Risk factors for opioid-induced respiratory depression and failure to rescue
Bibliographic record
Abstract
PURPOSE OF REVIEW: The primary objective of this review is to identify the risk factors for opioid-induced respiratory depression (OIRD) in the postoperative period. RECENT FINDINGS: In the postoperative period, OIRD has often been reported resulting in morbidity and mortality. The risk factors which predispose surgical patients to increased risk of OIRD are not clearly defined. A literature search was performed for adult surgical patients who were prescribed opioids during their hospital stay and any available reports on postoperative respiratory depression/respiratory events. SUMMARY: Elderly, female sex, presence of obstructive sleep apnea, chronic obstructive pulmonary disease, cardiac disease, diabetes mellitus, hypertension, neurologic disease, renal disease, obesity, two or more comorbidities, opioid dependence, use of patient controlled analgesia, different routes of administration of opioids and concomitant administration of sedatives are significant risk factors for postoperative OIRD. The majority of patients with OIRD are deeply sedated and inadequately monitored. In patients with underlying risk factors, the dose of opioids should be carefully titrated. Enhanced monitoring of sedation level, respiratory rate, pulse oximetry and capnography is needed in the first 24 h after surgery.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".