Sonography in Hypotension and Cardiac Arrest (SHoC): Rates of Abnormal Findings in Undifferentiated Hypotension and During Cardiac Arrest as a Basis for Consensus on a Hierarchical Point of Care Ultrasound Protocol
Bibliographic record
Abstract
INTRODUCTION: Point of care ultrasound (PoCUS) has become an established tool in the initial management of patients with undifferentiated hypotension. Current established protocols (RUSH and ACES) were developed by expert user opinion, rather than objective, prospective data. PoCUS also provides invaluable information during resuscitation efforts in cardiac arrest by determining presence/absence of cardiac activity and identifying reversible causes such as pericardial tamponade. There is no agreed guideline on how to safely and effectively incorporate PoCUS into the advanced cardiac life support (ACLS) algorithm. We wished to report disease incidence as a basis to develop a hierarchical approach to PoCUS in hypotension and during cardiac arrest. METHODS: We summarized the recorded incidence of PoCUS findings from the initial cohort during the interim analysis of two prospective studies. We propose that this will form the basis for developing a modified Delphi approach incorporating this data to obtain the input of a panel of international experts associated with five professional organizations led by the International Federation of Emergency Medicine (IFEM). The modified Delphi tool will be developed to reach an international consensus on how to integrate PoCUS for hypotensive emergency department patients as well as into cardiac arrest algorithms. RESULTS: Rates of abnormal PoCUS findings from 151 patients with undifferentiated hypotension included left ventricular dynamic changes (43%), IVC abnormalities (27%), pericardial effusion (16%), and pleural fluid (8%). Abdominal pathology was rare (fluid 5%, AAA 2%). During cardiac arrest there were no pericardial effusions, however abnormalities of ventricular contraction (45%) and valvular motion (39%) were common among the 43 patients included. CONCLUSIONS: A prospectively collected disease incidence-based hierarchy of scanning can be developed based on the reported findings. This will inform an international consensus process towards the development of proposed SHoC protocols for hypotension and cardiac arrest, comprised of the stepwise clinical-indication based approach of Core, Supplementary, and Additional PoCUS views. We hope that such a protocol would be structured in a way that enables the clinician to only perform views that are clinically indicated, which limits exposure to the frequent incidental positive findings that accompany the current "one size fits all" standard protocols.
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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 | 0.076 | 0.119 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.005 |
| 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 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".