Do Co‐intoxicants Increase Adverse Event Rates in the First 24 Hours in Patients Resuscitated from Acute Opioid Overdose?
Bibliographic record
Abstract
BACKGROUND: Patients frequently arrive in emergency departments (EDs) after being resuscitated from opioid overdose. Autopsy studies suggest that multidrug intoxication is a major risk factor for adverse outcomes after acute heroin overdose in patients. If this is true, there may be high-risk drug combinations that identify patients who require more intensive monitoring and prolonged observation. Our objective was to determine the impact of co-intoxication with alcohol, cocaine, or CNS depressant drugs on short-term adverse event rates in patients resuscitated from acute opioid overdose. METHODS: Data were extracted from the database of a prospective opioid overdose cohort study conducted between May 1997 and 1999. Patients were prospectively enrolled if they received naloxone for presumed opioid overdose. Investigators gathered clinical, demographic, and other predictor variables, including co-intoxicants used. Patients were followed to identify prespecified adverse outcome events occurring within 24 h, and multiple logistic regression was used to determine the association of concomitant drug use on short-term adverse event rates. RESULTS: Of 1155 patients studied, 58 (5%) had pure opioid overdose and 922 (80%) reported co-intoxicants, including alcohol, cocaine, and CNS depressants. Overall, out of 1056 patients with known outcome status there were 123 major adverse events (11.6%) and 194 minor adverse events (18.4%). After adjustment for age, gender, HIV status, cardiovascular disease, pulmonary disease and diabetes, we found that coadministration of alcohol, cocaine, or CNS depressants, alone or in combination, was not associated with increased risk of death or adverse events during the 24 h follow-up period. CONCLUSION: In patients resuscitated from acute opioid overdose, short-term outcomes are similar for patients with pure opioid overdose and multidrug intoxications. A history of cointoxication cannot be used to identify high-risk patients who require more intensive ED monitoring or prolonged observation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".