biostudies-literatureLevin ASFundação de Amparo à Pesquisa do Estado de São Paulo246https://www.ebi.ac.uk/biostudies/studies/S-EPMC9490728biostudies-literatureUnknown22(1)<h4>Background</h4>Optimal COVID-19 management is still undefined. In this complicated scenario, the construction of a computational model capable of extracting information from electronic medical records, correlating signs, symptoms and medical prescriptions, could improve patient management/prognosis.<h4>Methods</h4>The aim of this study is to investigate the correlation between drug prescriptions and outcome in patients with COVID-19. We extracted data from 3674 medical records of hospitalized patients: drug prescriptions, outcome, and demographics. The outcome evaluated was hospital outcome. We applied correlation analysis using a Logistic Regression algorithm for machine learning with Lasso and Matthews correlation coefficient.<h4>Results</h4>We found correlations between drugs and paBMC medical informatics and decision makingCorrelating drug prescriptions with prognosis in severe COVID-19: first step towards resource management.PMC94907282020/12859-02020/07205-0Rocha MBonfa ECarlotti DPNMontal AOliveira MSSegurado AFialkovitz GKallas EGDuarte AJSFerreira JCMorais AMCosta SFFreire MPNastri ACSFigueiredo PHMFRodrigues DSSiciliano RFSabino ECHCFMUSP COVID-19 Study GroupFusco SFerreira JEFrancisco PBRios ICCarvalho CTanaka CMarchini JFMPerondi BMagri MMFabianeLazari CSNunes FLSde Jesus MAHarima LSFilho GBMarcilio ILevin ASUtiyama EFregonesi Mde Souza HPGuimaraes TBraido MCMarmo CPerdigao-Neto LVKawano YOfalseCorrelating drug prescriptions with prognosis in severe COVID-19: first step towards resource management.<h4>Background</h4>Optimal COVID-19 management is still undefined. In this complicated scenario, the construction of a computational model capable of extracting information from electronic medical records, correlating signs, symptoms and medical prescriptions, could improve patient management/prognosis.<h4>Methods</h4>The aim of this study is to investigate the correlation between drug prescriptions and outcome in patients with COVID-19. We extracted data from 3674 medical records of hospitalized patients: drug prescriptions, outcome, and demographics. The outcome evaluated was hospital outcome. We applied correlation analysis using a Logistic Regression algorithm for machine learning with Lasso and Matthews correlation coefficient.<h4>Results</h4>We found correlations between drugs and pa2022-01-01T00:00:00Z2022 Sep2025-04-26T22:00:59.776Z2024-10-15T07:18:32.241ZS-EPMC94907283613127410.1186/s12911-022-01983-7