Evaluation of 10 QT prediction formulas in 881 middle-aged men from the seven countries study: Emphasis on the cubic root Fridericia's equation

Puddu, Paolo Emilio; Jouve, R; Mariotti, S; Giampaoli, Simona; Lanti, Mariapaola; Reale, A; Menotti, Alessandro

doi:10.1016/0022-0736(88)90096-9

Cited by 134 publications

(72 citation statements)

References 29 publications

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“…The validity of applying this data in a variety of dissimilar clinical situations can be questioned. This may contribute to the lack of agreement as to which of the many correction formulas is to be employed [3, 4, 5, 6, 7, 8]. A consensus seems to be developing that individualized QT correction may be the best method [1].…”

Section: Discussionmentioning

confidence: 99%

“…There are many correction formulas, all are derived from regression analyses of QT vs. RR plots [3, 4, 5, 6, 7, 8]. The QT and RR data upon which these formulas are based have been obtained from measurements of single beats from 12-lead EKGs during daytime hours at rest.…”

Section: Discussionmentioning

confidence: 99%

“…To correct for rate, a rate-normalized or corrected QT (QTc) interval is often used. While many correction formulas have been developed, there is no agreement as to the optimum method of QT correction [3,4,5,6,7,8]. However, most drugs that have caused torsades de pointes ventricular tachycardia clearly increase both the absolute QT and the QTc intervals [1].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of a 12-Lead Digital Holter System for 24-Hour QT Interval Assessment

et al. 2006

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Background: Drug induced QT prolongation may precipitate life threatening cardiac arrhythmias. Evaluation of the QT prolonging effect of new pharmaceutical agents in a ‘thorough QT/QTc study’ is being mandated by FDA. The purpose of this study was to evaluate an automated 12-lead digital Holter system for a thorough QT/QTc study. Methods: Five healthy volunteers underwent 24-hour digital Holter monitoring. Each recording underwent a fully automated QT analysis (AQA) followed by an onscreen complete manual over read (MOR). Each recording was analyzed twice at least 2 weeks apart. The effect of data sampling (5-min segment/hour), the system sensitivity to detect 5-ms increase in QT, and the ability to assess circadian variation were evaluated. Results: The AQA resulted in identical QT for the first and second analyses, but with obvious errors in QT measurements. Compared to the complete onscreen MOR, the mean QT was longer with AQA (416 ± 41 vs. 387 ± 30 ms, p < 0.001), correlation; r = 0.3. The reproducibility of AQA with complete MOR was very good (QT: 387 ± 30 vs. 387 ± 30 ms, coefficient of variation: 0.2%, r = 0.986. The 5-min mean QT intervals correlated well with the hourly mean QT intervals (r = 0.994, p < 0.001, coefficient of variation = 1 ms) and both showed a similar circadian variation. The system was sensitive to detect a 5-ms change in QT intervals (5 ± 2 ms, coefficient of variation = 0.6%, r = 0.998, p < 0.001). Conclusions: The AQA is not an acceptable method, while the automatic analysis with complete MOR is a highly sensitive and reproducible method. Data sampling by analyzing 5-min segments per hour is sensitive and reproducible.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of a 12-Lead Digital Holter System for 24-Hour QT Interval Assessment

et al. 2006

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“…cient to characterize a person's long-term QT interval length, and heart rate adjustment according to Bazett21 may be inadequate for both low and high heart rates. 28 All mentioned that potential sources of error would have led to nondifferential misclassification, resulting in dilution of the existing association between QT, prolongation and mortality. The association between QT, prolongation and cardiovascular mortality may be explained in several ways.…”

Section: Data Collectionmentioning

confidence: 99%

QT interval prolongation predicts cardiovascular mortality in an apparently healthy population.

Schouten¹,

Dekker²,

Meppelink³

et al. 1991

Circulation

568

361

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“…QT intervals were measured in lead II (ms) by Cardionics s software and corrected for heart rate by use of the Fridericia formula (QTc). 26 Subjects with an ECG recording at D0 and D3…”

Section: Study Populationmentioning

confidence: 99%

Association of KCNQ1, KCNE1, KCNH2 and SCN5A polymorphisms with QTc interval length in a healthy population

et al. 2005

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The QT interval (QT) reflects cardiac ventricular repolarization and varies according to various known factors such as heart rate, gender and age. Nevertheless, a high intrasubject stability of the QT-RR pattern also suggests that a genetic component contributes to individual QT length. To determine whether single nucleotide polymorphisms (SNPs) in genes encoding cardiac ion channels were associated with the heartrate corrected QT (QTc) length, we analyzed two groups of 200 subjects presenting the shortest and the longest QTc from a cohort of 2008 healthy subjects. A total of 17 polymorphisms were genotyped; they were all in the Hardy -Weinberg equilibrium in both groups. Neither allele nor haplotype frequencies of the 10 KCNQ1 SNPs showed a significant difference between the two groups. In contrast, KCNH2 2690 C (K897T) and SCN5A 5457 T (D1819D) minor alleles were significantly more frequent in the group with the shortest QTc interval, whereas KCNE1 253 A (D85N), SCN5A 1673 G (H558R) and 1141-3 A minor alleles were significantly more frequent in the group with the longest QTc interval. Interestingly, an interaction was also found between the KCNH2 2690 A4C SNP and the KCNQ1 2031 þ 932 A4G SNP suggesting that the effect of the KCNH2 2690 C allele on QTc length may occur within a particular genetic background. This suggests that genetic determinants located in KCNQ1, KCNE1, KCNH2 and SCN5A influence QTc length in healthy individuals and may represent risk factors for arrhythmias or cardiac sudden death in patients with cardiovascular diseases.

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Evaluation of 10 QT prediction formulas in 881 middle-aged men from the seven countries study: Emphasis on the cubic root Fridericia's equation

Cited by 134 publications

References 29 publications

Evaluation of a 12-Lead Digital Holter System for 24-Hour QT Interval Assessment

Evaluation of a 12-Lead Digital Holter System for 24-Hour QT Interval Assessment

QT interval prolongation predicts cardiovascular mortality in an apparently healthy population.

Association of KCNQ1, KCNE1, KCNH2 and SCN5A polymorphisms with QTc interval length in a healthy population

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