The TRIVIA Cohort for Surgical Management of Tetralogy of Fallot: Merging Population and Clinical Data for Real-World Scientific Evidence

Abstract

Background Guidelines for surgical management of tetralogy of Fallot (TOF) are often based on low-quality evidence due to the many challenges of congenital heart disease: heterogeneous cardiac anatomy, consequences from surgical interventions arising years later, and scarcity of hard outcomes. The overarching goal of the T etralogy of Fallot R esearch for I mprovement of V alve replacement I ntervention: A Bridge Across the Knowledge Gap (TRIVIA) study is to evaluate the long-term impact of the surgical management strategies in TOF. The specific objectives are: (1) to describe the long-term outcomes of TOF according to the native anatomy and the presence of genetic conditions, (2) to evaluate the long-term outcomes of surgical repair according to associated residual lesions, and (3) to evaluate the impact of paediatric pulmonary valve replacements on the long-term outcomes. Methods The TRIVIA study is a population-based cohort including all subjects with TOF in the province of Québec between 1980 and 2017. It links patient-level granular clinical data with long-term administrative health care data. We will evaluate mortality, cardiovascular interventions, and hospitalizations for adverse cardiovascular events using survival Cox models and marginal mean/rates models for recurrent events, respectively. Multivariate multilevel models will correct for potential confounders, and risk score matching will mitigate the potential of confounding by indication. Results The current TRIVIA cohort includes 1001 eligible subjects with TOF with complete lifelong follow-up for > 98%. The median follow-up is 17.1 years, totalling > 17,000 patient-years. Conclusions Universal health insurance data combined with granular clinical data enable the development of population-based cohorts, to which contemporary statistical methods are applied to address important research questions in congenital heart disease research.

The 30-Year Outcomes of Tetralogy of Fallot According to Native Anatomy and Genetic Conditions

“…Results: We included 960 subjects. The median follow-up was 17 years (interquartile range, [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Nonsyndromic cTOF subjects had a 30-year survival of 95% and had undergone a mean of 2.8 interventions and 0.5 hospitalisations per subject.…”

“…The rationale and design of the TRIVIA study were described previously. 14 Briefly, it is a retrospective populationbased cohort combining detailed clinical information and long-term administrative follow-up for all TOF subjects born from 1980 to 2015 in Qu ebec, Canada. TOF was defined as a ventricular septal defect by malalignment of the conal septum or overriding of the aorta with at least mild obstruction of the right ventricular outflow tract.…”

Comparison of Long-term Outcomes of Valve-Sparing and Transannular Patch Procedures for Correction of Tetralogy of Fallot

“…We analyzed a subset of the Tetralogy of Fallot Research for Improvement of Valve replacement Intervention: A Bridge Across the Knowledge Gap (TRIVIA) study, a retrospective population-based cohort including all patients with TOF born from 1980 to 2015 in Quebec, Canada. The detailed rationale and design of the TRIVIA study have been described previously . We included all patients with TOF who had at least mild pulmonary RVOT obstruction and underwent surgical correction with a VS procedure or TAP.…”

“…The detailed rationale and design of the TRIVIA study have been described previously. 21,22 We included all patients with TOF who had at least mild pulmonary RVOT obstruction and underwent surgical correction with a VS procedure or TAP. We excluded individuals with pulmonary atresia, TOF with absent pulmonary valve syndrome, and concomitant severe heart defects.…”

Reply to Abdi et al.—The Big Picture of the Long-term Outcomes of Tetralogy of Fallot

“…We believe that such real-world data will be of great value if met with modern statistical approaches such as longitudinal models, competitive risk assessment, and appropriate correction for indication and attrition biases. 3 Considering the heterogeneous trajectories of TOF, bayesian statistics and nonprobabilistic models of artificial intelligence could help to further characterise the intricate relationships between clinical factors and longitudinal events. 4 An added value for future studies would be to credit more importance to patientreported outcomes such as quality of life.…”