Bibliographic record
Abstract
OBJECTIVE: To determine the degree to which current Canadian clinical practice guidelines (CPGs) for common chronic conditions (ie, diabetes, dyslipidemias, hypertension, and osteoporosis) discuss the importance of patients' values and preferences in therapeutic decision making, and provide quantitative information that would allow for comprehensive shared informed decision making. DESIGN: Retrospective, observational review. MAIN OUTCOME MEASURES: The presence or absence of specific mentions of the importance of incorporating patients' values and preferences into therapeutic decision making; the number and type (relative or absolute) of quantitative descriptions of benefit or harm; the number of interventions for which a means of quantitatively determining the probability that an individual patient will experience an end point without and with implementation of the therapeutic intervention; and the number of descriptions of specific or comparative costs of treatment. RESULTS: Three of 5 CPGs mentioned that patients' values or preferences should influence treatment decisions. None of the CPGs recommended that benefits and harms of therapies be discussed with patients. Of the 63 quantitative mentions of therapeutic effects of interventions, 81%were presented using relative terms and 19% met our criteria for applicability to decision making for individual patients. Two of the 5 CPGs did not enumerate any harms. Three of the 5 CPGs made no mention of cost. CONCLUSION: Five prominent Canadian CPGs paid little attention to the issue of patients' values and preferences in therapeutic decision making, even though these issues are fundamental tenets of evidence-based practice. These 5 CPGs provided limited quantitative information on benefits and harms and therefore could not be used by clinicians to truly involve patients in informed decision making.
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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 | 0.173 | 0.653 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".