Pulse rate and pulse rate variability help to identify children with obstructive sleep apnea needing adenotonsillectomy
Bibliographic record
Abstract
Indroduction : nocturnal pulse oximetry has a high positive predictive value for polysomnographically-diagnosed obstructive sleep apnea(OSA) in children. When significant adenotonsillar hypertrophy is present, adenotonsillectomy(T&A) represents a common treatment for OSA in children. After T&A a reduction of pulse rate(PR) and pulse rate variability(PRV) is expected. Objective: We hypothesised that PR and PRV could help to predict those patients, referred for suspected OSA, who need surgical treatment. Methods : at-home nocturnal pulse oximetry recording was performed on 251 children(162 males), aged 4.5 yrs ± 2.5(mean ± SD), referred consecutively from February 2009 and November 2012 for suspected OSA and data were retrospectively analysed. Patients with significant comorbidities were excluded. For each analysis McGill Oximetry Score(MOS) was also categorized. Results : mean and maximum PR and PR variability were progressively higher as MOS increased. Moreover all PR values(lowest, mean, maximum, and PRV) were significantly higher in subjects who underwent T&A compared with those not surgically treated(p<0.01). Interestingly a negative correlation was found between PRV and the time spent between pulse oximetry recordings and T&A(p=0.03, rho spearman=-0.30). Children with a PRV ≥10 were significantly more likely to undergo a surgical treatment indication(Positive likelihood ratio=4.1). Importantly when both MOS and PRV were used, NPO could better predict those patients who underwent T&A. Conclusions : our data suggest that in children with OSA, PR and PRV, as measured by nocturnal pulse oximetry, complement MOS system as a useful parameter to guide clinical decisions.
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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 | 0.003 |
| 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) | 0.002 | 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".