Outcomes of Long-Term Noninvasive Ventilation Use in Children with Neuromuscular Disease: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Objectives To determine whether children with neuromuscular disorders using long-term noninvasive ventilation (NIV), continuous or bilevel positive airway pressure, have improved health outcomes compared with alternative treatment strategies. Data Sources: This systematic review is an extension of a scoping review. The search strategy used Medical Subject Headings and free-text terms for “child” and “noninvasive ventilation.” Studies of humans from 1990 onward were searched in MEDLINE (Ovid), Embase (Ovid), CINAHL (Ebsco), Cochrane Library (Wiley), and PubMed. The results were reviewed for articles reporting on neuromuscular disorders and health outcomes including mortality, hospitalization, quality of life, lung function, sleep study parameters, and healthcare costs. Data Extraction: Extracted data included study design, study duration, sample size, age, type of NIV, follow-up period, primary disease, and primary and secondary outcome measures. Studies were grouped by primary disease into three groups: spinal muscular atrophy, Duchenne muscular dystrophy, and other/multiple neuromuscular diseases. Data Synthesis: A total of 50 articles including 1,412 children across 36 different neuromuscular disorders are included in the review. Mortality is lower for children using long-term NIV compared with supportive care across all neuromuscular disease types. Overall, mortality does not differ when comparing the use of NIV with invasive mechanical ventilation, though heterogeneity suggests that mortality with NIV is higher for spinal muscular atrophy type 1 and lower for other/multiple neuromuscular diseases. The impact of long-term NIV on hospitalization rate differed by neuromuscular disease type with lower rates compared with supportive care but higher rates compared with supportive care use for spinal muscular atrophy type 1, and lower rates compared with before NIV for other/multiple neuromuscular diseases. Overall, lung function was unaltered and sleep study parameters were improved from baseline by long-term NIV use. There are few data to assess the impact of long-term NIV use on quality of life and healthcare costs. Conclusions Long-term NIV for children provides benefit for mortality, hospitalizations, and sleep study parameters for some sub-groups of children with neuromuscular disorders. High risk of bias and low study quality preclude strong conclusions.
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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 | 0.017 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.041 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".