Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation
Abstract Identifying patients who would benefit from extensive catheter ablation along with pulmonary vein isolation (PVI) among those with persistent atrial fibrillation (AF) has been a subject of controversy. The objective of this study was to apply uplift modeling, a machine learning method for a...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-02-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-52976-7 |
| _version_ | 1797275153541890048 |
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| author | Taiki Sato Yohei Sotomi Shungo Hikoso Tetsuhisa Kitamura Daisaku Nakatani Katsuki Okada Tomoharu Dohi Akihiro Sunaga Hirota Kida Yuki Matsuoka Nobuaki Tanaka Tetsuya Watanabe Nobuhiko Makino Yasuyuki Egami Takafumi Oka Hitoshi Minamiguchi Miwa Miyoshi Masato Okada Takashi Kanda Yasuhiro Matsuda Masato Kawasaki Masaharu Masuda Koichi Inoue Yasushi Sakata the OCVC-Arrhythmia Investigators |
| author_facet | Taiki Sato Yohei Sotomi Shungo Hikoso Tetsuhisa Kitamura Daisaku Nakatani Katsuki Okada Tomoharu Dohi Akihiro Sunaga Hirota Kida Yuki Matsuoka Nobuaki Tanaka Tetsuya Watanabe Nobuhiko Makino Yasuyuki Egami Takafumi Oka Hitoshi Minamiguchi Miwa Miyoshi Masato Okada Takashi Kanda Yasuhiro Matsuda Masato Kawasaki Masaharu Masuda Koichi Inoue Yasushi Sakata the OCVC-Arrhythmia Investigators |
| author_sort | Taiki Sato |
| collection | DOAJ |
| description | Abstract Identifying patients who would benefit from extensive catheter ablation along with pulmonary vein isolation (PVI) among those with persistent atrial fibrillation (AF) has been a subject of controversy. The objective of this study was to apply uplift modeling, a machine learning method for analyzing individual causal effect, to identify such patients in the EARNEST-PVI trial, a randomized trial in patients with persistent AF. We developed 16 uplift models using different machine learning algorithms, and determined that the best performing model was adaptive boosting using Qini coefficients. The optimal uplift score threshold was 0.0124. Among patients with an uplift score ≥ 0.0124, those who underwent extensive catheter ablation (PVI-plus) showed a significantly lower recurrence rate of AF compared to those who received only PVI (PVI-alone) (HR 0.40; 95% CI 0.19–0.84; P-value = 0.015). In contrast, among patients with an uplift score < 0.0124, recurrence of AF did not significantly differ between PVI-plus and PVI-alone (HR 1.17; 95% CI 0.57–2.39; P-value = 0.661). By employing uplift modeling, we could effectively identify a subset of patients with persistent AF who would benefit from PVI-plus. This model could be valuable in stratifying patients with persistent AF who need extensive catheter ablation before the procedure. |
| first_indexed | 2024-03-07T15:10:12Z |
| format | Article |
| id | doaj.art-834d1d3ef3bb495c8f290571a9068793 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-07T15:10:12Z |
| publishDate | 2024-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-834d1d3ef3bb495c8f290571a90687932024-03-05T18:42:40ZengNature PortfolioScientific Reports2045-23222024-02-0114111310.1038/s41598-024-52976-7Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillationTaiki Sato0Yohei Sotomi1Shungo Hikoso2Tetsuhisa Kitamura3Daisaku Nakatani4Katsuki Okada5Tomoharu Dohi6Akihiro Sunaga7Hirota Kida8Yuki Matsuoka9Nobuaki Tanaka10Tetsuya Watanabe11Nobuhiko Makino12Yasuyuki Egami13Takafumi Oka14Hitoshi Minamiguchi15Miwa Miyoshi16Masato Okada17Takashi Kanda18Yasuhiro Matsuda19Masato Kawasaki20Masaharu Masuda21Koichi Inoue22Yasushi Sakata23the OCVC-Arrhythmia InvestigatorsDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Social and Environmental Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineCardiovascular Center, Sakurabashi Watanabe HospitalDivision of Cardiology, Osaka General Medical CenterCardiovascular Division, Osaka Police HospitalDivision of Cardiology, Osaka Rosai HospitalDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineDepartment of Cardiology, Osaka Hospital, Japan Community Healthcare OrganizationCardiovascular Center, Sakurabashi Watanabe HospitalCardiovascular Division, Osaka Police HospitalCardiovascular Center, Kansai Rosai HospitalDivision of Cardiology, Osaka General Medical CenterCardiovascular Center, Kansai Rosai HospitalCardiovascular Center, Sakurabashi Watanabe HospitalDepartment of Cardiovascular Medicine, Osaka University Graduate School of MedicineAbstract Identifying patients who would benefit from extensive catheter ablation along with pulmonary vein isolation (PVI) among those with persistent atrial fibrillation (AF) has been a subject of controversy. The objective of this study was to apply uplift modeling, a machine learning method for analyzing individual causal effect, to identify such patients in the EARNEST-PVI trial, a randomized trial in patients with persistent AF. We developed 16 uplift models using different machine learning algorithms, and determined that the best performing model was adaptive boosting using Qini coefficients. The optimal uplift score threshold was 0.0124. Among patients with an uplift score ≥ 0.0124, those who underwent extensive catheter ablation (PVI-plus) showed a significantly lower recurrence rate of AF compared to those who received only PVI (PVI-alone) (HR 0.40; 95% CI 0.19–0.84; P-value = 0.015). In contrast, among patients with an uplift score < 0.0124, recurrence of AF did not significantly differ between PVI-plus and PVI-alone (HR 1.17; 95% CI 0.57–2.39; P-value = 0.661). By employing uplift modeling, we could effectively identify a subset of patients with persistent AF who would benefit from PVI-plus. This model could be valuable in stratifying patients with persistent AF who need extensive catheter ablation before the procedure.https://doi.org/10.1038/s41598-024-52976-7 |
| spellingShingle | Taiki Sato Yohei Sotomi Shungo Hikoso Tetsuhisa Kitamura Daisaku Nakatani Katsuki Okada Tomoharu Dohi Akihiro Sunaga Hirota Kida Yuki Matsuoka Nobuaki Tanaka Tetsuya Watanabe Nobuhiko Makino Yasuyuki Egami Takafumi Oka Hitoshi Minamiguchi Miwa Miyoshi Masato Okada Takashi Kanda Yasuhiro Matsuda Masato Kawasaki Masaharu Masuda Koichi Inoue Yasushi Sakata the OCVC-Arrhythmia Investigators Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation Scientific Reports |
| title | Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation |
| title_full | Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation |
| title_fullStr | Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation |
| title_full_unstemmed | Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation |
| title_short | Uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation |
| title_sort | uplift modeling to identify patients who require extensive catheter ablation procedures among patients with persistent atrial fibrillation |
| url | https://doi.org/10.1038/s41598-024-52976-7 |
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