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Janak Mehta Award This article is accompanied by an invited commentary by Dr. Krishna S. Iyer
Predicting mortality after congenital heart surgeries: Evaluation of the Aristotle and Risk Adjustement in Congenital Heart surgery-1 risk prediction scoring systems: A retrospective single center analysis of 1150 patients Shreedhar S. Joshi, G. Anthony, D. Manasa, T. Ashwini, A. M. Jagadeesh, Deepak P. Borde, Seetharam Bhat1, C. N. Manjunath2 Departments of Cardiac Anaesthesiology and 1Cardiac Surgery, and 2Cardiology, Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, Karnataka, India
ABSTRACT
Received: 10‑12‑13 Accepted: 22‑08‑14 Access this article online
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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. Key words: Aristotle basic complexity score; Aristotle comprehensive complexity score; mortality; outcome; pediatric cardiac surgery; risk adjustment in congenital heart surgery‑1
PMID: *** DOI: 10.4103/0971-9784.142057
INTRODUCTION
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Children with congenital heart defects who have undergone corrective surgeries have varied outcomes. The need to understand these outcomes and evaluate the results of congenital heart surgeries (CHS) is growing, as they
depend on many factors. It is difficult to make standardized risk estimation as each child, and corresponding procedures are unique. Risk prediction scoring systems are valid clinical research tools that allow meaningful comparison of outcome of therapy for children undergoing surgery for congenital heart diseases.
Address for correspondence: Dr. Shreedhar S. Joshi, Department of Cardiac Anaesthesia, Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bannerghata Road, Bengaluru ‑ 560 069, Karnataka, India. E‑mail: shreedhar.
[email protected]
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Annals of Cardiac Anaesthesia Vol. 17:4 Sep-Dec-2014
[Downloaded free from http://www.annals.in on Saturday, May 26, 2018, IP: 125.177.117.145] Joshi, et al.: Aristotle and RACHS scoring in Indian population
Risk adjustment is necessary because there are marked differences in the malformation complexity among the pediatric cardiac surgery populations from different hospitals or hospital groups. A scoring system is needed to investigate and compare the work and performance of the pediatric surgical team. Currently, Aristotle complexity score[1] and risk adjustment in congenital heart surgery (RACHS‑1)[2] are a few of systems used to predict the complexity adjusted outcome in pediatric cardiac surgery. The Aristotle basic complexity (ABC) score was devised as a quality control method for CHS, and it adjusts only complexity of procedures. The ABC score is based on three factors – potential for mortality, potential for morbidity and anticipated technical difficulty. The Aristotle comprehensive complexity (ACC) further adjusts complexity according to specific patient characteristics. It includes two categories of complexity factors‑procedure dependent and procedure independent factors. The RACHS‑1 was created in order to compare in‑hospital mortality for groups of children undergoing surgeries for congenital heart diseases. The model was evaluated with two large multi‑institutional data sets ‑ the Pediatric Cardiac Care Consortium (PCCC)[3] and hospital discharge data from three states in the USA. Our objective was to validate Aristotle (ABC and ACC) and RACHS‑1 prediction models for in‑hospital mortality after surgery for congenital heart disease in a single surgical unit. MATERIALS AND METHODS The study was conducted at a tertiary level cardiac referral center. The study was reviewed and approved by Ethical Review Board of the institute, which waived the need for patient consent. Patients younger than 18 years, who underwent cardiac surgery for congenital heart defects, from July 2007 to June 2013, under one surgical unit were enrolled. Data from patient records regarding the age, gender, weight, year of surgery, diagnosis, presence of pulmonary hypertension, [4] cardio‑pulmonary bypass (CPB) time and aortic cross‑clamp (AoX) time were obtained. ABC and ACC scores were calculated, and patients were allotted to RACHS‑1 categories retrospectively. Operations involving two or more procedures done concurrently were scored for the procedure with the higher ABC score. Primary outcome was all‑cause in‑hospital mortality. Statistical methods Statistical analyses were performed using SPSS 16.0 (SPSS Inc., Chicago, IL, USA). Continuous data are described as mean and standard deviation. Categorical Annals of Cardiac Anaesthesia Vol. 17:4 Sep-Dec-2014
data was analyzed by Chi‑square test. The analysis was done for overall performance, calibration (i.e. extent to which the model accurately predicts the dependent variable, which indicates the goodness of fit) and discrimination (i.e. ability to separate subjects who experienced the outcome event, from the others).[5] Discriminative power of scoring systems was assessed with area under the curve (AUC) of receiver operating curves (ROC), and z‑statistics was applied for comparing the systems amongst each other. Calibration was measured with Hosmer‑Lemeshow modification of χ2 test. The ABC and ACC score was modeled as a continuous variable, RACHS‑1 as categorical variable and in‑hospital mortality as a binary variable. The systems were assessed for net reclassification improvement (NRI) and integrated discrimination improvement (IDI). [6] NRI is interpreted as the proportion (%) of patients reclassified to a more appropriate risk category; whereas, IDI takes into account the size of these changes (i.e. reclassifications) and considers the actual change in calculated risk for each individual.[7] P
