Recommendation Map for Type 2 Diabetes: A Protocol for a Living Systematic Review of Clinical Practice Guidelines
Bibliographic record
Abstract
ABSTRACT Introduction The global burden of type 2 diabetes, emergence of numerous new therapeutics and rapidly evolving evidence calls for trustworthy and current clinical practice guidelines (CPGs). This living systematic review of national and international CPGs aims to iteratively summarize recommendations for the management of type 2 diabetes. Method and Analysis We will search electronic databases, professional academic association websites and guideline repositories from 2010 to April 1 2024 for national, international, or professional society CPGs addressing the management of type 2 diabetes. Our initial search will be followed by quarterly literature searches. Paired reviewers will independently assess the quality of identified CPGs using AGREE‐II. Recommendations and their associated methodological quality will be summarized and made available via a user‐friendly interactive online platform. Discussion This living systematic review of CPGs will enable clinicians, patients and system‐level decision‐makers to inform their decision‐making based on internationally available CPGs. It will also allow methodologists to identify gaps in evidence and recommendations to inform future directions in research and CPGs development. PROSPERO Registration Number CRD42023466448 ( https://www.crd.york.ac.uk/PROSPERO/ ).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.134 | 0.308 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.021 | 0.025 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.115 | 0.018 |
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".