Are the insulin injection guidelines really evidence-based? A systematic review of different guideline recommendations regarding insulin injection
Bibliographic record
Abstract
Objective The purpose of this systematic review was to evaluate evidence for different guideline recommendations regarding needle reuse, rotation, injection site for a certain type of insulin and needle length, and to assess whether these recommendations are evidence-based. Methods A search of computer was carried out in PubMed, Medline, Embase, CNKI, Weipu data, Wanfang data from 1946 to December 2016, and diabetes education official websites in United States, Australia, Canada, Denmark, Hongkong (China), Netherlands and United Kingdom for insulin injection guidelines published before December 2016. All inclusions of guidelines for insulin injection followed the criteria of inclusion and exclusion. Two researchers independently screened and evaluated the quality of included guidelines with Appraisal of Guidelines for Research and Evaluation, and then extracted relevant data for analysis. Results In the original search, 967 100 literatures were identified, and 10 guidelines were included in the final review. Guidelines were published from 2007 to 2016. We found that evidence of recommendations on using the pen needle only once, rotating the injection sites among different anatomic areas (abdomen, thigh, arm and buttocks) and determining the injection sites by insulin type are not accurate enough. Conclusion In these existing guidelines for insulin injection, some recommendations are not fully strict. Further randomised clinical trial is warranted to provide scientific basis for developing the recommendations. Key words: Insulin injection; Guideline; Systematic review
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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 | 0.034 | 0.171 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".