@article{RN347,
   author = {Kostka, K. and Duarte-Salles, T. and Prats-Uribe, A. and Sena, A. G. and Pistillo, A. and Khalid, S. and Lai, L. Y. H. and Golozar, A. and Alshammari, T. M. and Dawoud, D. M. and Nyberg, F. and Wilcox, A. B. and Andryc, A. and Williams, A. and Ostropolets, A. and Areia, C. and Jung, C. Y. and Harle, C. A. and Reich, C. G. and Blacketer, C. and Morales, D. R. and Dorr, D. A. and Burn, E. and Roel, E. and Tan, E. H. and Minty, E. and DeFalco, F. and de Maeztu, G. and Lipori, G. and Alghoul, H. and Zhu, H. and Thomas, J. A. and Bian, J. and Park, J. and Martínez Roldán, J. and Posada, J. D. and Banda, J. M. and Horcajada, J. P. and Kohler, J. and Shah, K. and Natarajan, K. and Lynch, K. E. and Liu, L. and Schilling, L. M. and Recalde, M. and Spotnitz, M. and Gong, M. and Matheny, M. E. and Valveny, N. and Weiskopf, N. G. and Shah, N. and Alser, O. and Casajust, P. and Park, R. W. and Schuff, R. and Seager, S. and DuVall, S. L. and You, S. C. and Song, S. and Fernández-Bertolín, S. and Fortin, S. and Magoc, T. and Falconer, T. and Subbian, V. and Huser, V. and Ahmed, W. U. and Carter, W. and Guan, Y. and Galvan, Y. and He, X. and Rijnbeek, P. R. and Hripcsak, G. and Ryan, P. B. and Suchard, M. A. and Prieto-Alhambra, D.},
   title = {Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS},
   journal = {Clin Epidemiol},
   volume = {14},
   pages = {369-384},
   note = {1179-1349 Kostka, Kristin Orcid: 0000-0003-2595-8736 Duarte-Salles, Talita Orcid: 0000-0002-8274-0357 Prats-Uribe, Albert Orcid: 0000-0003-1202-9153 Sena, Anthony G Pistillo, Andrea Orcid: 0000-0002-4467-0220 Khalid, Sara Lai, Lana Y H Golozar, Asieh Alshammari, Thamir M Orcid: 0000-0002-5630-2468 Dawoud, Dalia M Nyberg, Fredrik Orcid: 0000-0003-0892-5668 Wilcox, Adam B Andryc, Alan Orcid: 0000-0002-2663-2298 Williams, Andrew Ostropolets, Anna Areia, Carlos Jung, Chi Young Harle, Christopher A Reich, Christian G Orcid: 0000-0002-3641-055x Blacketer, Clair Morales, Daniel R Dorr, David A Burn, Edward Orcid: 0000-0002-9286-1128 Roel, Elena Tan, Eng Hooi Minty, Evan DeFalco, Frank de Maeztu, Gabriel Lipori, Gigi Alghoul, Hiba Orcid: 0000-0001-8234-5843 Zhu, Hong Thomas, Jason A Bian, Jiang Park, Jimyung Orcid: 0000-0002-6998-2546 Martínez Roldán, Jordi Posada, Jose D Banda, Juan M Orcid: 0000-0001-8499-824x Horcajada, Juan P Orcid: 0000-0001-9873-5459 Kohler, Julianna Shah, Karishma Natarajan, Karthik Orcid: 0000-0002-9066-9431 Lynch, Kristine E Liu, Li Orcid: 0000-0002-5265-4159 Schilling, Lisa M Recalde, Martina Spotnitz, Matthew Gong, Mengchun Matheny, Michael E Valveny, Neus Orcid: 0000-0003-1105-5018 Weiskopf, Nicole G Shah, Nigam Alser, Osaid Casajust, Paula Orcid: 0000-0003-2733-5436 Park, Rae Woong Schuff, Robert Seager, Sarah DuVall, Scott L Orcid: 0000-0002-4898-3865 You, Seng Chan Song, Seokyoung Orcid: 0000-0002-5653-7005 Fernández-Bertolín, Sergio Fortin, Stephen Magoc, Tanja Orcid: 0000-0001-8213-2266 Falconer, Thomas Orcid: 0000-0001-6904-1394 Subbian, Vignesh Huser, Vojtech Ahmed, Waheed-Ul-Rahman Orcid: 0000-0003-0880-0355 Carter, William Orcid: 0000-0001-5346-3453 Guan, Yin Galvan, Yankuic He, Xing Rijnbeek, Peter R Hripcsak, George Ryan, Patrick B Suchard, Marc A Orcid: 0000-0001-9818-479x Prieto-Alhambra, Daniel Orcid: 0000-0002-3950-6346 INV-016201/GATES/Bill & Melinda Gates Foundation/United States INV-016910/GATES/Bill & Melinda Gates Foundation/United States R01 LM006910/LM/NLM NIH HHS/United States UL1 TR002369/TR/NCATS NIH HHS/United States INV-016284/GATES/Bill & Melinda Gates Foundation/United States INV-019257/GATES/Bill & Melinda Gates Foundation/United States Journal Article New Zealand 2022/03/30 Clin Epidemiol. 2022 Mar 22;14:369-384. doi: 10.2147/CLEP.S323292. eCollection 2022.},
   abstract = {PURPOSE: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. PATIENTS AND METHODS: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. RESULTS: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. CONCLUSION: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.},
   keywords = {Ohdsi
Omop cdm
descriptive epidemiology
open science
real world data
real world evidence ,
ISSN = 1179-1349 (Print) 1179-1349 ,
DOI = 10.2147/clep.S323292},
   year = {2022},
   type = {Journal Article}
}

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COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS","journal":"Clin Epidemiol","volume":"14","pages":"369-384","note":"1179-1349 Kostka, Kristin Orcid: 0000-0003-2595-8736 Duarte-Salles, Talita Orcid: 0000-0002-8274-0357 Prats-Uribe, Albert Orcid: 0000-0003-1202-9153 Sena, Anthony G Pistillo, Andrea Orcid: 0000-0002-4467-0220 Khalid, Sara Lai, Lana Y H Golozar, Asieh Alshammari, Thamir M Orcid: 0000-0002-5630-2468 Dawoud, Dalia M Nyberg, Fredrik Orcid: 0000-0003-0892-5668 Wilcox, Adam B Andryc, Alan Orcid: 0000-0002-2663-2298 Williams, Andrew Ostropolets, Anna Areia, Carlos Jung, Chi Young Harle, Christopher A Reich, Christian G Orcid: 0000-0002-3641-055x Blacketer, Clair Morales, Daniel R Dorr, David A Burn, Edward Orcid: 0000-0002-9286-1128 Roel, Elena Tan, Eng Hooi Minty, Evan DeFalco, Frank de Maeztu, Gabriel Lipori, Gigi Alghoul, Hiba Orcid: 0000-0001-8234-5843 Zhu, Hong Thomas, Jason A Bian, Jiang Park, Jimyung Orcid: 0000-0002-6998-2546 Martínez Roldán, Jordi Posada, Jose D Banda, Juan M Orcid: 0000-0001-8499-824x Horcajada, Juan P Orcid: 0000-0001-9873-5459 Kohler, Julianna Shah, Karishma Natarajan, Karthik Orcid: 0000-0002-9066-9431 Lynch, Kristine E Liu, Li Orcid: 0000-0002-5265-4159 Schilling, Lisa M Recalde, Martina Spotnitz, Matthew Gong, Mengchun Matheny, Michael E Valveny, Neus Orcid: 0000-0003-1105-5018 Weiskopf, Nicole G Shah, Nigam Alser, Osaid Casajust, Paula Orcid: 0000-0003-2733-5436 Park, Rae Woong Schuff, Robert Seager, Sarah DuVall, Scott L Orcid: 0000-0002-4898-3865 You, Seng Chan Song, Seokyoung Orcid: 0000-0002-5653-7005 Fernández-Bertolín, Sergio Fortin, Stephen Magoc, Tanja Orcid: 0000-0001-8213-2266 Falconer, Thomas Orcid: 0000-0001-6904-1394 Subbian, Vignesh Huser, Vojtech Ahmed, Waheed-Ul-Rahman Orcid: 0000-0003-0880-0355 Carter, William Orcid: 0000-0001-5346-3453 Guan, Yin Galvan, Yankuic He, Xing Rijnbeek, Peter R Hripcsak, George Ryan, Patrick B Suchard, Marc A Orcid: 0000-0001-9818-479x Prieto-Alhambra, Daniel Orcid: 0000-0002-3950-6346 INV-016201/GATES/Bill & Melinda Gates Foundation/United States INV-016910/GATES/Bill & Melinda Gates Foundation/United States R01 LM006910/LM/NLM NIH HHS/United States UL1 TR002369/TR/NCATS NIH HHS/United States INV-016284/GATES/Bill & Melinda Gates Foundation/United States INV-019257/GATES/Bill & Melinda Gates Foundation/United States Journal Article New Zealand 2022/03/30 Clin Epidemiol. 2022 Mar 22;14:369-384. doi: 10.2147/CLEP.S323292. eCollection 2022.","abstract":"PURPOSE: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. PATIENTS AND METHODS: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. RESULTS: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. CONCLUSION: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.","keywords":"Ohdsi Omop cdm descriptive epidemiology open science real world data real world evidence , ISSN = 1179-1349 (Print) 1179-1349 , DOI = 10.2147/clep.S323292","year":"2022","bibtex":"@article{RN347,\r\n author = {Kostka, K. and Duarte-Salles, T. and Prats-Uribe, A. and Sena, A. G. and Pistillo, A. and Khalid, S. and Lai, L. Y. H. and Golozar, A. and Alshammari, T. M. and Dawoud, D. M. and Nyberg, F. and Wilcox, A. B. and Andryc, A. and Williams, A. and Ostropolets, A. and Areia, C. and Jung, C. Y. and Harle, C. A. and Reich, C. G. and Blacketer, C. and Morales, D. R. and Dorr, D. A. and Burn, E. and Roel, E. and Tan, E. H. and Minty, E. and DeFalco, F. and de Maeztu, G. and Lipori, G. and Alghoul, H. and Zhu, H. and Thomas, J. A. and Bian, J. and Park, J. and Martínez Roldán, J. and Posada, J. D. and Banda, J. M. and Horcajada, J. P. and Kohler, J. and Shah, K. and Natarajan, K. and Lynch, K. E. and Liu, L. and Schilling, L. M. and Recalde, M. and Spotnitz, M. and Gong, M. and Matheny, M. E. and Valveny, N. and Weiskopf, N. G. and Shah, N. and Alser, O. and Casajust, P. and Park, R. W. and Schuff, R. and Seager, S. and DuVall, S. L. and You, S. C. and Song, S. and Fernández-Bertolín, S. and Fortin, S. and Magoc, T. and Falconer, T. and Subbian, V. and Huser, V. and Ahmed, W. U. and Carter, W. and Guan, Y. and Galvan, Y. and He, X. and Rijnbeek, P. R. and Hripcsak, G. and Ryan, P. B. and Suchard, M. A. and Prieto-Alhambra, D.},\r\n title = {Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS},\r\n journal = {Clin Epidemiol},\r\n volume = {14},\r\n pages = {369-384},\r\n note = {1179-1349 Kostka, Kristin Orcid: 0000-0003-2595-8736 Duarte-Salles, Talita Orcid: 0000-0002-8274-0357 Prats-Uribe, Albert Orcid: 0000-0003-1202-9153 Sena, Anthony G Pistillo, Andrea Orcid: 0000-0002-4467-0220 Khalid, Sara Lai, Lana Y H Golozar, Asieh Alshammari, Thamir M Orcid: 0000-0002-5630-2468 Dawoud, Dalia M Nyberg, Fredrik Orcid: 0000-0003-0892-5668 Wilcox, Adam B Andryc, Alan Orcid: 0000-0002-2663-2298 Williams, Andrew Ostropolets, Anna Areia, Carlos Jung, Chi Young Harle, Christopher A Reich, Christian G Orcid: 0000-0002-3641-055x Blacketer, Clair Morales, Daniel R Dorr, David A Burn, Edward Orcid: 0000-0002-9286-1128 Roel, Elena Tan, Eng Hooi Minty, Evan DeFalco, Frank de Maeztu, Gabriel Lipori, Gigi Alghoul, Hiba Orcid: 0000-0001-8234-5843 Zhu, Hong Thomas, Jason A Bian, Jiang Park, Jimyung Orcid: 0000-0002-6998-2546 Martínez Roldán, Jordi Posada, Jose D Banda, Juan M Orcid: 0000-0001-8499-824x Horcajada, Juan P Orcid: 0000-0001-9873-5459 Kohler, Julianna Shah, Karishma Natarajan, Karthik Orcid: 0000-0002-9066-9431 Lynch, Kristine E Liu, Li Orcid: 0000-0002-5265-4159 Schilling, Lisa M Recalde, Martina Spotnitz, Matthew Gong, Mengchun Matheny, Michael E Valveny, Neus Orcid: 0000-0003-1105-5018 Weiskopf, Nicole G Shah, Nigam Alser, Osaid Casajust, Paula Orcid: 0000-0003-2733-5436 Park, Rae Woong Schuff, Robert Seager, Sarah DuVall, Scott L Orcid: 0000-0002-4898-3865 You, Seng Chan Song, Seokyoung Orcid: 0000-0002-5653-7005 Fernández-Bertolín, Sergio Fortin, Stephen Magoc, Tanja Orcid: 0000-0001-8213-2266 Falconer, Thomas Orcid: 0000-0001-6904-1394 Subbian, Vignesh Huser, Vojtech Ahmed, Waheed-Ul-Rahman Orcid: 0000-0003-0880-0355 Carter, William Orcid: 0000-0001-5346-3453 Guan, Yin Galvan, Yankuic He, Xing Rijnbeek, Peter R Hripcsak, George Ryan, Patrick B Suchard, Marc A Orcid: 0000-0001-9818-479x Prieto-Alhambra, Daniel Orcid: 0000-0002-3950-6346 INV-016201/GATES/Bill & Melinda Gates Foundation/United States INV-016910/GATES/Bill & Melinda Gates Foundation/United States R01 LM006910/LM/NLM NIH HHS/United States UL1 TR002369/TR/NCATS NIH HHS/United States INV-016284/GATES/Bill & Melinda Gates Foundation/United States INV-019257/GATES/Bill & Melinda Gates Foundation/United States Journal Article New Zealand 2022/03/30 Clin Epidemiol. 2022 Mar 22;14:369-384. doi: 10.2147/CLEP.S323292. eCollection 2022.},\r\n abstract = {PURPOSE: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. PATIENTS AND METHODS: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. RESULTS: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. CONCLUSION: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.},\r\n keywords = {Ohdsi\r\nOmop cdm\r\ndescriptive epidemiology\r\nopen science\r\nreal world data\r\nreal world evidence ,\r\nISSN = 1179-1349 (Print) 1179-1349 ,\r\nDOI = 10.2147/clep.S323292},\r\n year = {2022},\r\n type = {Journal Article}\r\n}\r\n\r\n","author_short":["Kostka, K.","Duarte-Salles, T.","Prats-Uribe, A.","Sena, A. G.","Pistillo, A.","Khalid, S.","Lai, L. Y. H.","Golozar, A.","Alshammari, T. M.","Dawoud, D. M.","Nyberg, F.","Wilcox, A. B.","Andryc, A.","Williams, A.","Ostropolets, A.","Areia, C.","Jung, C. Y.","Harle, C. A.","Reich, C. G.","Blacketer, C.","Morales, D. R.","Dorr, D. A.","Burn, E.","Roel, E.","Tan, E. H.","Minty, E.","DeFalco, F.","de Maeztu, G.","Lipori, G.","Alghoul, H.","Zhu, H.","Thomas, J. A.","Bian, J.","Park, J.","Martínez Roldán, J.","Posada, J. D.","Banda, J. M.","Horcajada, J. P.","Kohler, J.","Shah, K.","Natarajan, K.","Lynch, K. E.","Liu, L.","Schilling, L. M.","Recalde, M.","Spotnitz, M.","Gong, M.","Matheny, M. E.","Valveny, N.","Weiskopf, N. G.","Shah, N.","Alser, O.","Casajust, P.","Park, R. W.","Schuff, R.","Seager, S.","DuVall, S. L.","You, S. C.","Song, S.","Fernández-Bertolín, S.","Fortin, S.","Magoc, T.","Falconer, T.","Subbian, V.","Huser, V.","Ahmed, W. U.","Carter, W.","Guan, Y.","Galvan, Y.","He, X.","Rijnbeek, P. R.","Hripcsak, G.","Ryan, P. B.","Suchard, M. A.","Prieto-Alhambra, D."],"key":"RN347","id":"RN347","bibbaseid":"kostka-duartesalles-pratsuribe-sena-pistillo-khalid-lai-golozar-etal-unravelingcovid19alargescalecharacterizationof45millioncovid19casesusingcharybdis-2022","role":"author","urls":{},"keyword":["Ohdsi Omop cdm descriptive epidemiology open science real world data real world evidence","ISSN = 1179-1349 (Print) 1179-1349","DOI = 10.2147/clep.S323292"],"metadata":{"authorlinks":{}},"html":""},"bibtype":"article","biburl":"https://bibbase.org/network/files/qwipow2DJsAxqNp83","dataSources":["PJSqX8FMpCPRdw3CQ","qLDnCcKM9omXNrRY8","TB9sD3avjy7bNxfgS","vDmJPYmHEKAT3tMNL","PcZMFHooKwpboi2he","jZMXEeHTfokmisJDv"],"keywords":["ohdsi omop cdm descriptive epidemiology open science real world data real world evidence","issn = 1179-1349 (print) 1179-1349","doi = 10.2147/clep.s323292"],"search_terms":["unraveling","covid","large","scale","characterization","million","covid","cases","using","charybdis","kostka","duarte-salles","prats-uribe","sena","pistillo","khalid","lai","golozar","alshammari","dawoud","nyberg","wilcox","andryc","williams","ostropolets","areia","jung","harle","reich","blacketer","morales","dorr","burn","roel","tan","minty","defalco","de maeztu","lipori","alghoul","zhu","thomas","bian","park","martínez roldán","posada","banda","horcajada","kohler","shah","natarajan","lynch","liu","schilling","recalde","spotnitz","gong","matheny","valveny","weiskopf","shah","alser","casajust","park","schuff","seager","duvall","you","song","fernández-bertolín","fortin","magoc","falconer","subbian","huser","ahmed","carter","guan","galvan","he","rijnbeek","hripcsak","ryan","suchard","prieto-alhambra"],"title":"Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS","year":2022}