Feature selection for the accurate prediction of septic and cardiogenic shock ICU mortality in the acute phase
Aushev, Alexander (Universitat Politècnica de Catalunya. Departament de Ciències de la Computació)
Ripoll, Vicent Ribas (Eurecat. Centre Tecnològic de Catalunya)
Vellido, Alfredo (Universitat Politècnica de Catalunya. Departament de Ciències de la Computació)
Aletti, Federico (University of California San Diego)
Pinto, Bernardo Bollen (Hôpitaux Universitaires de Genève)
Herpain, Antoine (Université Libre de Bruxelles)
Post, Emiel Hendrik (Department of Intensive Care, Hôpital Erasme - Université Libre de Bruxelles, Brussels, Belgium)
Medina, Eduardo Romay (Hospital Universitari MútuaTerrassa (Terrassa, Catalunya))
Ferrer, Ricard (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Baselli, Giuseppe (Politecnico di Milano)
Bendjelid, Karim (Hôpitaux Universitaires de Genève)
Universitat Autònoma de Barcelona

Data:	2018
Resum:	Circulatory shock is a life-threatening disease that accounts for around one-third of all admissions to intensive care units (ICU). It requires immediate treatment, which is why the development of tools for planning therapeutic interventions is required to deal with shock in the critical care environment. In this study, the ShockOmics European project original database is used to extract attributes capable of predicting mortality due to shock in the ICU. Missing data imputation techniques and machine learning models were used, followed by feature selection from different data subsets. Selected features were later used to build Bayesian Networks, revealing causal relationships between features and ICU outcome. The main result is a subset of predictive features that includes well-known indicators such as the SOFA and APACHE II scores, but also less commonly considered ones related to cardiovascular function assessed through echocardiograpy or shock treatment with pressors. Importantly, certain selected features are shown to be most predictive at certain time-steps. This means that, as shock progresses, different attributes could be prioritized. Clinical traits obtained at 24h. from ICU admission are shown to accurately predict cardiogenic and septic shock mortality, suggesting that relevant life-saving decisions could be made shortly after ICU admission.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	PloS one, Vol. 13 (november 2018) , ISSN 1932-6203

DOI: 10.1371/journal.pone.0199089
PMID: 30457997

18 p, 1.2 MB

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