Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model.

Publikation

Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model.

Wissenschaftlicher Artikel/Review - 18.09.2023

De Filippo Ovidio, Cammann Victoria L, Pancotti Corrado, Di Vece Davide, Silverio Angelo, Schweiger Victor, Niederseer David, Szawan Konrad A, Würdinger Michael, Koleva Iva, Dusi Veronica, Bellino Michele, Vecchione Carmine, Parodi Guido, Bossone Eduardo, Gili Sebastiano, Neuhaus Michael, Franke Jennifer, Meder Benjamin, Jaguszewski Miłosz, Noutsias Michel, Knorr Maike, Jansen Thomas, Dichtl Wolfgang, von Lewinski Dirk, Burgdorf Christof, Kherad Behrouz, Tschope Carsten, Sarcon Annahita, Shinbane Jerold, Rajan Lawrence, Michels Guido, Pfister Roman, Cuneo Alessandro, Jacobshagen Claudius, Karakas Mahir, Koenig Wolfgang, Pott Alexander, Meyer Philippe, Roffi Marco, Banning Adrian, Wolfrum Mathias, Cuculi Florim, Kobza Richard, Fischer Thomas A, Vasankari Tuija, Airaksinen K E Juhani, Napp L Christian, Dworakowski Rafal, MacCarthy Philip, Kaiser Christoph A, Osswald Stefan, Galiuto Leonarda, Chan Christina, Bridgman Paul, Beug Daniel, Delmas Clément, Lairez Olivier, Gilyarova Ekaterina, Shilova Alexandra, Gilyarov Mikhail, El-Battrawy Ibrahim, Akin Ibrahim, Poledniková Karolina, Tousek Petr, Winchester David E, Massoomi Michael, Galuszka Jan, Ukena Christian, Poglajen Gregor, Carrilho-Ferreira Pedro, Hauck Christian, Paolini Carla, Bilato Claudio, Kobayashi Yoshio, Kato Ken, Ishibashi Iwao, Himi Toshiharu, Din Jehangir, Al-Shammari Ali, Prasad Abhiram, Rihal Charanjit S, Liu Kan, Schulze P Christian, Bianco Matteo, Jörg Lucas, Rickli Hans, Pestana Gonçalo, Nguyen Thanh H, Böhm Michael, Stöckelmaier Linda, Pinto Fausto J, Widimsky Petr, Felix Stephan B, Braun-Dullaeus Ruediger C, Rottbauer Wolfgang, Hasenfuß Gerd, Pieske Burkert M, Schunkert Heribert, Budnik Monika, Opolski Grzegorz, Thiele Holger, Bauersachs Johann, Horowitz John D, di Mario Carlo, Bruno Francesco, Kong William, Dalakoti Mayank, Imori Yoichi, Münzel Thomas, Crea Filippo, Lüscher Thomas F, Bax Jeroen J, Ruschitzka Frank, De Ferrari Gaetano Maria, Fariselli Piero, Ghadri Jelena R, Citro Rodolfo, D'Ascenzo Fabrizio, Templin Christian

Zitation

De Filippo O, Cammann V, Pancotti C, Di Vece D, Silverio A, Schweiger V, Niederseer D, Szawan K, Würdinger M, Koleva I, Dusi V, Bellino M, Vecchione C, Parodi G, Bossone E, Gili S, Neuhaus M, Franke J, Meder B, Jaguszewski M, Noutsias M, Knorr M, Jansen T, Dichtl W, von Lewinski D, Burgdorf C, Kherad B, Tschope C, Sarcon A, Shinbane J, Rajan L, Michels G, Pfister R, Cuneo A, Jacobshagen C, Karakas M, Koenig W, Pott A, Meyer P, Roffi M, Banning A, Wolfrum M, Cuculi F, Kobza R, Fischer T, Vasankari T, Airaksinen K, Napp L, Dworakowski R, MacCarthy P, Kaiser C, Osswald S, Galiuto L, Chan C, Bridgman P, Beug D, Delmas C, Lairez O, Gilyarova E, Shilova A, Gilyarov M, El-Battrawy I, Akin I, Poledniková K, Tousek P, Winchester D, Massoomi M, Galuszka J, Ukena C, Poglajen G, Carrilho-Ferreira P, Hauck C, Paolini C, Bilato C, Kobayashi Y, Kato K, Ishibashi I, Himi T, Din J, Al-Shammari A, Prasad A, Rihal C, Liu K, Schulze P, Bianco M, Jörg L, Rickli H, Pestana G, Nguyen T, Böhm M, Stöckelmaier L, Pinto F, Widimsky P, Felix S, Braun-Dullaeus R, Rottbauer W, Hasenfuß G, Pieske B, Schunkert H, Budnik M, Opolski G, Thiele H, Bauersachs J, Horowitz J, di Mario C, Bruno F, Kong W, Dalakoti M, Imori Y, Münzel T, Crea F, Lüscher T, Bax J, Ruschitzka F, De Ferrari G, Fariselli P, Ghadri J, Citro R, D'Ascenzo F, Templin C. Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model. Eur J Heart Fail 2023; 25:2299-2311.

Art

Wissenschaftlicher Artikel/Review (Englisch)

Zeitschrift

Eur J Heart Fail 2023; 25

Veröffentlichungsdatum

18.09.2023

eISSN (Online)

1879-0844

Seiten

2299-2311

Kurzbeschreibung/Zielsetzung

Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles.