Transcutaneous Carbon Dioxide Monitoring and Capnography During Pediatric Polysomnography
Bibliographic record
Abstract
INTRODUCTION: Transcutaneous monitoring and capnography are 2 surrogate methods of measuring arterial carbon dioxide levels employed by pediatric sleep laboratories. Both techniques are noninvasive, validated, and quantitative indirect predictors of arterial carbon dioxide level, and both have been widely adopted for use during pediatric and adult polysomnography (PSG). We hypothesized that there would be close agreement between the two techniques when compared in a pediatric population. METHODS: Children referred for diagnostic polysomnography to the Pediatric Sleep Laboratory at the Alberta Children's Hospital from June 2000 to October 2003 were included. All subjects underwent an overnight computerized PSG as per American Thoracic Society standards, including both transcutaneous and end-tidal monitoring. A registered PSG technician manually scored studies and eliminated all CO2 data that was not interpretable. Total "uninterpretable data" time was calculated for both channels. Statistical analysis of the level of agreement between transcutaneous and end-tidal signals was performed using a Bland-Altman analysis. RESULTS: The PSG studies of 609 children (363 males), mean age 7.9 +/- 4.6 years (range 0.1-18.4), were reviewed. On average, interpretable data was available for 61.8% +/- 35.1% and 71.5% +/- 25.2 % of total recording time from the end-tidal and transcutaneous channels respectively. The maximum and mean CO2 measurements obtained by both devices showed close agreement with a mean difference of 0.1 +/- 5.4 mm Hg and 0.6 +/- 3.9 mm Hg respectively. CONCLUSION: Transcutaneous and end-tidal carbon dioxide monitoring during polysomnography are well tolerated and provide interpretable and comparable results in the majority of children.
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 | 0.001 | 0.005 |
| 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 | 0.000 |
| 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".