title: Temporal variability of atrial fibrillation in pacemaker recipients for bradycardia: implications for crossover designed trials, study sample size, and identification of responder patients by means of arrhythmia burden.
abstract: BACKGROUND
  Most clinical trials that have tested pacing therapies to prevent and treat atrial tachyarrhythmias (AT) have chosen endpoints such as AT frequency or burden (defined as percentage of time a patient is in AT), but failed to show unequivocal evidence of a clinical impact.
  
  
  OBJECTIVE
  The aim of our multicenter prospective observational study was to measure the variability of AT burden and estimate its impact on study outcomes.
  
  
  RESULTS
  Two hundred and fifty patients indicated for permanent pacing and suffering from AT (age 71 +/- 9 years; 47.2% male) received a dual-chamber pacemaker. AT burden was measured in two consecutive, 2-month observation periods; the Monte Carlo method was then applied to simulate findings of a crossover design study. We simulated several models of therapy impact, each model being characterized by the percentage of responder patients and the percentage reduction in AT burden. To show a significant impact of AT therapies in a sample of 250 patients in whom 100, 75, or 50% would be theoretical responders to therapies, AT burden reduction should be at least 27, 32, or 57%, respectively. Temporal fluctuations in AT burden were so high that about 60% of patients would falsely appear as responders or nonresponders in a crossover study, regardless of AT burden reduction.
  
  
  CONCLUSIONS
  In patients paced for bradycardia and suffering from AT, high intrapatient variability in AT burden was measured. Various models of therapy impact showed that, in crossover trials of AT therapies, time-related fluctuations in AT burden negatively impact on sample sizes and impair the ability to identify patients as responders or nonresponders.
authors.affiliation: Cardiology Department, S. Anna Hospital, Como, Italy. gianlucabotto@interfree.it
authors.forename: Giovanni Luca
authors.initials: GL
authors.lastname: Botto
authors.forename: Massimo
authors.initials: M
authors.lastname: Santini
authors.forename: Luigi
authors.initials: L
authors.lastname: Padeletti
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Boriani
authors.forename: Gianni
authors.initials: G
authors.lastname: Luzzi
authors.forename: Francesco
authors.initials: F
authors.lastname: Zolezzi
authors.forename: Serafino
authors.initials: S
authors.lastname: Orazi
authors.forename: Alessandro
authors.initials: A
authors.lastname: Proclemer
authors.forename: Giacomo
authors.initials: G
authors.lastname: Chiarandà
authors.forename: Stefano
authors.initials: S
authors.lastname: Favale
authors.forename: Francesco
authors.initials: F
authors.lastname: Solimene
authors.forename: Mario
authors.initials: M
authors.lastname: Luzi
authors.forename: Marco
authors.initials: M
authors.lastname: Vimercati
authors.forename: Tiziana
authors.initials: T
authors.lastname: DeSanto
authors.forename: Andrea
authors.initials: A
authors.lastname: Grammatico
mesh_terms: D000368:Aged; D001281:Atrial Fibrillation / Q000150:complications*; D001919:Bradycardia / Q000150:complications* / Q000628:therapy*; D002304:Cardiac Pacing, Artificial / Q000706:statistics & numerical data*; D002986:Clinical Trials as Topic / Q000379:methods*; D017281:Cost of Illness; D018592:Cross-Over Studies; D005260:Female; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D011446:Prospective Studies; D012107:Research Design; D018401:Sample Size; D013997:Time Factors