Recomendações para realização de anestesia loco‐regional durante a pandemia de COVID‐19
Bibliographic record
Abstract
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 dessa 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. 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 postoperative period and provides safety to pati ents 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.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".