Literature DB >> 22520157

How to reliably deliver narrow individual-patient error bars for optimization of pacemaker AV or VV delay using a "pick-the-highest" strategy with haemodynamic measurements.

Darrel P Francis1.   

Abstract

Intuitive and easily-described, "pick-the-highest" is often recommended for quantitative optimization of AV and especially VV delay settings of biventricular pacemakers (BVP; cardiac resynchronization therapy, CRT). But reliable selection of the optimum setting is challenged by beat-to-beat physiological variation, which "pick-the-highest" combats by averaging multiple heartbeats. Optimization is not optimization unless the optimum is identified confidently. This document shows how to calculate how many heartbeats must be averaged to optimize reliably by pick-the-highest. Any reader, by conducting a few measurements, can calculate for locally-available methods (i) biological scatter between replicate measurements, and (ii) curvature of the biological response. With these, for any clinically-desired precision of optimization, the necessary number of heartbeats can be calculated. To achieve 95% confidence of getting within ±∆x of the true optimum, the number of heartbeats needed is 2(scatter/curvature)(2)/∆x(4) per setting. Applying published scatter/curvature values (which readers should re-evaluate locally) indicates that optimizing AV, even coarsely with a 40ms-wide band of precision, requires many thousand beats. For VV delay, the number approaches a million. Moreover, identifying the optimum twice as precisely requires 30-fold more beats. "Pick the highest" is quick to say but slow to do. We must not expect staff to do the impossible; nor criticise them for not doing so. Nor should we assume recommendations and published protocols are well-designed. Reliable AV or VV optimization, using "pick-the-highest" on commonly-recommended manual measurements, is unrealistic. Improving time-efficiency of the optimization process to become clinically realistic may need a curve-fitting strategy instead, with all acquired data marshalled conjointly.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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Year:  2012        PMID: 22520157     DOI: 10.1016/j.ijcard.2012.03.128

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  4 in total

1.  Reproducibility of measuring QRS duration and implications for optimization of interventricular pacing delay in cardiac resynchronization therapy.

Authors:  Charlotte Stephansen; Mads Brix Kronborg; Christoffer Tobias Witt; Jens Kristensen; Christian Gerdes; Anders Sommer; Jesper Møller Jensen; Jens Cosedis Nielsen
Journal:  Ann Noninvasive Electrocardiol       Date:  2018-12-06       Impact factor: 1.468

Review 2.  Strategies to improve cardiac resynchronization therapy.

Authors:  Kevin Vernooy; Caroline J M van Deursen; Marc Strik; Frits W Prinzen
Journal:  Nat Rev Cardiol       Date:  2014-05-20       Impact factor: 32.419

3.  Evidence that conflict regarding size of haemodynamic response to interventricular delay optimization of cardiac resynchronization therapy may arise from differences in how atrioventricular delay is kept constant.

Authors:  S M Afzal Sohaib; Andreas Kyriacou; Siana Jones; Charlotte H Manisty; Jamil Mayet; Prapa Kanagaratnam; Nicholas S Peters; Alun D Hughes; Zachary I Whinnett; Darrel P Francis
Journal:  Europace       Date:  2015-04-07       Impact factor: 5.214

4.  Optimizing atrio-ventricular delay in pacemakers using potentially implantable physiological biomarkers.

Authors:  Daniel Keene; Alejandra A Miyazawa; Monika Johal; Ahran D Arnold; Nadine Ali; Khulat A Saqi; Katherine March; Leah Burden; Darrel P Francis; Zachary I Whinnett; Matthew J Shun-Shin
Journal:  Pacing Clin Electrophysiol       Date:  2022-01-28       Impact factor: 1.912

  4 in total

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