Practical application of pressure-volume loop analysis in a swine model of medical cardiac arrest
Bibliographic record
Abstract
Abstract Introduction Cardiac arrest (CA) is the sudden cessation of cardiac activity, leading to haemodynamic collapse and high mortality. Advanced life support (ALS) standardises resuscitation, but the post-return of spontaneous circulation (ROSC) period remains turbulent and poorly understood. Up to 50% of patients who achieve ROSC struggle to maintain spontaneous circulation, leading to re-arrest, typically within minutes. Post-cardiac arrest syndrome (PCAS), involving brain injury and ischaemia-reperfusion injury, plays a key role in re-arrest. Pressure-volume loop (PVL) analysis offers insight into load-independent cardiac biomechanics in the post-ROSC period. The aim of this study is to explore the feasibility of PVL analysis in a swine model of CA. Methods This swine study utilised a ventricular fibrillation (VF) cardiac arrest model in combination with PVL analysis. The experiment included four phases: animal preparation, VF induction, resuscitation, and post-ROSC care. Yorkshire swine (45-70 kg) were sedated, anaesthetised, and VF was induced via an endocavitary electrode attached to a battery. After that, the animals were divided into 3-minute and 6-minute arrest groups before commencing ALS. Standard ALS protocols were followed, including CPR, defibrillation, and drug administration. If ROSC was obtained, animals underwent a 3-hour critical care period. Cardiac indices were compared between baseline and end-of-study values. Results Eight adult Yorkshire swine were enrolled in the study, with a mean weight of 50.2 ± 2.9 kg. VF induction was successfully achieved, and PVL data were collected in all animals except one, establishing a successful porcine VF CA model. In the resuscitation phase, all animals in the 3-minute group achieved ROSC, as opposed to one in the 6-minute group. Post-ROSC metabolic changes included acidaemia, elevated lactate and potassium, partially resolving by study end. Right ventricle PVL data were unreliable, while left ventricle PVL was reliable in 3 of 5 ROSC animals. Preload-recruitable stroke work (PRSW) data were found to be more reliable than the End-Diastolic Pressure-Volume Relationship (ESPVR), with a significant increase in LV PRSW of 34 ± 12% observed post-ROSC in all surviving animals (p<0.001). Discussion This study demonstrates the feasibility of applying PVL analysis to a post-ROSC swine model of cardiac arrest (CA). As expected, warm ischaemic time predicted ROSC, but PVL analysis offered valuable insights into load-independent parameters. While data quality issues hindered ESPVR analysis, PRSW was successfully evaluated, revealing a significant increase post-ROSC, highlighting its potential to guide the development of future therapeutic targets for post-ROSC interventions. The small sample size and technical challenges limited the scope of conclusions, emphasising the need for larger studies.Kaplan-Meier Curve and cycles to ROSC (A) LV PVL, (B) PRSW Pre and Post-ROSC
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".