Antimicrobial Resistance Following Prolonged Use of Hand Hygiene Products: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: This systematic review aimed to establish whether antimicrobial resistance (AMR) occurs following prolonged use of antimicrobial hand hygiene (HH) products, and, if so, in what magnitude. METHODS: Key bibliographic databases were searched to locate items on HH use and AMR development from database inception to December 2020. Records were screened and full texts of all potentially eligible articles were retrieved and checked for inclusion. The following data from the included studies were abstracted: type of HH product used, including the name of antimicrobial agent, study setting, country, study year, duration of use and development of AMR including the organisms involved. Quality assessment was done using the Newcastle-Ottawa Scale (NOS). RESULTS: Of 339 full-text articles assessed for eligibility, only four heterogeneous United States (US) studies conducted in the period between 1986 and 2015 were found eligible, and included. One hospital-based study showed evidence of AMR following long term use of HH products, two studies conducted in household settings showed no evidence of AMR, and another experimental study showed partial evidence of AMR. The overall certainty of the evidence was moderate. CONCLUSION: Prolonged use of HH products may cause AMR in health care settings, but perhaps not in other settings.
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 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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".