Personal protective equipment for reducing the risk of COVID-19 infection among health care workers involved in emergency trauma surgery during the pandemic: An umbrella review
Bibliographic record
Abstract
BACKGROUND: Health care facilities in low- and middle-income countries are inadequately resourced to adhere to current COVID-19 prevention recommendations. Recommendations for surgical emergency trauma care measures need to be adequately informed by available evidence and adapt to particular settings. To inform future recommendations, we set to summarize the effects of different personal protective equipment (PPE) on the risk of COVID-19 infection in health personnel caring for trauma surgery patients. METHODS: We conducted an umbrella review using Living Overview of Evidence platform for COVID-19, which performs regular automated searches in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and more than 30 other sources. Systematic reviews of experimental and observational studies assessing the efficacy of PPE were included. Indirect evidence from other health care settings was also considered. Risk of bias was assessed with the AMSTAR II tool (Assessing the Methodological Quality of Systematic Reviews, Ottawa, ON, Canada), and the Grading of Recommendations, Assessment, Development, and Evaluation approach for grading the certainty of the evidence is reported (registered in International Prospective Register of Systematic Reviews, CRD42020198267). RESULTS: Eighteen studies that fulfilled the selection criteria were included. There is high certainty that the use of N95 respirators and surgical masks is associated with a reduced risk of COVID-19 when compared with no mask use. In moderate- to high-risk environments, N95 respirators are associated with a further reduction in risk of COVID-19 infection compared with surgical masks. Eye protection also reduces the risk of contagion in this setting. Decontamination of masks and respirators with ultraviolet germicidal irradiation, vaporous hydrogen peroxide, or dry heat is effective and does not affect PPE performance or fit. CONCLUSION: The use of PPE drastically reduces the risk of COVID-19 compared with no mask use in health care workers. N95 and equivalent respirators provide more protection than surgical masks. Decontamination and reuse appear feasible to overcome PPE shortages and enhance the allocation of limited resources. These effects are applicable to emergency trauma care and should inform future recommendations. LEVEL OF EVIDENCE: Review, level II.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".