The Association of Cannabis Use Disorder with Acute Limb Ischemia and Critical Limb Ischemia
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Bibliographic record
Abstract
Objectives Heavy cannabis use has been associated with the development of acute myocardial infarction and stroke. The objective of this study was to determine if heavy, chronic cannabis use is associated with the development of acute limb ischemia (ALI) or critical limb ischemia (CLI). Methods We conducted a retrospective cohort study within the National Inpatient Sample (2006–2015). Patients without cannabis use disorder (CUD) were matched to patients with CUD in a 2:1 ratio using propensity scores. Our primary outcomes were incidence of ALI and CLI. Secondary outcomes included incidence of acute mesenteric ischemia (AMI), chronic mesenteric ischemia (CMI), frequency of open or endovascular interventions, length of stay, and total costs. Sensitivity analyses were performed with alternative models, including in the entire unmatched cohort with regression models utilizing survey weights to account for sampling methodology. Results We identified a cohort of 46,297 857 unmatched patients. Patients with CUD in the unmatched cohort were younger, with less cardiovascular risk factors, but higher rates of smoking and substance abuse. The matched cohort included 824,856 patients with CUD and 1,610,497 controls. Those with CUD had a higher incidence of ALI (OR 1.20 95% CI: 1.04-1.38 P=.016). Following multiple sensitivity analyses, there was no robust association between CLI and CUD. We observed no robust association of CUD with AMI, CMI, procedures performed, frequency of amputation, costs, or total length of stay. Conclusions Cannabis use disorder was associated with a significantly higher incidence of admission for acute limb ischemia. CUD was not associated with an increased risk of critical limb ischemia following sensitivity analysis. Given CUD is often seen in younger, less co-morbid patients it provides an important target for intervention in this population.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it