007 Partnering To Transform Clinical Research Into Evidence-Based Health Care Guidelines
Bibliographic record
Abstract
Background Despite the availability of clinical practice guidelines (CPGs) on the management of diabetes mellitus type 2 (DMT2), optimal control is not achieved in many parts of the world. Objectives To assess whether recent nationally-endorsed DMT2 CPGs refer to Cochrane reviews that relate to the recommendations of these CPGs. Methods MEDLINE, EMBASE, guideline agency websites and Google were searched for CPGs written in English on the management of DMT2 in any practice setting published between Jan 2008 – Jan 2013. Four raters independently appraised each CPG using the AGREE-II instrument. The Cochrane Library (CL) was searched for published reviews using ‘Diabetes mellitus, Type 2’ [MeSH]. Reviews published one year prior to the CPG’s publication date were considered ‘available’ reviews. Two reviewers independently assessed their relevance for the CPGs’ recommendations. Results Five CPGs were identified. The highest scores were for ‘clarity-of-presentation’ and the lowest were for ‘applicability’. The CL search retrieved 45 reviews; 7 of them were assessed as irrelevant. The Canadian-2008, the Australian-2009 and the UK-NICE-2008/2009 guidance referred respectively to 80%, 85.7% and 93.8% of “potential” Cochrane reviews. The American-Diabetes-Association Standards of Medical Care in Diabetes 2013 cited 9/38 and the Malaysian 1/18 recent review. This variation in the uptake of relevant Cochrane reviews was not directly related to the rigour-of-development domain score. Implications for Guideline Developers, Adaptors, Implementers, and/or Users Despite the increased production of Cochrane reviews, guidelines developers do not consistently refer to them. This needs to be explored and the practical means for maximising their uptake should be entertained.
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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 | 0.363 | 0.503 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.022 | 0.024 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.056 | 0.023 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".