New‐onset atrial fibrillation in critically ill adult patients—an <scp>SSAI</scp> clinical practice guideline
Bibliographic record
Abstract
BACKGROUND: Acute or new-onset atrial fibrillation (NOAF) is the most common cardiac arrhythmia in critically ill adult patients, and observational data suggests that NOAF is associated to adverse outcomes. METHODS: We prepared this guideline according to the Grading of Recommendations Assessment, Development and Evaluation methodology. We posed the following clinical questions: (1) what is the better first-line pharmacological agent for the treatment of NOAF in critically ill adult patients?, (2) should we use direct current (DC) cardioversion in critically ill adult patients with NOAF and hemodynamic instability caused by atrial fibrillation?, (3) should we use anticoagulant therapy in critically ill adult patients with NOAF?, and (4) should critically ill adult patients with NOAF receive follow-up after discharge from hospital? We assessed patient-important outcomes, including mortality, thromboembolic events, and adverse events. Patients and relatives were part of the guideline panel. RESULTS: The quantity and quality of evidence on the management of NOAF in critically ill adults was very limited, and we did not identify any relevant direct or indirect evidence from randomized clinical trials for the prespecified PICO questions. We were able to propose one weak recommendation against routine use of therapeutic dose anticoagulant therapy, and one best practice statement for routine follow-up by a cardiologist after hospital discharge. We were not able to propose any recommendations on the better first-line pharmacological agent or whether to use DC cardioversion in critically ill patients with hemodynamic instability induced by NOAF. An electronic version of this guideline in layered and interactive format is available in MAGIC: https://app.magicapp.org/#/guideline/7197. CONCLUSIONS: The body of evidence on the management of NOAF in critically ill adults is very limited and not informed by direct evidence from randomized clinical trials. Practice variation appears considerable.
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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 | 0.002 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".