A Novel Risk Prediction Model for 1-Year Mortality Following Congenital Heart Surgery − Analysis of >10,000 Patients Over 10 Years
Presented During:
Sunday, May 7, 2023: 7:45AM - 8:00AM
Los Angeles Convention Center
Posted Room Name:
403B
Abstract No:
108
Submission Type:
Abstract Submission
Authors:
Aditya Sengupta (1), Kimberlee Gauvreau (2), Katherine Kohlsaat (2), Ji Myung Lee (2), John Mayer (2), Pedro J. del Nido (2), Meena Nathan (2)
Institutions:
(1) The Mount Sinai Hospital/Boston Children's Hospital, Boston, MA, (2) Boston Children's Hospital, Boston, MA
Submitting Author:
Aditya Sengupta
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The Mount Sinai Hospital/Boston Children's Hospital
The Mount Sinai Hospital/Boston Children's Hospital
Co-Author(s):
Kimberlee Gauvreau
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Boston Children's Hospital
Boston Children's Hospital
Katherine Kohlsaat
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Boston Children's Hospital
Boston Children's Hospital
Ji Myung Lee
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Boston Children's Hospital
Boston Children's Hospital
John Mayer
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Boston Children's Hospital
Boston Children's Hospital
*Pedro del Nido
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Boston Children's Hospital
Boston Children's Hospital
*Meena Nathan
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Boston Children's Hospital
Boston Children's Hospital
Presenting Author:
Aditya Sengupta
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The Mount Sinai Hospital/Boston Children's Hospital
The Mount Sinai Hospital/Boston Children's Hospital
Abstract:
Objective: Given the dearth of clinical prediction rules for mortality at one year following discharge from congenital heart surgery (CHS), we sought to develop a novel risk prediction model that accounts for clinical, anatomic, echocardiographic, and socioeconomic factors.
Methods: This was a single-center, retrospective review of consecutive patients who underwent CHS (the index operation) from 01/2011-01/2021 with known survival status at one year following discharge from the index hospitalization. The primary outcome was post-discharge mortality at one year. Variables of interest included age, prematurity, non-cardiac anomalies or syndromes, the Childhood Opportunity Index (COI, a US Census tract-based, nationally-normed composite metric of contemporary child neighborhood opportunity comprising 29 indicators across education, health/environment, and socioeconomic domains), STAT mortality category, major adverse postoperative complications (e.g., prolonged mechanical ventilation, renal failure, etc.), and the Residual Lesion Score (RLS, a quality improvement metric that assesses residual lesion severity at discharge based on echocardiographic criteria and pre-discharge unplanned reinterventions). Logistic regression models were used to develop a weighted risk score for the primary outcome. The final prediction model was internally validated using a bootstrapping resampling approach to estimate the optimism-corrected C-statistic based on 500 samples.
Results: Of 10,412 consecutive patients who were discharged following CHS, 8,827 (84.8%) met entry criteria. The median age was 1.9 (IQR 0.3-8.1) years. There were 195 (2.2%) deaths at one year post-discharge. Uni- and multivariable logistic regression models of the primary outcome are shown in Table 1. A weighted risk score was formulated based on the variables in the final risk prediction model (Table 1), which included all aforementioned factors of interest (this model had a C-statistic of 0.82, 95% CI 0.80-0.85). The median risk score was 7 (IQR 5-9) points. Patients were categorized as low (score 0-5), medium (score 6-10), high (score 11-15), or very high (score 16-20) risk for 1-year mortality. The predicted probability of mortality was 0.3 ± 0.1%, 1.5 ± 0.9%, 8.0 ± 4.3%, and 34.5 ± 8.2% for low, medium, high, and very high risk patients, respectively.
Conclusions: A risk prediction model of 1-year mortality may guide prognostication and follow-up of high-risk patients following discharge from CHS.
Methods: This was a single-center, retrospective review of consecutive patients who underwent CHS (the index operation) from 01/2011-01/2021 with known survival status at one year following discharge from the index hospitalization. The primary outcome was post-discharge mortality at one year. Variables of interest included age, prematurity, non-cardiac anomalies or syndromes, the Childhood Opportunity Index (COI, a US Census tract-based, nationally-normed composite metric of contemporary child neighborhood opportunity comprising 29 indicators across education, health/environment, and socioeconomic domains), STAT mortality category, major adverse postoperative complications (e.g., prolonged mechanical ventilation, renal failure, etc.), and the Residual Lesion Score (RLS, a quality improvement metric that assesses residual lesion severity at discharge based on echocardiographic criteria and pre-discharge unplanned reinterventions). Logistic regression models were used to develop a weighted risk score for the primary outcome. The final prediction model was internally validated using a bootstrapping resampling approach to estimate the optimism-corrected C-statistic based on 500 samples.
Results: Of 10,412 consecutive patients who were discharged following CHS, 8,827 (84.8%) met entry criteria. The median age was 1.9 (IQR 0.3-8.1) years. There were 195 (2.2%) deaths at one year post-discharge. Uni- and multivariable logistic regression models of the primary outcome are shown in Table 1. A weighted risk score was formulated based on the variables in the final risk prediction model (Table 1), which included all aforementioned factors of interest (this model had a C-statistic of 0.82, 95% CI 0.80-0.85). The median risk score was 7 (IQR 5-9) points. Patients were categorized as low (score 0-5), medium (score 6-10), high (score 11-15), or very high (score 16-20) risk for 1-year mortality. The predicted probability of mortality was 0.3 ± 0.1%, 1.5 ± 0.9%, 8.0 ± 4.3%, and 34.5 ± 8.2% for low, medium, high, and very high risk patients, respectively.
Conclusions: A risk prediction model of 1-year mortality may guide prognostication and follow-up of high-risk patients following discharge from CHS.
CONGENTIAL:
Neonatal and Pediatric Cardiac Surgery
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