Recommendations for local-regional anesthesia during the COVID-19 pandemic
Bibliographic record
Abstract
Since the beginning of the COVID-19 pandemic, many questions have come up regarding safe anesthesia management of patients with the disease. Regional anesthesia, whether peripheral nerve or neuraxial, is a safe alternative for managing patients with COVID-19, by choosing modalities that mitigate pulmonary function involvement. Adopting regional anesthesia mitigates adverse effects in the post-operative period and provides safety to patients and teams, as long as there is compliance with individual protection and interpersonal transmission care measures. Respecting contra-indications and judicial use of safety techniques and norms are essential. The present manuscript aims to review the evidence available on regional anesthesia for patients with COVID-19 and offer practical recommendations for safe and efficient performance. Desde o início da pandemia de COVID-19, muitas questões surgiram referentes à segurança do manejo anestésico de pacientes acometidos pela doença. A anestesia regional, seja esta periférica ou neuroaxial, é alternativa segura no manejo do paciente COVID-19, desde que o emprego de modalidades que minimizam o comprometimento da função pulmonar seja escolhido. A adoção desta técnica anestésica minimiza os efeitos adversos no pós-operatório e oferece segurança para o paciente e equipe, desde que sejam respeitados os cuidados com proteção individual e de contágio interpessoal. Respeito às contraindicações e emprego criterioso das técnicas e normas de segurança são fundamentais. Este manuscrito tem por objetivo revisar as evidências disponíveis sobre anestesia regional em pacientes com COVID-19 e oferecer recomendações práticas para sua realização segura e eficiente.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".