Cannabis Dependence or Abuse in Kidney Transplantation: Implications for Posttransplant Outcomes
Bibliographic record
Abstract
BACKGROUND: Cannabis is categorized as an illicit drug in most US states, but legalization for medical indications is increasing. Policies and guidance on cannabis use in transplant patients remain controversial. METHODS: We examined a database linking national kidney transplant records (n = 52 689) with Medicare claims to identify diagnoses of cannabis dependence or abuse (CDOA) and associations [adjusted hazard ratio (aHR) with 95% upper and lower confidence limits (CLs)] with graft, patient, and other clinical outcomes. RESULTS: CDOA was diagnosed in only 0.5% (n = 254) and 0.3% (n = 163) of kidney transplant recipients in the years before and after transplant, respectively. Patients with pretransplant CDOA were more likely to be 19 to 30 years of age and of black race, and less likely to be obese, college-educated, and employed. After multivariate and propensity adjustment, CDOA in the year before transplant was not associated with death or graft failure in the year after transplant, but was associated with posttransplant psychosocial problems such as alcohol abuse, other drug abuse, noncompliance, schizophrenia, and depression. Furthermore, CDOA in the first year posttransplant was associated with an approximately 2-fold increased risk of death-censored graft failure (aHR, 2.29; 95% CL, 1.59-3.32), all-cause graft loss (aHR, 2.09; 95% CL, 1.50-2.91), and death (aHR, 1.79; 95% CL, 1.06-3.04) in the subsequent 2 years. Posttransplant CDOA was also associated with cardiovascular, pulmonary, and psychosocial problems, and with events such as accidents and fractures. CONCLUSIONS: Although associations likely, in part, reflect associated conditions or behaviors, clinical diagnosis of CDOA in the year after transplant appears to have prognostic implications for allograft and patient outcomes. Recipients with posttransplant CDOA warrant focused monitoring and support.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".