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56. Interventions to change general practitioner prescribing in primary care organisations

Author

Ashworth, Mark and Armstrong, David

Subjects
362.172
Abstract

What interventions are effective in influencing prescribing by general practitioners (GPs)? Two studies were conducted - a matched comparison survey of prescribing change in 26 practices forming a GP Commissioning Group (which piloted new ways to modify GP prescribing) and a longitudinal survey of 145 prescribing advisers (who were responsible for administering prescribing incentive schemes in their area). The effectiveness of differing financial incentives in influencing prescribing has already been described. This thesis supports the notion that non-profit making financial incentives, such as generating prescribing savings to be re-invested in other aspects of health care for the local community, may also be an effective motivator of prescribing change. GPs considered educational interventions to be the most effective approach but if prescribing were to change, interventions needed to tap into their professional values such as autonomy or the sense of belonging to a peer group. Interventions to change prescribing may be better targeted at individual GPs rather than the GP partnership as a whole since evidence was found that GPs tend to behave as individuals when considering prescribing change but collectively as partnerships in their approach to managerial issues. Since the formation of Primary Care Organisations (PCOs) in 1999, the predominant influence on prescribing has shifted away from emphasis on cost control toward attempts to improve prescribing quality. The effectiveness of interventions to improve prescribing quality is harder to demonstrate and remains largely unknown.

Published
2004

61. Ethnic differences in physical and mental multimorbidity in working age adults with a history of depression and/or anxiety.

Author

Ronaldson, Amy, de la Torre, Jorge Arias, Broadbent, Matthew, Ashworth, Mark, Armstrong, David, Bakolis, Ioannis, Hatch, Stephani L., Hotopf, Matthew, and Dregan, Alex

Subjects
PERSONALITY disorders, CARDIOVASCULAR diseases risk factors, MINORITIES, CONFIDENCE intervals, SUBSTANCE abuse, MENTAL depression, CARIBBEAN people, ALCOHOL drinking, RESEARCH funding, DESCRIPTIVE statistics, ANXIETY, LOGISTIC regression analysis, CLUSTER analysis (Statistics), WHITE people, COMORBIDITY, MENTAL illness
Abstract

Background: The current study used data from an ethnically diverse population from South London to examine ethnic differences in physical and mental multimorbidity among working age (18–64 years) adults in the context of depression and anxiety. Method: The study included 44 506 patients who had previously attended Improving Access to Psychological Therapies services in the London Borough of Lambeth. Multinomial logistic regression examined cross-sectional associations between ethnicity with physical and mental multimorbidity. Patterns of multimorbidity were identified using hierarchical cluster analysis. Results: Within 44 056 working age adults with a history of depression or anxiety from South London there were notable ethnic differences in physical multimorbidity. Adults of Black Caribbean ethnicity were more likely to have physical multimorbidity [adjusted relative risk ratio (aRRR) = 1.25, 95% confidence interval (CI) 1.15–1.36] compared to adults of White ethnicity. Relative to adults of White ethnicity, adults of Asian ethnicity were more likely to have physical multimorbidity at higher thresholds only (e.g. 4 + conditions; aRRR = 1.53, 95% CI 1.17–2.00). Three physical (atopic, cardiometabolic, mixed) and three mental (alcohol/substance use, common/severe mental illnesses, personality disorder) multimorbidity clusters emerged. Ethnic minority groups with multimorbidity had a higher probability of belonging to the cardiometabolic cluster. Conclusion: In an ethnically diverse population with a history of common mental health disorders, we found substantial between- and within-ethnicity variation in rates of physical, but not mental, multimorbidity. The findings emphasised the value of more granular definitions of ethnicity when examining the burden of physical and mental multimorbidity. [ABSTRACT FROM AUTHOR]

Published
2023
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65. Risk factors associated with overweight and obesity in people with severe mental illness in South Asia: cross-sectional study in Bangladesh, India, and Pakistan

Author

Appuhamy, Koralagamage Kavindu, primary, Podmore, Danielle, additional, Mitchell, Alex, additional, Ahmed, Helal Uddin, additional, Ashworth, Mark, additional, Boehnke, Jan R., additional, Chongtham, Virtu, additional, Chowdhury, Asiful Haidar, additional, Garcia, Olga P., additional, Holt, Richard I. G., additional, Huque, Rumana, additional, Muliyala, Krishna Prasad, additional, Onstenk, Eline Klein, additional, Rajan, Sukanya, additional, Shiers, David, additional, Siddiqi, Najma, additional, Manjunatha, S., additional, and Zavala, Gerardo A., additional

Published
2023
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66. 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
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67. Additional file 7 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 7: Table S1. Results of ITS analysis - Effect of the pandemic on primary care consultations by ethnic group, while controlling for age (Sensitivity analysis).

Published
2023
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68. Additional file 6 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 6: Results of ITS analysis - Effect of the pandemic on primary care consultations by complex multimorbidity status (Sensitivity analysis). Table S1. Results of ITS analysis - Effect of pandemic on total consultations, by complex multimorbidity status. Table S2. Results of ITS analysis - Effect of pandemic on total consultations, by complex multimorbidity status.

Published
2023
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69. Additional file 2 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 2: Missing Ethnicity Data Analysis. Table S1. Analysis of top 10 languages. Table S2. Analysis of top 10 countries of birth (COBs).

Published
2023
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70. Additional file 9 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 9: Results of ITS analysis - Effect of pandemic on primary care consultations by 18-category ethnic groups. Table S1. Results of ITS analysis - Effect of pandemic on total consultations, within the multimorbidity population – Heterogeneity within ethnic group.

Published
2023
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72. Additional file 3 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 3: Temporal trends in covariates, February 2018 to March 2021. Figure S1. Proportion of females. Figure S2. Proportion by age groups. Figure S3. Proportion by ethnic group. Figure S4. Proportion by social deprivation (IMD).

Published
2023
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74. Additional file 8 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 8: Figures of ITS model results. Figure S1. Total consultations by multimorbidity status. Figure S2. Face-to-Face consultations by multimorbidity status. Figure S3. Telephone consultations by multimorbidity status. Figure S4. Face-to-Face consultations by ethnic group. Figure S5. Telephone consultations by ethnic group.

Published
2023
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75. Additional file 5 of Ethnic inequalities in the impact of COVID-19 on primary care consultations: a time series analysis of 460,084 individuals with multimorbidity in South London

Author

McGreevy, Alice, Soley-Bori, Marina, Ashworth, Mark, Wang, Yanzhong, Rezel-Potts, Emma, Durbaba, Stevo, Dodhia, Hiten, and Fox-Rushby, Julia

Abstract

Additional file 5: Parameter estimates from the ITS models. Table S1. Results of ITS analysis - Effect of pandemic on primary care consultations by multimorbidity status. Table S2. Results of ITS analysis - Effect of pandemic on total primary care consultations within multimorbid population, by ethnicity. Table S3. Results of ITS analysis - Effect of pandemic on face-to-face and telephone consultations within multimorbid population, by ethnicity.

Published
2023
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76. 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

Subjects
Cardiovascular Diseases - epidemiology - prevention & control - diagnosis, Pandemics - prevention & control, SDG 3 - Good Health and Well-being, Risk Factors, Hypertension - complications - drug therapy - epidemiology, COVID-19 - epidemiology, Humans, General Medicine, Diabetes Mellitus, Type 2 - complications - drug therapy - epidemiology, General Biochemistry, Genetics and Molecular Biology
Abstract

How the Coronavirus Disease 2019 (COVID-19) pandemic has affected prevention and management of cardiovascular disease (CVD) is not fully understood. In this study, we used medication data as a proxy for CVD management using routinely collected, de-identified, individual-level data comprising 1.32 billion records of community-dispensed CVD medications from England, Scotland and Wales between April 2018 and July 2021. Here we describe monthly counts of prevalent and incident medications dispensed, as well as percentage changes compared to the previous year, for several CVD-related indications, focusing on hypertension, hypercholesterolemia and diabetes. We observed a decline in the dispensing of antihypertensive medications between March 2020 and July 2021, with 491,306 fewer individuals initiating treatment than expected. This decline was predicted to result in 13,662 additional CVD events, including 2,281 cases of myocardial infarction and 3,474 cases of stroke, should individuals remain untreated over their lifecourse. Incident use of lipid-lowering medications decreased by 16,744 patients per month during the first half of 2021 as compared to 2019. By contrast, incident use of medications to treat type 2 diabetes mellitus, other than insulin, increased by approximately 623 patients per month for the same time period. In light of these results, methods to identify and treat individuals who have missed treatment for CVD risk factors and remain undiagnosed are urgently required to avoid large numbers of excess future CVD events, an indirect impact of the COVID-19 pandemic.

Published
2023

79. Trends in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) infection and vaccine antibody prevalence in a multi‐ethnic inner‐city antenatal population: A cross‐sectional surveillance study.

Author

Andreeva, Daria, Gill, Carolyn, Brockbank, Anna, Hejmej, Joanna, Conti‐Ramsden, Fran, Doores, Katie J., Seed, Paul T., Poston, Lucilla, Edwards, David, Stewart, Robert, Howard, Louise M, Ashworth, Mark, Sandall, Jane, Happé, Francesca, Shennan, Andrew, Harding, Seeromanie, Greenough, Anne, Wolfe, Ingrid, Carson, Lauren, and Grey, Amanda

Subjects
SARS-CoV-2, COVID-19, ANTIBODY titer
Abstract

Objective: To determine severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) seroprevalence in pregnancy in an inner‐city setting and assess associations with demographic factors and vaccination timing. Design: Repeated cross‐sectional surveillance study. Setting: London maternity centre. Sample: A total of 906 pregnant women attending nuchal scans, July 2020–January 2022. Methods: Blood samples were tested for IgG antibodies against SARS‐CoV‐2 nucleocapsid (N) and spike (S) proteins. Self‐reported vaccination status and coronavirus disease 2019 (COVID‐19) infection were recorded. Multivariable regression models determined demographic factors associated with seroprevalence and antibody titres. Main outcome measures: Immunoglobulin G N‐ and S‐protein antibody titres. Results: Of the 960 women, 196 (20.4%) were SARS‐CoV‐2 seropositive from previous infection. Of these, 70 (35.7%) self‐reported previous infection. Among unvaccinated women, women of black ethnic backgrounds were most likely to be SARS‐CoV‐2 seropositive (versus white adjusted risk ratio [aRR] 1.88, 95% CI 1.35–2.61, p < 0.001). Women from black and mixed ethnic backgrounds were least likely to have a history of vaccination with seropositivity to S‐protein (versus white aRR 0.58, 95% CI 0.40–0.84, p = 0.004; aRR 0.56, 95% CI 0.34–0.92, p = 0.021, respectively). Double vaccinated, previously infected women had higher IgG S‐protein antibody titres than unvaccinated, previously infected women (mean difference 4.76 fold‐change, 95% CI 2.65–6.86, p < 0.001). Vaccination timing before versus during pregnancy did not affect IgG S‐antibody titres (mean difference −0.28 fold‐change, 95% CI −2.61 to 2.04, p = 0.785). Conclusions: This cross‐sectional study demonstrates high rates of asymptomatic SARS‐CoV‐2 infection with women of black ethnic backgrounds having higher infection risk and lower vaccine uptake. SARS‐CoV‐2 antibody titres were highest among double‐vaccinated, infected women. This article includes Author Insights, a video abstract available at: https://emckclac‐my.sharepoint.com/:v:/g/personal/k1888594_kcl_ac_uk/ESBeVJ8VdMtMtDOaAflgfLIBoKJ6i7g8v‐OkeQEc8cyTnA?e=v3fXo8. [ABSTRACT FROM AUTHOR]

Published
2023
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80. Multimorbidity clusters among people with serious mental illness: a representative primary and secondary data linkage cohort study.

Author

Ma, Ruimin, Romano, Eugenia, Ashworth, Mark, Yadegarfar, Mohammad E., Dregan, Alexandru, Ronaldson, Amy, de Oliveira, Claire, Jacobs, Rowena, Stewart, Robert, and Stubbs, Brendon

Subjects
STRUCTURAL equation modeling, CONFIDENCE intervals, CHRONIC diseases, MULTIPLE regression analysis, AGE distribution, SCHIZOPHRENIA, DISEASES, SEVERITY of illness index, SEX distribution, RESEARCH funding, ODDS ratio, CLUSTER analysis (Statistics), MENTAL illness, LONGITUDINAL method
Abstract

Background: People with serious mental illness (SMI) experience higher mortality partially attributable to higher long-term condition (LTC) prevalence. However, little is known about multiple LTCs (MLTCs) clustering in this population. Methods: People from South London with SMI and two or more existing LTCs aged 18+ at diagnosis were included using linked primary and mental healthcare records, 2012–2020. Latent class analysis (LCA) determined MLTC classes and multinominal logistic regression examined associations between demographic/clinical characteristics and latent class membership. Results: The sample included 1924 patients (mean (s.d.) age 48.2 (17.3) years). Five latent classes were identified: 'substance related' (24.9%), 'atopic' (24.2%), 'pure affective' (30.4%), 'cardiovascular' (14.1%), and 'complex multimorbidity' (6.4%). Patients had on average 7–9 LTCs in each cluster. Males were at increased odds of MLTCs in all four clusters, compared to the 'pure affective'. Compared to the largest cluster ('pure affective'), the 'substance related' and the 'atopic' clusters were younger [odds ratios (OR) per year increase 0.99 (95% CI 0.98–1.00) and 0.96 (0.95–0.97) respectively], and the 'cardiovascular' and 'complex multimorbidity' clusters were older (ORs 1.09 (1.07–1.10) and 1.16 (1.14–1.18) respectively). The 'substance related' cluster was more likely to be White, the 'cardiovascular' cluster more likely to be Black (compared to White; OR 1.75, 95% CI 1.10–2.79), and both more likely to have schizophrenia, compared to other clusters. Conclusion: The current study identified five latent class MLTC clusters among patients with SMI. An integrated care model for treating MLTCs in this population is recommended to improve multimorbidity care. [ABSTRACT FROM AUTHOR]

Published
2023
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86. 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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91. 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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99. 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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