• Je něco špatně v tomto záznamu ?

Fully automated QRS area measurement for predicting response to cardiac resynchronization therapy

F. Plesinger, AMW. van Stipdonk, R. Smisek, J. Halamek, P. Jurak, AH. Maass, M. Meine, K. Vernooy, FW. Prinzen

. 2020 ; 63 (-) : 159-163. [pub] 20190709

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc21020825

BACKGROUND: Cardiac resynchronization therapy (CRT) is an established treatment in patients with heart failure and conduction abnormalities. However, a significant number of patients do not respond to CRT. Currently employed criteria for selection of patients for this therapy (QRS duration and morphology) have several shortcomings. QRS area was recently shown to provide superior association with CRT response. However, its assessment was not fully automated and required the presence of an expert. OBJECTIVE: Our objective was to develop a fully automated method for the assessment of vector-cardiographic (VCG) QRS area from electrocardiographic (ECG) signals. METHODS: Pre-implantation ECG recordings (N = 864, 695 left-bundle-branch block, 589 men) in PDF files were converted to allow signal processing. QRS complexes were found and clustered into morphological groups. Signals were converted from 12‑lead ECG to 3‑lead VCG and an average QRS complex was built. QRS area was computed from individual areas in the X, Y and Z leads. Practical usability was evaluated using Kaplan-Meier plots and 5-year follow-up data. RESULTS: The automatically calculated QRS area values were 123 ± 48 μV.s (mean values and SD), while the manually determined QRS area values were 116 ± 51 ms; the correlation coefficient between the two was r = 0.97. The automated and manual methods showed the same ability to stratify the population (hazard ratios 2.09 vs 2.03, respectively). CONCLUSION: The presented approach allows the fully automatic and objective assessment of QRS area values. SIGNIFICANCE: Until this study, assessing QRS area values required an expert, which means both additional costs and a risk of subjectivity. The presented approach eliminates these disadvantages and is publicly available as part of free signal-processing software.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc21020825
003      
CZ-PrNML
005      
20210830102450.0
007      
ta
008      
210728s2020 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1016/j.jelectrocard.2019.07.003 $2 doi
035    __
$a (PubMed)31324399
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Plesinger, Filip $u Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
245    10
$a Fully automated QRS area measurement for predicting response to cardiac resynchronization therapy / $c F. Plesinger, AMW. van Stipdonk, R. Smisek, J. Halamek, P. Jurak, AH. Maass, M. Meine, K. Vernooy, FW. Prinzen
520    9_
$a BACKGROUND: Cardiac resynchronization therapy (CRT) is an established treatment in patients with heart failure and conduction abnormalities. However, a significant number of patients do not respond to CRT. Currently employed criteria for selection of patients for this therapy (QRS duration and morphology) have several shortcomings. QRS area was recently shown to provide superior association with CRT response. However, its assessment was not fully automated and required the presence of an expert. OBJECTIVE: Our objective was to develop a fully automated method for the assessment of vector-cardiographic (VCG) QRS area from electrocardiographic (ECG) signals. METHODS: Pre-implantation ECG recordings (N = 864, 695 left-bundle-branch block, 589 men) in PDF files were converted to allow signal processing. QRS complexes were found and clustered into morphological groups. Signals were converted from 12‑lead ECG to 3‑lead VCG and an average QRS complex was built. QRS area was computed from individual areas in the X, Y and Z leads. Practical usability was evaluated using Kaplan-Meier plots and 5-year follow-up data. RESULTS: The automatically calculated QRS area values were 123 ± 48 μV.s (mean values and SD), while the manually determined QRS area values were 116 ± 51 ms; the correlation coefficient between the two was r = 0.97. The automated and manual methods showed the same ability to stratify the population (hazard ratios 2.09 vs 2.03, respectively). CONCLUSION: The presented approach allows the fully automatic and objective assessment of QRS area values. SIGNIFICANCE: Until this study, assessing QRS area values required an expert, which means both additional costs and a risk of subjectivity. The presented approach eliminates these disadvantages and is publicly available as part of free signal-processing software.
650    _2
$a blokáda Tawarova raménka $x diagnóza $x terapie $7 D002037
650    12
$a srdeční resynchronizační terapie $7 D058406
650    _2
$a elektrokardiografie $7 D004562
650    12
$a srdeční selhání $x diagnóza $x terapie $7 D006333
650    _2
$a lidé $7 D006801
650    _2
$a mužské pohlaví $7 D008297
650    _2
$a výsledek terapie $7 D016896
650    _2
$a vektorkardiografie $7 D014672
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a van Stipdonk, Antonius M W $u Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands
700    1_
$a Smisek, Radovan $u Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
700    1_
$a Halamek, Josef $u Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
700    1_
$a Jurak, Pavel $u Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
700    1_
$a Maass, Alexander H $u Department of Cardiology, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands
700    1_
$a Meine, Mathias $u Department of Cardiology, University Medical Centre Utrecht, Utrecht, the Netherlands
700    1_
$a Vernooy, Kevin $u Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands
700    1_
$a Prinzen, Frits W $u Department of Physiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands. Electronic address: frits.prinzen@maastrichtuniversity.nl
773    0_
$w MED00010003 $t Journal of electrocardiology $x 1532-8430 $g Roč. 63, č. - (2020), s. 159-163
856    41
$u https://pubmed.ncbi.nlm.nih.gov/31324399 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20210728 $b ABA008
991    __
$a 20210830102450 $b ABA008
999    __
$a ok $b bmc $g 1691416 $s 1141271
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2020 $b 63 $c - $d 159-163 $e 20190709 $i 1532-8430 $m Journal of electrocardiology $n J Electrocardiol $x MED00010003
LZP    __
$a Pubmed-20210728

Najít záznam

Citační ukazatele

    Možnosti archivace