2024 RECOVER Guidelines: Basic Life Support. Evidence and knowledge gap analysis with treatment recommendations for small animal CPR
Bibliographic record
Abstract
OBJECTIVE: To systematically review evidence and devise treatment recommendations for basic life support (BLS) in dogs and cats and to identify critical knowledge gaps. DESIGN: Standardized, systematic evaluation of literature pertinent to BLS following Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. Prioritized questions were each reviewed by 2 Evidence Evaluators, and findings were reconciled by BLS Domain Chairs and Reassessment Campaign on Veterinary Resuscitation (RECOVER) Co-Chairs to arrive at treatment recommendations commensurate to quality of evidence, risk to benefit relationship, and clinical feasibility. This process was implemented using an Evidence Profile Worksheet for each question that included an introduction, consensus on science, treatment recommendations, justification for these recommendations, and important knowledge gaps. A draft of these worksheets was distributed to veterinary professionals for comment for 4 weeks prior to finalization. SETTING: Transdisciplinary, international collaboration in university, specialty, and emergency practice. RESULTS: Twenty questions regarding animal position, chest compression point and technique, ventilation strategies, as well as the duration of CPR cycles and chest compression pauses were examined, and 32 treatment recommendations were formulated. Out of these, 25 addressed chest compressions and 7 informed ventilation during CPR. The recommendations were founded predominantly on very low quality of evidence and expert opinion. These new treatment recommendations continue to emphasize the critical importance of high-quality, uninterrupted chest compressions, with a modification suggested for the chest compression technique in wide-chested dogs. When intubation is not possible, bag-mask ventilation using a tight-fitting facemask with oxygen supplementation is recommended rather than mouth-to-nose ventilation. CONCLUSIONS: These updated RECOVER BLS treatment recommendations emphasize continuous chest compressions, conformation-specific chest compression techniques, and ventilation for all animals. Very low quality of evidence due to absence of clinical data in dogs and cats consistently compromised the certainty of recommendations, emphasizing the need for more veterinary research in this area.
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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 | 0.067 | 0.222 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.017 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.015 |
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".