Peri‐mortem arrhythmias in the non‐cardiac intensive care unit
Bibliographic record
Abstract
BACKGROUND: Cardiovascular failure is recognized as a common final pathway at the end of life but there is a paucity of data describing terminal arrhythmias. AIM: We aimed to describe arrhythmias recorded peri-mortem in critically ill patients. STUDY DESIGN: We enrolled intensive care unit patients admitted to two tertiary Canadian medico-surgical centres. Participants wore a continuous electrocardiogram (ECG) monitor for 14 days, until discharge, removal or death. We recorded all significant occurrences of arrhythmias in the final hour of life. RESULTS: Among 39 patients wearing an ECG monitor at the time of death, 22 (56%) developed at least 1 terminal arrhythmia as adjudicated by an arrhythmia physician: 23% (n = 9) had ventricular fibrillation/polymorphic ventricular tachycardia, 18% (n = 7) had sinoatrial pauses, 15% (n = 6) had atrial fibrillation and 13% (n = 5) had high-degree atrioventricular block. Five participants (13%) developed multiple arrythmias. CONCLUSIONS: Arrhythmias are common in dying critically ill patients. There is a roughly even distribution between ventricular arrhythmias, atrial fibrillation, sinus node dysfunction and atrioventricular block. RELEVANCE TO CLINICAL PRACTICE: The results of this study may be most useful for critically ill patients who are organ donation candidates. The appearance of arrhythmias may serve as a marker of change in clinical status for organ donation teams to plan mobilization efforts. In participants who are sedated or intubated, arrhythmias could be a surrogate marker for respiratory or neurologic changes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".