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

Author

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

Published
2022
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7. Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries

Author

Wright, F Lucy, primary, Cheema, Kate, additional, Goldacre, Raph, additional, Hall, Nick, additional, Herz, Naomi, additional, Islam, Nazrul, additional, Karim, Zainab, additional, Moreno-Martos, David, additional, Morales, Daniel R, additional, O'Connell, Daniel, additional, Spata, Enti, additional, Akbari, Ashley, additional, Ashworth, Mark, additional, Barber, Mark, additional, Briffa, Norman, additional, Canoy, Dexter, additional, Denaxas, Spiros, additional, Khunti, Kamlesh, additional, Kurdi, Amanj, additional, Mamas, Mamas, additional, Priedon, Rouven, additional, Sudlow, Cathie, additional, Morris, Eva J A, additional, Lacey, Ben, additional, and Banerjee, Amitava, additional

Published
2022
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8. Indirect effects of the first two years of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries

Author

Wright, F Lucy, primary, Cheema, Kate, additional, Goldacre, Raph, additional, Hall, Nick, additional, Herz, Naomi, additional, Islam, Nazrul, additional, Karim, Zainab, additional, Moreno-Martos, David, additional, Morales, Daniel R, additional, O’Connell, Daniel, additional, Spata, Enti, additional, Akbari, Ashley, additional, Ashworth, Mark, additional, Barber, Mark, additional, Briffa, Norman, additional, Canoy, Dexter, additional, Denaxas, Spiros, additional, Khunti, Kamlesh, additional, Kurdi, Amanj, additional, Mamas, Mamas, additional, Priedon, Rouven, additional, Sudlow, Cathie, additional, Morris, Eva JA, additional, Lacey, Ben, additional, and Banerjee, Amitava, additional

Published
2022
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10. COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

Author

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

Published
2022
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14. Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries

Author

Wright, F Lucy, Cheema, Kate, Goldacre, Raph, Hall, Nick, Herz, Naomi, Islam, Nazrul, Karim, Zainab, Moreno-Martos, David, Morales, Daniel R, O'Connell, Daniel, Spata, Enti, Akbari, Ashley, Ashworth, Mark, Barber, Mark, Briffa, Norman, Canoy, Dexter, Denaxas, Spiros, Khunti, Kamlesh, Kurdi, Amanj, Mamas, Mamas, Priedon, Rouven, Sudlow, Cathie, Morris, Eva J A, Lacey, Ben, and Banerjee, Amitava

Abstract

Graphical AbstractMonthly total admissions for CVD as primary diagnosis across subtypes, across three countries in the UK and across pre-pandemic (2016–2019) and pandemic (2020–2021) periods.Key question: What is the impact in 2020 and 2021 of the COVID-19 pandemic on hospital admissions and procedures for six major CVDs in England, Scotland, and Wales?

Published
2023
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23. Linked electronic health records for research on a nationwide cohort of more than 54 million people in England:data resource

Author

Wood, Angela, Denholm, Rachel, Hollings, Sam, Cooper, Jennifer, Ip, Samantha, Walker, Venexia, Denaxas, Spiros, Akbari, Ashley, Banerjee, Amitava, Whiteley, William, Lai, Alvina, Sterne, Jonathan, Sudlow, Cathie, CVD-COVID-UK Consortium, Douiri, Abdel, Akinoso-Imran, Abdul Qadr, Jonas, Adrian, Shah, Ajay, Handy, Alex, Davies, Alun, Kurdi, Amanj, Hansell, Anna, Docherty, Annemarie, Pherwani, Arun, Dashtban, Ashkan, Bray, Ben, Cairns, Ben, Goldacre, Ben, Humberstone, Ben, Mateen, Bilal, Doble, Brett, Roberts, Brian, Morris, Carole, Dale, Caroline, Rogers, Caroline, Wolfe, Charles, Tomlinson, Christopher, Lawson, Claire, Du Toit, Clea, Berry, Colin, Smith, Craig, O’Connell, Dan, Harris, Daniel, Brind, David, Cromwell, David, Hughes, David, Martos, David Moreno, Ringham, Debbie, Lawler, Deborah, Lowe, Deborah, Nikiphorou, Elena, Withnell, Eloise, Di Angelantonio, Emanuele, Morris, Eva, Birney, Ewan, Falck, Fabian, Torabi, Fatemeh, Greaves, Felix, Falter, Florian, Zaccardi, Francesco, Kee, Frank, Davies, Gareth, Nicholson, George, Curry, Gwenetta, Zhang, Haoting, Hemingway, Harry, Wilde, Harry, Abbasizanjani, Hoda, Wu, Honghan, Tang, Howard, Wang, Huan, Mordi, Ify, MacArthur, Jackie, Lyons, Jane, Beveridge, Jennifer, Barrett, Jessica, Wu, Jianhua, Thygesen, Johan, Danesh, John, Dennis, John, Boyle, Jon, Halcox, Julian, Khunti, Kamlesh, Cheema, Kate, Brown, Katherine, Li, Ken, Kavanagh, Kim, North, Laura, Pasea, Laura, Ellins, Libby, Pierotti, Livia, Wright, Lucy, Martin, Lydia, Morrice, Lynn, Mamas, Mamas, Bennie, Marion, Barber, Mark, Macleod, Mary Joan, Caputo, Massimo, Buch, Maya, Mizani, Mehrdad, Katsoulis, Michalis, Gravenor, Mike, Inouye, Mike, Skrypak, Mirek, Gerstung, Moritz, Pirmohamed, Munir, Glickman, Myer, Herz, Naomi, Davies, Neil, Hall, Nick, Samani, Nilesh, Seminog, Olena, Lorgelly, Paula, Machado, Pedro, Li, Qiuju, Goldacre, Raph, Carragher, Raymond, Sofat, Reecha, Takhar, Rohan, Lyons, Ronan, Priedon, Rouven, Griffiths, Rowena, Payne, Rupert, Kolamunnage-Dona, Ruwanthi, Salim, Safa, Padmanabhan, Sandosh, Onida, Sarah, Kent, Seamus, Bacon, Seb, Manohar, Sinduja, Babu-Narayan, Sonya, Keene, Spencer, Varma, Susheel, Lawrence, Thomas, Wang, Tianxiao, Wilkinson, Tim, Norris, Tom, Palmer, Tom, Nafilyan, Vahé, Wood, Angela [0000-0002-7937-304X], and Apollo - University of Cambridge Repository

Subjects
Male, COVID-19/diagnosis, 030204 cardiovascular system & hematology, Cohort Studies, 0302 clinical medicine, COVID-19 Testing, Epidemiology, Electronic Health Records, Primary Health Care/statistics & numerical data, 030212 general & internal medicine, Child, Stroke, Cardiovascular Diseases/diagnosis, education.field_of_study, General Medicine, Middle Aged, Hospitalization, England, Cardiovascular Diseases, Child, Preschool, Cohort, Female, Medical emergency, Medical Record Linkage, Cohort study, Adult, medicine.medical_specialty, COVID-19 Vaccines, Adolescent, Population, MEDLINE, 03 medical and health sciences, Young Adult, Intensive care, medicine, Humans, England/epidemiology, education, Aged, Hospitalization/statistics & numerical data, Primary Health Care, business.industry, SARS-CoV-2, Public health, Research, Infant, Newborn, COVID-19, Infant, medicine.disease, United Kingdom, business
Abstract

Objective To describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust. Design Data resource comprising linked person level records from national healthcare settings for the English population, accessible within NHS Digital’s new trusted research environment. Setting EHRs from primary care, hospital episodes, death registry, covid-19 laboratory test results, and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular, and covid-19 vaccination data. Participants 54.4 million people alive on 1 January 2020 and registered with an NHS general practitioner in England. Main outcome measures Confirmed and suspected covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack and incident myocardial infarction) and all cause mortality between 1 January and 31 October 2020. Results The linked cohort includes more than 96% of the English population. By combining person level data across national healthcare settings, data on age, sex, and ethnicity are complete for around 95% of the population. Among 53.3 million people with no previous diagnosis of stroke or transient ischaemic attack, 98 721 had a first ever incident stroke or transient ischaemic attack between 1 January and 31 October 2020, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.2 million people with no previous diagnosis of myocardial infarction, 62 966 had an incident myocardial infarction during follow-up, of which 8% were recorded only in primary care and 12% only in death registry records. A total of 959 470 people had a confirmed or suspected covid-19 diagnosis (714 162 in primary care data, 126 349 in hospital admission records, 776 503 in covid-19 laboratory test data, and 50 504 in death registry records). Although 58% of these were recorded in both primary care and covid-19 laboratory test data, 15% and 18%, respectively, were recorded in only one. Conclusions This population-wide resource shows the importance of linking person level data across health settings to maximise completeness of key characteristics and to ascertain cardiovascular events and covid-19 diagnoses. Although this resource was initially established to support research on covid-19 and cardiovascular disease to benefit clinical care and public health and to inform healthcare policy, it can broaden further to enable a wide range of research.

Published
2021

24. Reply

Author

Pakpoor, Julia, Goldacre, Raph, Schmierer, Klaus, Giovannoni, Gavin, and Goldacre, Michael J.

Published
2014
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33. Declining comorbidity-adjusted mortality rates in English patients receiving maintenance renal replacement therapy

Author

Storey, Benjamin C., primary, Staplin, Natalie, additional, Harper, Charlie H., additional, Haynes, Richard, additional, Winearls, Christopher G., additional, Goldacre, Raph, additional, Emberson, Jonathan R., additional, Goldacre, Michael J., additional, Baigent, Colin, additional, Landray, Martin J., additional, and Herrington, William G., additional

Published
2018
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34. Cerebrovascular injury as a risk factor for amyotrophic lateral sclerosis

Author

Turner, Martin R, Goldacre, Raph, Talbot, Kevin, and Goldacre, Michael J

Subjects
MOTOR NEURON DISEASE, Adult, Intracranial Arteriovenous Malformations, Male, Adolescent, Amyotrophic Lateral Sclerosis, CEREBROVASCULAR, Middle Aged, Subarachnoid Hemorrhage, Embolization, Therapeutic, Stroke, Young Adult, England, Ischemic Attack, Transient, Risk Factors, Case-Control Studies, EPIDEMIOLOGY, Humans, Female, cardiovascular diseases, Neurodegeneration, ALS, Aged
Abstract

Objective To use an unbiased method to test a previously reported association between cerebral arteriovenous malformation (AVM) embolisation and the subsequent development of amyotrophic lateral sclerosis (ALS). Methods A hospital record linkage database was used to create cohorts of individuals coded as having cerebral and peripheral vessel AVMs, stroke (separately for haemorrhagic and ischaemic), transient ischaemic attack (TIA) and subarachnoid haemorrhage (SAH). The rate ratio for subsequent ALS was compared to a reference cohort. Results An increased rate ratio for ALS was found in relation to prior AVM (2.69; p=0.005), all strokes (1.38; p

Published
2015

37. Viral hepatitis and Parkinson disease

Author

Pakpoor, Julia, primary, Noyce, Alastair, additional, Goldacre, Raph, additional, Selkihova, Marianna, additional, Mullin, Stephen, additional, Schrag, Anette, additional, Lees, Andrew, additional, and Goldacre, Michael, additional

Published
2017
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39. Risk of subarachnoid haemorrhage in people admitted to hospital with selected immune-mediated diseases: record-linkage studies

Author

Ramagopalan, Sreeram V, Pakpoor, Julia, Seminog, Olena, Goldacre, Raph, Graham, Lee, and Goldacre, Michael J

Subjects
Stroke, Neurology, Immunology, Clinical Neurology, cardiovascular diseases
Abstract

BACKGROUND: Subarachnoid hemorrhage (SAH) is a devastating cause of stroke, occurring in relatively young people. It has been suggested that some immune-mediated diseases may be associated with an increased risk of SAH. METHODS: We analysed a database of linked statistical records of hospital admissions and death certificates for the whole of England (1999-2011). Rate ratios for SAH were determined, comparing immune-mediated disease cohorts with comparison cohorts. RESULTS: There were significantly elevated risks of SAH after hospital admission for the following individual immune-mediated diseases: Addison's disease, ankylosing spondylitis, autoimmune haemolytic anaemia, Crohn's disease, diabetes mellitus, idiopathic thrombocytopenia purpura, myxoedema, pernicious anaemia, primary biliary cirrhosis, psoriasis, rheumatoid arthritis, scleroderma, Sjogren's syndrome, SLE and thyrotoxicosis. Elevated risks that were greater than 2-fold were found for Addison's disease (rate ratio (RR) = 2.01, 95% confidence interval 1.3-2.97), idiopathic thrombocytopenia purpura (RR = 2.42, 1.86-3.11), primary biliary cirrhosis (RR = 2.21, 1.43-3.16) and SLE (RR = 3.76, 3.08-4.55). CONCLUSIONS: Our findings strongly support the suggestion that patients with some immune-mediated diseases have an increased risk of SAH. Further studies of the mechanisms behind this association are warranted.

Published
2013

43. Hospital admissions for vitamin D related conditions and subsequent immune-mediated disease: record-linkage studies

Author

Ramagopalan, Sreeram V, Goldacre, Raph, Disanto, Giulio, Giovannoni, Gavin, and Goldacre, Michael J

Subjects
Medicine(all)
Abstract

BACKGROUND: Previous studies have suggested that there may be an association between vitamin D deficiency and the risk of developing immune-mediated diseases. METHODS: We analyzed a database of linked statistical records of hospital admissions and death registrations for the whole of England (from 1999 to 2011). Rate ratios for immune-mediated disease were determined, comparing vitamin D deficient cohorts (individuals admitted for vitamin D deficiency or markers of vitamin D deficiency) with comparison cohorts. RESULTS: After hospital admission for either vitamin D deficiency, osteomalacia or rickets, there were significantly elevated rates of Addison's disease, ankylosing spondylitis, autoimmune hemolytic anemia, chronic active hepatitis, celiac disease, Crohn's disease, diabetes mellitus, pemphigoid, pernicious anemia, primary biliary cirrhosis, rheumatoid arthritis, Sjogren's syndrome, systemic lupus erythematosus, thyrotoxicosis, and significantly reduced risks for asthma and myxoedema. CONCLUSIONS: This study shows that patients with vitamin D deficiency may have an increased risk of developing some immune-mediated diseases, although we cannot rule out reverse causality or confounding. Further study of these associations is warranted and these data may aid further public health studies.

Published
2013

44. Psychiatric disorders in children with demyelinating diseases of the central nervous system.

Author

Pakpoor, Julia, Goldacre, Raph, Schmierer, Klaus, Giovannoni, Gavin, Waubant, Emmanuelle, and Goldacre, Michael J.

Subjects
*MULTIPLE sclerosis in children, *CHILD psychopathology, *MENTAL illness, *PATHOLOGICAL psychology, *CENTRAL nervous system diseases, *SOMATOFORM disorders in children
Abstract

Introduction: The profile of psychiatric disorders associated with multiple sclerosis (MS) may differ in children. We aimed to assess the risk of psychiatric disorders in children with MS and other demyelinating diseases, and vice versa. Patients and methods: We analyzed linked English Hospital Episode Statistics, and mortality data, 1999-2011. Cohorts were constructed of children admitted with MS and other central nervous system (CNS) demyelinating diseases. We searched for any subsequent episode of care with psychiatric disorders in these cohorts and compared to a reference cohort. Results: Children with CNS demyelinating diseases had an increased rate of psychotic disorders (rate ratio (RR) = 5.77 (95% confidence interval (CI) = 2.48-11.41)); anxiety, stress-related, and somatoform disorders (RR = 2.38 (1.39-3.81)); intellectual disability (RR = 6.56 (3.66-10.84)); and other behavioral disorders (RR = 8.99 (5.13-14.62)). In analysis of the pediatric MS cohort as the exposure, there were elevated rates of psychotic disorders (RR = 10.76 (2.93-27.63)), mood disorders (RR = 2.57 (1.03-5.31)), and intellectual disability (RR = 6.08 (1.25-17.80)). In reverse analyses, there were elevated rates of a recorded hospital episode with CNS demyelinating disease after a previous recorded episode with anxiety, stress-related, and somatoform disorders; attention-deficit hyperactivity disorder (ADHD); autism; intellectual disability; and other behavioral disorders. Conclusion: This analysis of a national diagnostic database provides strong evidence for an association between pediatric CNS demyelinating diseases and psychiatric disorders, and highlights a need for early involvement of mental health professionals. [ABSTRACT FROM AUTHOR]

Published
2018
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45. Associations between clinically diagnosed testicular hypofunction and systemic lupus erythematosus: a record linkage study.

Author

Pakpoor, Julia, Goldacre, Raph, and Goldacre, Michael J.

Subjects
*LUPUS erythematosus, *SEX hormones, *TESTOSTERONE, *AUTOIMMUNE diseases, *GENDER differences (Psychology)
Abstract

Systemic lupus erythematosus (SLE) has a high female predominance with a 9:1 female-to-male sex ratio, but males have poorer clinical outcomes than females. Gonadal hormones may mediate gender differences in SLE, but their role in SLE remains largely uncharacterised. We aimed to investigate a potential association between testicular hypofunction (TH), as a proxy for low testosterone levels, and SLE in males. A retrospective cohort study was conducted by analysing linked English national Hospital Episode Statistics (HES) and mortality data from 1999 to 2011. We calculated rates for SLE following TH, and TH following SLE, stratified and standardised by age, calendar year of first recorded admission, region of residence, and quintile of patients' Index of Deprivation score. The adjusted rate ratio (RR) of SLE following TH was 7.7 (95% confidence interval (95% CI) 2.5-18.1, p < 0.0001). The adjusted RR for TH following SLE was 6.5 (95% CI 2.1-15.1, p < 0.0001). The positive association between TH and SLE supports a hypothesis that low testosterone levels may influence the development of male SLE. Of clinical importance, it suggests that males with SLE are at increased risk of co-morbid TH (regardless of which precedes which) and this may warrant consideration in the management of patients. [ABSTRACT FROM AUTHOR]

Published
2018
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49. Trends over time in the incidence of congenital anophthalmia, microphthalmia and orbital malformation in England: database study.

Author

Dharmasena, Aruna, Keenan, Tiarnan, Goldacre, Raph, Hall, Nick, and Goldacre, Michael J.

Abstract

Aims: To study trends over time in the incidence of congenital anophthalmia, microphthalmia and orbital malformations in England, along with changes in hospital admission rates for these conditions. Methods: Using English National Hospital Episode Statistics (1999-2011), the annual rate of hospital admissions related to anophthalmia, microphthalmia and congenital malformations of orbit/lacrimal apparatus was calculated per 100 000 infants. The records were person-linked, which enabled patients' 'first record' rates to be calculated as proxies for incidence. Similar analyses on pre-1999 datasets were also undertaken for microphthalmia. Results: There was no systematic increase or decrease over time in the incidence of these conditions, but there was some fluctuation from year to year. The incidence of congenital anophthalmia ranged from 2.4 (95% CI 1.3 to 4.0) per 100 000 infants in 1999 to 0.4 (0 to 1.3) in 2011. The annual incidence of congenital microphthalmia was 10.8 (8.2 to 13.5) in 1999 and 10.0 (7.6 to 12.4) in 2011. The annual incidence of congenital orbital/lacrimal malformations was 0.5 (0 to 1.1) in 1999 and 0.7 (0 to 1.4) in 2011. Including multiple admissions per person, admission rates for microphthalmia showed a linear increase over time from 1999. The earlier data for microphthalmia indicated an increase in admission rates, but no change in incidence, from 1971 to 2011. Conclusions: The incidence of these conditions has remained stable in England in recent years. Although the incidence of microphthalmia was stable, hospital admission rates for it increased over time reflecting an increase in multiple admissions per affected person. These data may be useful for planning service provision. [ABSTRACT FROM AUTHOR]

Published
2017
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