<i>Choosing Wisely Canada</i>—Top five list in medical microbiology: An official position statement of the Association of Medical Microbiology and Infectious Disease (AMMI) Canada
Bibliographic record
Abstract
Background: Choosing Wisely Canada is a forum for health care professional societies to lead system change through identification and reduction of low-value practices. Microbiologic investigations are frequently overused and may contribute to unnecessary health care expenditures as well as patient harm. Methods: A Choosing Wisely Canada top five list in medical microbiology was developed by the Association of Medical Microbiology and Infectious Disease (AMMI) Canada through broad consultation of its members. Following an electronic survey of members, recommendations were developed and ranked by a working group, then further narrowed during a national open forum using the modified Delphi method. Feedback was solicited through an online forum prior to dissemination. Results: The top five declarative statements in medical microbiology are: ( 1 ) Don’t collect urine specimens for culture from adults who lack symptoms localizing to the urinary tract or fever, ( 2 ) Don’t routinely collect or process specimens for Clostridium difficile testing when stool is non-liquid or if the patient has had a prior nucleic acid amplification test result within the past 7 days, ( 3 ) Don’t obtain swabs from superficial ulcers for culture, ( 4 ) Don’t routinely order nucleic acid amplification testing on cerebrospinal fluid in patients without a compatible clinical syndrome, and ( 5 ) Don’t routinely obtain swabs during surgical procedures when fluid and/or tissue samples can be collected. Conclusions: This Choosing Wisely list represents a launching point to reduce low-value practices in microbiology. Strong implementation science around these statements will be needed to improve the value of microbiology testing in Canada.
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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".