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Record W2751140010 · doi:10.3138/jammi.1.1.02

<i>Choosing Wisely Canada</i> – top five list in infectious diseases: An official position statement of the Association of Medical Microbiology and Infectious Disease (AMMI) Canada

2016· article· en· W2751140010 on OpenAlexaffvenueabout
Jerome A. Leis, Gerald A. Evans, William Ciccotelli, Gary Garber, Daniel B. Gregson, Todd C. Lee, Nicole Le Saux, Derek R. MacFadden, Lynora Saxinger, Stephen D. Shafran, Wayne L. Gold

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsUniversity of AlbertaMcGill UniversityUniversity of CalgaryUniversity of OttawaSt Mary's Hospital CentreGrand River HospitalQueen's UniversityHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineInfectious disease (medical specialty)Family medicineHarmHealth careDiseasePsychologyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Overuse of investigations, treatments, and procedures contribute to rising health care costs and may cause patient harm. In an attempt to promote higher-value health care, the Choosing Wisely Canada campaign has encouraged professional societies to develop statements that are directly actionable by their members. Currently, there are variations in infectious diseases practice that lead some patients to receive therapies and investigations that lack benefit and are potentially harmful. METHODS: The Association of Medical Microbiology and Infectious Disease Canada (AMMI) Canada established its Choosing Wisely Canada top five list of recommendations using the framework put forward by Choosing Wisely Canada. Following an electronic survey of its members regarding low-value practices within infectious diseases, AMMI Canada convened a working group that developed a list of draft recommendations and ranked the top five recommendations by consensus. This list was shared with the AMMI Canada membership electronically and during a national open forum. Following revisions based on feedback received, the AMMI Canada Executive Council and Guidelines Committee endorsed the final list, which was disseminated online. RESULTS: The top five declarative statements on infectious diseases practices that physicians and patients should question include: do not routinely prescribe intravenous forms of highly bioavailable antimicrobial agents for patients who can reliably take and absorb oral medications; do not prescribe alternative second-line antimicrobials to patients reporting nonsevere reactions to penicillin when beta-lactams are the recommended first-line therapy; do not routinely repeat CD4 measurements in patients with HIV infection with HIV-1 RNA suppression for >2 years and CD4 counts >500/μL, unless virological failure occurs or intercurrent opportunistic infection develops; do not routinely repeat radiologic imaging in patients with osteomyelitis demonstrating clinical improvement following adequate antimicrobial therapy; and do not prescribe aminoglycosides for synergy to patients with bacteremia or native valve infective endocarditis caused by Staphylococcus aureus. CONCLUSIONS: The Choosing Wisely Canada statements in infectious diseases endorsed by AMMI Canada represent a starting point to engage AMMI Canada members in broader discussions related to resource stewardship within infectious diseases practice and to take action.

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 imitation

Not 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.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.243
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.075
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0120.008
Scholarly communication0.0150.005
Open science0.0060.006
Research integrity0.0200.021
Insufficient payload (model declined to judge)0.0150.010

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.

Opus teacher head0.031
GPT teacher head0.357
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations3
Published2016
Admission routes3
Has abstractyes

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