Non-Respiratory Indications for Polysomnography and Related Procedures in Children: An Evidence-Based Review
Bibliographic record
Abstract
OBJECTIVE: This evidence-based review provides a systematic and comprehensive review of the literature regarding the utility of polysomnography for the evaluation of non-respiratory sleep disorders in children including hypersomnias, parasomnias, sleep-related movement disorders, and sleep in other special populations. METHODS: A task force of pediatric sleep medicine experts performed a systematic review of the literature regarding the use of polysomnography for non-respiratory sleep disorders in children. They identified and graded 76 papers as evidence. RESULTS: The main results include (1) polysomnography combined with the multiple sleep latency test is useful for evaluating disorders of excessive somnolence to objectively quantify sleepiness. The results have to be interpreted with consideration of the pubertal stage and regularity of the sleep patterns of the child; (2) polysomnography is indicated in children with parasomnias or sleep related movement disorders who have a high likelihood of having obstructive sleep apnea (OSA); (3) polysomnography is not routinely indicated in children with enuresis unless there is a high likelihood of OSA; (4) polysomnography can be helpful in evaluating children with restless legs syndrome (RLS) and when periodic limb movement disorder (PLMD) is suspected. CONCLUSIONS: These findings suggest that, in children with non-respiratory sleep disorders, polysomnography should be a part of a comprehensive sleep evaluation in selected circumstances to determine the nature of the events in more detail or when the suspicion of OSA is relatively high.
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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".