Consideration of antimicrobial resistance and contextual factors in infectious disease guidelines: a systematic survey
Bibliographic record
Abstract
OBJECTIVES: Guidelines that include antimicrobial recommendations should explicitly consider contextual factors that influence antimicrobial resistance and their downstream effects on resistance selection. The objectives were to analyse (1) how, and to what extent, tuberculosis, gonorrhoea and respiratory tract infection guidelines are considering antimicrobial resistance; (2) are of acceptable quality and (3) if they can be easily contextualised to fit the needs of specific populations and health systems. METHODS: We conducted a systematic review and searched Ovid MEDLINE and Embase from 1 January 2007 to 7 June 2019 for tuberculosis, gonorrhoea and respiratory tract infection guidelines published in English. We also searched guideline databases, key websites and reference lists. We identified guidelines and recommendations that considered contextual factors including antimicrobial resistance, values, resource use, equity, acceptability and feasibility. We assessed quality of the guidelines using the Appraisal of Guidelines for Research and Evaluation II tool focusing on the domains scope and purpose, rigour of development, and editorial independence. RESULTS: We screened 10 365 records, of which 74 guidelines met inclusion criteria. Of these guidelines, 39% (n=29/74) met acceptable quality scores. Approximately two-thirds of recommendations considered antimicrobial resistance at the population and/or outcome level. Five of the 29 guidelines reported all factors required for recommendation contextualisation. Equity was the least considered across guidelines. DISCUSSION: Relatively few guidelines for highly prevalent infectious diseases are considering resistance at a local level, and many do not consider contextual factors necessary for appropriate antimicrobial use. Improving the quality of guidelines targeting specific regional areas is required. PROSPERO REGISTRATION NUMBER: CRD42020145235.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".