Can Assessment for Obstructive Sleep Apnea Help Predict Postadenotonsillectomy Respiratory Complications?
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine the frequency and type of respiratory complications after adenotonsillectomy in children. A second aim was to assess the ability of preoperative sleep studies to identify children at risk for respiratory complications. METHODS: Children referred for sleep studies between 1992 and 1998, who underwent adenotonsillectomy within 6 months of the preoperative study, were reviewed. The study focused on two variables: the obstructive apnea and hypopnea index and the oxygen saturation nadir. Medical charts were reviewed for postoperative respiratory complications. RESULTS: Three hundred forty-nine children were referred for sleep studies, and 163 met the inclusion criteria. Thirty-four children (21%) had postoperative respiratory complications requiring a medical intervention. Children experiencing respiratory complications were younger (aged < 2 yr; adjusted odds ratio, 4.3; 95% confidence interval, 1.7-11) and had an associated medical condition (odds ratio, 3; 95% confidence interval, 1.4-6.5). A preoperative obstructive apnea and hypopnea index of 5 or more events per hour increased the chance of postoperative respiratory complications (odds ratio, 7.2; 95% confidence interval, 2.7-19.3), as did a preoperative oxygen saturation nadir of 80% or less (odds ratio, 6.4; 95% confidence interval, 2.8-14.5). A preoperative oxygen saturation nadir of 80% or less had a likelihood ratio of 3.1, increasing the probability of postoperative respiratory complications from 20 to 50%. CONCLUSIONS: The data suggest, but do not prove, that preoperative nocturnal oximetry could be a useful preoperative test to identify children who are at increased risk for postoperative respiratory complications.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".