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Record W2015068426 · doi:10.1097/tp.0b013e3181d2fed7

Case Report: Drug Interaction Between Tacrolimus and Amiodarone With QT Prolongation

2010· letter· en· W2015068426 on OpenAlexaff
Cathy Burger, Catherine M. Clase, Azim S. Gangji

Bibliographic record

VenueTransplantation · 2010
Typeletter
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsTacrolimusMedicineAmiodaroneCoronary artery diseaseSinus rhythmInternal medicineDrug interactionAtrial fibrillationPharmacologyAnesthesiaCardiologyTransplantationPharmacokinetics

Abstract

fetched live from OpenAlex

Both amiodarone (Cordarone; Wyeth, Philadelphia, PA) and tacrolimus (Prograf; Astellas, Markham, ON) are metabolized through the cytochrome (CYP) P450 3A metabolic pathway (1, 2). Amiodarone is known to be a potent inhibitor of CYP 3A4 and can increase serum concentrations of drugs that are substrates of this enzyme system (such as tacrolimus). Previous case reports recommend diligent serum tacrolimus concentration monitoring and prospective tacrolimus dose reductions when the two drugs are given in combination (3, 4). This case report provides further evidence to support the drug interaction between tacrolimus and amiodarone as well as evidence of QT prolongation seen in a renal transplant recipient on this drug combination. CASE REPORT A 65-year-old man underwent a living, nonrelated, renal transplant. His medical history was significant for end-stage renal disease secondary to diabetes, sleep apnea, obesity, and bilateral knee arthroscopy. In addition, he had known coronary artery disease and had undergone coronary artery bypass grafting 5 years before transplant. He had been started on amiodarone postoperatively for presumed atrial fibrillation and maintained on 200 mg daily, since then. Preoperatively, he was in sinus rhythm, and a stress test and echocardiogram were normal. QTc was 440 ms (2 days preoperatively). Posttransplant, he began taking tacrolimus 3 mg orally two times per day for immunosuppression in combination with corticosteroids and mycophenolate mofetil 1000 mg orally two times per day. His initial tacrolimus dose had been empirically reduced by approximately 50% because of an anticipated drug interaction with amiodarone. He was also receiving sulfamethoxazole/trimethoprim, metoprolol, nifedipine, simvastatin, insulin, lansoprazole, betahistine, calcium carbonate, and alfacalcidol. The doses of nifedipine and simvastatin, both of which can interact with tacrolimus, were unchanged during the transplant period. His serum tacrolimus levels are presented in Figure 1.FIGURE 1.: Serum tacrolimus concentrations and QTc.On postoperative day 1, his electrocardiogram revealed normal sinus rhythm, with no evidence of ischemia; however, his QTc was prolonged and equal to 535 ms. His troponins were negative. His magnesium, potassium, calcium, and liver enzymes levels were within the normal range. He was empirically treated with magnesium intravenously, and as the QTc was not improving, the amiodarone was discontinued on postoperative day 2. After withdrawal of the amiodarone, his QTc slowly fell over the next few days to 493 ms on postoperative day 5, when he was discharged with good kidney function (Fig. 1). His tacrolimus serum concentrations were maintained in the 12.3 to 14.9 ng/mL range and he was discharged on a dose of 1.5 mg two times per day orally (∼25% of the usual recommended starting dose). DISCUSSION Both amiodarone and tacrolimus have been implicated in prolonging the QT interval (5–8). Our patient's borderline prolongation of QTc preoperatively might be attributable to long-term amiodarone use. Both amiodarone and tacrolimus are substrates at CYP 3A for enzyme metabolism and could potentially be implicated in increasing the concentration of the other agent through competition for metabolism sites. Some studies suggest that the risk of QT prolongation and torsades de pointes with tacrolimus is concentration dependent (5) whereas others do not (6). Tacrolimus-induced QT prolongation is believed to be due to inhibition of the delayed rectifier K+ current (IK), inward rectifier K+ current (IKI), L-type Ca2+ current (ICaL), and prolongation of the action potential duration although other pharmacological mechanisms have been postulated (5, 6). QT prolongation is common with amiodarone but with a low incidence of proarrhythmic events (<1%) (9). Torsades de pointes may be provoked in patients on amiodarone, usually in conjunction with electrolyte imbalances, increased amiodarone doses, or in combination with other drugs that prolong the QT interval (9). The amiodarone-induced inhibition of tacrolimus metabolism resulted in markedly lower doses of tacrolimus than would usually be expected to achieve desired therapeutic serum concentrations. In our patient, despite adjustment and reduction in tacrolimus dose, the patient still had an elevated tacrolimus level. Even more concerning was that the amiodarone-tacrolimus interaction led to a sudden and marked prolongation of the QT interval when tacrolimus was commenced and improved when the amiodarone was discontinued. This is a significant interaction because a large percentage of patients with end-stage renal disease have left ventricular hypertrophy (10) and subsequently are at higher risk of atrial fibrillation especially in the posttransplant operative period. Amiodarone is a commonly used agent for atrial fibrillation and given the importance of the amiodarone-tacrolimus interaction, we suggest that patients who are on, or require, amiodarone while on tacrolimus be closely monitored through serial electrocardiograms or on telemetry. Otherwise, consideration should be given to use an alternative agent. Cathy I. Burger1 Catherine M. Clase2 Azim S. Gangji2 1Department of Pharmacy St. Joseph's Healthcare Hamilton, ON 2Department of Medicine McMaster University Department of Nephrology and Transplant St. Joseph's Healthcare Hamilton, ON

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.256
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2010
Admission routes1
Has abstractyes

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