| Autor: |
Nikolas Bernaola, Guillermo de Lima, Miguel Riaño, Lucia Llanos, Sarah Heili-Frades, Olga Sanchez, Antonio Lara, Guillermo Plaza, Cesar Carballo, Paloma Gallego, Pedro Larrañaga, Concha Bielza |
| Rok vydání: |
2022 |
| DOI: |
10.1101/2022.05.09.22274832 |
| Popis: |
ObjectivesTo present a model that enhances the accuracy of clinicians when presented with a possibly critical Covid-19 patient.MethodsA retrospective study was performed with information of 5,745 SARS-CoV2 infected patients admitted to the Emergency room of 4 public Hospitals in Madrid belonging to Quirón Salud Health Group (QS) from March 2020 to February 2021. Demographics, clinical variables on admission, laboratory markers and therapeutic interventions were extracted from Electronic Clinical Records. Traits related to mortality were found through difference in means testing and through feature selection by learning multiple classification trees with random initialization and selecting the ones that were used the most. We validated the model through cross-validation and tested generalization with an external dataset from 4 hospitals belonging to Sanitas Hospitals Health Group. The usefulness of two different models in real cases was tested by measuring the effect of exposure to the model decision on the accuracy of medical professionals.ResultsOf the 5,745 admitted patients, 1,173 died. Of the 110 variables in the dataset, 34 were found to be related with our definition of criticality (death in |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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