Cardiomyopathy is the leading cause of death in patients with Duchenne muscular dystrophy. The relationship between cardiac and skeletal muscle progression is unclear. The objective of this study was to evaluate the correlation between muscle activity and cardiomyopathy. We hypothesised that cardiomyopathy and skeletal muscle activity are directly related.

Physical activity was assessed with accelerometers worn for 7 days. Average activity (vector magnitude/min) and percentage of time in different activities were reported. Cardiac MRI was used to assess left ventricular ejection fraction, global circumferential strain (Ecc), late gadolinium enhancement, and cardiac index. Associations were assessed between physical activity and cardiac variables using a Spearman correlation.

Duchenne muscular dystrophy subjects (n = 46) with an average age of 13 ± 4 years had a mean left ventricular ejection fraction of 57 ± 8%. All physical activity measures showed significant correlations with left ventricular ejection fraction (rho = 0.38, p = 0.01) and left ventricular cardiac index (rho = 0.51, p < 0.001). Less active subjects had lower left ventricular ejection fraction (p = 0.10) and left ventricular cardiac index (p < 0.01). Non-ambulatory patients (n = 29) demonstrated a stronger association between physical activity and left ventricular ejection fraction (rho = 0.40, p = 0.03) while ambulatory patients demonstrated a stronger association between physical activity and left ventricular cardiac index (rho = 0.53, p = 0.03). Ecc did not associate with physical activity in either cohort.

Physical activity correlates with left ventricular ejection fraction and left ventricular cardiac index and is modified by ambulation. Future analysis should assess the temporal relationship between physical activity and cardiomyopathy.

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.