Are Canadian Clinical Practice Guidelines Accounting for Adults With Multiple Chronic Diseases? A Systematic Review
Bibliographic record
Abstract
RATIONALE: Recommendations that are equipped with essential and adequate information promote adherence and support evidence-informed decision-making, which are crucial attributes of patient-centered care when caring for patients with multiple coexisting health conditions. AIMS AND OBJECTIVES: To systematically evaluate the content of recommendations of Clinical Practice Guidelines in Canada. METHOD: We searched PubMed, MEDLINE, Embase, and professional organization websites to identify 18 Canadian guidelines addressing 14 diseases prevalent in adults with multimorbidity in nonhospital settings. Two reviewers independently appraised the included guidelines using the international AGREE II tool, extracted 2,509 recommendations and assessed each recommendation to determine the presence of primary health outcomes, as well as secondary demographics and the number of involved diseases. We stratified the findings by potential modifiers: level of evidence (LOE) and type of recommendations (e.g., screening and diagnosis). RESULTS: Half of the guidelines were high-quality, with all domains scoring 50% or higher. The format and definitions of LOE were found to be heterogeneous. A significant portion focused on a single disease (72%), did not include any demographic information (72), or missed health outcomes (66%). Health outcomes were more frequently addressed in pharmacological (17.6%) and Nonpharmacological (14.5%) management recommendations than in screening (0.7%) and diagnosis (1.1%) recommendations. CONCLUSION: There is significant variation in guidelines. For health professionals such as primary care whose patients have multiple conditions, this variation is unacceptable. A centralized guideline development agency would reduce inconsistencies in formatting among guidelines, promoting adherence. Recommendations equipped with adequate information are pivotal in supporting patient-centered care through evidence-informed decision-making. PROSPERO registration: CRD42020105261.
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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 | 0.047 | 0.323 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.024 | 0.031 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".