Health care professionals' neckties as a source of transmission of bacteria to patients: a systematic review
Bibliographic record
Abstract
Background: There is growing concern that neckties worn by health care professionals may contribute to infections contracted in health care settings. We evaluated the evidence for health-care-associated infections resulting from neckties and whether the evidence is sufficient to warrant a tieless policy in Canada. Methods: We performed a systematic review to determine whether neckties worn by health care professionals colonize harmful pathogenic bacteria and whether they contribute to the spread of infection to patients in the inpatient or outpatient setting. We searched PubMed (1966 to 2017) and Embase (1974 to 2017). The level of evidence was appraised according to the Oxford Centre for Evidence-Based Medicine levels of evidence. We evaluated the quality of evidence and the risk of bias using the Jadad scale or the Newcastle-Ottawa Scale. Results: We screened 1675 citations, of which 6 were ultimately included in the systematic review. Only 1 study gave level 1b evidence (randomized controlled trial). Neckties were more likely than shirt pockets to colonize bacteria. There is limited evidence that neckties may be contaminated with pathogenic bacteria (e.g., methicillin-resistant Staphylococcus aureus) and very limited evidence that contaminated neckties may transmit bacteria (in a controlled experimental setting to a mannequin). Interpretation: There is no evidence of increased rates of health-care-associated infections related to the wearing of neckties by health care professionals. There is weak evidence that neckties are contaminated with pathogenic (and nonpathogenic) bacteria. The level of evidence was weak and the studies were heterogeneous. Evidence to support the need for a tieless dress code policy is lacking.
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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 | 0.015 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".