Cannabis Use Disorder and Perioperative Outcomes in Major Elective Surgeries
Bibliographic record
Abstract
BACKGROUND: Although cannabis is known to have cardiovascular and psychoactive effects, the implications of its use before surgery are currently unknown. The objective of the present study was to determine whether patients with an active cannabis use disorder have an elevated risk of postoperative complications. METHODS: The authors conducted a retrospective population-based cohort study of patients undergoing elective surgery in the United States using the Nationwide Inpatient Sample from 2006 to 2015. A sample of 4,186,622 inpatients 18 to 65 yr of age presenting for 1 of 11 elective surgeries including total knee replacement, total hip replacement, coronary artery bypass graft, caesarian section, cholecystectomy, colectomy, hysterectomy, breast surgery, hernia repair, laminectomy, and other spine surgeries was selected. The principal exposure was an active cannabis use disorder, as defined by International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) diagnostic codes for cannabis dependence and cannabis abuse. The primary outcome was a composite endpoint of in-hospital postoperative myocardial infarction, stroke, sepsis, deep vein thrombosis, pulmonary embolus, acute kidney injury requiring dialysis, respiratory failure, and in-hospital mortality. Secondary outcomes included hospital length of stay, total hospital costs, and the individual components of the composite endpoint. RESULTS: The propensity-score matched-pairs cohort consisted of 27,206 patients. There was no statistically significant difference between patients with (400 of 13,603; 2.9%) and without (415 of 13,603; 3.1%) a reported active cannabis use disorder with regard to the composite perioperative outcome (unadjusted odds ratio = 1.29; 95% CI, 1.17 to 1.42; P < 0.001; Adjusted odds ratio = 0.97; 95% CI, 0.84 to 1.11; P = 0.63). However, the adjusted odds of postoperative myocardial infarction was 1.88 (95% CI, 1.31 to 2.69; P < 0.001) times higher for patients with a reported active cannabis use disorder (89 of 13,603; 0.7%) compared with those without (46 of 13,603; 0.3%) an active cannabis use disorder (unadjusted odds ratio = 2.88; 95% CI, 2.34 to 3.55; P < 0.001). CONCLUSIONS: An active cannabis use disorder is associated with an increased perioperative risk of myocardial infarction.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".