Prone Cardiopulmonary Resuscitation: A Rapid Scoping and Expanded Grey Literature Review for the covid-19 Pandemic
Bibliographic record
Abstract
Prone Cardiopulmonary Resuscitation A Rapid Scoping and Expanded Grey Literature Review for the COVID-19 Pandemic Aim To rapidly identify and summarize the available science on prone resuscitation. To determine the value of undertaking a systematic review on this topic; and to identify knowledge gaps to aid future research, education and guidelines. Methods This review was guided by specific methodological framework and reporting items (PRISMA-ScR). We included studies, cases and grey literature regarding prone position and CPR/cardiac arrest. The databases searched were MEDLINE, Embase, CINAHL, Cochrane CENTRAL, Cochrane Database of Systematic Reviews, Scopus and Google Scholar. Expanded grey literature searching included internet search engine, targeted websites and social media. Results Of 453 identified studies, 24 (5%) studies met our inclusion criteria. There were four prone resuscitation-relevant studies examining: blood and tidal volumes generated by prone compressions; prone compression quality metrics on a manikin; and chest computed tomography scans for compression landmarking. Twenty case reports/series described the resuscitation of 25 prone patients. Prone compression quality was assessed by invasive blood pressure monitoring, exhaled carbon dioxide and pulse palpation. Recommended compression location was zero-to-two vertebral segments below the scapulae. Twenty of 25 cases (80%) survived prone resuscitation, although few cases reported long term outcome. Seven cases described full neurological recovery. Conclusion This scoping review did not identify sufficient evidence to justify a systematic review or modified resuscitation guidelines. It remains reasonable to initiate resuscitation in the prone position if turning the patient supine would lead to delays or risk to providers or patients. Prone resuscitation quality can be judged using end-tidal CO2, and arterial pressure tracing, with patients turned supine if insufficient.
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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 | 0.072 | 0.181 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.041 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".