Search

Your search keyword '"Takhar, Rohan"' showing total 18 results
Start Over Author "Takhar, Rohan"
18 results on '"Takhar, Rohan"'

3. The impact of the COVID-19 pandemic on cardiovascular disease prevention and management

Author

Dale, Caroline E., Takhar, Rohan, Carragher, Raymond, Katsoulis, Michail, Torabi, Fatemeh, Duffield, Stephen, Kent, Seamus, Mueller, Tanja, Kurdi, Amanj, Le Anh, Thu Nguyen, McTaggart, Stuart, Abbasizanjani, Hoda, Hollings, Sam, Scourfield, Andrew, Lyons, Ronan A., Griffiths, Rowena, Lyons, Jane, Davies, Gareth, Harris, Daniel, Handy, Alex, Mizani, Mehrdad A., Tomlinson, Christopher, Thygesen, Johan H., Ashworth, Mark, Denaxas, Spiros, Banerjee, Amitava, Sterne, Jonathan A. C., Brown, Paul, Bullard, Ian, Priedon, Rouven, Mamas, Mamas A., Slee, Ann, Lorgelly, Paula, Pirmohamed, Munir, Khunti, Kamlesh, Morris, Andrew D., Sudlow, Cathie, Akbari, Ashley, Bennie, Marion, Sattar, Naveed, and Sofat, Reecha

Published
2023
Full Text
View/download PDF

4. Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study

Author

Alexander, Daniel C, Asiimwe, Innocent G, Ball, Simon, Bennett, Frances, Borges, Maria Carolina, Butterworth, Adam, Chaturvedi, Nishi, Chopade, Sandesh, Clarkson, Christopher, Cox, Martin, Dale, Caroline, Denaxas, Spiros, Dunca, Diana, Engmann, Jorgen E, Fernandez-Sanles, Alba, Finan, Chris, Fitzpatrick, Natalie, Gallagher, Jean, Gonzalez-Izquierdo, Arturo, Gratton, Jasmine, Gross, Christian, Hemingway, Harry, Henry, Albert, Hidajat, Mira, Hingorani, Aroon, Hukerikar, Nikita, Jorgensen, Andrea, Joshi, Roshni, Katsoulis, Michail, Kuan, Valerie, Kumar, Rashmi, Lai, Alvina G, Langenberg, Claudia, Lawlor, Deborah, Mancini, Mary, Miller, Diane, Ogden, Margaret, Ozyigit, Eda B, Patel, Shilpa, Pirmohamed, Munir, Roberts, Amanda, Ryan, David, Schmidt, Amand F, Shah, Anoop D, Shah, Tina, Sofat, Reecha, Takhar, Rohan, Torralbo, Ana, Ullah, Ayath, Walker, Lauren E, Warwick, Alasdair, Wheeler, Eleanor, Wright, Victoria L, Wu, Honghan, Zwierzyna, Magdalena, Patalay, Praveetha, Nitsch, Dorothea, Mathur, Rohini, Partridge, Linda, Wong, Ian C K, Hingorani, Melanie, and Hingorani, Aroon D

Published
2023
Full Text
View/download PDF

5. 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
Full Text
View/download PDF

6. Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study

Author

Schnier, Christian, primary, McCarthy, Aoife, additional, Morales, Daniel R, additional, Akbari, Ashley, additional, Sofat, Reecha, additional, Dale, Caroline, additional, Takhar, Rohan, additional, Mamas, Mamas A., additional, Khunti, Kamlesh, additional, Zaccardi, Francesco, additional, Sudlow, Cathie LM, additional, and Wilkinson, Tim, additional

Published
2023
Full Text
View/download PDF

7. Use of Sodium Valproate and Other Anti-Seizure Medications in England and Wales During the COVID-19 Pandemic: A Population-Level Analysis of 60 Million Individuals

Author

Dale, Caroline, primary, Takhar, Rohan, additional, Fan, Yat Yi, additional, Torabi, Fatemeh, additional, Kim, Samuel, additional, Lambarth, Andrew, additional, Shankar, Ravi, additional, Tomlinson, Christopher, additional, Wilkinson, Tim, additional, Mueller, Tanja, additional, Kurdi, Amanj, additional, Ashworth, Mark, additional, Mamas, Mamas, additional, Khunti, Kamlesh, additional, Akbari, Ashley, additional, Morris, Andrew, additional, Pirmohamed, Munir, additional, Marson, Anthony, additional, Williams, David, additional, Sudlow, Cathie, additional, Sofat, Reecha, additional, and Consortium, CVD-COVID-UK, additional

Published
2023
Full Text
View/download PDF

8. Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study

Author

Kuan, Valerie, primary, Denaxas, Spiros, additional, Patalay, Praveetha, additional, Nitsch, Dorothea, additional, Mathur, Rohini, additional, Gonzalez-Izquierdo, Arturo, additional, Sofat, Reecha, additional, Partridge, Linda, additional, Roberts, Amanda, additional, Wong, Ian C K, additional, Hingorani, Melanie, additional, Chaturvedi, Nishi, additional, Hemingway, Harry, additional, Hingorani, Aroon D, additional, Alexander, Daniel C, additional, Asiimwe, Innocent G, additional, Ball, Simon, additional, Bennett, Frances, additional, Borges, Maria Carolina, additional, Butterworth, Adam, additional, Chopade, Sandesh, additional, Clarkson, Christopher, additional, Cox, Martin, additional, Dale, Caroline, additional, Dunca, Diana, additional, Engmann, Jorgen E, additional, Fernandez-Sanles, Alba, additional, Finan, Chris, additional, Fitzpatrick, Natalie, additional, Gallagher, Jean, additional, Gratton, Jasmine, additional, Gross, Christian, additional, Henry, Albert, additional, Hidajat, Mira, additional, Hingorani, Aroon, additional, Hukerikar, Nikita, additional, Jorgensen, Andrea, additional, Joshi, Roshni, additional, Katsoulis, Michail, additional, Kuan, Valerie, additional, Kumar, Rashmi, additional, Lai, Alvina G, additional, Langenberg, Claudia, additional, Lawlor, Deborah, additional, Mancini, Mary, additional, Miller, Diane, additional, Ogden, Margaret, additional, Ozyigit, Eda B, additional, Patel, Shilpa, additional, Pirmohamed, Munir, additional, Ryan, David, additional, Schmidt, Amand F, additional, Shah, Anoop D, additional, Shah, Tina, additional, Takhar, Rohan, additional, Torralbo, Ana, additional, Ullah, Ayath, additional, Walker, Lauren E, additional, Warwick, Alasdair, additional, Wheeler, Eleanor, additional, Wright, Victoria L, additional, Wu, Honghan, additional, and Zwierzyna, Magdalena, additional

Published
2023
Full Text
View/download PDF

9. 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
Full Text
View/download PDF

10. Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort

Author

Handy, Alex, Banerjee, Amitava, Wood, Angela M, Dale, Caroline, Sudlow, Cathie LM, Tomlinson, Christopher, Bean, Daniel, Thygesen, Johan H, Mizani, Mehrdad A, Katsoulis, Michail, Takhar, Rohan, Hollings, Sam, Denaxas, Spiros, Walker, Venexia, Dobson, Richard, Sofat, Reecha, CVD-COVID-UK Consortium, Handy, Alex [0000-0002-3739-1530], Banerjee, Amitava [0000-0001-8741-3411], Wood, Angela M [0000-0002-7937-304X], Sudlow, Cathie LM [0000-0002-7725-7520], Tomlinson, Christopher [0000-0002-0903-5395], Bean, Daniel [0000-0002-8594-7804], Thygesen, Johan H [0000-0002-7479-3459], Katsoulis, Michail [0000-0002-1756-9530], Denaxas, Spiros [0000-0001-9612-7791], Dobson, Richard [0000-0003-4224-9245], Sofat, Reecha [0000-0002-0242-6115], and Apollo - University of Cambridge Repository

Subjects
drug monitoring, COVID-19, Anticoagulants, Risk Assessment, Stroke, electronic health records, Fibrinolytic Agents, Risk Factors, Atrial Fibrillation, Humans, epidemiology, Female, Warfarin, Aged
Abstract

Funder: British Medical Association; FundRef: http://dx.doi.org/10.13039/501100000374, Funder: UK Research and Innovation; FundRef: http://dx.doi.org/10.13039/100014013, Funder: NIHR University College London Hospitals Biomedical Research Centre, Funder: AstraZeneca; FundRef: http://dx.doi.org/10.13039/100004325, Funder: NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, London, UK, Funder: UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, Funder: NIHR Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust, OBJECTIVE: To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes. METHODS: Individuals with AF and CHA2DS2-VASc score ≥2 on 1 January 2020 were identified using electronic health records for 56 million people in England and were followed up until 1 May 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19-related hospitalisation and death were analysed using logistic and Cox regression in individuals with pre-existing AT use versus no AT use, anticoagulants (AC) versus antiplatelets (AP), and direct oral anticoagulants (DOACs) versus warfarin. RESULTS: From 972 971 individuals with AF (age 79 (±9.3), female 46.2%) and CHA2DS2-VASc score ≥2, 88.0% (n=856 336) had pre-existing AT use, 3.8% (n=37 418) had a COVID-19 hospitalisation and 2.2% (n=21 116) died, followed up to 1 May 2021. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92, 95% CI 0.87 to 0.96), but higher odds of hospitalisation (OR=1.20, 95% CI 1.15 to 1.26). AC versus AP was associated with lower odds of death (OR=0.93, 95% CI 0.87 to 0.98) and higher hospitalisation (OR=1.17, 95% CI 1.11 to 1.24). For DOACs versus warfarin, lower odds were observed for hospitalisation (OR=0.86, 95% CI 0.82 to 0.89) but not for death (OR=1.00, 95% CI 0.95 to 1.05). CONCLUSIONS: Pre-existing AT use may be associated with lower odds of COVID-19 death and, while not evidence of causality, provides further incentive to improve AT coverage for eligible individuals with AF.

Published
2022
Full Text
View/download PDF

11. Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort

Author

Handy, Alex, primary, Banerjee, Amitava, additional, Wood, Angela M, additional, Dale, Caroline, additional, Sudlow, Cathie L M, additional, Tomlinson, Christopher, additional, Bean, Daniel, additional, Thygesen, Johan H, additional, Mizani, Mehrdad A, additional, Katsoulis, Michail, additional, Takhar, Rohan, additional, Hollings, Sam, additional, Denaxas, Spiros, additional, Walker, Venexia, additional, Dobson, Richard, additional, and Sofat, Reecha, additional

Published
2022
Full Text
View/download PDF

12. The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale analysis of trends in medication data

Author

Dale, Caroline E, primary, Takhar, Rohan, additional, Carragher, Ray, additional, Torabi, Fatemeh, additional, Katsoulis, Michalis, additional, Duffield, Stephen, additional, Kent, Seamus, additional, Mueller, Tanja, additional, Kurdi, Amanj, additional, McTaggart, Stuart, additional, Abbasizanjani, Hoda, additional, Hollings, Sam, additional, Scourfield, Andrew, additional, Lyons, Ronan, additional, Griffiths, Rowena, additional, Lyons, Jane, additional, Davies, Gareth, additional, Harris, Dan, additional, Handy, Alex, additional, Mizani, Mehrdad Alizadeh, additional, Tomlinson, Chris, additional, Ashworth, Mark, additional, Denaxas, Spiros, additional, Banerjee, Amitava, additional, Sterne, Jonathan, additional, Lovibond, Kate, additional, Brown, Paul, additional, Bullard, Ian, additional, Priedon, Rouven, additional, Mamas, Mamas A, additional, Slee, Ann, additional, Lorgelly, Paula, additional, Pirmohamed, Munir, additional, Khunti, Kamlesh, additional, Sattar, Naveed, additional, Morris, Andrew, additional, Sudlow, Cathie, additional, Akbari, Ashley, additional, Bennie, Marion, additional, and Sofat, Reecha, additional

Published
2022
Full Text
View/download PDF

15. 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
Full Text
View/download PDF

18. Identifying and visualising multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study

Author

Kuan, Valerie, Denaxas, Spiros, Patalay, Praveetha, Nitsch, Dorothea, Mathur, Rohini, Gonzalez-Izquierdo, Arturo, Sofat, Reecha, Partridge, Linda, Roberts, Amanda, Wong, Ian C K, Hingorani, Melanie, Chaturvedi, Nishi, Hemingway, Harry, Hingorani, Aroon D, Alexander, Daniel C, Asiimwe, Innocent G, Ball, Simon, Bennett, Frances, Borges, Maria Carolina, Butterworth, Adam, Chaturvedi, Nishi, Chopade, Sandesh, Clarkson, Christopher, Cox, Martin, Dale, Caroline, Denaxas, Spiros, Dunca, Diana, Engmann, Jorgen E, Fernandez-Sanles, Alba, Finan, Chris, Fitzpatrick, Natalie, Gallagher, Jean, Gonzalez-Izquierdo, Arturo, Gratton, Jasmine, Gross, Christian, Hemingway, Harry, Henry, Albert, Hidajat, Mira, Hingorani, Aroon, Hukerikar, Nikita, Jorgensen, Andrea, Joshi, Roshni, Katsoulis, Michail, Kuan, Valerie, Kumar, Rashmi, Lai, Alvina G, Langenberg, Claudia, Lawlor, Deborah, Mancini, Mary, Miller, Diane, Ogden, Margaret, Ozyigit, Eda B, Patel, Shilpa, Pirmohamed, Munir, Roberts, Amanda, Ryan, David, Schmidt, Amand F, Shah, Anoop D, Shah, Tina, Sofat, Reecha, Takhar, Rohan, Torralbo, Ana, Ullah, Ayath, Walker, Lauren E, Warwick, Alasdair, Wheeler, Eleanor, Wright, Victoria L, Wu, Honghan, and Zwierzyna, Magdalena

Abstract

Globally, there is a paucity of multimorbidity and comorbidity data, especially for minority ethnic groups and younger people. We estimated the frequency of common disease combinations and identified non-random disease associations for all ages in a multiethnic population.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results