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The role of cardiopulmonary exercise testing in predicting mortality and morbidity in people with congenital heart disease: A systematic review and meta-analysis. Curtis Wadey MSc @CWSport1 cw694@exeter.ac.uk Who am I… • Postgraduate researcher based at the Children’s Health and Exercise Research Centre (CHERC). • Third year PhD student: • “Cardiorespiratory fitness in young people with congenital heart disease”. • Background: • MSc in Paediatric Exercise and Health. • Primary Care since 2014 @CWSport1 cw694@exeter.ac.ukWho are we? cw694@exeter.ac.uk @CWSport1Aims • Fitness in ConHD • Background • Methods • Results • Evidence base ‘quality of evidence’ @CWSport1 cw694@exeter.ac.uk BackgroundWhat is congenital heart disease? “Congenital heart disease is here defined as a gross structural abnormality of the heart or intrathoracic great vessels that is actually or potentially of functional significance.” 1 Global birth prevalence is increasing (9.4 per 1000 live births)2 Recent estimates report that 97% of children born with 3 congenital heart disease will reach adulthood. 1Mitchell, 1971. Liu, 2019. Mandalenakis, 2020. @CWSport1 cw694@exeter.ac.uk Pulmonary gas exchange BackgroundWhat is a CPET Echocardiography,d transcranialressure doppler, and near spectroscopy Peaks (NIRS) ECG Thresholds O2 Slopes saturations Mechanical Work @CWSport1 cw694@exeter.ac.ukBackground @CWSport1 cw694@exeter.ac.ukBackground Rational for a review on CPET and prognosis. • Growing congenital heart population. • Cardiorespiratory fitness has been associated with future 1,2,3,4. clinical events • Unsure of Cochrane review findings – what do they mean for prognosis? 1Dimopoulos, 2006 Giardini,2009 Müller, 2015 Udholm 2018 @CWSport1 cw694@exeter.ac.ukMethods - RQ PICOS: • Population • Index Prognostic Factor • Comparator prognostic factors • Outcome • Timing • Setting cw694@exeter.ac.uk @CWSport1Methods @CWSport1 cw694@exeter.ac.ukMethods @CWSport1 cw694@exeter.ac.ukMethods Exercise linked with morbidity and mortality? • “Receiver operating characteristic (ROC) curves were used to optimal cut off values so that the sum of sensitivity and specificity was maximized.” • “Freedom from the occurrence of cardiac outcome was plotted using the Kaplan–Meier method, with comparisons by the log-rank test.“ • “Univariate Cox proportional hazard analyses.” @CWSport1 cw694@exeter.ac.uk Results Analysed patient outcome in other ways (n=14). Survival Analysis Statistics (n=34). cw694@exeter.ac.uk @CWSport1 Results • 48 Studies included • 34 studies (~18,000 participants) in meta-an. • Only 1% was paediatric data! • 18 potential prognostic factors • Most popular was Peak VO2 • 4 subtypes of ConHD in primary univariate analysis cw694@exeter.ac.uk @CWSport1 Meta-analysis Univariate Reduction in events: • Peak VO 2-18% • V EVCO 2-8% • Heart rate reserve 2-30% Reduction in events: • Fontan 6-18% • Mix 2–22% • TGA 1-16% • ToF 4-30%Multivariate cw694@exeter.ac.uk @CWSport1@CWSport1 cw694@exeter.ac.uk Risk of bias • All studies - RoB was low in 12 studies (25%), moderate in 31 (65%), and high in 5 (10%) studies. • Studies included in the meta- analysis - 10 (29%), 23 (68%), and 1 (2%) were considered low, moderate, and high RoB, respectively. • For studies to be considered as a low risk of bias they must have received a low grading in five out of the six QUIPS domains and reported: o a detailed description of their cohort, o prospective studies with registered protocols, o no evidence of selection bias, o low levels of study attrition, o well-described CPET protocols, o followed up patients in multiple ways (i.e. office for national statistics, hospital records and contacted patients), o report/adjusted for comparator prognostic factors, o appropriate statistical analyses. @CWSport1 cw694@exeter.ac.ukAdditional findings Types of ergometry: • Cycle ergometer (n=16), • treadmill (n=24), • combination of cycle or treadmill ergometers (n=5) • Failed to report (n=3) • Protocols used: Bruce, modified Bruce, Naughton, step, or ramp. • Majority of the studies used respiratory exchange ratio to validate a maximal effort. • Few studies explored assumptions or non-linear trends. @CWSport1 cw694@exeter.ac.uk“Should we care about fitness in our congenital heart disease patients?” @CWSport1 cw694@exeter.ac.ukConclusions Clinical implications • CRF measured by CPET appears to be associated with future MACE in people with ConHD. • Although data are limited, no study reported a MACE during the CPET. Research implications • Given the low to moderate quality of included studies there is currently insufficient evidence to definitively determine the prognostic influence of CRF. • Adequately powered studies should follow, utilising contemporary prognostic factor research and reporting guidelines.Recommendations 1. Firstly, at a minimum all studies should explicitly report any adverse events that occurred during CPET 2. Follow the prognostic factor and prognostic modelling reporting frameworks (REMARK, PROGRESS and TRIPOD). 3. Future research should aim to prospectively register their trials with transparent prognostic factors of interest. 4. Studies should report the HR (or equivalent summary statistic) of all scales of the prognostic factor (i.e. % predicted, mL/kg/min) 5. Avoid using summary statistics computed from dichotomous CPET data unless to answer a specific research question. 6. To estimate the independent effect of CRF, studies should control for common covariates such as age at the test and resting oxygen saturations as a minimum. 7. Lastly, there was an over reliance on secondary criteria (i.e. RER) to validate peak efforts, which likely confounds peak CPET results. Instead, if clinically appropriate and feasible, studies should confirm a plateau in oxygen consumption @CWSport1 cw694@exeter.ac.uk https://www.prognosisresearch.com/ After thoughts “We need less research, better research, and research done for the right reasons. ” Altman @CWSport1 cw694@exeter.ac.uk