Decreasing Pain and Anxiety Associated with Patient‐Activated Atrial Shock: A Placebo‐Controlled Study of Adjunctive Sedation with Oral Triazolam
Bibliographic record
Abstract
INTRODUCTION: Implantable atrial defibrillators (IADs) have proved to be safe and effective in the management of atrial fibrillation. A potential limitation of self-activated IAD therapy is patient-reported pain and anxiety. The main objective of the present study was to determine whether triazolam improved patient perception of the shock experience or altered patient memory of shock discomfort relative to placebo. METHODS AND RESULTS: A total of 15 men and women (mean age: 59 +/- 6 years) were enrolled in this double-blind, placebo-controlled, crossover study of triazolam. Randomized study medication was administered orally 75 minutes prior to scheduled atrial shock delivery. Patient perception of the shock experience was assessed along with sedation, memory, anxiety, and mood. Triazolam reduced mean pre-shock anxiety (t= 2.98, df = 14, P = 0.01) and shock-related pain (t= 2.74, df = 13, P = 0.01) and intensity (t= 2.64, df = 13, P = 0.018) relative to placebo. Similarly, participants recalled less discomfort the morning after shock with triazolam than with placebo (t= 2.82, df = 11, P = 0.017). CONCLUSIONS: This study was the first to investigate the use of an oral benzodiazepine administered prior to patient-activated shock delivery with an IAD. Our data indicate that oral triazolam is beneficial in decreasing pain and anxiety associated with self-activated atrial defibrillation. If triazolam provides a similar benefit in the community to that which has been reported here, this medication could be offered to patients as an adjunct to intermittent IAD therapy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".