MétaCan
Menu
Back to cohort

A review of infection prevention and control guidelines for dental offices during the COVID-19 pandemic in mid-2020

2021· review· en· W4411598065 on OpenAlexvenueno aff
Dempsey Wood

Bibliographic record

VenueCanadian Journal of Infection Control · 2021
Typereview
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakInfection controlSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineVirologyCoronavirus InfectionsIntensive care medicineOutbreakInfectious disease (medical specialty)PathologyDisease

Abstract

fetched live from OpenAlex

Background: The COVID-19 pandemic was a challenge for all dental professionals who had to rapidly update infection prevention and control (IPAC) guidelines and protocols due to increased risk of SARS-CoV-2 transmission during common aerosol-generating procedures (AGPs), and a lack of consensus on how best to mitigate the risk of transmission in a dental office. Thus, the purpose of this descriptive study was to compare the variance in IPAC guidelines for dental offices that emerged, and to assess practice consistency from early to mid-2020. Methods: A comprehensive literature search was conducted from May 26 to July 8, 2020 for IPAC documentation specific to the dental office during the COVID-19 pandemic. Documents that met the inclusion criteria were independently reviewed. Data was extracted using a framework based on the following IPAC domains: pre-appointment, waiting room, personal protective equipment (PPE) selection, treatment room, and post-dismissal. Results: A total of 67 IPAC documents specific to dental offices were reviewed in this study. Included documents originated from 22 dental associations, 17 peer-reviewed articles, 13 dental regulators, 11 government bodies, two public health units, and two dental corporations. There was a great degree of variance with IPAC guidelines from the pre-appointment stage, during treatment, and post-treatment. Recommendations that emerged with some level of consistency involved pre-screening patients for COVID-19 symptoms (97%), staggering appointments (84%), social distancing, minimizing occupants in the waiting room, wearing a face shield over protective eyewear for AGPs (92%), and preprocedural rinses (84%). There was less consistency with recommendations for consolidating multiple appointments (36%), waiting room ventilation (46%), N95 masks (47%) versus FFP2/FFP3 masks (30%) use for AGPs, fit-testing respirators (37%), enclosing open operatories for AGPs (28%), prioritizing minimally invasive procedures (30%), and using third-party laundry companies (32%). Conclusions: The risk of SARS-CoV-2 transmission, lack of consensus on mode of spread, and need for rapid action resulted in a significant variation in most downstream IPAC interventions in the hierarchy of controls, including choice of PPE, treatment room, and post-dismissal domains. Upstream interventions, including pre-appointment and waiting room domains, were relatively consistent in practices in early to mid-2020.

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)0.026
metaresearch head score (Gemma)0.102
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.102
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0240.018
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.101
GPT teacher head0.435
Teacher spread0.334 · 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
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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Infection ControlSame topicDental Research and COVID-19French-language works237,207