Browsing by Author "Xu, Meng"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Creation of a novel algorithm to identify patients with Becker and Duchenne muscular dystrophy within an administrative database and application of the algorithm to assess cardiovascular morbidity
    (Cambridge University Press, 2019-03) Soslow, Jonathan H.; Hall, Matthew; Burnette, W. Bryan; Hor, Kan; Chisolm, Joanne; Spurney, Christopher; Godown, Justin; Xu, Meng; Slaughter, James C.; Markham, Larry W.; Pediatrics, School of Medicine
    BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
  • Thumbnail Image
    Item
    Non-contrast cardiovascular magnetic resonance detection of myocardial fibrosis in Duchenne muscular dystrophy
    (Elsevier, 2021-04-29) Raucci, Frank J., Jr.; Xu, Meng; George‑Durrett, Kristen; Crum, Kimberly; Slaughter, James C.; Parra, David A.; Markham, Larry W.; Soslow, Jonathan H.; Pediatrics, School of Medicine
    Background: Duchenne muscular dystrophy (DMD) leads to progressive cardiomyopathy. Detection of myocardial fibrosis with late gadolinium enhancement (LGE) by cardiovascular magnetic resonance (CMR) is critical for clinical management. Due to concerns of brain deposition of gadolinium, non-contrast methods for detecting and monitoring myocardial fibrosis would be beneficial. Objectives: We hypothesized that native T1 mapping and/or circumferential (εcc) and longitudinal (εls) strain can detect myocardial fibrosis. Methods: 156 CMRs with gadolinium were performed in 66 DMD boys and included: (1) left ventricular ejection fraction (LVEF), (2) LGE, (3) native T1 mapping and myocardial tagging (εcc-tag measured using harmonic phase analysis). LGE was graded as: (1) presence/absence by segment, slice, and globally; (2) global severity from 0 (no LGE) to 4 (severe); (3) percent LGE using full width half maximum (FWHM). εls and εcc measured using feature tracking. Regression models to predict LGE included native T1 and either εcc-tag or εls and εcc measured at each segment, slice, and globally. Results: Mean age and LVEF at first CMR were 14 years and 54%, respectively. Global εls and εcc strongly predicted presence or absence of LGE (OR 2.6 [1.1, 6.0], p = 0.029, and OR 2.3 [1.0, 5.1], p = 0.049, respectively) while global native T1 did not. Global εcc, εls, and native T1 predicted global severity score (OR 2.6 [1.4, 4.8], p = 0.002, OR 2.6 [1.4, 6.0], p = 0.002, and OR 1.8 [1.1, 3.1], p = 0.025, respectively). εls correlated with change in LGE by severity score (n = 33, 3.8 [1.0, 14.2], p = 0.048) and εcc-tag correlated with change in percent LGE by FWHM (n = 34, OR 0.2 [0.1, 0.9], p = 0.01). Conclusions: Pre-contrast sequences predict presence and severity of LGE, with εls and εcc being more predictive in most models, but there was not an observable advantage over using LVEF as a predictor. Change in LGE was predicted by εls (global severity score) and εcc-tag (FWHM). While statistically significant, our results suggest these sequences are currently not a replacement for LGE and may only have utility in a very limited subset of DMD patients.
  • Thumbnail Image
    Item
    Physical Activity Correlates With Skeletal Muscle MRI Findings in Individuals With Duchenne Muscular Dystrophy
    (Wiley, 2025) Tamaroff, Jaclyn; Joy, Nicholas; Damon, Bruce; Markham, Larry W.; Donnelly, Thomas; Su, Karry; Buchowski, Maciej S.; Crum, Kimberly; Slaughter, James C.; Xu, Meng; Burnette, W. Bryan; Soslow, Jonathan; Pediatrics, School of Medicine
    Introduction/aims: Skeletal muscle magnetic resonance imaging (MRI) is a validated noninvasive tool to assess Duchenne muscular dystrophy (DMD) progression. There is interest in finding DMD biomarkers that decrease the burden of clinical trial participation, such as wearable devices. Our aim was to evaluate the relationship between activity, via accelerometry, and skeletal muscle MRI, particularly T2 mapping. Methods: DMD children and young adults completed skeletal muscle MRI and were asked to wear an accelerometer on the dominant wrist for 7 days. MRI data included fat-suppressed transverse relaxation time (T2) mapping of the calves and longitudinal relaxation time (T1) mapping. Activity was assessed as vector magnitudes (VMs) and fraction of time (FOT) in activity groups (sedentary 1 or 2, low 1 or 2, moderate-to-vigorous physical activity (MVPA)). Results: Participants (n = 22; median age 11.4 years, 41% ambulatory) wore the accelerometer for a median of 7 days. Longer T2 in multiple lower extremity muscles was negatively correlated with VMs per minute (tibialis posterior Spearman's rho = -0.68, p < 0.001), even when accounting for age, ambulatory status, or glucocorticoid use. Longer T2 of the tibialis posterior was positively correlated with FOT in sedentary 1 (rho = 0.49, p = 0.02) and negatively correlated with FOT in higher activity levels (low 1 (rho = -0.58, p = 0.004), low 2 (rho = -0.67, p = 0.002), MVPA (rho = -0.7, p < 0.001)). Discussion: In individuals with DMD, longer T2 on skeletal muscle MRI of the calves moderately correlated with lower activity levels indicating the potential use of home accelerometry as a future clinical trial biomarker of skeletal muscle health and progression in DMD.