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10 p, 927.8 KB A machine learning predictive model for post-ureteroscopy urosepsis needing intensive care unit admission : A case-control yau endourology study from nine european centres / Pietropaolo, A. (University Hospital Southampton. Department of Urology) ; Geraghty, R.M. (Freeman Hospital. Department of Urology) ; Veeratterapillay, R. (Freeman Hospital. Department of Urology) ; Rogers, Alistair (Freeman Hospital. Department of Urology) ; Kallidonis, P. (University of Patras. Department of Urology) ; Villa, L. (IRCCS Ospedale San Raffaele. Urology) ; Boeri, Luca (IRCCS Fondazione Ca Granda Ospedale Maggiore Policlinico (Milà, Itàlia)) ; Montanari, E. (IRCCS Fondazione Ca' Granda-Ospedale Maggiore Policlinico. University of Milan) ; Atis, G. (Istanbul Medeniyet University. Department of Urology) ; Emiliani, Esteban (Institut d'Investigació Biomèdica Sant Pau) ; Sener, T.E. (Marmara University. Department of Urology) ; Al Jaafari, F. (Victoria Hospital) ; Fitzpatrick, J. (Freeman Hospital. Department of Urology) ; Shaw, M. (Freeman Hospital. Department of Urology) ; Harding, C. (Freeman Hospital. Department of Urology) ; Somani, B.K. (University Hospital Southampton. Department of Urology)
Introduction: With the rise in the use of ureteroscopy and laser stone lithotripsy (URSL), a proportionate increase in the risk of post-procedural urosepsis has also been observed. The aims of our paper were to analyse the predictors for severe urosepsis using a machine learning model (ML) in patients that needed intensive care unit (ICU) admission and to make comparisons with a matched cohort. [...]
2021 - 10.3390/jcm10173888
Journal of clinical medicine, Vol. 10 Núm. 17 (january 2021) , p. 3888  
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