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The Pediatric Heart Network Normal Echocardiogram Database Study had unanticipated challenges. We sought to describe these challenges and lessons learned to improve the design of future studies.
Challenges were divided into three categories: enrolment, echocardiographic imaging, and protocol violations. Memoranda, Core Lab reports, and adjudication logs were reviewed. A centre-level questionnaire provided information regarding local processes for data collection. Descriptive statistics were used, and chi-square tests determined differences in imaging quality.
For the 19 participating centres, challenges with enrolment included variations in Institutional Review Board definitions of “retrospective” eligibility, overestimation of non-White participants, centre categorisation of Hispanic participants that differed from National Institutes of Health definitions, and exclusion of potential participants due to missing demographic data. Institutional Review Board amendments resolved many of these challenges. There was an unanticipated burden imposed on centres due to high numbers of echocardiograms that were reviewed but failed to meet submission criteria. Additionally, image transfer software malfunctions delayed Core Lab image review and feedback. Between the early and late study periods, the proportion of unacceptable echocardiograms submitted to the Core Lab decreased (14 versus 7%, p < 0.01). Most protocol violations were from eligibility violations and inadvertent protected health information disclosure (overall 2.5%). Adjudication committee reviews led to protocol changes.
Numerous challenges encountered during the Normal Echocardiogram Database Study prolonged study enrolment. The retrospective design and flaws in image transfer software were key impediments to study completion and should be considered when designing future studies collecting echocardiographic images as a primary outcome.
Outcome analyses in large administrative databases are ideal for rare diseases such as Becker and Duchenne muscular dystrophy. Unfortunately, Becker and Duchenne do not yet have specific International Classification of Disease-9/-10 codes. We hypothesised that an algorithm could accurately identify these patients within administrative data and improve assessment of cardiovascular morbidity.
Hospital discharges (n=13,189) for patients with muscular dystrophy classified by International Classification of Disease-9 code: 359.1 were identified from the Pediatric Health Information System database. An identification algorithm was created and then validated at three institutions. Multi-variable generalised linear mixed-effects models were used to estimate the associations of length of stay, hospitalisation cost, and 14-day readmission with age, encounter severity, and respiratory disease accounting for clustering within the hospital.
The identification algorithm improved identification of patients with Becker and Duchenne from 55% (code 359.1 alone) to 77%. On bi-variate analysis, left ventricular dysfunction and arrhythmia were associated with increased cost of hospitalisation, length of stay, and mortality (p<0.001). After adjustment, Becker and Duchenne patients with left ventricular dysfunction and arrhythmia had increased length of stay with rate ratio 1.4 and 1.2 (p<0.001 and p=0.004) and increased cost of hospitalization with rate ratio 1.4 and 1.4 (both p<0.001).
Our algorithm accurately identifies patients with Becker and Duchenne and can be used for future analysis of administrative data. Our analysis demonstrates the significant effects of cardiovascular disease on length of stay and hospitalisation cost in patients with Becker and Duchenne. Better recognition of the contribution of cardiovascular disease during hospitalisation with earlier more intensive evaluation and therapy may help improve outcomes in this patient population.
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