Neuraxial anaesthesia and peripheral nerve blocks during the COVID‐19 pandemic: a literature review and practice recommendations
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) has had a significant impact on global healthcare services. In an attempt to limit the spread of infection and to preserve healthcare resources, one commonly used strategy has been to postpone elective surgery, whilst maintaining the provision of anaesthetic care for urgent and emergency surgery. General anaesthesia with airway intervention leads to aerosol generation, which increases the risk of COVID-19 contamination in operating rooms and significantly exposes the healthcare teams to COVID-19 infection during both tracheal intubation and extubation. Therefore, the provision of regional anaesthesia may be key during this pandemic, as it may reduce the need for general anaesthesia and the associated risk from aerosol-generating procedures. However, guidelines on the safe performance of regional anaesthesia in light of the COVID-19 pandemic are limited. The goal of this review is to provide up-to-date, evidence-based recommendations or expert opinion when evidence is limited, for performing regional anaesthesia procedures in patients with suspected or confirmed COVID-19 infection. These recommendations focus on seven specific domains including: planning of resources and staffing; modifying the clinical environment; preparing equipment, supplies and drugs; selecting appropriate personal protective equipment; providing adequate oxygen therapy; assessing for and safely performing regional anaesthesia procedures; and monitoring during the conduct of anaesthesia and post-anaesthetic care. Implicit in these recommendations is preserving patient safety whilst protecting healthcare providers from possible exposure.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".