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COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

Fatemeh Torabi Orcid Logo, Johan H Thygesen Orcid Logo, Christopher Tomlinson Orcid Logo, Sam Hollings, Mehrdad Mizani Orcid Logo, Alex Handy Orcid Logo, Ashley Akbari Orcid Logo, Amitava Banerjee Orcid Logo, Jennifer Cooper Orcid Logo, Alvina Lai Orcid Logo, Ken Li, Bilal Mateen Orcid Logo, Naveed Sattar Orcid Logo, Reecha Sofat Orcid Logo, Ana Torralbo Orcid Logo, Honghan Wu Orcid Logo, Angela Wood Orcid Logo, Jonathan A C Sterne Orcid Logo, Christina Pagel Orcid Logo, William Whiteley Orcid Logo, Cathie Sudlow Orcid Logo, Harry Hemingway Orcid Logo, Spiros Denaxas Orcid Logo, Hoda Abbasizanjani, Nida Ahmed, Badar Ahmed, Ashley Akbari, Abdul Qadr Akinoso-Imran, Elias Allara, Freya Allery, Emanuele Di Angelantonio, Mark Ashworth, Vandana Ayyar-Gupta, Sonya Babu-Narayan, Seb Bacon, Steve Ball, Ami Banerjee, Mark Barber, Jessica Barrett, Marion Bennie, Colin Berry, Jennifer Beveridge, Ewan Birney, Lana Bojanić, Thomas Bolton, Anna Bone, Jon Boyle, Tasanee Braithwaite, Ben Bray, Norman Briffa, David Brind, Katherine Brown, Maya Buch, Dexter Canoy, Massimo Caputo, Raymond Carragher, Alan Carson, Genevieve Cezard, Jen-Yu Amy Chang, Kate Cheema, Richard Chin, Yogini Chudasama, Jennifer Cooper, Emma Copland, Rebecca Crallan, Rachel Cripps, David Cromwell, Vasa Curcin, Gwenetta Curry, Caroline Dale, John Danesh, Jayati Das-Munshi, Ashkan Dashtban, Alun Davies, Joanna Davies, Gareth Davies, Neil Davies, Joshua Day, Antonella Delmestri, Spiros Denaxas, Rachel Denholm, John Dennis, Alastair Denniston, Salil Deo, Baljean Dhillon, Annemarie Docherty, Tim Dong, Abdel Douiri, Johnny Downs, Alexandru Dregan, Elizabeth A Ellins, Martha Elwenspoek, Fabian Falck, Florian Falter, Yat Yi Fan, Joseph Firth, Lorna Fraser, Rocco Friebel, Amir Gavrieli, Moritz Gerstung, Ruth Gilbert, Clare Gillies, Myer Glickman, Ben Goldacre, Raph Goldacre, Felix Greaves, Mark Green, Luca Grieco, Rowena Griffiths, Deepti Gurdasani, Julian Halcox, Nick Hall, Tuankasfee Hama, Alex Handy, Anna Hansell, Pia Hardelid, Flavien Hardy, Daniel Harris, Camille Harrison, Katie Harron, Abdelaali Hassaine, Lamiece Hassan, Russell Healey, Harry Hemingway, Angela Henderson, Naomi Herz, Johannes Heyl, Mira Hidajat, Irene Higginson, Rosie Hinchliffe, Julia Hippisley-Cox, Frederick Ho, Mevhibe Hocaoglu, Sam Hollings, Elsie Horne, David Hughes, Ben Humberstone, Mike Inouye, Samantha Ip, Nazrul Islam, Caroline Jackson, David Jenkins, Xiyun Jiang, Shane Johnson, Umesh Kadam, Costas Kallis, Zainab Karim, Jake Kasan, Michalis Katsoulis, Kim Kavanagh, Frank Kee, Spencer Keene, Seamus Kent, Sara Khalid, Anthony Khawaja, Kamlesh Khunti, Richard Killick, Deborah Kinnear, Rochelle Knight, Ruwanthi Kolamunnage-Dona, Evan Kontopantelis, Amanj Kurdi, Ben Lacey, Alvina Lai, Andrew Lambarth, Milad Nazarzadeh Larzjan, Deborah Lawler, Thomas Lawrence, Claire Lawson, Qiuju Li, Ken Li, Miguel Bernabeu Llinares, Paula Lorgelly, Deborah Lowe, Jane Lyons, Ronan Lyons, Pedro Machado, Mary Joan Macleod, John Macleod, Evaleen Malgapo, Mamas Mamas, Mohammad Mamouei, Sinduja Manohar, Rutendo Mapeta, Javiera Leniz Martelli, David Moreno Martos, Bilal Mateen, Aoife McCarthy, Craig Melville, Rebecca Milton, Mehrdad Mizani, Marta Pineda Moncusi, Daniel Morales, Ify Mordi, Lynn Morrice, Carole Morris, Eva Morris, Yi Mu, Tanja Mueller, Lars Murdock, Vahé Nafilyan, George Nicholson, Elena Nikiphorou, John Nolan, Tom Norris, Ruth Norris, Laura North, Teri-Louise North, Dan O'Connell, Dominic Oliver, Adejoke Oluyase, Abraham Olvera-Barrios, Efosa Omigie, Sarah Onida, Sandosh Padmanabhan, Tom Palmer, Laura Pasea, Riyaz Patel, Rupert Payne, Jill Pell, Carmen Petitjean, Arun Pherwani, Owen Pickrell, Livia Pierotti, Munir Pirmohamed, Rouven Priedon, Dani Prieto-Alhambra, Alastair Proudfoot, Terry Quinn, Jennifer Quint, Elena Raffetti, Kazem Rahimi, Shishir Rao, Cameron Razieh, Brian Roberts, Caroline Rogers, Jennifer Rossdale, Safa Salim, Nilesh Samani, Naveed Sattar, Christian Schnier, Roy Schwartz, David Selby, Olena Seminog, Sharmin Shabnam, Ajay Shah, Jon Shelton, James Sheppard, Shubhra Sinha, Mirek Skrypak, Martina Slapkova, Katherine Sleeman, Craig Smith, Reecha Sofat, Filip Sosenko, Matthew Sperrin, Sarah Steeg, Jonathan Sterne, Serban Stoica, Maria Sudell, Cathie Sudlow, Luanluan Sun, Arun Karthikeyan Suseeladevi, Michael Sweeting, Matt Sydes, Rohan Takhar, Howard Tang, Johan Thygesen, George Tilston, Claire Tochel, Clea du Toit, Christopher Tomlinson, Renin Toms, Fatemeh Torabi, Ana Torralbo, Julia Townson, Adnan Tufail, Tapiwa Tungamirai, Susheel Varma, Sebastian Vollmer, Venexia Walker, Tianxiao Wang, Huan Wang, Alasdair Warwick, Ruth Watkinson, Harry Watson, William Whiteley, Hannah Whittaker, Harry Wilde, Tim Wilkinson, Gareth Williams, Michelle Williams, Richard Williams, Eloise Withnell, Charles Wolfe, Angela Wood, Lucy Wright, Honghan Wu, Jinge Wu, Jianhua Wu, Tom Yates, Francesco Zaccardi, Haoting Zhang, Huayu Zhang, Luisa Zuccolo

The Lancet Digital Health, Volume: 4, Issue: 7, Pages: e542 - e557

Swansea University Authors: Fatemeh Torabi Orcid Logo, Ashley Akbari Orcid Logo

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DOI (Published version): 10.1016/s2589-7500(22)00091-7

Abstract

BackgroundUpdatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible f...

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Published in: The Lancet Digital Health
ISSN: 2589-7500
Published: Elsevier BV 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58863
first_indexed 2021-12-31T14:15:04Z
last_indexed 2023-01-11T14:39:45Z
id cronfa58863
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-07-25T16:28:52.0746744</datestamp><bib-version>v2</bib-version><id>58863</id><entry>2021-12-01</entry><title>COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records</title><swanseaauthors><author><sid>f569591e1bfb0e405b8091f99fec45d3</sid><ORCID>0000-0002-5853-4625</ORCID><firstname>Fatemeh</firstname><surname>Torabi</surname><name>Fatemeh Torabi</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>aa1b025ec0243f708bb5eb0a93d6fb52</sid><ORCID>0000-0003-0814-0801</ORCID><firstname>Ashley</firstname><surname>Akbari</surname><name>Ashley Akbari</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-12-01</date><deptcode>MEDS</deptcode><abstract>BackgroundUpdatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.MethodsIn this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.FindingsAmong 57&#x2009;032&#x2009;174 individuals included in the cohort, 13&#x2009;990&#x2009;423 COVID-19 events were identified in 7&#x2009;244&#x2009;925 individuals, equating to an infection rate of 12&#xB7;7% during the study period. Of 7&#x2009;244&#x2009;925 individuals, 460&#x2009;737 (6&#xB7;4%) were admitted to hospital and 158&#x2009;020 (2&#xB7;2%) died. Of 460&#x2009;737 individuals who were admitted to hospital, 48&#x2009;847 (10&#xB7;6%) were admitted to the intensive care unit (ICU), 69&#x2009;090 (15&#xB7;0%) received non-invasive ventilation, and 25&#x2009;928 (5&#xB7;6%) received invasive ventilation. Among 384&#x2009;135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23&#x2009;485 [30&#xB7;4%] of 77&#x2009;202 patients) than wave 2 (44&#x2009;220 [23&#xB7;1%] of 191&#x2009;528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50&#xB7;7%] of 5063 patients). 15&#x2009;486 (9&#xB7;8%) of 158&#x2009;020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10&#x2009;884 (6&#xB7;9%) of 158&#x2009;020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1.InterpretationOur analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources.</abstract><type>Journal Article</type><journal>The Lancet Digital Health</journal><volume>4</volume><journalNumber>7</journalNumber><paginationStart>e542</paginationStart><paginationEnd>e557</paginationEnd><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2589-7500</issnPrint><issnElectronic/><keywords/><publishedDay>1</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2022</publishedYear><publishedDate>2022-07-01</publishedDate><doi>10.1016/s2589-7500(22)00091-7</doi><url/><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>British Heart Foundation Data Science Centre, led by Health Data Research UK.</funders><projectreference/><lastEdited>2022-07-25T16:28:52.0746744</lastEdited><Created>2021-12-01T15:56:12.1908707</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Fatemeh</firstname><surname>Torabi</surname><orcid>0000-0002-5853-4625</orcid><order>1</order></author><author><firstname>Johan H</firstname><surname>Thygesen</surname><orcid>0000-0002-7479-3459</orcid><order>2</order></author><author><firstname>Christopher</firstname><surname>Tomlinson</surname><orcid>0000-0002-0903-5395</orcid><order>3</order></author><author><firstname>Sam</firstname><surname>Hollings</surname><order>4</order></author><author><firstname>Mehrdad</firstname><surname>Mizani</surname><orcid>0000-0002-2441-895x</orcid><order>5</order></author><author><firstname>Alex</firstname><surname>Handy</surname><orcid>0000-0002-3739-1530</orcid><order>6</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>7</order></author><author><firstname>Amitava</firstname><surname>Banerjee</surname><orcid>0000-0001-8741-3411</orcid><order>8</order></author><author><firstname>Jennifer</firstname><surname>Cooper</surname><orcid>0000-0001-9364-7353</orcid><order>9</order></author><author><firstname>Alvina</firstname><surname>Lai</surname><orcid>0000-0001-8960-8095</orcid><order>10</order></author><author><firstname>Ken</firstname><surname>Li</surname><order>11</order></author><author><firstname>Bilal</firstname><surname>Mateen</surname><orcid>0000-0003-4423-6472</orcid><order>12</order></author><author><firstname>Naveed</firstname><surname>Sattar</surname><orcid>0000-0002-1604-2593</orcid><order>13</order></author><author><firstname>Reecha</firstname><surname>Sofat</surname><orcid>0000-0002-0242-6115</orcid><order>14</order></author><author><firstname>Ana</firstname><surname>Torralbo</surname><orcid>0000-0003-2738-8503</orcid><order>15</order></author><author><firstname>Honghan</firstname><surname>Wu</surname><orcid>0000-0002-0213-5668</orcid><order>16</order></author><author><firstname>Angela</firstname><surname>Wood</surname><orcid>0000-0002-7937-304x</orcid><order>17</order></author><author><firstname>Jonathan A C</firstname><surname>Sterne</surname><orcid>0000-0001-8496-6053</orcid><order>18</order></author><author><firstname>Christina</firstname><surname>Pagel</surname><orcid>0000-0002-2857-1628</orcid><order>19</order></author><author><firstname>William</firstname><surname>Whiteley</surname><orcid>0000-0002-4816-8991</orcid><order>20</order></author><author><firstname>Cathie</firstname><surname>Sudlow</surname><orcid>0000-0002-7725-7520</orcid><order>21</order></author><author><firstname>Harry</firstname><surname>Hemingway</surname><orcid>0000-0003-2279-0624</orcid><order>22</order></author><author><firstname>Spiros</firstname><surname>Denaxas</surname><orcid>0000-0001-9612-7791</orcid><order>23</order></author><author><firstname>Hoda</firstname><surname>Abbasizanjani</surname><order>24</order></author><author><firstname>Nida</firstname><surname>Ahmed</surname><order>25</order></author><author><firstname>Badar</firstname><surname>Ahmed</surname><order>26</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><order>27</order></author><author><firstname>Abdul 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Bernabeu</firstname><surname>Llinares</surname><order>172</order></author><author><firstname>Paula</firstname><surname>Lorgelly</surname><order>173</order></author><author><firstname>Deborah</firstname><surname>Lowe</surname><order>174</order></author><author><firstname>Jane</firstname><surname>Lyons</surname><order>175</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><order>176</order></author><author><firstname>Pedro</firstname><surname>Machado</surname><order>177</order></author><author><firstname>Mary 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Moreno</firstname><surname>Martos</surname><order>186</order></author><author><firstname>Bilal</firstname><surname>Mateen</surname><order>187</order></author><author><firstname>Aoife</firstname><surname>McCarthy</surname><order>188</order></author><author><firstname>Craig</firstname><surname>Melville</surname><order>189</order></author><author><firstname>Rebecca</firstname><surname>Milton</surname><order>190</order></author><author><firstname>Mehrdad</firstname><surname>Mizani</surname><order>191</order></author><author><firstname>Marta Pineda</firstname><surname>Moncusi</surname><order>192</order></author><author><firstname>Daniel</firstname><surname>Morales</surname><order>193</order></author><author><firstname>Ify</firstname><surname>Mordi</surname><order>194</order></author><author><firstname>Lynn</firstname><surname>Morrice</surname><order>195</order></author><author><firstname>Carole</firstname><surname>Morris</surname><order>196</order></author><author><firstname>Eva</firstname><surname>Morris</surname><order>197</order></author><author><firstname>Yi</firstname><surname>Mu</surname><order>198</order></author><author><firstname>Tanja</firstname><surname>Mueller</surname><order>199</order></author><author><firstname>Lars</firstname><surname>Murdock</surname><order>200</order></author><author><firstname>Vah&#xE9;</firstname><surname>Nafilyan</surname><order>201</order></author><author><firstname>George</firstname><surname>Nicholson</surname><order>202</order></author><author><firstname>Elena</firstname><surname>Nikiphorou</surname><order>203</order></author><author><firstname>John</firstname><surname>Nolan</surname><order>204</order></author><author><firstname>Tom</firstname><surname>Norris</surname><order>205</order></author><author><firstname>Ruth</firstname><surname>Norris</surname><order>206</order></author><author><firstname>Laura</firstname><surname>North</surname><order>207</order></author><author><firstname>Teri-Louise</firstname><surname>North</surname><order>208</order></author><author><firstname>Dan</firstname><surname>O'Connell</surname><order>209</order></author><author><firstname>Dominic</firstname><surname>Oliver</surname><order>210</order></author><author><firstname>Adejoke</firstname><surname>Oluyase</surname><order>211</order></author><author><firstname>Abraham</firstname><surname>Olvera-Barrios</surname><order>212</order></author><author><firstname>Efosa</firstname><surname>Omigie</surname><order>213</order></author><author><firstname>Sarah</firstname><surname>Onida</surname><order>214</order></author><author><firstname>Sandosh</firstname><surname>Padmanabhan</surname><order>215</order></author><author><firstname>Tom</firstname><surname>Palmer</surname><order>216</order></author><author><firstname>Laura</firstname><surname>Pasea</surname><order>217</order></author><author><firstname>Riyaz</firstname><surname>Patel</surname><order>218</order></author><author><firstname>Rupert</firstname><surname>Payne</surname><order>219</order></author><author><firstname>Jill</firstname><surname>Pell</surname><order>220</order></author><author><firstname>Carmen</firstname><surname>Petitjean</surname><order>221</order></author><author><firstname>Arun</firstname><surname>Pherwani</surname><order>222</order></author><author><firstname>Owen</firstname><surname>Pickrell</surname><order>223</order></author><author><firstname>Livia</firstname><surname>Pierotti</surname><order>224</order></author><author><firstname>Munir</firstname><surname>Pirmohamed</surname><order>225</order></author><author><firstname>Rouven</firstname><surname>Priedon</surname><order>226</order></author><author><firstname>Dani</firstname><surname>Prieto-Alhambra</surname><order>227</order></author><author><firstname>Alastair</firstname><surname>Proudfoot</surname><order>228</order></author><author><firstname>Terry</firstname><surname>Quinn</surname><order>229</order></author><author><firstname>Jennifer</firstname><surname>Quint</surname><order>230</order></author><author><firstname>Elena</firstname><surname>Raffetti</surname><order>231</order></author><author><firstname>Kazem</firstname><surname>Rahimi</surname><order>232</order></author><author><firstname>Shishir</firstname><surname>Rao</surname><order>233</order></author><author><firstname>Cameron</firstname><surname>Razieh</surname><order>234</order></author><author><firstname>Brian</firstname><surname>Roberts</surname><order>235</order></author><author><firstname>Caroline</firstname><surname>Rogers</surname><order>236</order></author><author><firstname>Jennifer</firstname><surname>Rossdale</surname><order>237</order></author><author><firstname>Safa</firstname><surname>Salim</surname><order>238</order></author><author><firstname>Nilesh</firstname><surname>Samani</surname><order>239</order></author><author><firstname>Naveed</firstname><surname>Sattar</surname><order>240</order></author><author><firstname>Christian</firstname><surname>Schnier</surname><order>241</order></author><author><firstname>Roy</firstname><surname>Schwartz</surname><order>242</order></author><author><firstname>David</firstname><surname>Selby</surname><order>243</order></author><author><firstname>Olena</firstname><surname>Seminog</surname><order>244</order></author><author><firstname>Sharmin</firstname><surname>Shabnam</surname><order>245</order></author><author><firstname>Ajay</firstname><surname>Shah</surname><order>246</order></author><author><firstname>Jon</firstname><surname>Shelton</surname><order>247</order></author><author><firstname>James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spelling 2022-07-25T16:28:52.0746744 v2 58863 2021-12-01 COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records f569591e1bfb0e405b8091f99fec45d3 0000-0002-5853-4625 Fatemeh Torabi Fatemeh Torabi true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 2021-12-01 MEDS BackgroundUpdatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.MethodsIn this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.FindingsAmong 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1.InterpretationOur analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Journal Article The Lancet Digital Health 4 7 e542 e557 Elsevier BV 2589-7500 1 7 2022 2022-07-01 10.1016/s2589-7500(22)00091-7 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University British Heart Foundation Data Science Centre, led by Health Data Research UK. 2022-07-25T16:28:52.0746744 2021-12-01T15:56:12.1908707 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Fatemeh Torabi 0000-0002-5853-4625 1 Johan H Thygesen 0000-0002-7479-3459 2 Christopher Tomlinson 0000-0002-0903-5395 3 Sam Hollings 4 Mehrdad Mizani 0000-0002-2441-895x 5 Alex Handy 0000-0002-3739-1530 6 Ashley Akbari 0000-0003-0814-0801 7 Amitava Banerjee 0000-0001-8741-3411 8 Jennifer Cooper 0000-0001-9364-7353 9 Alvina Lai 0000-0001-8960-8095 10 Ken Li 11 Bilal Mateen 0000-0003-4423-6472 12 Naveed Sattar 0000-0002-1604-2593 13 Reecha Sofat 0000-0002-0242-6115 14 Ana Torralbo 0000-0003-2738-8503 15 Honghan Wu 0000-0002-0213-5668 16 Angela Wood 0000-0002-7937-304x 17 Jonathan A C Sterne 0000-0001-8496-6053 18 Christina Pagel 0000-0002-2857-1628 19 William Whiteley 0000-0002-4816-8991 20 Cathie Sudlow 0000-0002-7725-7520 21 Harry Hemingway 0000-0003-2279-0624 22 Spiros Denaxas 0000-0001-9612-7791 23 Hoda Abbasizanjani 24 Nida Ahmed 25 Badar Ahmed 26 Ashley Akbari 27 Abdul Qadr Akinoso-Imran 28 Elias Allara 29 Freya Allery 30 Emanuele Di Angelantonio 31 Mark Ashworth 32 Vandana Ayyar-Gupta 33 Sonya Babu-Narayan 34 Seb Bacon 35 Steve Ball 36 Ami Banerjee 37 Mark Barber 38 Jessica Barrett 39 Marion Bennie 40 Colin Berry 41 Jennifer Beveridge 42 Ewan Birney 43 Lana Bojanić 44 Thomas Bolton 45 Anna Bone 46 Jon Boyle 47 Tasanee Braithwaite 48 Ben Bray 49 Norman Briffa 50 David Brind 51 Katherine Brown 52 Maya Buch 53 Dexter Canoy 54 Massimo Caputo 55 Raymond Carragher 56 Alan Carson 57 Genevieve Cezard 58 Jen-Yu Amy Chang 59 Kate Cheema 60 Richard Chin 61 Yogini Chudasama 62 Jennifer Cooper 63 Emma Copland 64 Rebecca Crallan 65 Rachel Cripps 66 David Cromwell 67 Vasa Curcin 68 Gwenetta Curry 69 Caroline Dale 70 John Danesh 71 Jayati Das-Munshi 72 Ashkan Dashtban 73 Alun Davies 74 Joanna Davies 75 Gareth Davies 76 Neil Davies 77 Joshua Day 78 Antonella Delmestri 79 Spiros Denaxas 80 Rachel Denholm 81 John Dennis 82 Alastair Denniston 83 Salil Deo 84 Baljean Dhillon 85 Annemarie Docherty 86 Tim Dong 87 Abdel Douiri 88 Johnny Downs 89 Alexandru Dregan 90 Elizabeth A Ellins 91 Martha Elwenspoek 92 Fabian Falck 93 Florian Falter 94 Yat Yi Fan 95 Joseph Firth 96 Lorna Fraser 97 Rocco Friebel 98 Amir Gavrieli 99 Moritz Gerstung 100 Ruth Gilbert 101 Clare Gillies 102 Myer Glickman 103 Ben Goldacre 104 Raph Goldacre 105 Felix Greaves 106 Mark Green 107 Luca Grieco 108 Rowena Griffiths 109 Deepti Gurdasani 110 Julian Halcox 111 Nick Hall 112 Tuankasfee Hama 113 Alex Handy 114 Anna Hansell 115 Pia Hardelid 116 Flavien Hardy 117 Daniel Harris 118 Camille Harrison 119 Katie Harron 120 Abdelaali Hassaine 121 Lamiece Hassan 122 Russell Healey 123 Harry Hemingway 124 Angela Henderson 125 Naomi Herz 126 Johannes Heyl 127 Mira Hidajat 128 Irene Higginson 129 Rosie Hinchliffe 130 Julia Hippisley-Cox 131 Frederick Ho 132 Mevhibe Hocaoglu 133 Sam Hollings 134 Elsie Horne 135 David Hughes 136 Ben Humberstone 137 Mike Inouye 138 Samantha Ip 139 Nazrul Islam 140 Caroline Jackson 141 David Jenkins 142 Xiyun Jiang 143 Shane Johnson 144 Umesh Kadam 145 Costas Kallis 146 Zainab Karim 147 Jake Kasan 148 Michalis Katsoulis 149 Kim Kavanagh 150 Frank Kee 151 Spencer Keene 152 Seamus Kent 153 Sara Khalid 154 Anthony Khawaja 155 Kamlesh Khunti 156 Richard Killick 157 Deborah Kinnear 158 Rochelle Knight 159 Ruwanthi Kolamunnage-Dona 160 Evan Kontopantelis 161 Amanj Kurdi 162 Ben Lacey 163 Alvina Lai 164 Andrew Lambarth 165 Milad Nazarzadeh Larzjan 166 Deborah Lawler 167 Thomas Lawrence 168 Claire Lawson 169 Qiuju Li 170 Ken Li 171 Miguel Bernabeu Llinares 172 Paula Lorgelly 173 Deborah Lowe 174 Jane Lyons 175 Ronan Lyons 176 Pedro Machado 177 Mary Joan Macleod 178 John Macleod 179 Evaleen Malgapo 180 Mamas Mamas 181 Mohammad Mamouei 182 Sinduja Manohar 183 Rutendo Mapeta 184 Javiera Leniz Martelli 185 David Moreno Martos 186 Bilal Mateen 187 Aoife McCarthy 188 Craig Melville 189 Rebecca Milton 190 Mehrdad Mizani 191 Marta Pineda Moncusi 192 Daniel Morales 193 Ify Mordi 194 Lynn Morrice 195 Carole Morris 196 Eva Morris 197 Yi Mu 198 Tanja Mueller 199 Lars Murdock 200 Vahé Nafilyan 201 George Nicholson 202 Elena Nikiphorou 203 John Nolan 204 Tom Norris 205 Ruth Norris 206 Laura North 207 Teri-Louise North 208 Dan O'Connell 209 Dominic Oliver 210 Adejoke Oluyase 211 Abraham Olvera-Barrios 212 Efosa Omigie 213 Sarah Onida 214 Sandosh Padmanabhan 215 Tom Palmer 216 Laura Pasea 217 Riyaz Patel 218 Rupert Payne 219 Jill Pell 220 Carmen Petitjean 221 Arun Pherwani 222 Owen Pickrell 223 Livia Pierotti 224 Munir Pirmohamed 225 Rouven Priedon 226 Dani Prieto-Alhambra 227 Alastair Proudfoot 228 Terry Quinn 229 Jennifer Quint 230 Elena Raffetti 231 Kazem Rahimi 232 Shishir Rao 233 Cameron Razieh 234 Brian Roberts 235 Caroline Rogers 236 Jennifer Rossdale 237 Safa Salim 238 Nilesh Samani 239 Naveed Sattar 240 Christian Schnier 241 Roy Schwartz 242 David Selby 243 Olena Seminog 244 Sharmin Shabnam 245 Ajay Shah 246 Jon Shelton 247 James Sheppard 248 Shubhra Sinha 249 Mirek Skrypak 250 Martina Slapkova 251 Katherine Sleeman 252 Craig Smith 253 Reecha Sofat 254 Filip Sosenko 255 Matthew Sperrin 256 Sarah Steeg 257 Jonathan Sterne 258 Serban Stoica 259 Maria Sudell 260 Cathie Sudlow 261 Luanluan Sun 262 Arun Karthikeyan Suseeladevi 263 Michael Sweeting 264 Matt Sydes 265 Rohan Takhar 266 Howard Tang 267 Johan Thygesen 268 George Tilston 269 Claire Tochel 270 Clea du Toit 271 Christopher Tomlinson 272 Renin Toms 273 Fatemeh Torabi 274 Ana Torralbo 275 Julia Townson 276 Adnan Tufail 277 Tapiwa Tungamirai 278 Susheel Varma 279 Sebastian Vollmer 280 Venexia Walker 281 Tianxiao Wang 282 Huan Wang 283 Alasdair Warwick 284 Ruth Watkinson 285 Harry Watson 286 William Whiteley 287 Hannah Whittaker 288 Harry Wilde 289 Tim Wilkinson 290 Gareth Williams 291 Michelle Williams 292 Richard Williams 293 Eloise Withnell 294 Charles Wolfe 295 Angela Wood 296 Lucy Wright 297 Honghan Wu 298 Jinge Wu 299 Jianhua Wu 300 Tom Yates 301 Francesco Zaccardi 302 Haoting Zhang 303 Huayu Zhang 304 Luisa Zuccolo 305 58863__24733__2ba7a3d8cfee48e0b58a0d26e4e7467e.pdf 58863.pdf 2022-07-25T16:27:33.2764592 Output 1269785 application/pdf Version of Record true © 2022 The Author(s). This is an Open Access article under the CC BY 4.0 license true eng https://creativecommons.org/licenses/by/4.0/
title COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
spellingShingle COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
Fatemeh Torabi
Ashley Akbari
title_short COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
title_full COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
title_fullStr COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
title_full_unstemmed COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
title_sort COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records
author_id_str_mv f569591e1bfb0e405b8091f99fec45d3
aa1b025ec0243f708bb5eb0a93d6fb52
author_id_fullname_str_mv f569591e1bfb0e405b8091f99fec45d3_***_Fatemeh Torabi
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
author Fatemeh Torabi
Ashley Akbari
author2 Fatemeh Torabi
Johan H Thygesen
Christopher Tomlinson
Sam Hollings
Mehrdad Mizani
Alex Handy
Ashley Akbari
Amitava Banerjee
Jennifer Cooper
Alvina Lai
Ken Li
Bilal Mateen
Naveed Sattar
Reecha Sofat
Ana Torralbo
Honghan Wu
Angela Wood
Jonathan A C Sterne
Christina Pagel
William Whiteley
Cathie Sudlow
Harry Hemingway
Spiros Denaxas
Hoda Abbasizanjani
Nida Ahmed
Badar Ahmed
Ashley Akbari
Abdul Qadr Akinoso-Imran
Elias Allara
Freya Allery
Emanuele Di Angelantonio
Mark Ashworth
Vandana Ayyar-Gupta
Sonya Babu-Narayan
Seb Bacon
Steve Ball
Ami Banerjee
Mark Barber
Jessica Barrett
Marion Bennie
Colin Berry
Jennifer Beveridge
Ewan Birney
Lana Bojanić
Thomas Bolton
Anna Bone
Jon Boyle
Tasanee Braithwaite
Ben Bray
Norman Briffa
David Brind
Katherine Brown
Maya Buch
Dexter Canoy
Massimo Caputo
Raymond Carragher
Alan Carson
Genevieve Cezard
Jen-Yu Amy Chang
Kate Cheema
Richard Chin
Yogini Chudasama
Jennifer Cooper
Emma Copland
Rebecca Crallan
Rachel Cripps
David Cromwell
Vasa Curcin
Gwenetta Curry
Caroline Dale
John Danesh
Jayati Das-Munshi
Ashkan Dashtban
Alun Davies
Joanna Davies
Gareth Davies
Neil Davies
Joshua Day
Antonella Delmestri
Spiros Denaxas
Rachel Denholm
John Dennis
Alastair Denniston
Salil Deo
Baljean Dhillon
Annemarie Docherty
Tim Dong
Abdel Douiri
Johnny Downs
Alexandru Dregan
Elizabeth A Ellins
Martha Elwenspoek
Fabian Falck
Florian Falter
Yat Yi Fan
Joseph Firth
Lorna Fraser
Rocco Friebel
Amir Gavrieli
Moritz Gerstung
Ruth Gilbert
Clare Gillies
Myer Glickman
Ben Goldacre
Raph Goldacre
Felix Greaves
Mark Green
Luca Grieco
Rowena Griffiths
Deepti Gurdasani
Julian Halcox
Nick Hall
Tuankasfee Hama
Alex Handy
Anna Hansell
Pia Hardelid
Flavien Hardy
Daniel Harris
Camille Harrison
Katie Harron
Abdelaali Hassaine
Lamiece Hassan
Russell Healey
Harry Hemingway
Angela Henderson
Naomi Herz
Johannes Heyl
Mira Hidajat
Irene Higginson
Rosie Hinchliffe
Julia Hippisley-Cox
Frederick Ho
Mevhibe Hocaoglu
Sam Hollings
Elsie Horne
David Hughes
Ben Humberstone
Mike Inouye
Samantha Ip
Nazrul Islam
Caroline Jackson
David Jenkins
Xiyun Jiang
Shane Johnson
Umesh Kadam
Costas Kallis
Zainab Karim
Jake Kasan
Michalis Katsoulis
Kim Kavanagh
Frank Kee
Spencer Keene
Seamus Kent
Sara Khalid
Anthony Khawaja
Kamlesh Khunti
Richard Killick
Deborah Kinnear
Rochelle Knight
Ruwanthi Kolamunnage-Dona
Evan Kontopantelis
Amanj Kurdi
Ben Lacey
Alvina Lai
Andrew Lambarth
Milad Nazarzadeh Larzjan
Deborah Lawler
Thomas Lawrence
Claire Lawson
Qiuju Li
Ken Li
Miguel Bernabeu Llinares
Paula Lorgelly
Deborah Lowe
Jane Lyons
Ronan Lyons
Pedro Machado
Mary Joan Macleod
John Macleod
Evaleen Malgapo
Mamas Mamas
Mohammad Mamouei
Sinduja Manohar
Rutendo Mapeta
Javiera Leniz Martelli
David Moreno Martos
Bilal Mateen
Aoife McCarthy
Craig Melville
Rebecca Milton
Mehrdad Mizani
Marta Pineda Moncusi
Daniel Morales
Ify Mordi
Lynn Morrice
Carole Morris
Eva Morris
Yi Mu
Tanja Mueller
Lars Murdock
Vahé Nafilyan
George Nicholson
Elena Nikiphorou
John Nolan
Tom Norris
Ruth Norris
Laura North
Teri-Louise North
Dan O'Connell
Dominic Oliver
Adejoke Oluyase
Abraham Olvera-Barrios
Efosa Omigie
Sarah Onida
Sandosh Padmanabhan
Tom Palmer
Laura Pasea
Riyaz Patel
Rupert Payne
Jill Pell
Carmen Petitjean
Arun Pherwani
Owen Pickrell
Livia Pierotti
Munir Pirmohamed
Rouven Priedon
Dani Prieto-Alhambra
Alastair Proudfoot
Terry Quinn
Jennifer Quint
Elena Raffetti
Kazem Rahimi
Shishir Rao
Cameron Razieh
Brian Roberts
Caroline Rogers
Jennifer Rossdale
Safa Salim
Nilesh Samani
Naveed Sattar
Christian Schnier
Roy Schwartz
David Selby
Olena Seminog
Sharmin Shabnam
Ajay Shah
Jon Shelton
James Sheppard
Shubhra Sinha
Mirek Skrypak
Martina Slapkova
Katherine Sleeman
Craig Smith
Reecha Sofat
Filip Sosenko
Matthew Sperrin
Sarah Steeg
Jonathan Sterne
Serban Stoica
Maria Sudell
Cathie Sudlow
Luanluan Sun
Arun Karthikeyan Suseeladevi
Michael Sweeting
Matt Sydes
Rohan Takhar
Howard Tang
Johan Thygesen
George Tilston
Claire Tochel
Clea du Toit
Christopher Tomlinson
Renin Toms
Fatemeh Torabi
Ana Torralbo
Julia Townson
Adnan Tufail
Tapiwa Tungamirai
Susheel Varma
Sebastian Vollmer
Venexia Walker
Tianxiao Wang
Huan Wang
Alasdair Warwick
Ruth Watkinson
Harry Watson
William Whiteley
Hannah Whittaker
Harry Wilde
Tim Wilkinson
Gareth Williams
Michelle Williams
Richard Williams
Eloise Withnell
Charles Wolfe
Angela Wood
Lucy Wright
Honghan Wu
Jinge Wu
Jianhua Wu
Tom Yates
Francesco Zaccardi
Haoting Zhang
Huayu Zhang
Luisa Zuccolo
format Journal article
container_title The Lancet Digital Health
container_volume 4
container_issue 7
container_start_page e542
publishDate 2022
institution Swansea University
issn 2589-7500
doi_str_mv 10.1016/s2589-7500(22)00091-7
publisher Elsevier BV
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description BackgroundUpdatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework.MethodsIn this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.FindingsAmong 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1.InterpretationOur analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources.
published_date 2022-07-01T05:00:17Z
_version_ 1860789985272135680
score 11.100225

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