Cannabis Use in Inpatients With Schizophrenia Spectrum Disorders at a Community Hospital
Bibliographic record
Abstract
BACKGROUND: Cannabis is the second most used recreational drug in the United States and one of the most used substances in patients with schizophrenia spectrum disorder (SSD). Unfortunately, the increased use is likely to continue as more states legalize recreational use of cannabis. Although the association between cannabis and schizophrenia has been studied extensively, the understanding of the relationship is still evolving. In this study, we sought to determine the prevalence and potential factors associated with cannabis use (CU) among inpatients with SSD at a community teaching hospital. METHODS: We performed a retrospective review of the electronic medical charts of patients discharged from the psychiatric unit of our hospital from July 1, 2017 through October 31, 2017. Patients were included in this study if: 1) They were ≥ 18 years old; 2) They had discharge diagnosis of SSD; and 3) They had urine drug testing performed. Pertinent sociodemographic and clinical variables, including substance use status and hospital length of stay (LOS), were abstracted. Univariate frequencies and summary statistics were performed. Odds ratios (ORs) were determined by logistic regression analysis of bivariate and multivariate analyses. RESULTS: Three hundred sixty-five (52.2%) patients had a discharge diagnosis of SSD, and only 322 had urine toxicology result for cannabinoids and were included in analysis. Of the 322 patients, 41.5% (n = 133) screened positive for cannabinoids. Of the 133 patients, 78% were African American, 15% were Hispanic and 5% were White; 77% were male and the median age was 36 years. Bivariate analyses showed tobacco use (OR: 2.8, 95% confidence interval (CI): 1.7 - 4.6), alcohol use (OR: 3.4, 95% CI: 2.9 - 7.0), younger age (OR: 2.8, 95% CI: 1.8 - 4.5), male gender (OR: 2.9, 95% CI: 2.2 - 3.2), unemployment (OR: 3.91, 95% CI: 3.49 - 7.35), homelessness (OR: 3.18, 95% CI: 2.76 - 3.84) and LOS (OR: 3.46, 95% CI: 2.93 - 4.31) were significantly associated with CU. Result of multivariate analysis was similar to that found in bivariate analysis. CONCLUSIONS: CU appears to be prevalent among patients with SSD. Clinicians and public health professionals are encouraged to understand the health implications of its use in patients with mental illness especially against the backdrop of current marijuana laws.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".