A Fatal Case of Massive Verapamil Overdose: An Overview of the Treatment Options
Bibliographic record
Abstract
Calcium channel blocker overdose is usually very fatal and challenging to manage. The patients are usually asymptomatic on admission, but deteriorate very rapidly. Currently, there is no specific antidote, and the treatment is supportive requiring high level of critical care, and may necessitate extracorporeal membrane oxygenation. The use of high-dose insulin is reported to help stabilize the blood pressure and wean off inotropes. The recommendations for supportive treatment in patients with calcium channel blocker overdose are based upon low-quality evidence reports including case series and animal studies. We present the case of a 55-year-old male with a history of atrial fibrillation who was admitted to the hospital 30 min after intentionally ingesting 80 tablets of 180 mg extended release verapamil. On admission, the patient was asymptomatic, but electrocardiogram (ECG) showed a complete heart block which necessitated a transcutaneous pacing, followed by transvenous pacemaker placement. Rapid deterioration of the patient's hemodynamic status led to the patient getting intubated and was started on pressors as well as high-dose insulin. Despite all the aggressive measures, the patient died in less than 24 h after being admitted. We report this case to provide a brief review of the treatment options available at this time, because to date, there is no specific antidote for such overdose, and it remains very fatal despite the amount of supportive care provided.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".