L-Tryptophan As Treatment for Pediatric Non-Rapid Eye Movement Parasomnia
Bibliographic record
Abstract
OBJECTIVE: Parasomnias are common in childhood but there is no established treatment for parasomnias. The aim of this study was to (1) report on the outcome of using L-tryptophan to manage parasomnias in children and (2) examine sleep architecture and subjective psychological/sleep symptoms in children with parasomnia. METHOD: A retrospective analysis was conducted of charts of children (3-18 years old) who underwent polysomnographic testing and were diagnosed with primary parasomnia. Study patients were either prescribed L-tryptophan (daily dose range: 500-4500 mg, mean dose of 2400 mg) to manage their parasomnias or administered no treatment whereby parents/guardians declined treatment. Questionnaires assessing sleep and psychosocial symptoms were administered at the initial clinical consultation and a follow-up parasomnia outcome questionnaire was administered over the phone to parents/guardians. RESULTS: One hundred and sixty-five children (106 boys, 59 girls) received a sleep diagnosis of primary parasomnia. A significantly (p < 0.001) higher proportion (84%) of children taking L-tryptophan experienced improvements in their parasomnia symptoms compared with those (47%) who chose not to use L-tryptophan. Polysomnography revealed that children with parasomnias had an altered sleep architecture based on age-related normative values. Children with a diagnosis of parasomnia were also subjectively more fatigued and endorsed more depressive symptoms. CONCLUSIONS: This study finds that parasomnias in children are not benign and that treatment with L-tryptophan provides a favorable outcome. Children diagnosed with parasomnia had altered sleep architecture, were more fatigued, and endorsed depressive symptoms. This study supports the need to diagnose and treat parasomnias in children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".