Cardiopulmonary resuscitation in primary and community care during the COVID-19 pandemic
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), can be spread by droplets or aerosols, particularly through direct or close contact and aerosol generating procedures (AGPs).1 Supplies of personal protective equipment (PPE)2 are limited, raising uncertainties in clinical judgement about the balance between benefit (to the patient) and risk (to the healthcare worker) during medical procedures, such as cardiopulmonary resuscitation (CPR) undertaken without adequate protection during the COVID-19 pandemic. Lack of PPE has caused intense anxiety in view of the increased number of deaths in healthcare workers including in primary and community care.2 CPR can be a complex intervention comprising airway management, ventilation, chest compressions, drug therapy, and defibrillation.3 While the intubation component of CPR is almost universally classified as an AGP, there is controversy around the risk of chest compression (to the person performing it, and to other staff and bystanders).4 Risks to healthcare workers will vary depending on the setting where such individuals work (primary or community care versus hospital-based care); and whether the individual works in an environment where …
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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 | 0.010 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.028 | 0.028 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".