A Systematic Review on the Usage of Long-term Non-invasive Ventilation in Children With Central Nervous System Disorders
Bibliographic record
Abstract
Abstract Rational: Long-term non-invasive ventilation(LT-NIV) has become a common treatment for sleep-related breathing disorders(SRBD) in children. Children with central nervous system disorders(CNS) often experience SRBD due to muscle dysfunction and brain impairment. Although LT-NIV has shown to improve respiratory function and quality of life in other conditions, its effectiveness in children with CNS disorders remains uncertain. This systematic review assesses the impact of LT-NIV on mortality, hospitalization, respiratory function, sleep and life quality in children with CNS disorders. Methods: This systematic review is an extension of a scoping review of LT-NIV in children. The scoping review was developed for MEDLINE(Ovid) and later translated to Embase, CINAHL, and Cochrane Library. Medical Subject Headings(MeSH) and free-text terms for “child” and “non-invasive ventilation” were used. The results of the scoping review were searched for studies on children with CNS disorders. Studies of children using NIV <3 months or in an acute care setting were excluded. Results: The search identified 55 studies, including 2,105 children with CNS disorders using LT-NIV. Of these studies, 19 reported LT-NIV outcomes specifically for CNS disorders. While most studies addressed CNS disorders within broader contexts of NIV, only four studies were specifically focused on CNS disorders(4/19,21%). Congenital central hypoventilation syndrome(CCHS) was the single most common CNS disorder in the included studies(7/19, 37%). Mortality rate from seven studies showed 13% of CNS children die on LT-NIV. Hospitalization rates varied across four studies: one reported unchanged rates with 33 visits pre- and post-LT-NIV; another found children with CNS disorders had 3.3 times higher odds of hospitalization compare to other children using LT-NIV(p < 0.001); a third noted a decline in hospitalization with age; and an outlier case documented 24 admissions after decannulation and LT-NIV initiation. Sleep parameters across three studies indicate improvement in the apnea-hypopnea index (AHI)(pre-NIV 26.2 vs. post-NIV 6.2 events/h). Another reported improvement in SpO₂ (88% to 97%), EtCO₂ (48 mmHg to 37 mmHg), and sleep efficiency. Among different CNS disorders, cerebral palsy shows a significant AHI reduction (pre-NIV 45.1 vs post-NIV 10.4 events/h). Conclusion: This review supports that LT-NIV may be beneficial for some children with SRBD in the context of CNS disorders. Data on hospitalization and mortality rates in children with CNS disorders using LT-NIV is limited. There is no data on respiratory function and quality of life. With limited data on the outcomes, future studies need to focus on understanding outcomes of LT-NIV use in children with CNS disorders.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".