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1. Rapid Biomedical Research Classification: The Pandemic PACT Advanced Categorisation Engine

Author

Rohanian, Omid, Nouriborji, Mohammadmahdi, Seminog, Olena, Furst, Rodrigo, Mendy, Thomas, Levanita, Shanthi, Kadri-Alabi, Zaharat, Jabin, Nusrat, Toale, Daniela, Humphreys, Georgina, Antonio, Emilia, Bucher, Adrian, Norton, Alice, and Clifton, David A.

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, 68T50, I.2.7
Abstract

This paper introduces the Pandemic PACT Advanced Categorisation Engine (PPACE) along with its associated dataset. PPACE is a fine-tuned model developed to automatically classify research abstracts from funded biomedical projects according to WHO-aligned research priorities. This task is crucial for monitoring research trends and identifying gaps in global health preparedness and response. Our approach builds on human-annotated projects, which are allocated one or more categories from a predefined list. A large language model is then used to generate `rationales' explaining the reasoning behind these annotations. This augmented data, comprising expert annotations and rationales, is subsequently used to fine-tune a smaller, more efficient model. Developed as part of the Pandemic PACT project, which aims to track and analyse research funding and clinical evidence for a wide range of diseases with outbreak potential, PPACE supports informed decision-making by research funders, policymakers, and independent researchers. We introduce and release both the trained model and the instruction-based dataset used for its training. Our evaluation shows that PPACE significantly outperforms its baselines. The release of PPACE and its associated dataset offers valuable resources for researchers in multilabel biomedical document classification and supports advancements in aligning biomedical research with key global health priorities.

Published
2024

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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5. A protocol for a living mapping review of global research funding for infectious diseases with a pandemic potential – PANDEMIC PACT

Author

Seminog, Olena, primary, Furst, Rodrigo, additional, Mendy, Thomas, additional, Rohanian, Omid, additional, Levanita, Shanthi, additional, Kadri-Alabi, Zaharat, additional, Jabin, Nusrat, additional, Humphreys, Georgina, additional, Antonio, Emilia, additional, Bucher, Adrian, additional, and Norton, Alice, additional

Published
2024
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7. 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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8. 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
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14. Relative Contribution of Trends in Myocardial Infarction Event Rates and Case Fatality to Declines in Mortality: An International Comparative Study of 1.95 Million Events in 80.4 Million People in Four Countries

Author

Camacho, Ximena, primary, Nedkoff, Lee, additional, Wright, F. Lucy, additional, Nghiem, Nhung, additional, Buajitti, Emmalin, additional, Goldacre, Raphael, additional, Rosella, Laura, additional, Seminog, Olena, additional, Tan, Eng Joo, additional, Hayes, Alison, additional, Hayen, Andrew, additional, Wilson, Nick, additional, Blakely, Tony, additional, and Clarke, Philip, additional

Published
2021
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15. Risk of fractures in patients with multiple sclerosis: record-linkage study

Author

Ramagopalan Sreeram V, Seminog Olena, Goldacre Raphael, and Goldacre Michael J

Subjects
Multiple sclerosis, Fractures, Epidemiology, Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Background Patients with multiple sclerosis (MS) have been reported to be at higher risk of fracture than other people. We sought to test this hypothesis in a large database of hospital admissions in England. Methods We analysed a database of linked statistical records of hospital admissions and death certificates for the whole of England (1999–2010). Rate ratios for fractures were determined, comparing fracture rates in a cohort of all people in England admitted with MS and rates in a comparison cohort. Results Significantly elevated risk for all fractures was found in patients with MS (rate ratio (RR) = 1.99, 95% confidence interval (CI) = 1.93-2.05)). Risks were particularly high for femoral fractures (femoral neck fracture RR = 2.79 (2.65-2.93); femoral shaft fracture RR 6.69 (6.12-7.29)), and fractures of the tibia or ankle RR = 2.81 (2.66-2.96). Conclusions Patients with MS have an increased risk of fractures. Caregivers should aim to optimize bone health in MS patients.

Published
2012
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18. Clinical associations between gout and multiple sclerosis, Parkinson’s disease and motor neuron disease: record-linkage studies

Author

Pakpoor, Julia, Seminog, Olena O, Ramagopalan, Sreeram V, and Goldacre, Michael J

Subjects
Adult, Male, Risk, Multiple Sclerosis, Gout, Databases, Factual, Clinical Neurology, nutritional and metabolic diseases, Parkinson Disease, Middle Aged, Uric Acid, Hospitalization, Young Adult, England, Parkinson’s disease, Humans, Female, Motor neuron disease, Research Article, Aged, Retrospective Studies
Abstract

Background Uric acid has antioxidant effects on neurons. Abnormally high levels of uric acid are, however, associated with gout. Previous studies have suggested that high levels of uric acid (and the presence of gout) may exert a protective effect against the risk of developing some neurological diseases. We aimed to investigate this hypothesis in a large database of hospital admissions in England. Methods We analysed a database of linked statistical records of hospital admissions and death registrations in England (1999–2012). A cohort of people with gout was constructed and followed for development of multiple sclerosis (MS), Parkinson’s disease (PD) or motor neuron disease (MND). Then, conversely, cohorts of all people in the database with MS, PD or MND were constructed and followed for subsequent gout. Rate ratios (RRs) were determined, comparing these cohorts with people in a reference cohort. Results In the gout cohort, we observed a modest elevation of the overall risk of subsequent MS, PD and MND (respectively, RR = 1.27 (95% confidence interval 1.03-1.55), 1.11 (1.05-1.17) and 1.28 (1.11-1.48) which was largely attributable to an increased risk observed in the early years after hospitalisation for gout. The increased risk of neurological disease did not remain after 5 years. In the cohorts of people with MS or PD, there was a significantly reduced risk of subsequent gout admission (RR = 0.79 (0.69-0.89) and 0.83 (0.79-0.87), respectively). This inverse association was sustained over time. There was also a reduced risk of MND following gout which only emerged more than five years following initial gout admission (RR at 5+ years 0.35 (0.15-0.68)). Conclusions This study investigated the epidemiological evidence for a protective role of high serum concentration of uric acid, for which we used gout as a proxy, in the aetiology of MS, PD or MND. Our observations do not support this hypothesis. However, when the order was reversed, and we retrospectively followed up patients with MS, PD and MND for a number of years, we found a statistically significant deficit of gout. This suggests that there is relationship between some aspects of these neurodegenerative diseases and metabolism of uric acid.

Published
2015

20. 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

28. Associations between Klinefelter's syndrome and autoimmune diseases: English national record linkage studies.

Author

Seminog, Olena O., Seminog, Alla B., Yeates, David, and Goldacre, Michael J.

Subjects
*AUTOIMMUNE diseases, *KLINEFELTER'S syndrome, *MEDICAL record linkage, *CHROMOSOME abnormalities, *HYPOTHYROIDISM, *LUPUS erythematosus
Abstract

There are reports suggesting that people with Klinefelter's syndrome (KS) may be at increased risk of some autoimmune diseases, but the evidence is not substantial. We wanted to add to the evidence by systematically assessing the risk of autoimmune diseases in a national cohort of people with KS. We selected records of all people with KS in a record-linked dataset of all hospital day cases and inpatient admissions in England, 1999-2011; and we followed them up by electronic record linkage to identify the occurrence of autoimmune diseases. We compared their occurrence in the KS cohort with a control cohort, studied in the same way, and expressed the results as rate ratios (RR). Of 30 autoimmune diseases studied in people with KS, there were significantly increased risks of seven-Addison's disease (RR 11.7, 95% confidence interval 2.4-34.4), diabetes mellitus type 1 (6.1, 4.4-8.3), multiple sclerosis (4.3, 1.2-11.0), acquired hypothyroidism (2.7, 1.8-4.0), rheumatoid arthritis (3.3, 2.0-5.2), Sjogren's syndrome (19.3, 4.0-57.0) and systemic lupus erythematosus (18.1, 2.2-65.6). We concluded that people with KS have increased risk of some autoimmune diseases, particularly those that are female-predominant. The increased risk of autoimmune diseases associated with the XXY karyotype may hold clues to the pathogenesis of some aspects of autoimmunity. [ABSTRACT FROM AUTHOR]

Published
2015
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29. Abstract T P138.

Author

Seminog, Olena O, Hall, Nick, and Goldacre, Michael J

Published
2014

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