Literature DB >> 8946461

If Dr. Bazett had had a computer....

M Malik1.   

Abstract

The original data of 109 pairs of RR and QT intervals published by Dr. Bazett in 1920 were subjected to a computerized optimization of the QT/RR relationship. Four generic formulae expressing QT interval as alpha + beta RR mu, alpha + beta e mu RR, alpha + beta e(1/mu RR), and alpha + beta ln mu(10 x RR) were used, and for each formula, optimum combinations parameters alpha, beta, and mu were established that lead to minimum differences between the actual QT interval intervals and values predicted by the model. The results show that independent of the generic formula used, parameters of the model can be selected that provide a close fit of the measured values. Compared to the optimum models obtained in this way, the optimum fit of the Bazett model, QT = beta RR1/2, overestimates the QT intervals for slow heart rates. In addition to demonstrating the procedure of obtaining an optimum QT/RR model for a given data set, the study suggests that critical understanding of the principal limitations of every QT/RR model is more important than its mathematical form.

Entities:  

Mesh:

Year:  1996        PMID: 8946461     DOI: 10.1111/j.1540-8159.1996.tb03191.x

Source DB:  PubMed          Journal:  Pacing Clin Electrophysiol        ISSN: 0147-8389            Impact factor:   1.976


  9 in total

Review 1.  Continuous and less invasive central hemodynamic monitoring by blood pressure waveform analysis.

Authors:  Ramakrishna Mukkamala; Da Xu
Journal:  Am J Physiol Heart Circ Physiol       Date:  2010-07-09       Impact factor: 4.733

2.  QT interval prolongation in end-stage liver disease cannot be explained by nonhepatic factors.

Authors:  Divyang Patel; Prabhpreet Singh; William Katz; Christopher Hughes; Kapil Chopra; Jan Němec
Journal:  Ann Noninvasive Electrocardiol       Date:  2014-04-24       Impact factor: 1.468

3.  Relation between QT and RR intervals is highly individual among healthy subjects: implications for heart rate correction of the QT interval.

Authors:  M Malik; P Färbom; V Batchvarov; K Hnatkova; A J Camm
Journal:  Heart       Date:  2002-03       Impact factor: 5.994

Review 4.  Evaluation of drug-induced QT interval prolongation: implications for drug approval and labelling.

Authors:  M Malik; A J Camm
Journal:  Drug Saf       Date:  2001       Impact factor: 5.606

5.  QT & RR variability spots the earliest autonomic deregulation in diabetes. Fading of vagal sino-atrial drive but not of sympathetic ventricular responsiveness to life challenges.

Authors:  Radu Negoes; Oana Istrătescu; Mihaela Dincă-Panaitescu; Erban Dincă-Panaitescu; Alin Achim
Journal:  Integr Physiol Behav Sci       Date:  2002 Apr-Jun

6.  Tube-load model parameter estimation for monitoring arterial hemodynamics.

Authors:  Guanqun Zhang; Jin-Oh Hahn; Ramakrishna Mukkamala
Journal:  Front Physiol       Date:  2011-11-01       Impact factor: 4.566

Review 7.  Sources of QTc variability: Implications for effective ECG monitoring in clinical practice.

Authors:  Katerina Hnatkova; Marek Malik
Journal:  Ann Noninvasive Electrocardiol       Date:  2019-11-24       Impact factor: 1.468

8.  Problems with Bazett QTc correction in paediatric screening of prolonged QTc interval.

Authors:  Irena Andršová; Katerina Hnatkova; Kateřina Helánová; Martina Šišáková; Tomáš Novotný; Petr Kala; Marek Malik
Journal:  BMC Pediatr       Date:  2020-12-14       Impact factor: 2.125

9.  A Simple Adaptive Transfer Function for Deriving the Central Blood Pressure Waveform from a Radial Blood Pressure Waveform.

Authors:  Mingwu Gao; William C Rose; Barry Fetics; David A Kass; Chen-Huan Chen; Ramakrishna Mukkamala
Journal:  Sci Rep       Date:  2016-09-14       Impact factor: 4.379

  9 in total

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