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Federated learning for describing COVID-19 patients and hospital outcomes: An unCoVer analysis
Background Since the onset of the pandemic, the unCoVer network has been identifying real-world data from EMR of hospitalised patients with COVID-19 across countries. These heterogeneous data are integrated into a multi-user data repository operated through Opal/DataSHIELD, an interoperable open-sou...
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Published in: | European journal of public health 2022-10, Vol.32 (Supplement_3) |
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container_title | European journal of public health |
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creator | Peñalvo, JL Mertens, E Cottam, J Berrozpe-Maldonado, V Fernández-Lobón, D Solarte-Pabón, O Menasalvas, E |
description | Background
Since the onset of the pandemic, the unCoVer network has been identifying real-world data from EMR of hospitalised patients with COVID-19 across countries. These heterogeneous data are integrated into a multi-user data repository operated through Opal/DataSHIELD, an interoperable open-source server application, providing privacy-preserving access to individual-level information for federated data analyses.
Methods
unCoVer's federated data platform provided access to EMR collected between 02/2020 - 04/2022 from 6 hospitals in Bosnia and Herzegovina (1), Romania (2), Spain (2), and Turkey (1) for a total of 14,236 patients. Demographics, and co-morbidities at admission, length of hospital stay and intensive care (ICU) needs, are presented according to the patients' status at discharge.
Results
A total of 11,248 (79.0%) of all patients reviewed recovered from COVID-19 after an average 11.5 (SD 10.8) days hospitalised, with only 4.09% of patients needing ICU. A smaller proportion of patients were transferred (5.93%), and 2143 (15.1%) were considered in-hospital deaths after an average 11.6 (SD 10.5) days in the hospital where most (81.2%) needed ICU. Recovered patients had a mean age of 57.7 (SD 16.3) years old, and gender neutral (51.2% men), in contrast to deceased patients that were 74.2 (SD 12.4) years old (59.7% men). Current smoking was infrequent for both recovered or deceased patients (3.27%, and 2.83%, respectively). Cardiometabolic conditions were less commonly reported among later recovered patients in comparison with deceased patients: obesity (10.7% vs 12.1%), diabetes (15.9% vs 27.4%), hypertension (23.2% vs 42.7%), and CVD (9.33% vs 44.9%). Chronic pulmonary disease was also more frequent among deceased patients (10.3% vs 18.1%).
Conclusions
Characteristics of hospitalised COVID-19 patients differ according to outcomes at discharge with more in-hospital death reported among older, chronic patients across 6 hospitals in 4 countries.
Key messages
* Federated analyses provide unique opportunities for robust results by privacy-preserving accessing individual-level data from heterogeneous data sources.
* The unCoVer network aims to demonstrate the usability of the infrastructure to address research questions related to the COVID-19 while extending the concept to other clinical areas. |
doi_str_mv | 10.1093/eurpub/ckac131.254 |
format | article |
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Since the onset of the pandemic, the unCoVer network has been identifying real-world data from EMR of hospitalised patients with COVID-19 across countries. These heterogeneous data are integrated into a multi-user data repository operated through Opal/DataSHIELD, an interoperable open-source server application, providing privacy-preserving access to individual-level information for federated data analyses.
Methods
unCoVer's federated data platform provided access to EMR collected between 02/2020 - 04/2022 from 6 hospitals in Bosnia and Herzegovina (1), Romania (2), Spain (2), and Turkey (1) for a total of 14,236 patients. Demographics, and co-morbidities at admission, length of hospital stay and intensive care (ICU) needs, are presented according to the patients' status at discharge.
Results
A total of 11,248 (79.0%) of all patients reviewed recovered from COVID-19 after an average 11.5 (SD 10.8) days hospitalised, with only 4.09% of patients needing ICU. A smaller proportion of patients were transferred (5.93%), and 2143 (15.1%) were considered in-hospital deaths after an average 11.6 (SD 10.5) days in the hospital where most (81.2%) needed ICU. Recovered patients had a mean age of 57.7 (SD 16.3) years old, and gender neutral (51.2% men), in contrast to deceased patients that were 74.2 (SD 12.4) years old (59.7% men). Current smoking was infrequent for both recovered or deceased patients (3.27%, and 2.83%, respectively). Cardiometabolic conditions were less commonly reported among later recovered patients in comparison with deceased patients: obesity (10.7% vs 12.1%), diabetes (15.9% vs 27.4%), hypertension (23.2% vs 42.7%), and CVD (9.33% vs 44.9%). Chronic pulmonary disease was also more frequent among deceased patients (10.3% vs 18.1%).
Conclusions
Characteristics of hospitalised COVID-19 patients differ according to outcomes at discharge with more in-hospital death reported among older, chronic patients across 6 hospitals in 4 countries.
Key messages
* Federated analyses provide unique opportunities for robust results by privacy-preserving accessing individual-level data from heterogeneous data sources.
* The unCoVer network aims to demonstrate the usability of the infrastructure to address research questions related to the COVID-19 while extending the concept to other clinical areas.</description><identifier>ISSN: 1101-1262</identifier><identifier>EISSN: 1464-360X</identifier><identifier>DOI: 10.1093/eurpub/ckac131.254</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>COVID-19 ; Data ; Demographics ; Diabetes ; Diabetes mellitus ; Federated learning ; Heart diseases ; Hospitals ; Hypertension ; Lung diseases ; Obesity ; Pandemics ; Patients ; Privacy ; Public health ; Smoking</subject><ispartof>European journal of public health, 2022-10, Vol.32 (Supplement_3)</ispartof><rights>The Author(s) 2022. Published by Oxford University Press on behalf of the European Public Health Association. 2022</rights><rights>The Author(s) 2022. Published by Oxford University Press on behalf of the European Public Health Association.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2024-227ce4c3ac6ec637a49faf6e870b5e8e34ad4e124e6c2178879dff03081ca54c3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,1604,27866,27924,27925</link.rule.ids></links><search><creatorcontrib>Peñalvo, JL</creatorcontrib><creatorcontrib>Mertens, E</creatorcontrib><creatorcontrib>Cottam, J</creatorcontrib><creatorcontrib>Berrozpe-Maldonado, V</creatorcontrib><creatorcontrib>Fernández-Lobón, D</creatorcontrib><creatorcontrib>Solarte-Pabón, O</creatorcontrib><creatorcontrib>Menasalvas, E</creatorcontrib><title>Federated learning for describing COVID-19 patients and hospital outcomes: An unCoVer analysis</title><title>European journal of public health</title><description>Background
Since the onset of the pandemic, the unCoVer network has been identifying real-world data from EMR of hospitalised patients with COVID-19 across countries. These heterogeneous data are integrated into a multi-user data repository operated through Opal/DataSHIELD, an interoperable open-source server application, providing privacy-preserving access to individual-level information for federated data analyses.
Methods
unCoVer's federated data platform provided access to EMR collected between 02/2020 - 04/2022 from 6 hospitals in Bosnia and Herzegovina (1), Romania (2), Spain (2), and Turkey (1) for a total of 14,236 patients. Demographics, and co-morbidities at admission, length of hospital stay and intensive care (ICU) needs, are presented according to the patients' status at discharge.
Results
A total of 11,248 (79.0%) of all patients reviewed recovered from COVID-19 after an average 11.5 (SD 10.8) days hospitalised, with only 4.09% of patients needing ICU. A smaller proportion of patients were transferred (5.93%), and 2143 (15.1%) were considered in-hospital deaths after an average 11.6 (SD 10.5) days in the hospital where most (81.2%) needed ICU. Recovered patients had a mean age of 57.7 (SD 16.3) years old, and gender neutral (51.2% men), in contrast to deceased patients that were 74.2 (SD 12.4) years old (59.7% men). Current smoking was infrequent for both recovered or deceased patients (3.27%, and 2.83%, respectively). Cardiometabolic conditions were less commonly reported among later recovered patients in comparison with deceased patients: obesity (10.7% vs 12.1%), diabetes (15.9% vs 27.4%), hypertension (23.2% vs 42.7%), and CVD (9.33% vs 44.9%). Chronic pulmonary disease was also more frequent among deceased patients (10.3% vs 18.1%).
Conclusions
Characteristics of hospitalised COVID-19 patients differ according to outcomes at discharge with more in-hospital death reported among older, chronic patients across 6 hospitals in 4 countries.
Key messages
* Federated analyses provide unique opportunities for robust results by privacy-preserving accessing individual-level data from heterogeneous data sources.
* The unCoVer network aims to demonstrate the usability of the infrastructure to address research questions related to the COVID-19 while extending the concept to other clinical areas.</description><subject>COVID-19</subject><subject>Data</subject><subject>Demographics</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Federated learning</subject><subject>Heart diseases</subject><subject>Hospitals</subject><subject>Hypertension</subject><subject>Lung diseases</subject><subject>Obesity</subject><subject>Pandemics</subject><subject>Patients</subject><subject>Privacy</subject><subject>Public health</subject><subject>Smoking</subject><issn>1101-1262</issn><issn>1464-360X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>7TQ</sourceid><recordid>eNqNkMtOwzAQRS0EEqXwA6wssXbrVxKHXRUoVKrUDVSssFxnAilpHOx40b8nVfoBrOaOdO5odBC6Z3TGaC7mEH0Xd3P7YywTbMYTeYEmTKaSiJR-XA6ZUUYYT_k1uglhTylNMsUn6HMJJXjTQ4kbML6t2y9cOY9LCNbXu9NabLarJ8Jy3Jm-hrYP2LQl_nahq3vTYBd76w4QHvGixbEt3Bb8QJjmGOpwi64q0wS4O88pel8-vxWvZL15WRWLNbGcckk4zyxIK4xNwaYiMzKvTJWCyuguAQVCmlIC4xJSy1mmVJaXVUUFVcyaZChO0cN4t_PuN0Lo9d5FPzwRNFeJzKlQLBkoPlLWuxA8VLrz9cH4o2ZUnzzq0aM-e9SDx6FExpKL3X_4PzWEeC8</recordid><startdate>20221021</startdate><enddate>20221021</enddate><creator>Peñalvo, JL</creator><creator>Mertens, E</creator><creator>Cottam, J</creator><creator>Berrozpe-Maldonado, V</creator><creator>Fernández-Lobón, D</creator><creator>Solarte-Pabón, O</creator><creator>Menasalvas, E</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>TOX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T2</scope><scope>7TQ</scope><scope>C1K</scope><scope>DHY</scope><scope>DON</scope><scope>K9.</scope><scope>NAPCQ</scope></search><sort><creationdate>20221021</creationdate><title>Federated learning for describing COVID-19 patients and hospital outcomes: An unCoVer analysis</title><author>Peñalvo, JL ; Mertens, E ; Cottam, J ; Berrozpe-Maldonado, V ; Fernández-Lobón, D ; Solarte-Pabón, O ; Menasalvas, E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2024-227ce4c3ac6ec637a49faf6e870b5e8e34ad4e124e6c2178879dff03081ca54c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>COVID-19</topic><topic>Data</topic><topic>Demographics</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Federated learning</topic><topic>Heart diseases</topic><topic>Hospitals</topic><topic>Hypertension</topic><topic>Lung diseases</topic><topic>Obesity</topic><topic>Pandemics</topic><topic>Patients</topic><topic>Privacy</topic><topic>Public health</topic><topic>Smoking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Peñalvo, JL</creatorcontrib><creatorcontrib>Mertens, E</creatorcontrib><creatorcontrib>Cottam, J</creatorcontrib><creatorcontrib>Berrozpe-Maldonado, V</creatorcontrib><creatorcontrib>Fernández-Lobón, D</creatorcontrib><creatorcontrib>Solarte-Pabón, O</creatorcontrib><creatorcontrib>Menasalvas, E</creatorcontrib><collection>Oxford Academic Journals (Open Access)</collection><collection>CrossRef</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>PAIS Index</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><jtitle>European journal of public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Peñalvo, JL</au><au>Mertens, E</au><au>Cottam, J</au><au>Berrozpe-Maldonado, V</au><au>Fernández-Lobón, D</au><au>Solarte-Pabón, O</au><au>Menasalvas, E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Federated learning for describing COVID-19 patients and hospital outcomes: An unCoVer analysis</atitle><jtitle>European journal of public health</jtitle><date>2022-10-21</date><risdate>2022</risdate><volume>32</volume><issue>Supplement_3</issue><issn>1101-1262</issn><eissn>1464-360X</eissn><abstract>Background
Since the onset of the pandemic, the unCoVer network has been identifying real-world data from EMR of hospitalised patients with COVID-19 across countries. These heterogeneous data are integrated into a multi-user data repository operated through Opal/DataSHIELD, an interoperable open-source server application, providing privacy-preserving access to individual-level information for federated data analyses.
Methods
unCoVer's federated data platform provided access to EMR collected between 02/2020 - 04/2022 from 6 hospitals in Bosnia and Herzegovina (1), Romania (2), Spain (2), and Turkey (1) for a total of 14,236 patients. Demographics, and co-morbidities at admission, length of hospital stay and intensive care (ICU) needs, are presented according to the patients' status at discharge.
Results
A total of 11,248 (79.0%) of all patients reviewed recovered from COVID-19 after an average 11.5 (SD 10.8) days hospitalised, with only 4.09% of patients needing ICU. A smaller proportion of patients were transferred (5.93%), and 2143 (15.1%) were considered in-hospital deaths after an average 11.6 (SD 10.5) days in the hospital where most (81.2%) needed ICU. Recovered patients had a mean age of 57.7 (SD 16.3) years old, and gender neutral (51.2% men), in contrast to deceased patients that were 74.2 (SD 12.4) years old (59.7% men). Current smoking was infrequent for both recovered or deceased patients (3.27%, and 2.83%, respectively). Cardiometabolic conditions were less commonly reported among later recovered patients in comparison with deceased patients: obesity (10.7% vs 12.1%), diabetes (15.9% vs 27.4%), hypertension (23.2% vs 42.7%), and CVD (9.33% vs 44.9%). Chronic pulmonary disease was also more frequent among deceased patients (10.3% vs 18.1%).
Conclusions
Characteristics of hospitalised COVID-19 patients differ according to outcomes at discharge with more in-hospital death reported among older, chronic patients across 6 hospitals in 4 countries.
Key messages
* Federated analyses provide unique opportunities for robust results by privacy-preserving accessing individual-level data from heterogeneous data sources.
* The unCoVer network aims to demonstrate the usability of the infrastructure to address research questions related to the COVID-19 while extending the concept to other clinical areas.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><doi>10.1093/eurpub/ckac131.254</doi><oa>free_for_read</oa></addata></record> |
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source | PubMed Central(OA); PAIS Index; Oxford Academic Journals (Open Access) |
subjects | COVID-19 Data Demographics Diabetes Diabetes mellitus Federated learning Heart diseases Hospitals Hypertension Lung diseases Obesity Pandemics Patients Privacy Public health Smoking |
title | Federated learning for describing COVID-19 patients and hospital outcomes: An unCoVer analysis |
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