Effectiveness of a simple medication adjustment protocol for optimizing peri-cardioversion rate control: A derivation and validation cohort study
Bibliographic record
Abstract
BackgroundRate control medications are foundational in the management of persistent atrial fibrillation (AF). There are no guidelines for adjusting these medications prior to elective direct-current cardioversion (DCCV).ObjectiveTo derive and validate a preprocedural medication adjustment protocol that maintains peri-DCCV rate control and minimizes risk of postconversion bradycardia, pauses, need for pacing, and cardiopulmonary resuscitation (CPR).MethodsConsecutive patients with persistent AF awaiting elective DCCV across 2 hospitals were screened for inclusion into derivation, validation, and control cohorts. In the derivation cohort, each patient taking an atrioventricular (AV) nodal blocker had medications adjusted based on heart rate (HR) 2 days before DCCV, and the magnitude of dose adjustment was compared with peri-DCCV HR. The adjustment protocol that achieved the highest percentage of optimal peri-DCCV rate control was tested prospectively in the validation cohort and compared to a standard-of-care control group.ResultsThe optimal protocol from the derivation cohort (n = 71), based on the 2-day pre-DCCV HR, was to (1) CONTINUE AV nodal blocker for HR ≥ 100 beats per minute (bpm), (2) reduce dose by ONE increment when 80–99 bpm, (3) reduce dose by TWO increments when 60–79 bpm, and (4) HOLD when <60 bpm. In the prospective validation cohort (n = 106), this protocol improved peri-DCCV rate control (82% vs 62%, P < .001) compared to current standard of care (n = 107). There were no conversion pauses ≥5 seconds, need for pacing, or CPR post-DCCV.ConclusionThis simple preprocedural medication adjustment protocol provides an effective strategy of optimizing peri-DCCV rate control in patients with AF. Rate control medications are foundational in the management of persistent atrial fibrillation (AF). There are no guidelines for adjusting these medications prior to elective direct-current cardioversion (DCCV). To derive and validate a preprocedural medication adjustment protocol that maintains peri-DCCV rate control and minimizes risk of postconversion bradycardia, pauses, need for pacing, and cardiopulmonary resuscitation (CPR). Consecutive patients with persistent AF awaiting elective DCCV across 2 hospitals were screened for inclusion into derivation, validation, and control cohorts. In the derivation cohort, each patient taking an atrioventricular (AV) nodal blocker had medications adjusted based on heart rate (HR) 2 days before DCCV, and the magnitude of dose adjustment was compared with peri-DCCV HR. The adjustment protocol that achieved the highest percentage of optimal peri-DCCV rate control was tested prospectively in the validation cohort and compared to a standard-of-care control group. The optimal protocol from the derivation cohort (n = 71), based on the 2-day pre-DCCV HR, was to (1) CONTINUE AV nodal blocker for HR ≥ 100 beats per minute (bpm), (2) reduce dose by ONE increment when 80–99 bpm, (3) reduce dose by TWO increments when 60–79 bpm, and (4) HOLD when <60 bpm. In the prospective validation cohort (n = 106), this protocol improved peri-DCCV rate control (82% vs 62%, P < .001) compared to current standard of care (n = 107). There were no conversion pauses ≥5 seconds, need for pacing, or CPR post-DCCV. This simple preprocedural medication adjustment protocol provides an effective strategy of optimizing peri-DCCV rate control in patients with AF.
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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 | 0.001 | 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".