Amiodarone Treatment of Junctional Ectopic Tachycardia in a Neonate Receiving Extracorporeal Membrane Oxygenation
Bibliographic record
Abstract
OBJECTIVE: To describe the administration of amiodarone and the resulting serum concentrations in a neonate receiving extracorporeal membrane oxygenation (ECMO). CASE SUMMARY: A 3463 g, 38 week gestational age male diagnosed with tetralogy of Fallot developed junctional ectopic tachycardia (JET) and required ECMO support following cardiac surgery. The patient continued to show JET despite cooling, pacing, and intravenous amiodarone infusion, with the dose initiated at 10 microg/kg/min. Sinus rhythm was achieved following 5 days of treatment, additional amiodarone boluses, and an increase in the infusion rate to 20 microg/kg/min. Two serum concentrations of amiodarone were obtained during therapy. On day 4, the concentration was 0.9 mg/L at the 20 microg/kg/min infusion rate; a bolus dose of 5 mg/kg was administered 1 hour later. The serum concentration the following day, with the infusion rate unchanged, was 2 mg/L. DISCUSSION: ECMO is used increasingly postoperatively in patients with congenital cardiac abnormalities. The incidence of JET following repair of tetralogy of Fallot is 22%. Despite the minimal information on the pharmacokinetics of amiodarone in neonates, it has been used in doses up to 20 microg/kg/min for the treatment of postoperative JET. As of August 25, 2006, we found no reports describing its dosage and use in patients undergoing ECMO. CONCLUSIONS: The delivery of amiodarone to a patient receiving ECMO may be complicated by the administration of large blood volumes, circuit changes, and binding to the circuit. Neonates receiving ECMO may require larger amiodarone doses to achieve a therapeutic effect. Further investigation is required to define the pharmacokinetics and pharmacodynamics of amiodarone in neonates receiving ECMO.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".