Left Ventricular Performance During Acute Rate Control in Atrial Fibrillation: The Importance of Heart Rate and Agent Used
Bibliographic record
Abstract
BACKGROUND: The relation between heart rate and left ventricular function during rate control in atrial fibrillation is incompletely understood. METHODS: Twenty-four patients (age 67 +/- 11 years) with symptomatic recent onset rapid atrial fibrillation and rapid ventricular rate (> 110 bpm) were randomly assigned to receive either intravenous digoxin (13 mcg/kg) or intravenous diltiazem (0.25 mg/kg bolus plus a maintenance infusion). A portable radionuclide detector was used to collect validated measures of relative left ventricular volumes, along with heart rate data, every 15 seconds for 6 hours. RESULTS: Heart rate decreased significantly at 15 minutes and 180 minutes in the diltiazem group (from 133 +/- 18 bpm to 111 +/- 26 bpm [P <.01] to 94 +/- 24 bpm [P <.001]) but not in the digoxin group (from 129 +/- 18 bpm to 126 +/- 17 bpm [P = NS] to 118 +/- 15 bpm [P = NS]). Left ventricular ejection fraction improved in both groups to a similar extent (from 39 +/- 10% to 50 +/- 8%, [P <.05] after diltiazem, and from 38 +/- 8% to 52 +/- 11% [P <.05] after digoxin at baseline vs 180 minutes, respectively). The ejection fraction vs heart rate slope was steeper in the digoxin group than in the diltiazem group (-0.34 +/- 0.18 vs -0.16 +/- 0.17, P =.048) indicating a more pronounced improvement in ejection fraction per unit decrease in heart rate. CONCLUSION: In patients with acute atrial fibrillation, digoxin led to similar improvements in ejection fraction compared to diltiazem despite a slower and less potent heart rate slowing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".