Minimal subphenotyping model for acute heart failure with preserved ejection fraction
Abstract Aims Application of the latent class analysis to acute heart failure with preserved ejection fraction (HFpEF) showed that the heterogeneous acute HFpEF patients can be classified into four distinct phenotypes with different clinical outcomes. This model‐based clustering required a total of...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-08-01
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| Series: | ESC Heart Failure |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ehf2.13928 |
| _version_ | 1818197136510025728 |
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| author | Yohei Sotomi Taiki Sato Shungo Hikoso Sho Komukai Bolrathanak Oeun Tetsuhisa Kitamura Daisaku Nakatani Hiroya Mizuno Katsuki Okada Tomoharu Dohi Akihiro Sunaga Hirota Kida Masahiro Seo Masamichi Yano Takaharu Hayashi Akito Nakagawa Yusuke Nakagawa Shunsuke Tamaki Tomohito Ohtani Yoshio Yasumura Takahisa Yamada Yasushi Sakata OCVC‐Heart Failure Investigator |
| author_facet | Yohei Sotomi Taiki Sato Shungo Hikoso Sho Komukai Bolrathanak Oeun Tetsuhisa Kitamura Daisaku Nakatani Hiroya Mizuno Katsuki Okada Tomoharu Dohi Akihiro Sunaga Hirota Kida Masahiro Seo Masamichi Yano Takaharu Hayashi Akito Nakagawa Yusuke Nakagawa Shunsuke Tamaki Tomohito Ohtani Yoshio Yasumura Takahisa Yamada Yasushi Sakata OCVC‐Heart Failure Investigator |
| author_sort | Yohei Sotomi |
| collection | DOAJ |
| description | Abstract Aims Application of the latent class analysis to acute heart failure with preserved ejection fraction (HFpEF) showed that the heterogeneous acute HFpEF patients can be classified into four distinct phenotypes with different clinical outcomes. This model‐based clustering required a total of 32 variables to be included. However, this large number of variables will impair the clinical application of this classification algorithm. This study aimed to identify the minimal number of variables for the development of optimal subphenotyping model. Methods and results This study is a post hoc analysis of the PURSUIT‐HFpEF study (N = 1095), a prospective, multi‐referral centre, observational study of acute HFpEF [UMIN000021831]. We previously applied the latent class analysis to the PURSUIT‐HFpEF dataset and established the full 32‐variable model for subphenotyping. In this study, we used the Cohen's kappa statistic to investigate the minimal number of discriminatory variables needed to accurately classify the phenogroups in comparison with the full 32‐variable model. Cohen's kappa statistic of the top‐X number of discriminatory variables compared with the full 32‐variable derivation model showed that the models with ≥16 discriminatory variables showed kappa value of >0.8, suggesting that the minimal number of discriminatory variables for the optimal phenotyping model was 16. The 16‐variable model consists of C‐reactive protein, creatinine, gamma‐glutamyl transferase, brain natriuretic peptide, white blood cells, systolic blood pressure, fasting blood sugar, triglyceride, clinical scenario classification, infection‐triggered acute decompensated HF, estimated glomerular filtration rate, platelets, neutrophils, GWTG‐HF (Get With The Guidelines‐Heart Failure) risk score, chronic kidney disease, and CONUT (Controlling Nutritional Status) score. Characteristics and clinical outcomes of the four phenotypes subclassified by the minimal 16‐variable model were consistent with those by the full 32‐variable model. The four phenotypes were labelled based on their characteristics as ‘rhythm trouble’, ‘ventricular‐arterial uncoupling’, ‘low output and systemic congestion’, and ‘systemic failure’, respectively. Conclusions The phenotyping model with top 16 variables showed almost perfect agreement with the full 32‐variable model. The minimal model may enhance the future clinical application of this clustering algorithm. |
| first_indexed | 2024-12-12T01:45:11Z |
| format | Article |
| id | doaj.art-f9eb86bba95b437e8be85ec5b11814ba |
| institution | Directory Open Access Journal |
| issn | 2055-5822 |
| language | English |
| last_indexed | 2024-12-12T01:45:11Z |
| publishDate | 2022-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | ESC Heart Failure |
| spelling | doaj.art-f9eb86bba95b437e8be85ec5b11814ba2022-12-22T00:42:37ZengWileyESC Heart Failure2055-58222022-08-01942738274610.1002/ehf2.13928Minimal subphenotyping model for acute heart failure with preserved ejection fractionYohei Sotomi0Taiki Sato1Shungo Hikoso2Sho Komukai3Bolrathanak Oeun4Tetsuhisa Kitamura5Daisaku Nakatani6Hiroya Mizuno7Katsuki Okada8Tomoharu Dohi9Akihiro Sunaga10Hirota Kida11Masahiro Seo12Masamichi Yano13Takaharu Hayashi14Akito Nakagawa15Yusuke Nakagawa16Shunsuke Tamaki17Tomohito Ohtani18Yoshio Yasumura19Takahisa Yamada20Yasushi Sakata21OCVC‐Heart Failure InvestigatorDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDivision of Biomedical Statistics, Department of Integrated Medicine, Graduate School of Medicine Osaka University Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Social and Environmental Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDivision of Cardiology Osaka General Medical Center Osaka JapanDivision of Cardiology Osaka Rosai Hospital Osaka JapanCardiovascular Division Osaka Police Hospital Osaka JapanDivision of Cardiology Amagasaki Chuo Hospital Hyogo JapanDivision of Cardiology Kawanishi City Hospital Hyogo JapanDepartment of Cardiology Rinku General Medical Center Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanDivision of Cardiology Amagasaki Chuo Hospital Hyogo JapanDivision of Cardiology Osaka General Medical Center Osaka JapanDepartment of Cardiovascular Medicine Osaka University Graduate School of Medicine Osaka JapanAbstract Aims Application of the latent class analysis to acute heart failure with preserved ejection fraction (HFpEF) showed that the heterogeneous acute HFpEF patients can be classified into four distinct phenotypes with different clinical outcomes. This model‐based clustering required a total of 32 variables to be included. However, this large number of variables will impair the clinical application of this classification algorithm. This study aimed to identify the minimal number of variables for the development of optimal subphenotyping model. Methods and results This study is a post hoc analysis of the PURSUIT‐HFpEF study (N = 1095), a prospective, multi‐referral centre, observational study of acute HFpEF [UMIN000021831]. We previously applied the latent class analysis to the PURSUIT‐HFpEF dataset and established the full 32‐variable model for subphenotyping. In this study, we used the Cohen's kappa statistic to investigate the minimal number of discriminatory variables needed to accurately classify the phenogroups in comparison with the full 32‐variable model. Cohen's kappa statistic of the top‐X number of discriminatory variables compared with the full 32‐variable derivation model showed that the models with ≥16 discriminatory variables showed kappa value of >0.8, suggesting that the minimal number of discriminatory variables for the optimal phenotyping model was 16. The 16‐variable model consists of C‐reactive protein, creatinine, gamma‐glutamyl transferase, brain natriuretic peptide, white blood cells, systolic blood pressure, fasting blood sugar, triglyceride, clinical scenario classification, infection‐triggered acute decompensated HF, estimated glomerular filtration rate, platelets, neutrophils, GWTG‐HF (Get With The Guidelines‐Heart Failure) risk score, chronic kidney disease, and CONUT (Controlling Nutritional Status) score. Characteristics and clinical outcomes of the four phenotypes subclassified by the minimal 16‐variable model were consistent with those by the full 32‐variable model. The four phenotypes were labelled based on their characteristics as ‘rhythm trouble’, ‘ventricular‐arterial uncoupling’, ‘low output and systemic congestion’, and ‘systemic failure’, respectively. Conclusions The phenotyping model with top 16 variables showed almost perfect agreement with the full 32‐variable model. The minimal model may enhance the future clinical application of this clustering algorithm.https://doi.org/10.1002/ehf2.13928HFpEFAcute decompensated heart failurePhenotypingMinimal model |
| spellingShingle | Yohei Sotomi Taiki Sato Shungo Hikoso Sho Komukai Bolrathanak Oeun Tetsuhisa Kitamura Daisaku Nakatani Hiroya Mizuno Katsuki Okada Tomoharu Dohi Akihiro Sunaga Hirota Kida Masahiro Seo Masamichi Yano Takaharu Hayashi Akito Nakagawa Yusuke Nakagawa Shunsuke Tamaki Tomohito Ohtani Yoshio Yasumura Takahisa Yamada Yasushi Sakata OCVC‐Heart Failure Investigator Minimal subphenotyping model for acute heart failure with preserved ejection fraction ESC Heart Failure HFpEF Acute decompensated heart failure Phenotyping Minimal model |
| title | Minimal subphenotyping model for acute heart failure with preserved ejection fraction |
| title_full | Minimal subphenotyping model for acute heart failure with preserved ejection fraction |
| title_fullStr | Minimal subphenotyping model for acute heart failure with preserved ejection fraction |
| title_full_unstemmed | Minimal subphenotyping model for acute heart failure with preserved ejection fraction |
| title_short | Minimal subphenotyping model for acute heart failure with preserved ejection fraction |
| title_sort | minimal subphenotyping model for acute heart failure with preserved ejection fraction |
| topic | HFpEF Acute decompensated heart failure Phenotyping Minimal model |
| url | https://doi.org/10.1002/ehf2.13928 |
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