Long-Term Non-invasive Ventilation in Children With Down Syndrome: A Systematic Review
Bibliographic record
Abstract
Context: Children with Down syndrome are at risk for obstructive sleep apnea, which may not be resolved by adenotonsillecotmy, as well as other respiratory disorders that may impact breathing during sleep. Long-term non-invasive ventilation, including continuous and bilevel positive airway pressure delivery, is an alternate treatment strategy. Objective: To assess the use and outcomes of long-term non-invasive ventilation in children with Down syndrome including comparison to other children using long-term non-invasive ventilation. Data Sources: The search strategy for the scoping review used Medical Subject Headings (MeSH) and free-text terms for "child" and "non-invasive ventilation." MEDLINE (Ovid), Embase (Ovid), CINAHL (Ebsco), Cochrane Library (Wiley), and PubMed databases were searched (1990-2021). Study Selection: The scoping review results were searched to identify studies including data on at least three children with Down Syndrome using long-term non-invasive ventilation. Data Extraction: Study characteristics, subject characteristics, technology type, and outcome measurements were extracted. Results: A total of 28 articles included 543 children with Down syndrome using long-term non-invasive ventilation. Children with Down syndrome accounted for 18% of children using long-term non-invasive ventilation. Data on efficacy, feasibility, and adherence in children with Down syndrome are comparable to other children. Children with Down syndrome may have greater difficulty initiating long-term non-invasive ventilation, longer time to establish use, and a higher rate of inability to establish use. Outcome data is limited but suggest favorable impact on cardiac function and attention. Limitations: Articles related to long-term non-invasive ventilation use in adolescents and young adults may have been excluded. Conclusions: Children with Down syndrome make up a significant portion of the population of children using long-term non-invasive ventilation. While there is more limited data available with respect to the use and outcomes for children with Down syndrome compared to the other children, long-term non-invasive ventilation is an effective and well-tolerated therapy with no clear differences in the use or outcomes for children with Down syndrome. Additional work is needed to understand potential challenges around establishing long-term non-invasive ventilation use in children with Down syndrome. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=206533, identifier: CRD206533.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".