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S991 How “Dirty” Are the Endoscope Channels? A Systematic Review and Meta-Analysis of Reprocessed Endoscopes

2021· review· en· W3209706484 on OpenAlexaboutno aff
Hemant Goyal, Sára Larsen, Abhilash Perisetti, Pardeep Bansal, Aman Ali, Nikolaj Birk Larsen, Lotte Ockert, Sven Adamsen, Benjamin Tharian, Nirav Thosani

Bibliographic record

VenueThe American Journal of Gastroenterology · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicMedical Device Sterilization and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFunnel plotSubgroup analysisMeta-analysisPublication biasEndoscopeSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Introduction: The duodenoscope elevator mechanism has been considered a culprit for multiple outbreaks from contaminated reusable patient-ready duodenoscopes. These outbreaks necessitated FDA to issue various Safety Communications and recommend endoscopy units to transition to duodenoscopes with innovative designs that ease or eliminate reprocessing. However, numerous studies have documented microbes in the channels of reprocessed gastrointestinal (GI) endoscopes, including duodenoscopes and linear echoendoscopes. Our aim is to estimate the channel contamination rate of patient-ready reprocessed GI endoscopes based on the currently available data. Methods: We searched PubMed, Web of Science, and Embase from January 1, 2010, until October 10, 2020, for studies investigating contamination rates of channels of patient-ready flexible GI endoscopes by following the PRISMA guidelines. A random-effects model based on the proportion distribution was used to calculate pooled total contamination rate. A subgroup analysis was carried out for studies originating from North America (USA and Canada). We used the meta-package (metafor) in RStudio version 3.6.2 to conduct the statistical analyses. Heterogeneity between the included studies was analyzed using the inconsistency index (I2) statistics. Publication bias was assessed using funnel plots and Egger’s regression tests. Results: We identified 1,230 peer-reviewed studies after duplicates were removed. Finally, 20 studies fulfilled the inclusion criteria, including 1,059 positive cultures from 7,903 samples. The total weighted contamination rate was 19.98% ± 0.024 (95% Cl: 15.29%-24.68%; I2=98.6%) (figure 1a). Subgroup analysis amongst studies from North America (n=7) showed a contamination rate of 6.01% ± 0.011 (95% Cl: 3.88%-8.15%; I2=89.3%) (figure 1b). I2 indicated high heterogeneity. Egger’s regression test indicated no significant publication bias for both groups (Egger’s test of publication bias: p=0.0531 and p=0.0655). Conclusion: Our analysis demonstrates that 19.98% of reprocessed patient-ready GI endoscopes may be contaminated. The contamination rate was lower amongst US studies, which may be attributed to the actions taken in the US to overcome this issue. However, our findings highlight that the elevator mechanism is not the only obstacle when reprocessing endoscopes. More studies are needed to fully determine the role of contaminated endoscope channels in the cross-transmission between the patients.Figure 1.: 1a: Pooled estimates of contamination rates beyond the elevator. 1b: Pooled estimates of contamination rates beyond the elevator for studies conducted in North America. Cl: confidence interval; EUS: Endoscopic ultrasound; prop: proportion.

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)0.024
metaresearch head score (Gemma)0.062
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.062
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.035
Bibliometrics0.0100.010
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.047
GPT teacher head0.318
Teacher spread0.271 · 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 designMeta-analysis
Domainnot available
GenreReview

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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