. Multiple risk stratification scoring systems have been developed, including Aristotle Basic Complexity Score (ABC), Aristotle Comprehensive Complexity Score (ACC), Society of Thoracic Surgeons and European Association for Cardiothoracic Surgery (STS-EACTS), and Risk Adjustment in Congenital Heart Surgery (RACHS-1). This study aims to access the superior risk stratification scoring system model in predicting mortality and morbidity. Methods : The authors used Embase, PubMed, Scopus, and ProQuest as the primary databases for searching and included studies from hand searching. The area under the receiver operating characteristic curve was compared. Results : A total of 11 articles were included in this review. The AUC of ABC for predicting mortality ranges from 0.59 to 0.71, and morbidity ranges from 0.673 to 0.743. The AUC of ACC score for predicting mortality ranges from 0.704 to 0.87, and a study revealed the AUC of morbidity is 0.730. The AUC of RACHS-1 for predicting mortality ranges from 0.68 to 0.782. The AUC of STS-EACTS for predicting mortality ranges from 0.739 to 0.8 and 0.732 for predicting morbidity. Conclusion : ABC, ACC, RACHS-1, and STS-EACTS have acceptable to excellent discriminatory ability in predicting mortality and morbidity among CHD patients requiring cardiac surgery.

Aims and Objectives: To validate Aristotle basic complexity and Aristotle comprehensive complexity (ABC and ACC) and risk adjustment in congenital heart surgery-1 (RACHS-1) prediction models for in hospital mortality after surgery for congenital heart disease in a single surgical unit. Materials and Methods: Patients younger than 18 years, who had undergone surgery for congenital heart diseases from July 2007 to July 2013 were enrolled. Scoring for ABC and ACC scoring and assigning to RACHS-1 categories were done retrospectively from retrieved case files. Discriminative power of scoring systems was assessed with area under curve (AUC) of receiver operating curves (ROC). Calibration (test for goodness of fit of the model) was measured with Hosmer-Lemeshow modification of χ2 test. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were applied to assess reclassification. Results: A total of 1150 cases were assessed with an all-cause in-hospital mortality rate of 7.91%. When modeled for multivariate regression analysis, the ABC (χ2 = 8.24, P = 0.08), ACC (χ2 = 4.17 , P = 0.57) and RACHS-1 (χ2 = 2.13 , P = 0.14) scores showed good overall performance. The AUC was 0.677 with 95% confidence interval (CI) of 0.61-0.73 for ABC score, 0.704 (95% CI: 0.64-0.76) for ACC score and for RACHS-1 it was 0.607 (95%CI: 0.55-0.66). ACC had an improved predictability in comparison to RACHS-1 and ABC on analysis with NRI and IDI. Conclusions: ACC predicted mortality better than ABC and RCAHS-1 models. A national database will help in developing predictive models unique to our populations, till then, ACC scoring model can be used to analyze individual performances and compare with other institutes.

We present a case report of a 55-year-old lady who presented with progressive dysphagia and was diagnosed with a Kommerell′s aneurysm and a right-sided aortic arch. This case report outlines our management strategy and the challenges encountered during the perioperative period in a patient with this rare anomaly.

Aims and Objectives: To validate Aristotle basic complexity and Aristotle comprehensive complexity (ABC and ACC) and risk adjustment in congenital heart surgery-1 (RACHS-1) prediction models for in hospital mortality after surgery for congenital heart disease in a single surgical unit. Materials and Methods: Patients younger than 18 years, who had undergone surgery for congenital heart diseases from July 2007 to July 2013 were enrolled. Scoring for ABC and ACC scoring and assigning to RACHS-1 categories were done retrospectively from retrieved case files. Discriminative power of scoring systems was assessed with area under curve (AUC) of receiver operating curves (ROC). Calibration (test for goodness of fit of the model) was measured with Hosmer-Lemeshow modification of χ² test. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were applied to assess reclassification. Results: A total of 1150 cases were assessed with an all-cause in-hospital mortality rate of 7.91%. When modeled for multivariate regression analysis, the ABC (χ² = 8.24, P = 0.08), ACC (χ² = 4.17, P = 0.57) and RACHS-1 (χ² = 2.13, P = 0.14) scores showed good overall performance. The AUC was 0.677 with 95% confidence interval (CI) of 0.61-0.73 for ABC score, 0.704 (95% CI: 0.64-0.76) for ACC score and for RACHS-1 it was 0.607 (95%CI: 0.55-0.66). ACC had an improved predictability in comparison to RACHS-1 and ABC on analysis with NRI and IDI. Conclusions: ACC predicted mortality better than ABC and RCAHS-1 models. A national database will help in developing predictive models unique to our populations, till then, ACC scoring model can be used to analyze individual performances and compare with other institutes. [ABSTRACT FROM AUTHOR]

Eustachian valve (EV), a remnant of the right valve of sinus venosus in the right atrium can be puzzling. Often it is confused with Chiari network or atrial adhesions and is reported with unusual complications. We report a case of large EV impeding cannulation of inferior vena cava (IVC) during aortic valve replacement. Transesophageal echocardiography diagnosed the presence of large EV and warned of the difficulty with IVC cannulation and helped preparedness for an alternative plan during surgery.