Treatment of sleep-disordered breathing in children with myelomeningocele
Bibliographic record
Abstract
The prevalence of moderate to severe sleep-disordered breathing (SDB) in patients with myelomeningocele may be as high as 20%, but little information is available regarding treatment of these patients. To assess the efficacy and complications of treatments for these children, we collected data on 73 patients from seven pediatric sleep laboratories. Obstructive sleep apnea (OSA, n = 30) and central apnea (n = 25) occurred more frequently than central hypoventilation (n = 12). We also describe a sleep-exacerbated restrictive lung disease type of SDB in 6 patients who had hypoxemia during sleep without apnea or central hypoventilation. For each type of SDB, effective treatments were identified in a stepwise process, moving towards more complex and invasive therapies. For OSA, adenotonsillectomy was often ineffective (10/14), whereas nasal continuous positive airway pressure (CPAP) was usually successful (18/21). For central apnea, methylxanthines and/or supplemental oxygen proved sufficient in 2 of 9 and 3 of 6, respectively, but noninvasive positive pressure ventilation was required in 7 children. For central hypoventilation, supplemental oxygen (alone or with methylxanthines), noninvasive positive pressure ventilation, and tracheostomy with positive pressure ventilation were effective in 3, 2, and 2 patients, respectively. Sleep-exacerbated restrictive lung disease always required supplemental oxygen treatment, but in 2 cases also required noninvasive positive pressure ventilation; nutritional and orthopedic procedures also were helpful. Posterior fossa decompression was used for the first three types of SDB, but data were insufficient to delineate specific recommendations for or against its use. In summary, evaluation by an experienced, multidisciplinary team can establish an effective treatment regime for a child with myelomeningocele and SDB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".