An interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study

Danila Azzolina, Gianmaria Cammarota, Enrico Boero, Paola Berchialla, Savino Spadaro, Federico Longhini, Cristian Deana, Daniele Guerino Biasucci, Stefano D’Incà, Irene Batticci, Nicola Fasano, Edoardo De Robertis, Rachele Simonte, Salvatore Maurizio Maggiore, Valentina Bellini, Elena Giovanna Bignami, Luigi Vetrugno, Unknown, Vito Marco Ranieri, Anna Pesamosca, Agnese Cattarossi, Saskia Granzotti, Alessandro Cavarape, Andrea Cortegiani, Lisa Mattuzzi, Luca Flaibani, Nicola Federici, Francesco Meroi, Marco Tescione, Andrea Bruni, Eugenio Garofalo, Mattia Bernardinetti, Felice Urso, Camilla Colombotto, Francesco Forfori, Sandro Pregnolato, Francesco Corradi, Federico Dazzi, Sara Tempini, Alessandro Isirdi, Moro Federico, Nicole Giovane, Milo Vason, Carlo Alberto Volta, Fabio Gori, Michela Neri, Auro Caraffa, Giovanni Cosco, Eugenio Vadalà, Demetrio Labate, Nicola Polimeni, Marilena Napolitano, Sebastiano Macheda, Angela Corea, Lucia Lentin, Michele Divella, Daniele Orso, Clara Zaghis, Silvia Del Rio, Serena Tomasino, Alessandro Brussa, Natascia D’Andrea, Simone Bressan, Giuseppe Neri, Pietro Giammanco, Alberto Nicolò Galvano, Mariachiara Ippolito, Fabrizio Ricci, Francesca Stefani, Lolita Fasoli, Piergiorgio Bresil, Federica Curto, Lorenzo Pirazzoli, Carlo Frangioni, Mattia Puppo, Sabrina Mussetta, Michele Autelli, Giuseppe Giglio, Filippo Riccone, Erika Taddei

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DOI: 10.1186/s44158-025-00291-6
Published: 2025-10-27
Container: Journal of Anesthesia, Analgesia and Critical Care
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1186/s44158-025-00291-6,
  title = {An interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study},
  author = {Danila Azzolina and Gianmaria Cammarota and Enrico Boero and Paola Berchialla and Savino Spadaro and Federico Longhini and Cristian Deana and Daniele Guerino Biasucci and Stefano D’Incà and Irene Batticci and Nicola Fasano and Edoardo De Robertis and Rachele Simonte and Salvatore Maurizio Maggiore and Valentina Bellini and Elena Giovanna Bignami and Luigi Vetrugno and Unknown and Vito Marco Ranieri and Anna Pesamosca and Agnese Cattarossi and Saskia Granzotti and Alessandro Cavarape and Andrea Cortegiani and Lisa Mattuzzi and Luca Flaibani and Nicola Federici and Francesco Meroi and Marco Tescione and Andrea Bruni and Eugenio Garofalo and Mattia Bernardinetti and Felice Urso and Camilla Colombotto and Francesco Forfori and Sandro Pregnolato and Francesco Corradi and Federico Dazzi and Sara Tempini and Alessandro Isirdi and Moro Federico and Nicole Giovane and Milo Vason and Carlo Alberto Volta and Fabio Gori and Michela Neri and Auro Caraffa and Giovanni Cosco and Eugenio Vadalà and Demetrio Labate and Nicola Polimeni and Marilena Napolitano and Sebastiano Macheda and Angela Corea and Lucia Lentin and Michele Divella and Daniele Orso and Clara Zaghis and Silvia Del Rio and Serena Tomasino and Alessandro Brussa and Natascia D’Andrea and Simone Bressan and Giuseppe Neri and Pietro Giammanco and Alberto Nicolò Galvano and Mariachiara Ippolito and Fabrizio Ricci and Francesca Stefani and Lolita Fasoli and Piergiorgio Bresil and Federica Curto and Lorenzo Pirazzoli and Carlo Frangioni and Mattia Puppo and Sabrina Mussetta and Michele Autelli and Giuseppe Giglio and Filippo Riccone and Erika Taddei},
  year = {2025},
  journal = {Journal of Anesthesia, Analgesia and Critical Care},
  doi = {10.1186/s44158-025-00291-6},
  url = {https://doi.org/10.1186/s44158-025-00291-6}
}

RIS

TY  - JOUR
TI  - An interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study
AU  - Danila Azzolina
AU  - Gianmaria Cammarota
AU  - Enrico Boero
AU  - Paola Berchialla
AU  - Savino Spadaro
AU  - Federico Longhini
AU  - Cristian Deana
AU  - Daniele Guerino Biasucci
AU  - Stefano D’Incà
AU  - Irene Batticci
AU  - Nicola Fasano
AU  - Edoardo De Robertis
AU  - Rachele Simonte
AU  - Salvatore Maurizio Maggiore
AU  - Valentina Bellini
AU  - Elena Giovanna Bignami
AU  - Luigi Vetrugno
AU  - Unknown
AU  - Vito Marco Ranieri
AU  - Anna Pesamosca
AU  - Agnese Cattarossi
AU  - Saskia Granzotti
AU  - Alessandro Cavarape
AU  - Andrea Cortegiani
AU  - Lisa Mattuzzi
AU  - Luca Flaibani
AU  - Nicola Federici
AU  - Francesco Meroi
AU  - Marco Tescione
AU  - Andrea Bruni
AU  - Eugenio Garofalo
AU  - Mattia Bernardinetti
AU  - Felice Urso
AU  - Camilla Colombotto
AU  - Francesco Forfori
AU  - Sandro Pregnolato
AU  - Francesco Corradi
AU  - Federico Dazzi
AU  - Sara Tempini
AU  - Alessandro Isirdi
AU  - Moro Federico
AU  - Nicole Giovane
AU  - Milo Vason
AU  - Carlo Alberto Volta
AU  - Fabio Gori
AU  - Michela Neri
AU  - Auro Caraffa
AU  - Giovanni Cosco
AU  - Eugenio Vadalà
AU  - Demetrio Labate
AU  - Nicola Polimeni
AU  - Marilena Napolitano
AU  - Sebastiano Macheda
AU  - Angela Corea
AU  - Lucia Lentin
AU  - Michele Divella
AU  - Daniele Orso
AU  - Clara Zaghis
AU  - Silvia Del Rio
AU  - Serena Tomasino
AU  - Alessandro Brussa
AU  - Natascia D’Andrea
AU  - Simone Bressan
AU  - Giuseppe Neri
AU  - Pietro Giammanco
AU  - Alberto Nicolò Galvano
AU  - Mariachiara Ippolito
AU  - Fabrizio Ricci
AU  - Francesca Stefani
AU  - Lolita Fasoli
AU  - Piergiorgio Bresil
AU  - Federica Curto
AU  - Lorenzo Pirazzoli
AU  - Carlo Frangioni
AU  - Mattia Puppo
AU  - Sabrina Mussetta
AU  - Michele Autelli
AU  - Giuseppe Giglio
AU  - Filippo Riccone
AU  - Erika Taddei
PY  - 2025
JO  - Journal of Anesthesia, Analgesia and Critical Care
DO  - 10.1186/s44158-025-00291-6
UR  - https://doi.org/10.1186/s44158-025-00291-6
ER  -

APA

Azzolina, D., Cammarota, G., Boero, E., Berchialla, P., Spadaro, S., Longhini, F., Deana, C., Biasucci, D. G., D’Incà, S., Batticci, I., Fasano, N., Robertis, E. D., Simonte, R., Maggiore, S. M., Bellini, V., Bignami, E. G., Vetrugno, L., Unknown, Ranieri, V. M., Pesamosca, A., Cattarossi, A., Granzotti, S., Cavarape, A., Cortegiani, A., Mattuzzi, L., Flaibani, L., Federici, N., Meroi, F., Tescione, M., Bruni, A., Garofalo, E., Bernardinetti, M., Urso, F., Colombotto, C., Forfori, F., Pregnolato, S., Corradi, F., Dazzi, F., Tempini, S., Isirdi, A., Federico, M., Giovane, N., Vason, M., Volta, C. A., Gori, F., Neri, M., Caraffa, A., Cosco, G., Vadalà, E., Labate, D., Polimeni, N., Napolitano, M., Macheda, S., Corea, A., Lentin, L., Divella, M., Orso, D., Zaghis, C., Rio, S. D., Tomasino, S., Brussa, A., D’Andrea, N., Bressan, S., Neri, G., Giammanco, P., Galvano, A. N., Ippolito, M., Ricci, F., Stefani, F., Fasoli, L., Bresil, P., Curto, F., Pirazzoli, L., Frangioni, C., Puppo, M., Mussetta, S., Autelli, M., Giglio, G., Riccone, F., & Taddei, E. (2025). An interpretable machine learning tool for predicting perioperative cardiac events in patients scheduled for hip fracture surgery: insights from the multicenter LUSHIP study. Journal of Anesthesia, Analgesia and Critical Care. https://doi.org/10.1186/s44158-025-00291-6

Source records

crossref · retrieved 2026-11-11T03:21:49.387Z