TY - JOUR
T1 - Malperfusion syndrome in patients undergoing repair for acute type A aortic dissection
T2 - Presentation, mortality, and utility of the Penn classification
AU - Dell'Aquila, Angelo M.
AU - Wisniewski, Konrad
AU - Georgevici, Adrian Iustin
AU - Szabó, Gábor
AU - Onorati, Francesco
AU - Rossetti, Cecilia
AU - Conradi, Lenard
AU - Demal, Till
AU - Rukosujew, Andreas
AU - Peterss, Sven
AU - Caroline, Radner
AU - Buech, Joscha
AU - Fiore, Antonio
AU - Folliguet, Thierry
AU - Perrotti, Andrea
AU - Hervé, Amélie
AU - Nappi, Francesco
AU - Pinto, Angel G.
AU - Lega, Javier Rodriguez
AU - Pol, Marek
AU - Kacer, Petr
AU - Mazzaro, Enzo
AU - Gatti, Giuseppe
AU - Vendramin, Igor
AU - Piani, Daniela
AU - Ferrante, Luisa
AU - Rinaldi, Mauro
AU - Quintana, Eduard
AU - Pruna-Guillen, Robert
AU - Gerelli, Sebastien
AU - Di Perna, Dario
AU - Acharya, Metesh
AU - Sherzad, Hiwa
AU - Mariscalco, Giovanni
AU - Field, Mark
AU - Harky, Amer
AU - Kuduvalli, Manoj
AU - Pettinari, Matteo
AU - Rosato, Stefano
AU - Juvonen, Tatu
AU - Mikko, Jormalainen
AU - Mäkikallio, Timo
AU - Mustonen, Caius
AU - Biancari, Fausto
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024
Y1 - 2024
N2 - Background: The current study aims to report the presentation of the malperfusion syndrome in patients with acute type A aortic dissection admitted to surgery and its impact on mortality. Methods: Data were retrieved from the multicenter European Registry of Type A Aortic Dissection. The Penn classification was used to categorize malperfusion syndromes. A machine-learning algorithm was applied to assess the multivariate interaction's importance regarding in-hospital mortality. Results: A total of 3902 consecutive patients underwent repair for acute type A aortic dissection. Local malperfusion syndrome occurred in 1584 (40.59%) patients. Multiorgan involvement occurred in 582 patients (36.74%) whereas 1002 patients (63.26%) had single-organ malperfusion. The prevalence was the greatest for cerebral (21.27%) followed by peripheral (13.94%), myocardial (9.7%), renal (9.33%), mesenteric (4.15%), and spinal malperfusion (2.10%). Multiorgan involvement predominantly occurred in organs perfused by the downstream aorta. Malperfusion significantly increased the risk of mortality (P < .001; odds ratio, 1.94 ± 0.29). The Boruta machine-learning algorithm identified the Penn classification as significantly associated with in-hospital mortality (P < .0001, variable importance = 7.91); however, 8 other variables yielded greater prediction importance. According to the Penn classification, mortality rates were 12.38% for Penn A, 20.71% for Penn B, 28.90% for Penn C, and 31.84% for Penn BC, respectively. Conclusions: Nearly one half of the examined cohort presented with signs of malperfusion syndrome predominantly attributable to local involvement. More than one third of patients with local malperfusion syndrome had a multivessel involvement. Furthermore, different levels of Penn classification can be used only as a first tool for preliminary stratification of early mortality risk.
AB - Background: The current study aims to report the presentation of the malperfusion syndrome in patients with acute type A aortic dissection admitted to surgery and its impact on mortality. Methods: Data were retrieved from the multicenter European Registry of Type A Aortic Dissection. The Penn classification was used to categorize malperfusion syndromes. A machine-learning algorithm was applied to assess the multivariate interaction's importance regarding in-hospital mortality. Results: A total of 3902 consecutive patients underwent repair for acute type A aortic dissection. Local malperfusion syndrome occurred in 1584 (40.59%) patients. Multiorgan involvement occurred in 582 patients (36.74%) whereas 1002 patients (63.26%) had single-organ malperfusion. The prevalence was the greatest for cerebral (21.27%) followed by peripheral (13.94%), myocardial (9.7%), renal (9.33%), mesenteric (4.15%), and spinal malperfusion (2.10%). Multiorgan involvement predominantly occurred in organs perfused by the downstream aorta. Malperfusion significantly increased the risk of mortality (P < .001; odds ratio, 1.94 ± 0.29). The Boruta machine-learning algorithm identified the Penn classification as significantly associated with in-hospital mortality (P < .0001, variable importance = 7.91); however, 8 other variables yielded greater prediction importance. According to the Penn classification, mortality rates were 12.38% for Penn A, 20.71% for Penn B, 28.90% for Penn C, and 31.84% for Penn BC, respectively. Conclusions: Nearly one half of the examined cohort presented with signs of malperfusion syndrome predominantly attributable to local involvement. More than one third of patients with local malperfusion syndrome had a multivessel involvement. Furthermore, different levels of Penn classification can be used only as a first tool for preliminary stratification of early mortality risk.
KW - aortic dissection
KW - machine learning
KW - malperfusion
KW - 3126 Surgery, anesthesiology, intensive care, radiology
U2 - 10.1016/j.jtcvs.2024.11.003
DO - 10.1016/j.jtcvs.2024.11.003
M3 - Article
C2 - 39522713
AN - SCOPUS:85211054797
SN - 0022-5223
JO - Journal of Thoracic and Cardiovascular Surgery
JF - Journal of Thoracic and Cardiovascular Surgery
ER -