Clinical Pharmacokinetics

, Volume 53, Issue 5, pp 397–407 | Cite as

The Role of Digitalis Pharmacokinetics in Converting Atrial Fibrillation and Flutter to Regular Sinus Rhythm

  • Roger W. Jelliffe
Current Opinion


This report examined the role of digitalis pharmacokinetics in helping to guide therapy with digitalis glycosides with regard to converting atrial fibrillation (AF) or flutter to regular sinus rhythm (RSR). Pharmacokinetic models of digitoxin and digoxin, containing a peripheral non-serum effect compartment, were used to analyze outcomes in a non-systematic literature review of five clinical studies, using the computed concentrations of digitoxin and digoxin in the effect compartment of these models in an analysis of their outcomes. Four cases treated by the author were similarly examined. Three literature studies showed results no different from placebo. Dosage regimens achieved ≤11 ng/g in the model’s peripheral compartment. However, two other studies achieved significant conversion to RSR. Their peripheral concentrations were 9–14 ng/g. In the four patients treated by the author, three converted using classical clinical titration with incremental doses, plus therapeutic drug monitoring and pharmacokinetic guidance from the models for maintenance dosage. They converted at peripheral concentrations of 9–18 ng/g, similar to the two studies above. No toxicity was seen. Successful maintenance was achieved, using the models and their pharmacokinetic guidance, by giving somewhat larger than average recommended dosage regimens in order to maintain peripheral concentrations present at conversion. The fourth patient did not convert, but only reached peripheral concentrations of 6–7 ng/g, similar to the studies in which conversion was no better than placebo. Pharmacokinetic analysis and guidance play a highly significant role in converting AF to RSR. To the author’s knowledge, this has not been specifically described before. In my experience, conversion of AF or flutter to RSR does not occur until peripheral concentrations of 9–18 ng/g are reached. Results in the four cases correlated well with the literature findings. More work is needed to further evaluate these provocative findings.


Atrial Fibrillation Digoxin Atrial Flutter Digitoxin Ventricular Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Supported by NIH Grants EB005803 and GM068968.

Conflicts of Interest

The author has no conflicts of interest to disclose.


  1. 1.
    Doherty J. Digitalis glycosides—pharmacokinetics and their clinical implications. Ann Int Med. 1973;79:229–38.PubMedCrossRefGoogle Scholar
  2. 2.
    Jelliffe RW, Bechtol LD, Crabtree R. The bioavailability and pharmacokinetic behavior of digitoxin. Technical report 2012-1, Laboratory of Applied Pharmacokinetics, University of Southern California School of Medicine, Los Angeles, CA.Google Scholar
  3. 3.
    Jelliffe R, Milman M, Schumitzky A, Bayard D, Van Guilder M. A two-compartment population pharmacokinetic-pharmacodynamic model of digoxin in adults, with implications for dosage. Ther Drug Monit. [Epub 2014 Jan 31].Google Scholar
  4. 4.
    Reuning R, Sams R, Notari R. Role of pharmacokinetics in drug dosage adjustment. 1. Pharmacologic effects, kinetics, and apparent volume of distribution of digoxin. J Clin Pharmacol. 1973;13:127–41.Google Scholar
  5. 5.
    Falk R, Knowlton A, Bernard S, Gotlieb N, Battinelli N. Digoxin for converting atrial fibrillation to sinus rhythm. A random double-blinded trial. Ann Int Med. 1987;4:503–6.CrossRefGoogle Scholar
  6. 6.
    The Digitalis in Acute Atrial Fibrillation (DAAF) Trial Group. Intravenous digoxin in acute atrial fibrillation. Results of a randomized, placebo-controlled multicentre trial in 239 patients. Eur Heart J. 1997;18:649–54.CrossRefGoogle Scholar
  7. 7.
    Hornestam B, Jerling M, Karlsson M, Help P, for the DAAF Trial Group. Intravenously administered digoxin in patients with acute atrial fibrillation: a population pharmacokinetic/pharmacodynamic analysis based on the Digitalis in Acute Atrial Fibrillation Trial. Eur J Clin Pharmacol. 2003;58:747–55.PubMedGoogle Scholar
  8. 8.
    Jordaens L, Trouerbach J, Calle P, Taviernier E, Derycke E, Vertongen P, Bergez B, Vanderkerckhove Y. Conversion of atrial fibrillation to sinus rhythm and rate control by digoxin in comparison to placebo. Eur Heart J. 1997;18:643–8.PubMedCrossRefGoogle Scholar
  9. 9.
    Weiner P, Bassan M, Jarchovsky J, Iusim S, Plavnick L. Clinical course of acute atrial fibrillation treated with rapid digitalization. Am Heart J. 1983;105:223–7.PubMedCrossRefGoogle Scholar
  10. 10.
    Hou Z-Y, Chang M-S, Chen C-Y, Tu M-S, Lin S-L, Chiang H-T, Woosley R. Acute treatment of recent onset atrial fibrillation and flutter with a tailored dosing regimen of intravenous amiodarone: a randomized, digoxin controlled study. Eur Heart J. 1995;16:521–8.PubMedGoogle Scholar
  11. 11.
    Okita G, Kelsey F, Talso P, Smith L, Geiling E. Studies on the renal excretion of radioactive digitoxin in human subjects with cardiac failure. Circulation. 1953;7:161–8.PubMedCrossRefGoogle Scholar
  12. 12.
    Jelliffe R, Schumitzky A, Bayard D, Milman M, Van Guilder M, Wang X, Jiang F, Barbaut X, Maire P. Model-based, goal-oriented, individualized drug therapy: linkage of population modeling, new “multiple model” dosage design, Bayesian feedback, and individualized target goals. Clin Pharmacokinet. 1998;34:57–77.PubMedCrossRefGoogle Scholar
  13. 13.
    Jelliffe R, Bayard D, Milman M, Van Guilder M, Schumitzky A. Achieving target goals most precisely using nonparametric compartmental models and “multiple model” design of dosage regimens. Ther Drug Monit. 2000;22:346–53.PubMedCrossRefGoogle Scholar
  14. 14.
    Milman M, Jiang F, Jelliffe R. Creating discrete joint densities from continuous ones: the moment-matching, maximum entropy approach. Comput Biol Med. 2001;31:197–214.PubMedCrossRefGoogle Scholar
  15. 15.
    Jelliffe R, Buell J, Kalaba R. Reduction of digitalis toxicity by computer-assisted glycoside dosage regimens. Ann Int Med. 1972;77:891–906.PubMedCrossRefGoogle Scholar
  16. 16.
    Jelliffe R. Factors to consider in planning digoxin therapy. J Chron Dis. 1971;24:407–16.PubMedCrossRefGoogle Scholar
  17. 17.
    Jelliffe R. Estimation of creatinine clearance in patients with unstable renal function, without a urine specimen. Am J Nephrol. 2002;22:320–4.PubMedCrossRefGoogle Scholar
  18. 18.
    Jelliffe R, Schumitzky A, Bayard D, Leary R, Van Guilder M, Goutelle S, et al. The USC Pmetrics and Bestdose software—the software with integrated population modeling, simulation, and maximally precise dosage [software demonstration]. Population Approach Group Europe; 5–8 Jun 2012; Venice.Google Scholar
  19. 19.
    Capucci A, Boriani G, Rubino I, Della Casa S, Sanguinetti M, Magnani B. A controlled study of oral propafenone versus digoxin plus quinidine in converting recent onset atrial fibrillation to sinus rhythm. Int J Cardiol. 1994;43:305–13.PubMedCrossRefGoogle Scholar
  20. 20.
    Cowan J, Gardiner P, Reid D, Newell D, Campbell R. A comparison of amiodarone and digoxin in the treatment of atrial fibrillation complicating suspected acute myocardial infarction. J Cardiovasc Pharmacol. 1986;8:256.CrossRefGoogle Scholar
  21. 21.
    Halinen M, Huttunen M, Paakkinnen S, Tarssanen L. Comparison of sotalol with digoxin–quinidine for conversion of acute atrial fibrillation to sinus rhythm (the Sotalol–Digoxin/Quinidine Trial). Am J Cardiol. 1995;76:495–4998.PubMedCrossRefGoogle Scholar
  22. 22.
    Jelliffe R. Some comments and suggestions concerning population pharmacokinetic modeling, especially of digoxin, and its relation to clinical therapy. Ther Drug Monit. 2012;34:368–77.PubMedCrossRefGoogle Scholar
  23. 23.
    Chamberlain D, White R, Howard M, Smith T. Plasma digoxin concentrations in patients with atrial fibrillation. Br Med J. 1970;3:429–32.PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Chamberlain D. Plasma digoxin concentrations as a guide to therapeutic requirements. In: Davies D, Prichard B, editors. Biological effects of drugs in relation to their plasma concentrations. Baltimore: University Park Press; 1973. p. 135–43.Google Scholar
  25. 25.
    Goldman S, Probst P, Selzer A, Cohn K. Inefficacy of “therapeutic” serum levels of digoxin in controlling the ventricular rate in atrial fibrillation. Am J Cardiol. 1975;35:651–5.PubMedCrossRefGoogle Scholar
  26. 26.
    Lely A, van Enter C. Large scale digitoxin intoxication. Br Med J. 1970;3:737–40.PubMedCentralPubMedCrossRefGoogle Scholar
  27. 27.
    Beller G, Smith T, Abelmann W, Haber E, Hood W. Digitalis intoxication. A prospective clinical study with serum level correlations. N Engl J Med. 1971;284:989–97.PubMedCrossRefGoogle Scholar
  28. 28.
    Jelliffe R, Bayard D, Leary R, Schumitzky A, Van Guilder M, Botnen A, et al. A hybrid Bayesian method to obtain Bayesian posterior parameter distributions in nonparametric pharmacokinetic models for individual patients. Technical Report 2011-1, Laboratory of Applied Pharmacokinetics, University of Southern California School of Medicine.
  29. 29.
    Hoeschen R, Cuddy T. Dose-response relation between therapeutic levels of serum digoxin and systolic time intervals. Am J Cardiol. 1975;35:469–72.PubMedCrossRefGoogle Scholar
  30. 30.
    Jelliffe RW, Schumitzky A, Van Guilder M, Liu M, Hu L, Maire P, Gomis P, Barbaut X, Tahani B. Individualizing drug dosage regimens: roles of population pharmacokinetic and dynamic models, Bayesian fitting, and adaptive control. Ther Drug Monit. 1993;15:380–93.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Laboratory of Applied PharmacokineticsKeck School of Medicine, University of Southern California, Children’s Hospital of Los AngelesLos AngelesUSA

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