Abstract 302: Chest Compressions Should Be Performed on Arresting Patients with Left Ventricular Assist Devices (LVAD)
Bibliographic record
Abstract
Introduction: Patients with implanted Left ventricular assist devices (LVAD) are being assessed by an increasing number of health care providers. Despite a lack of evidence, many emergency medical systems and hospitals have discouraged providers from performing chest compressions in these patients when they present in cardiac arrest. This deviation from conventional resuscitation algorithms is secondary to concern that chest compressions could dislodge the LVAD. Objective: To determine the rate of cannula dislodgment for patients presenting in cardiac arrest with known implanted LVAD devices receiving standard chest compression cardiopulmonary resuscitation. Methods: We retrospectively analyzed the outcomes of all patients who received chest compressions for cardiac arrest over a 4 year period in a large urban hospital. Eight cases were reviewed for both cannula integrity and outcomes. Results: Using autopsy and adequate flow through device as proxy for intact inflow/outflow cannulas, none of the eight patients receiving chest compressions had cannula dislodgment. Four of the 8 patients had return of neurologic function. Two additional patients had return of effective circulation without return of neurologic function. One patient had documented flow on the device without return of native heart function. The final patient did not have documented flow during resuscitation but autopsy showed no dislodgment. Conclusions: In this small retrospective study, standard chest compressions in patients with LVADs appear to be safe, without evidence of cannula dislodgment. Standard chest compressions for LVAD patients in circulatory arrest should be performed.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".