Trends in the Medical Use of Synthetic Cannabinoids Among Older Adults in Ontario, Canada
Bibliographic record
Abstract
Letters6 October 2020Trends in the Medical Use of Synthetic Cannabinoids Among Older Adults in Ontario, CanadaDena M. Sommer, MD, Jonathan S. Zipursky, MD, Vasily Giannakeas, MPH, Jennifer A. Watt, MD, PhD, Paula A. Rochon, MD, MPH, and Nathan M. Stall, MDDena M. Sommer, MDUniversity of Toronto, Toronto, Ontario, Canada (D.M.S.), Jonathan S. Zipursky, MDUniversity of Toronto, Sinai Health System, and Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada (J.S.Z.), Vasily Giannakeas, MPHWomen's College Hospital, ICES, and University of Toronto, Toronto, Ontario, Canada (V.G.), Jennifer A. Watt, MD, PhDUniversity of Toronto and St. Michael's Hospital–Unity Health Toronto, Toronto, Ontario, Canada (J.A.W.), Paula A. Rochon, MD, MPHUniversity of Toronto, Women's College Hospital, and ICES, Toronto, Ontario, Canada (P.A.R.), and Nathan M. Stall, MDUniversity of Toronto, Sinai Health System, and Women's College Hospital, Toronto, Ontario, Canada (N.M.S.)Author, Article, and Disclosure Informationhttps://doi.org/10.7326/M20-0598 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Background: The medical applications of cannabis and its synthetic derivatives (cannabinoids) are growing rapidly (1). Although synthetic cannabinoids are approved for the treatment of chemotherapy-induced nausea and vomiting, they are commonly prescribed off-label to older adults for various conditions, including chronic pain, sleep disturbances, and the behavioral and psychological symptoms of dementia (1, 2). Older adults may be particularly susceptible to the adverse effects of these drugs, including psychomotor, cognitive, mental health, and cardiovascular complications (1).Objective: To describe yearly trends in synthetic cannabinoid prescriptions to older adults in Ontario, Canada, between 1997 and 2017, and the characteristics of persons ...References1. Minerbi A, Häuser W, Fitzcharles MA. Medical cannabis for older patients. Drugs Aging. 2019;36:39-51. [PMID: 30488174] doi:10.1007/s40266-018-0616-5 CrossrefMedlineGoogle Scholar2. van den Elsen GA, Ahmed AI, Lammers M, et al. Efficacy and safety of medical cannabinoids in older subjects: a systematic review. Ageing Res Rev. 2014;14:56-64. [PMID: 24509411] doi:10.1016/j.arr.2014.01.007 CrossrefMedlineGoogle Scholar3. Cesamet. Package insert. Valeant Pharmaceuticals International; 2006. Accessed at www.accessdata.fda.gov/drugsatfda_docs/label/2006/018677s011lbl.pdf on 21 January 2020. Google Scholar4. Whiting PF, Wolff RF, Deshpande S, et al. Cannabinoids for medical use: a systematic review and meta-analysis. JAMA. 2015 Jun 23-30;313:2456-73. [PMID: 26103030] doi:10.1001/jama.2015.6358 CrossrefMedlineGoogle Scholar5. Statistics Canada. National Cannabis Survey, third quarter 2019. Accessed at www150.statcan.gc.ca/n1/daily-quotidien/191030/dq191030a-eng.htm on 21 January 2020. Google Scholar Author, Article, and Disclosure InformationAffiliations: University of Toronto, Toronto, Ontario, Canada (D.M.S.)University of Toronto, Sinai Health System, and Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada (J.S.Z.)Women's College Hospital, ICES, and University of Toronto, Toronto, Ontario, Canada (V.G.)University of Toronto and St. Michael's Hospital–Unity Health Toronto, Toronto, Ontario, Canada (J.A.W.)University of Toronto, Women's College Hospital, and ICES, Toronto, Ontario, Canada (P.A.R.)University of Toronto, Sinai Health System, and Women's College Hospital, Toronto, Ontario, Canada (N.M.S.)Financial Support: This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Dr. Rochon holds the RTO/ERO Chair in Geriatric Medicine at the University of Toronto, which supported this project. Dr. Stall is supported by the University of Toronto Department of Medicine's Eliot Phillipson Clinician-Scientist Training Program and the Vanier Canada Graduate Scholarship.Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M20-0598.Reproducible Research Statement: Study protocol and statistical code: The full data set creation plan and underlying analytic code are available from the authors on request (e-mail, nathan.[email protected]utoronto.ca), with the understanding that the computer programs may rely on coding templates or macros that are unique to ICES and therefore either are inaccessible or may require modification. Data set: The data set from this study is held securely in coded form at ICES. Although data-sharing agreements prohibit ICES from making the data set publicly available, access may be granted to persons who meet prespecified criteria for confidential access, available at www.ices.on.ca/DAS.Corresponding Author: Nathan M. Stall, MD, Division of Geriatric Medicine, Department of Medicine, Institute of Health Policy, Management and Evaluation, University of Toronto, Women's College Research Institute, Women's College Hospital, 76 Grenville Street, Toronto, ON M5S 1B2, Canada; e-mail, nathan.[email protected]utoronto.ca.This article was published at Annals.org on 21 July 2020. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited byIncremento y cambio en el perfil de las intoxicaciones en ancianosIncrease and change in the profile of poisonings in the elderly 6 October 2020Volume 173, Issue 7Page: 589-591KeywordsCannabinoidsCannabisDementiaDrug synthesisDrugsElderlyGeriatricsHealth careHospital medicineSleep ePublished: 21 July 2020 Issue Published: 6 October 2020 Copyright & PermissionsCopyright © 2020 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".