Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence
This study aimed to improve echocardiographic assessment of pulmonary hypertension (PH) in patients presenting with severe tricuspid regurgitation (TR). Echocardiographic assessment of PH in patients with severe TR carries several pitfalls for underestimation, hence concealing the true severity of P...
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| Veröffentlicht in: | JACC. Cardiovascular interventions 2022-02, Vol.15 (4), p.381-394 |
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| creator | Fortmeier, Vera Lachmann, Mark Körber, Maria I. Unterhuber, Matthias von Scheidt, Moritz Rippen, Elena Harmsen, Gerhard Gerçek, Muhammed Friedrichs, Kai Peter Roder, Fabian Rudolph, Tanja K. Yuasa, Shinsuke Joner, Michael Laugwitz, Karl-Ludwig Baldus, Stephan Pfister, Roman Lurz, Philipp Rudolph, Volker |
| description | This study aimed to improve echocardiographic assessment of pulmonary hypertension (PH) in patients presenting with severe tricuspid regurgitation (TR).
Echocardiographic assessment of PH in patients with severe TR carries several pitfalls for underestimation, hence concealing the true severity of PH in very sick patients in particular, and ultimately obscuring the impact of PH on survival after transcatheter tricuspid valve intervention (TTVI).
All patients in this study underwent TTVI for severe TR between 2016 and 2020. To predict the mean pulmonary artery pressure (mPAP) solely based on echocardiographic parameters, we trained an extreme gradient boosting (XGB) algorithm. The derivation cohort was constituted by 116 out of 162 patients with both echocardiography and right heart catheterization data, preprocedurally obtained, from a bicentric registry. Moreover, 142 patients from an independent institution served for external validation.
Systolic pulmonary artery pressure was consistently underestimated by echocardiography in comparison to right heart catheterization (40.3 ± 15.9 mm Hg vs 44.1 ± 12.9 mm Hg; P = 0.0066), and the assessment was most discrepant among patients with severe defects of the tricuspid valve and impaired right ventricular systolic function. Using 9 echocardiographic parameters as input variables, an XGB algorithm could reliably predict mPAP levels (R = 0.96, P < 2.2 × 10-16). Moreover, patients with elevations in predicted mPAP levels ≥29.9 mm Hg showed significantly reduced 2-year survival after TTVI (58.3% [95% CI: 41.7%-81.6%] vs 78.8% [95% CI: 68.7%-90.5%]; P = 0.026). Importantly, the poor prognosis associated with elevation in predicted mPAP levels was externally confirmed (HR for 2-year mortality: 2.9 [95% CI: 1.5-5.7]; P = 0.002).
PH in patients with severe TR can be reliably assessed based on echocardiographic parameters in conjunction with an XGB algorithm, and elevations in predicted mPAP levels translate into increased mortality after TTVI.
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| doi_str_mv | 10.1016/j.jcin.2021.12.043 |
| format | Article |
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Echocardiographic assessment of PH in patients with severe TR carries several pitfalls for underestimation, hence concealing the true severity of PH in very sick patients in particular, and ultimately obscuring the impact of PH on survival after transcatheter tricuspid valve intervention (TTVI).
All patients in this study underwent TTVI for severe TR between 2016 and 2020. To predict the mean pulmonary artery pressure (mPAP) solely based on echocardiographic parameters, we trained an extreme gradient boosting (XGB) algorithm. The derivation cohort was constituted by 116 out of 162 patients with both echocardiography and right heart catheterization data, preprocedurally obtained, from a bicentric registry. Moreover, 142 patients from an independent institution served for external validation.
Systolic pulmonary artery pressure was consistently underestimated by echocardiography in comparison to right heart catheterization (40.3 ± 15.9 mm Hg vs 44.1 ± 12.9 mm Hg; P = 0.0066), and the assessment was most discrepant among patients with severe defects of the tricuspid valve and impaired right ventricular systolic function. Using 9 echocardiographic parameters as input variables, an XGB algorithm could reliably predict mPAP levels (R = 0.96, P < 2.2 × 10-16). Moreover, patients with elevations in predicted mPAP levels ≥29.9 mm Hg showed significantly reduced 2-year survival after TTVI (58.3% [95% CI: 41.7%-81.6%] vs 78.8% [95% CI: 68.7%-90.5%]; P = 0.026). Importantly, the poor prognosis associated with elevation in predicted mPAP levels was externally confirmed (HR for 2-year mortality: 2.9 [95% CI: 1.5-5.7]; P = 0.002).
PH in patients with severe TR can be reliably assessed based on echocardiographic parameters in conjunction with an XGB algorithm, and elevations in predicted mPAP levels translate into increased mortality after TTVI.
[Display omitted]</description><identifier>ISSN: 1936-8798</identifier><identifier>EISSN: 1876-7605</identifier><identifier>DOI: 10.1016/j.jcin.2021.12.043</identifier><identifier>PMID: 35210045</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Artificial Intelligence ; Humans ; Hypertension, Pulmonary - diagnostic imaging ; pulmonary hypertension ; Severity of Illness Index ; transcatheter tricuspid valve intervention ; Treatment Outcome ; tricuspid regurgitation ; Tricuspid Valve - diagnostic imaging ; Tricuspid Valve Insufficiency</subject><ispartof>JACC. Cardiovascular interventions, 2022-02, Vol.15 (4), p.381-394</ispartof><rights>2022 American College of Cardiology Foundation</rights><rights>Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-6ccbe16c23230b062306d6b869492c2d199acc177f1f242a003164144db47c003</citedby><cites>FETCH-LOGICAL-c400t-6ccbe16c23230b062306d6b869492c2d199acc177f1f242a003164144db47c003</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1936879821022524$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35210045$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fortmeier, Vera</creatorcontrib><creatorcontrib>Lachmann, Mark</creatorcontrib><creatorcontrib>Körber, Maria I.</creatorcontrib><creatorcontrib>Unterhuber, Matthias</creatorcontrib><creatorcontrib>von Scheidt, Moritz</creatorcontrib><creatorcontrib>Rippen, Elena</creatorcontrib><creatorcontrib>Harmsen, Gerhard</creatorcontrib><creatorcontrib>Gerçek, Muhammed</creatorcontrib><creatorcontrib>Friedrichs, Kai Peter</creatorcontrib><creatorcontrib>Roder, Fabian</creatorcontrib><creatorcontrib>Rudolph, Tanja K.</creatorcontrib><creatorcontrib>Yuasa, Shinsuke</creatorcontrib><creatorcontrib>Joner, Michael</creatorcontrib><creatorcontrib>Laugwitz, Karl-Ludwig</creatorcontrib><creatorcontrib>Baldus, Stephan</creatorcontrib><creatorcontrib>Pfister, Roman</creatorcontrib><creatorcontrib>Lurz, Philipp</creatorcontrib><creatorcontrib>Rudolph, Volker</creatorcontrib><title>Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence</title><title>JACC. Cardiovascular interventions</title><addtitle>JACC Cardiovasc Interv</addtitle><description>This study aimed to improve echocardiographic assessment of pulmonary hypertension (PH) in patients presenting with severe tricuspid regurgitation (TR).
Echocardiographic assessment of PH in patients with severe TR carries several pitfalls for underestimation, hence concealing the true severity of PH in very sick patients in particular, and ultimately obscuring the impact of PH on survival after transcatheter tricuspid valve intervention (TTVI).
All patients in this study underwent TTVI for severe TR between 2016 and 2020. To predict the mean pulmonary artery pressure (mPAP) solely based on echocardiographic parameters, we trained an extreme gradient boosting (XGB) algorithm. The derivation cohort was constituted by 116 out of 162 patients with both echocardiography and right heart catheterization data, preprocedurally obtained, from a bicentric registry. Moreover, 142 patients from an independent institution served for external validation.
Systolic pulmonary artery pressure was consistently underestimated by echocardiography in comparison to right heart catheterization (40.3 ± 15.9 mm Hg vs 44.1 ± 12.9 mm Hg; P = 0.0066), and the assessment was most discrepant among patients with severe defects of the tricuspid valve and impaired right ventricular systolic function. Using 9 echocardiographic parameters as input variables, an XGB algorithm could reliably predict mPAP levels (R = 0.96, P < 2.2 × 10-16). Moreover, patients with elevations in predicted mPAP levels ≥29.9 mm Hg showed significantly reduced 2-year survival after TTVI (58.3% [95% CI: 41.7%-81.6%] vs 78.8% [95% CI: 68.7%-90.5%]; P = 0.026). Importantly, the poor prognosis associated with elevation in predicted mPAP levels was externally confirmed (HR for 2-year mortality: 2.9 [95% CI: 1.5-5.7]; P = 0.002).
PH in patients with severe TR can be reliably assessed based on echocardiographic parameters in conjunction with an XGB algorithm, and elevations in predicted mPAP levels translate into increased mortality after TTVI.
[Display omitted]</description><subject>Artificial Intelligence</subject><subject>Humans</subject><subject>Hypertension, Pulmonary - diagnostic imaging</subject><subject>pulmonary hypertension</subject><subject>Severity of Illness Index</subject><subject>transcatheter tricuspid valve intervention</subject><subject>Treatment Outcome</subject><subject>tricuspid regurgitation</subject><subject>Tricuspid Valve - diagnostic imaging</subject><subject>Tricuspid Valve Insufficiency</subject><issn>1936-8798</issn><issn>1876-7605</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kMFu1DAURSMEoqXwAyyQl2wSnh2Pk0hsqqrQSpWoaBFLK3Fepm-U2MF2Rp0dn8K38GU4msKSjf0snXttnyx7y6HgwNWHXbEzZAsBghdcFCDLZ9kpryuVVwo2z9PclCqvq6Y-yV6FsANQ0FTiZXZSbgQHkJvT7OedG_dktyw-ILtdxsnZ1h_Y1WFGH9EGcpbdtr7t3SOjdYyENgb2neIDu8M9emT3nswSZup___qK28VvKSYsBbsDu5zm0R3WC859pIEMtSO7thHHkbZoDb7OXgztGPDN036Wfft0eX9xld98-Xx9cX6TGwkQc2VMh1wZUYoSOlBpVb3qatXIRhjR86ZpjeFVNfBBSNEClFxJLmXfycqk01n2_tg7e_djwRD1RMGkZ7QW3RK0UGVZbwRAlVBxRI13IXgc9OxpSlo0B72a1zu9mterec2FTuZT6N1T_9JN2P-L_FWdgI9HANMv94ReB0OrgZ48mqh7R__r_wO1ZZcC</recordid><startdate>20220228</startdate><enddate>20220228</enddate><creator>Fortmeier, Vera</creator><creator>Lachmann, Mark</creator><creator>Körber, Maria I.</creator><creator>Unterhuber, Matthias</creator><creator>von Scheidt, Moritz</creator><creator>Rippen, Elena</creator><creator>Harmsen, Gerhard</creator><creator>Gerçek, Muhammed</creator><creator>Friedrichs, Kai Peter</creator><creator>Roder, Fabian</creator><creator>Rudolph, Tanja K.</creator><creator>Yuasa, Shinsuke</creator><creator>Joner, Michael</creator><creator>Laugwitz, Karl-Ludwig</creator><creator>Baldus, Stephan</creator><creator>Pfister, Roman</creator><creator>Lurz, Philipp</creator><creator>Rudolph, Volker</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20220228</creationdate><title>Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence</title><author>Fortmeier, Vera ; Lachmann, Mark ; Körber, Maria I. ; Unterhuber, Matthias ; von Scheidt, Moritz ; Rippen, Elena ; Harmsen, Gerhard ; Gerçek, Muhammed ; Friedrichs, Kai Peter ; Roder, Fabian ; Rudolph, Tanja K. ; Yuasa, Shinsuke ; Joner, Michael ; Laugwitz, Karl-Ludwig ; Baldus, Stephan ; Pfister, Roman ; Lurz, Philipp ; Rudolph, Volker</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-6ccbe16c23230b062306d6b869492c2d199acc177f1f242a003164144db47c003</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial Intelligence</topic><topic>Humans</topic><topic>Hypertension, Pulmonary - diagnostic imaging</topic><topic>pulmonary hypertension</topic><topic>Severity of Illness Index</topic><topic>transcatheter tricuspid valve intervention</topic><topic>Treatment Outcome</topic><topic>tricuspid regurgitation</topic><topic>Tricuspid Valve - diagnostic imaging</topic><topic>Tricuspid Valve Insufficiency</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fortmeier, Vera</creatorcontrib><creatorcontrib>Lachmann, Mark</creatorcontrib><creatorcontrib>Körber, Maria I.</creatorcontrib><creatorcontrib>Unterhuber, Matthias</creatorcontrib><creatorcontrib>von Scheidt, Moritz</creatorcontrib><creatorcontrib>Rippen, Elena</creatorcontrib><creatorcontrib>Harmsen, Gerhard</creatorcontrib><creatorcontrib>Gerçek, Muhammed</creatorcontrib><creatorcontrib>Friedrichs, Kai Peter</creatorcontrib><creatorcontrib>Roder, Fabian</creatorcontrib><creatorcontrib>Rudolph, Tanja K.</creatorcontrib><creatorcontrib>Yuasa, Shinsuke</creatorcontrib><creatorcontrib>Joner, Michael</creatorcontrib><creatorcontrib>Laugwitz, Karl-Ludwig</creatorcontrib><creatorcontrib>Baldus, Stephan</creatorcontrib><creatorcontrib>Pfister, Roman</creatorcontrib><creatorcontrib>Lurz, Philipp</creatorcontrib><creatorcontrib>Rudolph, Volker</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>JACC. Cardiovascular interventions</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fortmeier, Vera</au><au>Lachmann, Mark</au><au>Körber, Maria I.</au><au>Unterhuber, Matthias</au><au>von Scheidt, Moritz</au><au>Rippen, Elena</au><au>Harmsen, Gerhard</au><au>Gerçek, Muhammed</au><au>Friedrichs, Kai Peter</au><au>Roder, Fabian</au><au>Rudolph, Tanja K.</au><au>Yuasa, Shinsuke</au><au>Joner, Michael</au><au>Laugwitz, Karl-Ludwig</au><au>Baldus, Stephan</au><au>Pfister, Roman</au><au>Lurz, Philipp</au><au>Rudolph, Volker</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence</atitle><jtitle>JACC. Cardiovascular interventions</jtitle><addtitle>JACC Cardiovasc Interv</addtitle><date>2022-02-28</date><risdate>2022</risdate><volume>15</volume><issue>4</issue><spage>381</spage><epage>394</epage><pages>381-394</pages><issn>1936-8798</issn><eissn>1876-7605</eissn><abstract>This study aimed to improve echocardiographic assessment of pulmonary hypertension (PH) in patients presenting with severe tricuspid regurgitation (TR).
Echocardiographic assessment of PH in patients with severe TR carries several pitfalls for underestimation, hence concealing the true severity of PH in very sick patients in particular, and ultimately obscuring the impact of PH on survival after transcatheter tricuspid valve intervention (TTVI).
All patients in this study underwent TTVI for severe TR between 2016 and 2020. To predict the mean pulmonary artery pressure (mPAP) solely based on echocardiographic parameters, we trained an extreme gradient boosting (XGB) algorithm. The derivation cohort was constituted by 116 out of 162 patients with both echocardiography and right heart catheterization data, preprocedurally obtained, from a bicentric registry. Moreover, 142 patients from an independent institution served for external validation.
Systolic pulmonary artery pressure was consistently underestimated by echocardiography in comparison to right heart catheterization (40.3 ± 15.9 mm Hg vs 44.1 ± 12.9 mm Hg; P = 0.0066), and the assessment was most discrepant among patients with severe defects of the tricuspid valve and impaired right ventricular systolic function. Using 9 echocardiographic parameters as input variables, an XGB algorithm could reliably predict mPAP levels (R = 0.96, P < 2.2 × 10-16). Moreover, patients with elevations in predicted mPAP levels ≥29.9 mm Hg showed significantly reduced 2-year survival after TTVI (58.3% [95% CI: 41.7%-81.6%] vs 78.8% [95% CI: 68.7%-90.5%]; P = 0.026). Importantly, the poor prognosis associated with elevation in predicted mPAP levels was externally confirmed (HR for 2-year mortality: 2.9 [95% CI: 1.5-5.7]; P = 0.002).
PH in patients with severe TR can be reliably assessed based on echocardiographic parameters in conjunction with an XGB algorithm, and elevations in predicted mPAP levels translate into increased mortality after TTVI.
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| source | MEDLINE; Elsevier ScienceDirect Journals Complete; EZB Electronic Journals Library |
| subjects | Artificial Intelligence Humans Hypertension, Pulmonary - diagnostic imaging pulmonary hypertension Severity of Illness Index transcatheter tricuspid valve intervention Treatment Outcome tricuspid regurgitation Tricuspid Valve - diagnostic imaging Tricuspid Valve Insufficiency |
| title | Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence |
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