Obstructive sleep apnoea and polymorphisms: implications for anaesthesia care
Bibliographic record
Abstract
With a worldwide obesity pandemic, the incidence of obstructive sleep apnoea (OSA) is increasing; obesity is the most significant risk factor in children. Increasing evidence suggests that OSA is in part mediated through markers of inflammation. Systemic and pulmonary hypertension, right ventricular hypertrophy, prediabetes, and other conditions are common. Adenotonsillectomy improves only ~70% of children; 30% require other interventions, e.g. weight loss programs. The gold standard for diagnosis is a sleep-polysomnogram which are expensive and not readily available. The McGill oximetry score (saw-tooth desaturations during obstruction and arousal) is more cost-effective. Repeated episodes of desaturation alter the opioid receptors such that analgesia is achieved at much lower levels of opioid than in patients undergoing the same procedure but without OSA. This response is of great concern because a standard dose of opioids may be a relative overdose. Polymorphism variations in cytochrome CYP2D6 have major effects upon drug efficacy and side effects. Codeine, hydrocodone, oxycodone, and tramadol are all prodrugs that require CYP2D6 for conversion to the active compound. CYP2D6 is quite variable and patients can be divided into 4 classes: For codeine for example, poor metaboliser (PM) have virtually no conversion to morphine, intermediate metabolisers (IM) have some conversion to morphine, extensive metabolisers (EM) have a normal rate of conversion to morphine, and ultra-rapid metabolisers (RM) convert excessive amounts of codeine to morphine. Such variations result in some patients achieving no analgesia because there is reduced conversion to the active moiety whereas others convert an excessive amount of drug to the active compound thus resulting in relative or actual overdose despite appropriate dosing. Thus, OSA patients may have both opioid sensitivity due to recurrent desaturations and altered drug metabolism resulting in higher than intended blood levels of opioid. OSA patients should only receive one-third to half the usual dose of opioid. In those under the age of six, an effort should be made to avoid opioids altogether and use opioid sparing techniques such as alternating acetaminophen and ibuprofen.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".