Bibliographic record
Abstract
This workshop will provide participants a hands-on opportunity to explore and reflect on the relationship between evidence, and specifically evidence based medicine, and the contemporary North American opioid epidemics. EBM emerged through the late twentieth century to promote good (conscientious, explicit and judicious) use of best evidence to inform clinical decision making. By the 1990s it was an established and dominant paradigm informing North American clinical practice. The 1990s and 2000s also saw a massive increase in the use of prescribed opioids for the management of pain. This was despite there being little good evidence for their efficacy and safety for chronic pain management. Harms from opioids continued to mount through the 2000s, prompting increasing scholarship into their safety. By 2010, Canada had its first national clinical practice guideline (CPG) for the use of opioids for chronic pain management, followed in 2016 by the Centres for Disease Control in the United States and then by an update of the Canadian guidelines in 2017. Neither country has yet seen a comprehensive CPG for the management of chronic non-cancer pain. In this workshop, we will use first a historical perspective and then a population health perspective to critically examine the role of evidence, and specifically evidence synthesis in the form of CPGs, vis-à-vis opioid use and the population level opioid-related harms. From a historical perspective, we will draw on some of our current bibliometric research of a highly cited pre-EBM opioid prescribing guideline and compare this to the content of a contemporary (‘EBM-informed’) CPG. Participants will work individually and in small groups to examine, compare and contrast specific recommendations from these two guidelines, published more than 30 years apart. This will provide an opportunity to reflect on the value and utility of using current best evidence versus expert opinion to inform guideline development. The second half of this workshop will take a population health perspective and focus on a set of highly influential Canadian and American studies into the dose-related harms of prescribed opioids. Participants will trace the path from the publication of these studies to their synthesis in CPGs in the form of specific recommendations for opioid dosing. We will consider the particular form in which the study data were interpreted and how this influenced guideline recommendations. Participants will be offered the opportunity to use alternate modes of analysing the same data, for example from population health perspectives. We will then consider whether and how these different modes of analysis could influence clinical practice recommendations.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".