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Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January-September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7-7.8%, p(FDR) < 0.001) and unspecified disorders of the brain (8.1%, 5.7-10.5%, p(FDR) < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19-25%), cerebrovascular diseases (24%, 13-35%), nontraumatic intracranial hemorrhage (34%, 20-50%), encephalitis and/or myelitis (37%, 17-60%) and myopathy (72%, 67-77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease.
Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19
Le, Trang T.;Gutiérrez-Sacristán, Alba;Son, Jiyeon;Hong, Chuan;South, Andrew M.;Beaulieu-Jones, Brett K.;Loh, Ne Hooi Will;Luo, Yuan;Morris, Michele;Ngiam, Kee Yuan;Patel, Lav P.;Samayamuthu, Malarkodi J.;Schriver, Emily;Tan, Amelia L. M.;Moore, Jason;Cai, Tianxi;Omenn, Gilbert S.;Avillach, Paul;Kohane, Isaac S.;Aaron, James R.;Agapito, Giuseppe;Albayrak, Adem;Alessiani, Mario;Amendola, Danilo F.;Angoulvant, François;Anthony, Li L. L. J.;Aronow, Bruce J.;Atz, Andrew;Balshi, James;Bell, Douglas S.;Bellasi, Antonio;Bellazzi, Riccardo;Benoit, Vincent;Beraghi, Michele;Bernal Sobrino, José Luis;Bernaux, Mélodie;Bey, Romain;Blanco Martínez, Alvar;Boeker, Martin;Bonzel, Clara-Lea;Booth, John;Bosari, Silvano;Bourgeois, Florence T.;Bradford, Robert L.;Brat, Gabriel A.;Bréant, Stéphane;Brown, Nicholas W.;Bryant, William A.;Bucalo, Mauro;Burgun, Anita;Cannataro, Mario;Carmona, Aldo;Caucheteux, Charlotte;Champ, Julien;Chen, Krista;Chen, Jin;Chiovato, Luca;Chiudinelli, Lorenzo;Cimino, James J.;Colicchio, Tiago K.;Cormont, Sylvie;Cossin, Sébastien;Craig, Jean B.;Cruz Bermúdez, Juan Luis;Cruz Rojo, Jaime;Dagliati, Arianna;Daniar, Mohamad;Daniel, Christel;Davoudi, Anahita;Devkota, Batsal;Dubiel, Julien;Esteve, Loic;Fan, Shirley;Follett, Robert W.;Gaiolla, Paula S. A.;Ganslandt, Thomas;García Barrio, Noelia;Garmire, Lana X.;Gehlenborg, Nils;Geva, Alon;Gradinger, Tobias;Gramfort, Alexandre;Griffier, Romain;Griffon, Nicolas;Grisel, Olivier;Hanauer, David A.;Haverkamp, Christian;He, Bing;Henderson, Darren W.;Hilka, Martin;Holmes, John H.;Horki, Petar;Huling, Kenneth M.;Hutch, Meghan R.;Issitt, Richard W.;Jannot, Anne Sophie;Jouhet, Vianney;Kavuluru, Ramakanth;Keller, Mark S.;Kirchoff, Katie;Klann, Jeffrey G.;Krantz, Ian D.;Kraska, Detlef;Krishnamurthy, Ashok K.;L’Yi, Sehi;Leblanc, Judith;Leite, Andressa R. R.;Lemaitre, Guillaume;Lenert, Leslie;Leprovost, Damien;Liu, Molei;Lozano-Zahonero, Sarah;Lynch, Kristine E.;Mahmood, Sadiqa;Maidlow, Sarah;Makoudjou Tchendjou, Adeline C.;Malovini, Alberto;Mandl, Kenneth D.;Mao, Chengsheng;Maram, Anupama;Martel, Patricia;Masino, Aaron J.;Matheny, Michael E.;Maulhardt, Thomas;Mazzitelli, Maria;McDuffie, Michael T.;Mensch, Arthur;Ashraf, Fatima;Milano, Marianna;Minicucci, Marcos F.;Moal, Bertrand;Moraleda, Cinta;Morris, Jeffrey S.;Moshal, Karyn L.;Mousavi, Sajad;Murad, Douglas A.;Murphy, Shawn N.;Naughton, Thomas P.;Neuraz, Antoine;Norman, James B.;Obeid, Jihad;Okoshi, Marina P.;Olson, Karen L.;Orlova, Nina;Ostasiewski, Brian D.;Palmer, Nathan P.;Paris, Nicolas;Pedrera Jimenez, Miguel;Pfaff, Emily R.;Pillion, Danielle;Prokosch, Hans U.;Prudente, Robson A.;Quirós González, Víctor;Ramoni, Rachel B.;Raskin, Maryna;Rieg, Siegbert;Roig Domínguez, Gustavo;Rojo, Pablo;Sáez, Carlos;Salamanca, Elisa;Sandrin, Arnaud;Santos, Janaina C. C.;Savino, Maria;Schuettler, Juergen;Scudeller, Luigia;Sebire, Neil J.;Balazote, Pablo Serrano;Serre, Patricia;Serret-Larmande, Arnaud;Shakeri, Zahra;Silvio, Domenick;Sliz, Piotr;Sonday, Charles;Spiridou, Anastasia;Tan, Bryce W. Q.;Tan, Byorn W. L.;Tanni, Suzana E.;Taylor, Deanne M.;Terriza-Torres, Ana I.;Tibollo, Valentina;Tippmann, Patric;Torti, Carlo;Trecarichi, Enrico M.;Tseng, Yi-Ju;Vallejos, Andrew K.;Varoquaux, Gael;Vella, Margaret;Vie, Jill-Jênn;Vitacca, Michele;Wagholikar, Kavishwar B.;Waitman, Lemuel R.;Wassermann, Demian;Weber, Griffin M.;William, Yuan;Yehya, Nadir;Zambelli, Alberto;Zhang, Harrison G.;Zoeller, Daniela;Zucco, Chiara;Visweswaran, Shyam;Mowery, Danielle L.;Xia, Zongqi;null, null
2021-01-01
Abstract
Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January-September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7-7.8%, p(FDR) < 0.001) and unspecified disorders of the brain (8.1%, 5.7-10.5%, p(FDR) < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19-25%), cerebrovascular diseases (24%, 13-35%), nontraumatic intracranial hemorrhage (34%, 20-50%), encephalitis and/or myelitis (37%, 17-60%) and myopathy (72%, 67-77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1491955
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.