A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients
Abstract Patients with influenza and SARS-CoV2/Coronavirus disease 2019 (COVID-19) infections have a different clinical course and outcomes. We developed and validated a supervised machine learning pipeline to distinguish the two viral infections using the available vital signs and demographic datas...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-06-01
|
| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-021-00467-8 |
| _version_ | 1797430123690983424 |
|---|---|
| author | Naveena Yanamala Nanda H. Krishna Quincy A. Hathaway Aditya Radhakrishnan Srinidhi Sunkara Heenaben Patel Peter Farjo Brijesh Patel Partho P. Sengupta |
| author_facet | Naveena Yanamala Nanda H. Krishna Quincy A. Hathaway Aditya Radhakrishnan Srinidhi Sunkara Heenaben Patel Peter Farjo Brijesh Patel Partho P. Sengupta |
| author_sort | Naveena Yanamala |
| collection | DOAJ |
| description | Abstract Patients with influenza and SARS-CoV2/Coronavirus disease 2019 (COVID-19) infections have a different clinical course and outcomes. We developed and validated a supervised machine learning pipeline to distinguish the two viral infections using the available vital signs and demographic dataset from the first hospital/emergency room encounters of 3883 patients who had confirmed diagnoses of influenza A/B, COVID-19 or negative laboratory test results. The models were able to achieve an area under the receiver operating characteristic curve (ROC AUC) of at least 97% using our multiclass classifier. The predictive models were externally validated on 15,697 encounters in 3125 patients available on TrinetX database that contains patient-level data from different healthcare organizations. The influenza vs COVID-19-positive model had an AUC of 98.8%, and 92.8% on the internal and external test sets, respectively. Our study illustrates the potentials of machine-learning models for accurately distinguishing the two viral infections. The code is made available at https://github.com/ynaveena/COVID-19-vs-Influenza and may have utility as a frontline diagnostic tool to aid healthcare workers in triaging patients once the two viral infections start cocirculating in the communities. |
| first_indexed | 2024-03-09T09:24:05Z |
| format | Article |
| id | doaj.art-72d1d24198684f2fb4d0f2544abe5ac2 |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-09T09:24:05Z |
| publishDate | 2021-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-72d1d24198684f2fb4d0f2544abe5ac22023-12-02T06:49:29ZengNature Portfolionpj Digital Medicine2398-63522021-06-014111010.1038/s41746-021-00467-8A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patientsNaveena Yanamala0Nanda H. Krishna1Quincy A. Hathaway2Aditya Radhakrishnan3Srinidhi Sunkara4Heenaben Patel5Peter Farjo6Brijesh Patel7Partho P. Sengupta8Division of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteDivision of Cardiology, West Virginia University Medicine Heart & Vascular InstituteAbstract Patients with influenza and SARS-CoV2/Coronavirus disease 2019 (COVID-19) infections have a different clinical course and outcomes. We developed and validated a supervised machine learning pipeline to distinguish the two viral infections using the available vital signs and demographic dataset from the first hospital/emergency room encounters of 3883 patients who had confirmed diagnoses of influenza A/B, COVID-19 or negative laboratory test results. The models were able to achieve an area under the receiver operating characteristic curve (ROC AUC) of at least 97% using our multiclass classifier. The predictive models were externally validated on 15,697 encounters in 3125 patients available on TrinetX database that contains patient-level data from different healthcare organizations. The influenza vs COVID-19-positive model had an AUC of 98.8%, and 92.8% on the internal and external test sets, respectively. Our study illustrates the potentials of machine-learning models for accurately distinguishing the two viral infections. The code is made available at https://github.com/ynaveena/COVID-19-vs-Influenza and may have utility as a frontline diagnostic tool to aid healthcare workers in triaging patients once the two viral infections start cocirculating in the communities.https://doi.org/10.1038/s41746-021-00467-8 |
| spellingShingle | Naveena Yanamala Nanda H. Krishna Quincy A. Hathaway Aditya Radhakrishnan Srinidhi Sunkara Heenaben Patel Peter Farjo Brijesh Patel Partho P. Sengupta A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients npj Digital Medicine |
| title | A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients |
| title_full | A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients |
| title_fullStr | A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients |
| title_full_unstemmed | A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients |
| title_short | A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients |
| title_sort | vital sign based prediction algorithm for differentiating covid 19 versus seasonal influenza in hospitalized patients |
| url | https://doi.org/10.1038/s41746-021-00467-8 |
| work_keys_str_mv | AT naveenayanamala avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT nandahkrishna avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT quincyahathaway avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT adityaradhakrishnan avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT srinidhisunkara avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT heenabenpatel avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT peterfarjo avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT brijeshpatel avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT parthopsengupta avitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT naveenayanamala vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT nandahkrishna vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT quincyahathaway vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT adityaradhakrishnan vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT srinidhisunkara vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT heenabenpatel vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT peterfarjo vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT brijeshpatel vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients AT parthopsengupta vitalsignbasedpredictionalgorithmfordifferentiatingcovid19versusseasonalinfluenzainhospitalizedpatients |