Cannabis-related cognitive impairment
Bibliographic record
Abstract
OBJECTIVES: In patients with cancer, the use of medical cannabis has increased significantly during the recent years. There is evidence that cannabis consumption may affect cognitive performance; however, this potential effect has not been investigated prospectively in patients with cancer to date. We aimed to evaluate the effect of cannabis consumption on cognitive abilities as well as on symptom relief in patients with cancer during chemotherapy treatment. PATIENTS AND METHODS: A prospective study was carried out on a group of 17 patients on cannabis treatment (case) who were compared with 17 patients not on cannabis treatment (control). Participants completed self-reported questionnaires (the Hospital Anxiety and Depression Scale, Brief Fatigue Inventory, European Organization of Research and Treatment of Cancer core questions on the Quality of Life Questionnaire) and underwent the following neurocognitive tests: Montreal Cognitive Assessment, Digit Symbol Substitution subtest (WAIS III) and Digital-Finger Tapping Test. The evaluation was conducted before the initiation of cannabis consumption and 3 months later during the period of cannabis use. RESULTS: Improvement in executive functioning was demonstrated in the case group. In aspects of symptoms, improvement in fatigue, appetite and sleep disorder was demonstrated after cannabis consumption. Patients consuming cannabis did not differ from the control group in cognitive functioning over 3 months of use. No significant cognitive decline was observed in either group over time. CONCLUSION: These preliminary findings suggest that the short-term use of cannabis during chemotherapy treatment improved disease-related symptoms and did not affect cognitive skills in patients with cancer.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".