Epicardial vasospasm and concomitant ventricular tachycardia treated with Beta-1-specific Beta-blockade: a case series in support of nebivolol
Bibliographic record
Abstract
Background: Patients who experience ventricular tachycardia and cardiac arrest induced by epicardial vasospasm are at high risk for recurrent cardiac events. Conventional treatment includes calcium channel-blockade, long-acting nitrates, and the withdrawal of beta-blockade. These guidelines have not been proven effective in randomized controlled trials, and the evidence against beta-blockade is primarily anecdotal. Ongoing medical management in the setting of treatment failure is unclear, but abnormal sympathetic activity has been implicated in both spasm and ventricular arrhythmias. Case presentation: We describe three patients with spasm-related ventricular arrhythmias and unacceptably poor response to conventional treatment. Clinical stability and asymptomatic status were achieved following the addition of nebivolol, a third-generation, lipophilic beta-1-specific beta-blocker. Discussion: Selective beta-blockade may represent a therapeutic option in patients with high-risk epicardial spasm and ventricular arrhythmias. Furthermore, the apparent success of nebivolol in this setting suggests that hyperactive sympathetic input may represent a causal or aggravating factor in spasm-associated ventricular arrhythmias.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".