Characterization of Sleep Disordered Breathing in Children with Duchenne Muscular Dystrophy Using AASM Criteria versus Disease Specific Criteria: What Is the Difference?
Bibliographic record
Abstract
RATIONALE:Duchenne muscular dystrophy (DMD) is the most common pediatric neuromuscular disorder. These individuals are at risk of developing sleep disordered breathing (SDB) and pulmonary exacerbations because of progressive muscle weakness. Non-invasive ventilation (NIV) devices have been traditionally prescribed for SDB treatment based on American Academy of Sleep Medicine (AASM) criteria and has been shown to improve quality of life and reduce morbidity and mortality. Recently, DMD specific criteria for SDB have been published for the prescription of NIV. Our aim was to evaluate the differences in clinical management (ie prescription of NIV) that would arise from using the AASM versus the DMD specific criteria for polysomnography (PSG) interpretation in children and adolescents with DMD. METHODS:We performed a multicenter, retrospective chart review of children with DMD followed at The Hospital for Sick Children, Toronto, Ontario, Canada and Rady Children's Hospital, San Diego, USA that underwent diagnostic PSGs between August 1, 2012 to February 29, 2020. Baseline characteristics, pulmonary function tests and PSG data were summarized using descriptive statistics. The prescription of NIV based on AASM Criteria and DMD Criteria was described using odds ratios. SPSS version 26 was used for statistical analysis. Institutional Review Board approval was obtained from both institutions. RESULTS:105 male children with DMD were included. The mean SD for age in years and BMI z-score were 12.13.8 years and 0.22.3, respectively. See Table The proportion of children with DMD that met at least 1 AASM criteria and at least 1 DMD criteria were 48/105 (45.7%) and 71/105 (67.6%), respectively. 32 of 105 (30.5%) children with DMD met neither AASM nor DMD criteria. Fifty-four children with DMD (51.4%) were prescribed NIV. The most common AASM criteria and DMD criteria to be met were OAHI 5 events/hour (40.9%) and AHI 5 events/hour (48.6%), respectively. There was a greater chance of being prescribed NIV using DMD specific criteria rather than AASM criteria (OR, 4.0; 95%CI, 1.6-9.8, p-value= 0.005) and (OR, 3.4; 95%CI, 1.5-7.5, p-value= 0.003), respectively. CONCLUSIONS:There were more children with DMD diagnosed with nocturnal hypoventilation and prescribed NIV using DMD specific criteria as compared to AASM criteria. Future prospective cohort studies are required to evaluate changes in clinical outcomes when NIV is prescribed using DMD specific criteria versus AASM criteria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".