52 Impact of National Marijuana Legalization on Delirium Rates and Opioid Use in Acute Burns
Bibliographic record
Abstract
Abstract Introduction Cannabis use has been associated with larger total burn size areas, longer hospital stays, and an increased number of operations. Legalization of marijuana in Colorado has led to marked increases in burn injuries. Tetahydrocannabinol (‘THC’) use has been shown to increase psychosis, anxiety, and depression, however, it is unknown how this has impacted rates of ICU related delirium in the burn context. Further, observational studies have shown that marijuana use has decreased opioid-related overdoses, but it is unknown how chronic marijuana use affects opioid consumption in the ICU. Thus, it is unknown how national marijuana legalization has impacted ICU rates of delirium and opioid use. As such, the objectives of this study are to describe trends of marijuana legalization on burns and determine if the amount of delirium and opioid use while in hospital has increased after national marijuana legalization. Methods We conducted a retrospective cohort study of 514 patients admitted to an ABA-verified centre one year prior to national marijuana legalization and one-year afterwards. Inclusion criteria consisted of an acute burn injury admission. Data included demographics, toxicology screening information, hospital rates of delirium, and pain medication use. Statistical analysis consisted of student’s t-test, one-way ANOVA, Kruskal-Wallis, Mann-Whitney U, Fisher’s exact, and χ2 test. P value of < 0.05 was considered statistically significant. Results Out of 514 patients, 422 were included; 203 prior to legalization (‘PL’) and 219 afterwards (‘AL’). Cohorts were similar regarding age, gender, inhalation injury, and smoking history. TBSA, length of stay, police custody, major psychiatric illness, alcoholism, and drug dependence were significantly higher in the AL cohort. Positive cannabinoid screens were similar in each cohort (13.3 versus 13.7%), however in both cohorts a large proportion of admissions did not have a toxicology screen completed (58.4–63.5%). Delirium rates (PL=0.5%, AL=4.1%; p=0.02) and opioid use (PL=48%; AL=52%;X2(1, N=422)=5.7, p=0.02) were significantly higher in the AL cohort. Conclusions National legalization of marijuana is associated with increased in-hospital delirium rates and opioid consumption in the acute burn context. Every effort should be made to ensure toxicology screens are completed on admission with the appropriate use of both opioid and adjunct pain medication regimens. In addition, for those not eligible for a toxicology screen due to delayed arrival time to the burn centre, an in-depth discussion should be completed to elicit drug history.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".