Impact of Timing of Preprocedural Opioids on Adverse Events in Procedural Sedation
Bibliographic record
Abstract
BACKGROUND: The risk of respiratory depression is increased when opioids are added to sedative agents. In our recent multicenter emergency department (ED) procedural sedation cohort, we reported a strong association between preprocedural opioids and sedation-related adverse events. We sought to examine the association between timing of opioids and the incidence of adverse sedation outcomes. METHODS: We conducted a secondary analysis of a prospective cohort of children aged 0 to 18 years who received sedation for a painful procedure in six Canadian pediatric EDs from July 2010 to February 2015. The primary risk factor was timing of opioid administration, adjusted for age, opioid type, preprocedural and sedation medications, and procedure type. Outcomes were 1) oxygen desaturation, 2) vomiting, and 3) positive pressure ventilation (PPV). RESULTS: Of the 6,295 children in the original cohort, 1,806 (29%) received a preprocedural opioid. Patients receiving preprocedural opioids had a higher incidence of oxygen desaturation (risk difference = 4.3%, 95% confidence interval [CI] = 2.9% to 5.8%), vomiting (risk difference 2.0%, 95% CI = 0.7% to 3.3%), and PPV (risk difference = 1.5%, 95% CI = 0.7% to 2.3%). Multivariable regression with timing of opioids modeled as a restricted cubic spline revealed the risk for each outcome was highest when opioids were administered in the 30 minutes prior to sedation. Timing of opioid administration was statistically significantly associated with oxygen desaturation and vomiting (p < 0.0001) but not with PPV (p = 0.113). CONCLUSIONS: Timing of opioids was significantly associated with the risk of oxygen desaturation and vomiting. Being aware of this increased risk will help clinicians prepare for sedation and the potential need for patient rescue.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".