A review of infection prevention and control guidelines for dental offices during the COVID-19 pandemic in mid-2020
Bibliographic record
Abstract
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.
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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 | 0.026 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.024 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".