Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms
Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndrome) are factors commonly related to AF recurrence. This study aims to assess the predictive value of laboratory and clinical parameters responsible f...
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ftpubmed:oai:pubmedcentral.nih.gov:6510876 2023-05-15T15:10:58+02:00 Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms Budzianowski, Jan Hiczkiewicz, Jarosław Burchardt, Paweł Pieszko, Konrad Rzeźniczak, Janusz Budzianowski, Paweł Korybalska, Katarzyna 2018-08-23 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510876/ http://www.ncbi.nlm.nih.gov/pubmed/30140958 https://doi.org/10.1007/s00380-018-1244-z en eng Springer Japan http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510876/ http://www.ncbi.nlm.nih.gov/pubmed/30140958 http://dx.doi.org/10.1007/s00380-018-1244-z © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. CC-BY Original Article Text 2018 ftpubmed https://doi.org/10.1007/s00380-018-1244-z 2019-06-02T00:13:45Z Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndrome) are factors commonly related to AF recurrence. This study aims to assess the predictive value of laboratory and clinical parameters responsible for early recurrence of atrial fibrillation (ERAF) following cryoballoon ablation (CBA) using statistical assessment and machine learning algorithms. This study group comprised 118 consecutive patients (mean age, 62.5 ± 7.8 years; women 36%) with paroxysmal (54.1%) and persistent (45.9%) AF who underwent their first pulmonary vein isolation (PVI) performed by CBA (Arctic Front Advance 2nd generation 28 mm). The biomarker concentrations were measured at baseline and after CBA in a 24-h follow-up. ERAF was defined as at least a 30-s episode of arrhythmia registered by a 24 h-Holter monitor within the 3 months following the procedure. 56 clinical, laboratory and procedural variables were collected from each patient. We used two classification algorithms: support vector machines, gradient boosted tree. The synthetic minority over-sampling technique (SMOTE) was used to provide a balanced training data set. Within a period of 3 months 21 patients (17.8%) experienced ERAF. The statistical analysis indicated that the lowered levels of post-ablation TnT (p = 0.043) and CK-MB (p = 0.010) with the TnT elevation (p = 0.044) were the predictors of ERAF following CBA. In addition, diabetes and statin treatment were significantly associated with ERAF after CBA (p < 0.05). The machine learning algorithms confirmed the results obtained in the univariate analysis. Text Arctic PubMed Central (PMC) Arctic Heart and Vessels 34 2 352 359 |
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Original Article Budzianowski, Jan Hiczkiewicz, Jarosław Burchardt, Paweł Pieszko, Konrad Rzeźniczak, Janusz Budzianowski, Paweł Korybalska, Katarzyna Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
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Original Article |
description |
Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndrome) are factors commonly related to AF recurrence. This study aims to assess the predictive value of laboratory and clinical parameters responsible for early recurrence of atrial fibrillation (ERAF) following cryoballoon ablation (CBA) using statistical assessment and machine learning algorithms. This study group comprised 118 consecutive patients (mean age, 62.5 ± 7.8 years; women 36%) with paroxysmal (54.1%) and persistent (45.9%) AF who underwent their first pulmonary vein isolation (PVI) performed by CBA (Arctic Front Advance 2nd generation 28 mm). The biomarker concentrations were measured at baseline and after CBA in a 24-h follow-up. ERAF was defined as at least a 30-s episode of arrhythmia registered by a 24 h-Holter monitor within the 3 months following the procedure. 56 clinical, laboratory and procedural variables were collected from each patient. We used two classification algorithms: support vector machines, gradient boosted tree. The synthetic minority over-sampling technique (SMOTE) was used to provide a balanced training data set. Within a period of 3 months 21 patients (17.8%) experienced ERAF. The statistical analysis indicated that the lowered levels of post-ablation TnT (p = 0.043) and CK-MB (p = 0.010) with the TnT elevation (p = 0.044) were the predictors of ERAF following CBA. In addition, diabetes and statin treatment were significantly associated with ERAF after CBA (p < 0.05). The machine learning algorithms confirmed the results obtained in the univariate analysis. |
format |
Text |
author |
Budzianowski, Jan Hiczkiewicz, Jarosław Burchardt, Paweł Pieszko, Konrad Rzeźniczak, Janusz Budzianowski, Paweł Korybalska, Katarzyna |
author_facet |
Budzianowski, Jan Hiczkiewicz, Jarosław Burchardt, Paweł Pieszko, Konrad Rzeźniczak, Janusz Budzianowski, Paweł Korybalska, Katarzyna |
author_sort |
Budzianowski, Jan |
title |
Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
title_short |
Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
title_full |
Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
title_fullStr |
Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
title_full_unstemmed |
Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
title_sort |
predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms |
publisher |
Springer Japan |
publishDate |
2018 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510876/ http://www.ncbi.nlm.nih.gov/pubmed/30140958 https://doi.org/10.1007/s00380-018-1244-z |
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Arctic |
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Arctic |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510876/ http://www.ncbi.nlm.nih.gov/pubmed/30140958 http://dx.doi.org/10.1007/s00380-018-1244-z |
op_rights |
© The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1007/s00380-018-1244-z |
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