title: Derivation and validation of a simple exercise-based algorithm for prediction of genetic testing in relatives of LQTS probands.
abstract: BACKGROUND
  Genetic testing can diagnose long-QT syndrome (LQTS) in asymptomatic relatives of patients with an identified mutation; however, it is costly and subject to availability. The accuracy of a simple algorithm that incorporates resting and exercise ECG parameters for screening LQTS in asymptomatic relatives was evaluated, with genetic testing as the gold standard.
  
  
  RESULTS
  Asymptomatic first-degree relatives of genetically characterized probands were recruited from 5 centers. QT intervals were measured at rest, during exercise, and during recovery. Receiver operating characteristics were used to establish optimal cutoffs. An algorithm for identifying LQTS carriers was developed in a derivation cohort and validated in an independent cohort. The derivation cohort consisted of 69 relatives (28 with LQT1, 20 with LQT2, and 21 noncarriers). Mean age was 35±18 years, and resting corrected QT interval (QTc) was 466±39 ms. Abnormal resting QTc (females ≥480 ms; males ≥470 ms) was 100% specific for gene carrier status, but was observed in only 48% of patients; however, mutations were observed in 68% and 42% of patients with a borderline or normal resting QTc, respectively. Among these patients, 4-minute recovery QTc ≥445 ms correctly restratified 22 of 25 patients as having LQTS and 19 of 21 patients as being noncarriers. The combination of resting and 4-minute recovery QTc in a screening algorithm yielded a sensitivity of 0.94 and specificity of 0.90 for detecting LQTS carriers. When applied to the validation cohort (n=152; 58 with LQT1, 61 with LQT2, and 33 noncarriers; QTc=443±47 ms), sensitivity was 0.92 and specificity was 0.82.
  
  
  CONCLUSIONS
  A simple algorithm that incorporates resting and exercise-recovery QTc is useful in identifying LQTS in asymptomatic relatives.
authors: University of Western Ontario, London, Canada.
authors: Raymond W
authors: RW
authors: Sy
authors: Christian
authors: C
authors: van der Werf
authors: Ishvinder S
authors: IS
authors: Chattha
authors: Priya
authors: P
authors: Chockalingam
authors: Arnon
authors: A
authors: Adler
authors: Jeffrey S
authors: JS
authors: Healey
authors: Mark
authors: M
authors: Perrin
authors: Michael H
authors: MH
authors: Gollob
authors: Allan C
authors: AC
authors: Skanes
authors: Raymond
authors: R
authors: Yee
authors: Lorne J
authors: LJ
authors: Gula
authors: Peter
authors: P
authors: Leong-Sit
authors: Sami
authors: S
authors: Viskin
authors: George J
authors: GJ
authors: Klein
authors: Arthur A
authors: AA
authors: Wilde
authors: Andrew D
authors: AD
authors: Krahn
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D002648:Child; D015331:Cohort Studies; D015444:Exercise / Q000502:physiology*; D005080:Exercise Test / Q000379:methods / Q000592:standards*; D005260:Female; D005820:Genetic Testing / Q000379:methods / Q000592:standards*; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008133:Long QT Syndrome / Q000175:diagnosis / Q000235:genetics* / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D055815:Young Adult