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Wang F, Gao J, Hao S, Tsang KT, Wong JPH, Fung K, Li ATW, Jia C, Cheng S. Empowering Chinese university health service providers to become mental health champions: insights from the ACE-LYNX intervention. Front Psychiatry 2024; 15:1349476. [PMID: 38585479 PMCID: PMC10995288 DOI: 10.3389/fpsyt.2024.1349476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 02/28/2024] [Indexed: 04/09/2024] Open
Abstract
Background Evidence shows that there is a high prevalence of mental health challenges including depression and anxiety, among Chinese university students. Providing mental health care providers with professional training is crucial to implementing effective mental health promotion initiatives in university settings. Globally, the focus of the mental health system is shifting to recovery and the importance of empowerment is increasingly being emphasized. There is a call to integrate empowerment education into professional training programs for health service providers with the goal of mobilizing them to become mental health champions capable of advancing mental health care. Method The ACE-LYNX (Acceptance and Commitment to Empowerment-Linking Youth and Xin i.e., "heart(s)" in Chinese) intervention took place at six universities in Jinan, Shandong Province, China. It aimed to promote mental health literacy and build capacity among mental health service providers (MHSPs) to enable them to become mental health champions at their universities and beyond. A total of 139 university MHSPs participated. We collected pre-, immediate post- and three-month-post-surveys. In addition, we recruited forty-five participants to take part in three-month- post-intervention focus group interviews to explore their experiences taking part in ACE-LYNX and applying the knowledge, skills, and insights they gained from the intervention. Result This paper reports on the effects of empowerment education, which is a key component of ACE-LYNX, on the MHSPs. Four themes were identified: 1) conscious awareness and behavioral change through psychological empowerment users; 2) professional insights and motivation for organizational empowerment; 3) non-self in the continuum of collective empowerment; and 4) interdisciplinary challenges and divergences in empowerment action. Discussion We found that it is critical to integrate empowerment education into professional training. The process of MHSPs developing their empowerment practice is characterized by their moving from individual to collective empowerment along a continuum, with organizational and collective empowerment taking place in a longer time frame. Experiential learning, empathy education, and critical reflection accelerated the continuous iterative transformative process of empowerment practices. To advance the integration of empowerment into mental health care, the engagement of organizational decision-makers and policy makers in empowerment training is critical to ensure alignment of empowerment values and competence at all levels of service provision.
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Affiliation(s)
- Fenghua Wang
- Department of Social Work, School of Philosophy and Social Development, Shandong University, Jinan, Shandong, China
| | - Jianguo Gao
- Department of Social Work, School of Philosophy and Social Development, Shandong University, Jinan, Shandong, China
| | - Suyu Hao
- Department of Social Work, Law School, Qingdao University of Science and Technology, Qingdao, Shandong, China
| | - Ka Tat Tsang
- Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada
| | | | - Kenneth Fung
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Alan Tai-Wai Li
- Primary Care, Regent Park Community Health Centre, Toronto, ON, Canada
| | - Cunxian Jia
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, Shandong, China
| | - Shengli Cheng
- Department of Social Work, School of Philosophy and Social Development, Shandong University, Jinan, Shandong, China
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Maughan AL, Lunsky Y, Lake J, Mills JS, Fung K, Steel L, Weiss JA. Parent, child, and family outcomes following Acceptance And Commitment Therapy for parents of autistic children: A randomized controlled trial. Autism 2024; 28:367-380. [PMID: 37165863 PMCID: PMC10851654 DOI: 10.1177/13623613231172241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
LAY ABSTRACT Parents of autistic children commonly experience difficulties with their own mental health. This study looked at the effects of a brief group-based Acceptance and Commitment Therapy program, developed for parents of autistic children, youth, and adults. ACT focuses on increasing psychological flexibility, which is the ability to be mindful and accepting of difficult thoughts and experiences, shown to be important for mental wellness. Participants included 54 parents of autistic people, ages 3-34. Parents were randomly divided into two groups: a Treatment group that received the intervention right away, and a Waitlist group that completed the program after the Treatment group completed the trial. All parents filled out questionnaires right before the program began, and at 3, 7, and 17 weeks after randomization. Compared to the group that was waiting to participate in the program, parents in the Treatment group reported greater improvements in depression and family distress, and these improvements were still present 4 months later. Parents in the Treatment group also reported short-term improvements in their positive feelings and personal goals, compared to those waiting. Results showed that ACT may help improve some aspects of mental health for parents of autistic children, but further research is recommended.
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Affiliation(s)
| | - Yona Lunsky
- Centre for Addiction and Mental Health, Canada
| | | | | | | | - Lee Steel
- Centre for Addiction and Mental Health, Canada
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Dennis CL, Brennenstuhl S, Brown HK, Grigoriadis S, Vigod SN, Marini FC, Fung K. Traditional postpartum rituals among immigrant and non-immigrant Chinese women. Transcult Psychiatry 2024; 61:85-94. [PMID: 37993996 PMCID: PMC10903143 DOI: 10.1177/13634615231213829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Due to cultural and systemic factors, Chinese-Canadians tend to use mental health services less or when mental health problems are more severe. Services need to be more culturally responsive in their treatment of mental illness. Around important life events, when there may be heightened vulnerability to mental illness, this is especially important. In this study, postpartum cultural practices were examined among recent immigrant, longer-term immigrant, and Canadian-born Chinese women. We conducted a longitudinal cohort study of 493 women in Toronto, Ontario, with livebirths in 2011-2014. Participants completed a demographic survey and Postpartum Rituals Questionnaire. Most women (82.2%) practiced at least one postpartum ritual. Younger age (OR 0.93; 95% CI 0.87-0.99) and greater participation in the heritage culture (OR 1.28; 95% CI 1.02-1.61) were associated with ritual practice. From among five types of postpartum rituals identified (i.e., avoidance of homeostatic disturbances, dietary practices, wind avoidance, organized support, and cold avoidance), dietary practices were most commonly undertaken and cold avoidance was least commonly undertaken. There were differences in postpartum ritual patterns by immigration status, with immigrant women being more likely to undertake a greater number of rituals, to attribute these rituals to Chinese culture, and to ascribe health benefits to these rituals and being less likely to feel forced into performing these rituals. Our findings underscore the importance of clinicians becoming more aware of Chinese postpartum rituals to provide women with culturally competent and patient-centered care.
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Affiliation(s)
- Cindy-Lee Dennis
- Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Lunenfeld-Tannenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
| | - Sarah Brennenstuhl
- Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Canada
| | - Hilary K. Brown
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Department of Health and Society, University of Toronto Scarborough, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
| | - Sophie Grigoriadis
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Simone N. Vigod
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Women's College Research Institute, Women's College Hospital, Toronto, Canada
| | - Flavia C. Marini
- Lunenfeld-Tannenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
| | - Kenneth Fung
- Department of Psychiatry, University of Toronto, Toronto, Canada
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Papalia F, Fung K, Chen Y, Thornton GD, Geatches N, Cousins F, Kirkham K, Westwood M. Innovative approach to medical leadership and management development: clinician secondment to a management consulting firm. BMJ Lead 2023; 7:304-306. [PMID: 37192097 DOI: 10.1136/leader-2022-000688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 04/13/2023] [Indexed: 05/18/2023]
Abstract
BACKGROUND AND AIM Opportunities to participate in leadership and management with protected time can be limited for clinical trainees. The aim of this fellowship was to gain experience of gold standard healthcare management by becoming part of multidisciplinary teams working to deliver transformational change in the National Health Service (NHS). METHODS A 6-month pilot fellowship, structured as an Out of Programme Experience was created for two registrars to be seconded to the healthcare division of Deloitte, a leading professional services firm. Competitive selection was jointly administered by the Director of Medical Education at St Bartholomew's Hospital and Deloitte. RESULTS The successful candidates worked on service-led and digital transformation projects, interfacing with senior NHS executives and directors. Trainees gained direct experience and understanding of high-level decision making in the NHS, tackling complex service delivery problems and the practical realities of delivering change within a constrained budget. One impact of this pilot has been completion of a business case to scale up the fellowship into an established programme that can allow other trainees to apply. CONCLUSION This innovative fellowship has allowed interested trainees an opportunity to broaden the relevant skills and experience in leadership and management required in specialty training curriculum with real-life application in the NHS.
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Affiliation(s)
- Francesco Papalia
- Cardiology, Barts Health NHS Trust, London, UK
- Cardiology, Barking, Havering and Redbridge University Hospitals NHS Trust, London, UK
| | | | - Yang Chen
- Cardiology, Barts Health NHS Trust, London, UK
- Leadership and Training, Royal College of Physicians, London, UK
| | - George D Thornton
- Cardiology, Barts Health NHS Trust, London, UK
- Institute of Cardiovascular Science, University College London, London, UK
| | | | | | | | - Mark Westwood
- Cardiology, Barts Health NHS Trust, London, UK
- Queen Mary University of London, London, UK
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Jarvis GE, Andermann L, Ayonrinde OA, Beder M, Cénat JM, Ben-Cheikh I, Fung K, Gajaria A, Gómez-Carrillo A, Guzder J, Hanafi S, Kassam A, Kronick R, Lashley M, Lewis-Fernández R, McMahon A, Measham T, Nadeau L, Rousseau C, Sadek J, Schouler-Ocak M, Wieman C, Kirmayer LJ. Taking Action on Racism and Structural Violence in Psychiatric Training and Clinical Practice. Can J Psychiatry 2023; 68:780-808. [PMID: 37198904 PMCID: PMC10517653 DOI: 10.1177/07067437231166985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Affiliation(s)
- G Eric Jarvis
- Division of Social and Transcultural Psychiatry, McGill University, Montréal, QC, Canada; Cultural Consultation Service and Culture and Psychosis Working Group, Jewish General Hospital, Montréal, QC, Canada
| | - Lisa Andermann
- Equity and Inclusion Council; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Oyedeji A Ayonrinde
- Department of Psychiatry, Queen's University, Kingston, ON, Canada; Community Psychiatry, Providence Care, Kingston, ON, Canada
| | - Michaela Beder
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Jude Mary Cénat
- School of Psychology, University of Ottawa, Ottawa, Ontario, Canada; Interdisciplinary Centre for Black Health, University of Ottawa, Ottawa, ON, Canada
| | - Imen Ben-Cheikh
- Department of Psychiatry, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Kenneth Fung
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Asian Initiative in Mental Health, University Health Network, Toronto, ON, Canada; Society for the Study of Psychiatry and Culture, Beverly Hills, CA, USA
| | - Amy Gajaria
- Margaret and Wallace McCain Centre for Child, Youth, and Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Ana Gómez-Carrillo
- Montréal Children's Hospital (MCH), McGill University Health Centre (MUHC), Montréal, QC, Canada; Inuulitsivik Health Centre, Puvirnituq, QC, Canada; Ungava Tulattavik Health Centre, Kuujjuaq, QC, Canada
| | | | - Sarah Hanafi
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Azaad Kassam
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada; Ottawa Newcomer Health Centre, Ottawa, ON, Canada; Wholistic Health and Wellness, Mohawk Council of Akwesasne, Akwesasne, QC, Canada
| | - Rachel Kronick
- Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University, Montréal, QC, Canada; Lady Davis Institute and Sherpa Research Institute, Montréal, QC, Canada
| | - Myrna Lashley
- Department of Psychiatry, McGill University, Montréal, QC, Canada; Research Ethics Board, CIUSSS du Centre-Ouest-de-l'île-de-Montréal, Sir B. Mortimer Jewish General Hospital, Montréal, QC, Canada; Lady Davis Institute for Medical Research, Sir B. Mortimer Jewish General Hospital, Montréal, QC, Canada
| | - Roberto Lewis-Fernández
- Columbia University, New York, NY, USA; New York State Center of Excellence for Cultural Competence and Research Area Leader, Anxiety, Mood, Eating and Related Disorders, New York State Psychiatric Institute, New York, NY, USA
| | | | - Toby Measham
- Department of Psychiatry, McGill University, Montréal, QC, Canada; Divisions of Child Psychiatry and Social and Transcultural Psychiatry, McGill University, Montréal, QC, Canada
| | - Lucie Nadeau
- Department of Psychiatry, McGill University, Montréal, QC, Canada; Montréal University Health Centre, Montréal, QC, Canada; Inuulitsivik Health Centre, Puvirnituq, QC, Canada
| | - Cécile Rousseau
- Division of Social and Cultural Psychiatry, McGill University, Montréal, QC, Canada
| | - Joseph Sadek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Meryam Schouler-Ocak
- Social Psychiatry, Charité - Universitätsmedizin, Berlin, Germany; Psychiatric University Clinic of Charité at St. Hedwig Hospital, Berlin, Germany
| | - Cornelia Wieman
- Indigenous Physicians Association of Canada (IPAC), Vancouver, BC, Canada; First Nations Health Authority (FNHA), Vancouver, BC, Canada
| | - Laurence J Kirmayer
- Division of Social and Transcultural Psychiatry, McGill University, Montréal, QC, Canada; Culture and Mental Health Research Unit, Lady Davis Institute, Jewish General Hospital, Montréal, QC, Canada
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Villela RM, Bawks J, Weir H, Weir D, Ho AO, Kljenak D, Ahmad Y, Amanullah S, Fung K, Petit L. Experiential Psychotherapy Training is Essential for Residents. Can J Psychiatry 2023; 68:699-700. [PMID: 37046406 PMCID: PMC10585128 DOI: 10.1177/07067437231167806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Affiliation(s)
- Renata M. Villela
- Ontario Psychiatric Association, Toronto, Ontario, Canada
- Ontario Medical Association Section on Psychiatry, Toronto, Ontario, Canada
| | - Jordan Bawks
- Ontario Psychiatric Association, Toronto, Ontario, Canada
| | - Heather Weir
- Ontario Medical Association Section on Psychiatry, Toronto, Ontario, Canada
| | - Doug Weir
- Ontario Medical Association, Toronto, Ontario, Canada
| | - Angela O. Ho
- Ontario Psychiatric Association, Toronto, Ontario, Canada
- Ontario Medical Association Section on Psychiatry, Toronto, Ontario, Canada
| | - Diana Kljenak
- Ontario Medical Association Section on Psychiatry, Toronto, Ontario, Canada
| | - Yusra Ahmad
- Ontario Psychiatric Association, Toronto, Ontario, Canada
- Ontario Medical Association Section on Psychiatry, Toronto, Ontario, Canada
| | - Shabbir Amanullah
- Ontario Medical Association Section on Psychiatry, Toronto, Ontario, Canada
| | - Kenneth Fung
- Ontario Psychiatric Association, Toronto, Ontario, Canada
| | - Lyndal Petit
- Ontario Psychiatric Association, Toronto, Ontario, Canada
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Simon J, Fung K, Raisi-Estabragh Z, Aung N, Khanji MY, Zsarnóczay E, Merkely B, Munroe PB, Harvey NC, Piechnik SK, Neubauer S, Leeson P, Petersen SE, Maurovich-Horvat P. Association between subclinical atherosclerosis and cardiac structure and function-results from the UK Biobank Study. Eur Heart J Imaging Methods Pract 2023; 1:qyad010. [PMID: 37822973 PMCID: PMC10563379 DOI: 10.1093/ehjimp/qyad010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 07/03/2023] [Indexed: 10/13/2023]
Abstract
Aims Heart failure (HF) is a major health problem and early diagnosis is important. Atherosclerosis is the main cause of HF and carotid intima-media thickness (IMT) is a recognized early measure of atherosclerosis. This study aimed to investigate whether increased carotid IMT is associated with changes in cardiac structure and function in middle-aged participants of the UK Biobank Study without overt cardiovascular disease. Methods and results Participants of the UK Biobank who underwent CMR and carotid ultrasound examinations were included in this study. Patients with heart failure, angina, atrial fibrillation, and history of myocardial infarction or stroke were excluded. We used multivariable linear regression models adjusted for age, sex, physical activity, body mass index, body surface area, hypertension, diabetes, smoking, ethnicity, socioeconomic status, alcohol intake, and laboratory parameters. In total, 4301 individuals (61.6 ± 7.5 years, 45.9% male) were included. Multivariable linear regression analyses showed that increasing quartiles of IMT was associated with increased left and right ventricular (LV and RV) and left atrial volumes and greater LV mass. Moreover, increased IMT was related to lower LV end-systolic circumferential strain, torsion, and both left and right atrial ejection fractions (all P < 0.05). Conclusion Increased IMT showed an independent association over traditional risk factors with enlargement of all four cardiac chambers, decreased function in both atria, greater LV mass, and subclinical LV dysfunction. There may be additional risk stratification that can be derived from the IMT to identify those most likely to have early cardiac structural/functional changes.
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Affiliation(s)
- Judit Simon
- MTA-SE Cardiovascular Imaging Research Group, Medical Imaging Centre, Semmelweis University, Üllői út 78, H-1082 Budapest, Hungary
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary, Városmajor u 68, H-1122 Budapest, Hungary
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London EC1M 6BQ, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, United Kingdom
| | - Zahra Raisi-Estabragh
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London EC1M 6BQ, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, United Kingdom
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London EC1M 6BQ, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, United Kingdom
| | - Mohammed Y Khanji
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London EC1M 6BQ, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, United Kingdom
- Barts Health NHS Trust, Newham University Hospital, Glen Road, Plaistow, London E1 1BB, United Kingdom
| | - Emese Zsarnóczay
- MTA-SE Cardiovascular Imaging Research Group, Medical Imaging Centre, Semmelweis University, Üllői út 78, H-1082 Budapest, Hungary
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary, Városmajor u 68, H-1122 Budapest, Hungary
| | - Béla Merkely
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary, Városmajor u 68, H-1122 Budapest, Hungary
| | - Patricia B Munroe
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London EC1M 6BQ, United Kingdom
| | - Nicholas C Harvey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton SO16 6YD, United Kingdom
| | - Stefan K Piechnik
- National Institute for Health Research, Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Stefan Neubauer
- National Institute for Health Research, Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Paul Leeson
- Oxford Cardiovascular Clinical Research Facility, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Level 1, John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London EC1M 6BQ, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, United Kingdom
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group, Medical Imaging Centre, Semmelweis University, Üllői út 78, H-1082 Budapest, Hungary
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary, Városmajor u 68, H-1122 Budapest, Hungary
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Yu YK, Yao ZY, Wei YX, Kou CG, Yao B, Sun WJ, Li SY, Fung K, Jia CX. Depressive Symptoms as a Mediator between Excessive Daytime Sleepiness and Suicidal Ideation among Chinese College Students. Int J Environ Res Public Health 2022; 19:16334. [PMID: 36498403 PMCID: PMC9736464 DOI: 10.3390/ijerph192316334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/02/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
The purpose of this study was to verify the mediating role of depressive symptoms between excessive daytime sleepiness and suicidal ideation in college students. Of the 6944 participants, 2609 (37.6%) were male and 4335 (62.4%) were female. College students with excessive daytime sleepiness (p < 0.001) and those with depressive symptoms (p < 0.001) were more likely to have suicidal ideation. Moreover, both excessive daytime sleepiness (β = 0.14, 95% CI: 1.01−1.32) and depressive symptoms (β = 1.47, 95% CI: 3.80−5.00) were associated with suicidal ideation. The effect size of the mediating role of depressive symptoms in excessive daytime sleepiness to suicidal ideation was 50.41% for the entire sample, 58.33% for males, and 42.98% for females. Depressive symptoms partially mediated the relationship between excessive daytime sleepiness and suicidal ideation. The timely assessment of depressive symptoms in college students with excessive daytime sleepiness, and intervention, may reduce their risk of suicidal ideation.
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Affiliation(s)
- Yao-Kun Yu
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University & Shandong University Center for Suicide Prevention Research, 44 West Wenhua Road, Jinan 250012, China
| | - Zhi-Ying Yao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University & Shandong University Center for Suicide Prevention Research, 44 West Wenhua Road, Jinan 250012, China
| | - Yan-Xin Wei
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University & Shandong University Center for Suicide Prevention Research, 44 West Wenhua Road, Jinan 250012, China
| | - Chang-Gui Kou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun 130021, China
| | - Bin Yao
- Student Mental Health Education and Counseling Center, Xi’an Jiaotong University, Xi’an 710049, China
| | - Wen-Jun Sun
- Student Work Office, College of Textile and Clothing, Qingdao University, Qingdao 266071, China
| | - Su-Yun Li
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao 266071, China
| | - Kenneth Fung
- Department of Psychiatry, University of Toronto, Toronto Western Hospital, 399 Bathurst St. 9 EW, Toronto, ON M5T2S8, Canada
| | - Cun-Xian Jia
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University & Shandong University Center for Suicide Prevention Research, 44 West Wenhua Road, Jinan 250012, China
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Aung N, Fung K, Woodbridge SP, Kenawy AA, Jensen MT, Khanji MY, Petersen SE. Annotation and quality assessment of left ventricular filling and relaxation pattern using one-dimensional convolutional neural network. Eur Heart J Cardiovasc Imaging 2022. [DOI: 10.1093/ehjci/jeac141.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Institute For Health Research (NIHR), UK
Introduction
Aberrations in left ventricular (LV) filling or relaxation – known as diastolic dysfunction – occur in heart failure with preserved ejection fraction. CMR is the reference modality for the assessment of ventricular systolic function, however, its role in evaluation of diastolic function is limited at present. One promising technique to assess diastolic function by CMR is the derivation of LV filling and emptying rates from the volume-time curves of cine images.
Purpose
To automatically assess the quality of LV filling-rate curves and annotate the peak emptying and filling rates.
Methods
A previously-described deep-learning network was used to automatically segment the entire cardiac cycle captured by short-axis SSFP cine images from the UK Biobank1. The LV filling-rate curves derived from the volume-time data were smoothed with Savitzky–Golay filter. The peak emptying rate (PER), early peak filling rate (PFR-E) and late peak filling rate (PFR-A) were first annotated by a simple peak finding algorithm from Python Scipy signal module. The preliminary annotated curves were reviewed by five human experts (i) to check for peak-annotation errors and (ii) to provide the curve quality score ranging from 1 to 3 for each peak (score 1 denotes good quality, score 2 represents moderate quality and score 3 indicates poor quality). Higher total score (minimum = 3, maximum = 9), therefore, represents poorer overall curve quality. This expert-annotated dataset was used to train two separate one-dimensional convolutional neural networks (1D-CNN) (Figure 1) for peak annotation and curve quality assessment (QA) using Tensorflow library in Python.
Results
The data from 6,328 LV filling-rate curves were split into the training and testing sets (80:20). The fine-tuned 1D-CNN comprising six hidden layers with two residual connections annotated the PER, PFR-E and PFR-A with the test-set accuracy of 95%, 95% and 98%, respectively. A second trained 1D-CNN for QA based on similar architecture predicted the overall curve quality score with a small error rate (mean absolute error: 0.46, mean squared error: 0.68). These two networks were used to quality check and label 19,409 UK Biobank CMR studies (See Figure 2 for exemplary results). After removing data from poor-quality curves (quality score ≥ 5), 18,735 studies remained. The mean±standard deviation of PER, PFR-E and PFR-A are 461±110 ml/s, 359±117 ml/s and 336±120 ml/s, respectively. Ageing is associated with lower PFR-E (−58.4 ml/s, 95% confidence interval [CI]: −56.1 to −60.7 ml/s per decade increment) and higher PFR-A (18.3 ml/s, 95% CI: 15.8 to 20.8 ml/s per decade increment).
Conclusion
The 1D-CNN models can be used to automatically grade the quality of LV filling rate curves and label important diastolic parameters with a high level of accuracy. The derived data recapitulate impaired LV relaxation pattern associated with ageing and can be used as surrogate indices of diastology by CMR. Figure 1Figure 2
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Affiliation(s)
- N Aung
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
| | - K Fung
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
| | - S P Woodbridge
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
| | - A A Kenawy
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
| | - M T Jensen
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
| | - M Y Khanji
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
| | - S E Petersen
- Queen Mary University of London, William Harvey Research Institute , London , United Kingdom of Great Britain & Northern Ireland
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10
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Aung N, Vargas JD, Yang C, Fung K, Sanghvi MM, Piechnik SK, Neubauer S, Manichaikul A, Rotter JI, Taylor KD, Lima JAC, Bluemke DA, Kawut SM, Petersen SE, Munroe PB. Genome-wide association analysis reveals insights into the genetic architecture of right ventricular structure and function. Nat Genet 2022; 54:783-791. [PMID: 35697868 DOI: 10.1038/s41588-022-01083-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 04/22/2022] [Indexed: 01/03/2023]
Abstract
Right ventricular (RV) structure and function influence the morbidity and mortality from coronary artery disease (CAD), dilated cardiomyopathy (DCM), pulmonary hypertension and heart failure. Little is known about the genetic basis of RV measurements. Here we perform genome-wide association analyses of four clinically relevant RV phenotypes (RV end-diastolic volume, RV end-systolic volume, RV stroke volume, RV ejection fraction) from cardiovascular magnetic resonance images, using a state-of-the-art deep learning algorithm in 29,506 UK Biobank participants. We identify 25 unique loci associated with at least one RV phenotype at P < 2.27 ×10-8, 17 of which are validated in a combined meta-analysis (n = 41,830). Several candidate genes overlap with Mendelian cardiomyopathy genes and are involved in cardiac muscle contraction and cellular adhesion. The RV polygenic risk scores (PRSs) are associated with DCM and CAD. The findings substantially advance our understanding of the genetic underpinning of RV measurements.
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Affiliation(s)
- Nay Aung
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Jose D Vargas
- Veterans Affairs Medical Center, Washington, DC, USA.,Georgetown University, Washington, DC, USA
| | - Chaojie Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Kenneth Fung
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Mihir M Sanghvi
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.,National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Stefan K Piechnik
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Joao A C Lima
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - David A Bluemke
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - Steven M Kawut
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Steffen E Petersen
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. .,National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK. .,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK.
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK. .,National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK.
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11
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Simon J, Fung K, Raisi-Estabragh Z, Aung N, Khanji MY, Kolossváry M, Merkely B, Munroe PB, Harvey NC, Piechnik SK, Neubauer S, Petersen SE, Maurovich-Horvat P. Light to moderate coffee consumption is associated with lower risk of death: a UK Biobank study. Eur J Prev Cardiol 2022; 29:982-991. [PMID: 35048949 DOI: 10.1093/eurjpc/zwac008] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 12/29/2021] [Indexed: 11/14/2022]
Abstract
AIMS To study the association of daily coffee consumption with all-cause and cardiovascular (CV) mortality and major CV outcomes. In a subgroup of participants who underwent cardiovascular magnetic resonance (CMR) imaging, we evaluated the association between regular coffee intake and cardiac structure and function. METHODS AND RESULTS UK Biobank participants without clinically manifested heart disease at the time of recruitment were included. Regular coffee intake was categorized into three groups: zero, light-to-moderate (0.5-3 cups/day), and high (>3 cups/day). In the multivariate analysis, we adjusted for the main CV risk factors. We included 468 629 individuals (56.2 ± 8.1 years, 44.2% male), of whom 22.1% did not consume coffee regularly, 58.4% had 0.5-3 cups per day, and 19.5% had >3 cups per day. Compared to non-coffee drinkers, light-to-moderate (0.5-3 cups per day) coffee drinking was associated with lower risk of all-cause mortality [multivariate hazard ratio (HR) = 0.88, 95% confidence interval (CI): 0.83-0.92; P < 0.001] and CV mortality (multivariate HR = 0.83, 95% CI: 0.74-0.94; P = 0.006), and incident stroke (multivariate HR = 0.79, 95% CI: 0.63-0.99 P = 0.037) after a median follow-up of 11 years. CMR data were available in 30 650 participants. Both light-to-moderate and high coffee consuming categories were associated with dose-dependent increased left and right ventricular end-diastolic, end-systolic and stroke volumes, and greater left ventricular mass. CONCLUSION Coffee consumption of up to three cups per day was associated with favourable CV outcomes. Regular coffee consumption was also associated with a likely healthy pattern of CMR metrics in keeping with the reverse of age-related cardiac alterations.
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Affiliation(s)
- Judit Simon
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts NHS Trust, West Smithfield, London, UK
| | - Zahra Raisi-Estabragh
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts NHS Trust, West Smithfield, London, UK
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts NHS Trust, West Smithfield, London, UK
| | - Mohammed Y Khanji
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts NHS Trust, West Smithfield, London, UK
- Newham University Hospital, Glen Road, Plaistow, Barts Health NHS Trust, London, UK
| | - Márton Kolossváry
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Béla Merkely
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Patricia B Munroe
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Nicholas C Harvey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Stefan K Piechnik
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research, Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research, Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts NHS Trust, West Smithfield, London, UK
- Health Data Research UK, London, UK
- Alan Turing Institute, London, UK
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
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12
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McCready A, Quinn M, Francis P, Stortz R, Kuruvilla S, Stewart P, Palma D, Lang P, Read N, Sathya J, Venkatesan V, Nichols A, MacNeil D, Fung K, Mendez A, Carreau C, Hawkins S, Parker C, Warner L, Winquist E. Impact of a Head and Neck Cancer Chemoradiation (HNC CRT) Nurse Practitioner (NP) on Patient Outcomes. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2021.12.143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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13
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Rauseo E, Omer M, Amir-Khalili A, Sojoudi A, Le TT, Cook SA, Hausenloy DJ, Ang B, Toh DF, Bryant J, Chin CWL, Paiva JM, Fung K, Cooper J, Khanji MY, Aung N, Petersen SE. A Systematic Quality Scoring Analysis to Assess Automated Cardiovascular Magnetic Resonance Segmentation Algorithms. Front Cardiovasc Med 2022; 8:816985. [PMID: 35242820 PMCID: PMC8886212 DOI: 10.3389/fcvm.2021.816985] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/22/2021] [Indexed: 12/29/2022] Open
Abstract
Background The quantitative measures used to assess the performance of automated methods often do not reflect the clinical acceptability of contouring. A quality-based assessment of automated cardiac magnetic resonance (CMR) segmentation more relevant to clinical practice is therefore needed. Objective We propose a new method for assessing the quality of machine learning (ML) outputs. We evaluate the clinical utility of the proposed method as it is employed to systematically analyse the quality of an automated contouring algorithm. Methods A dataset of short-axis (SAX) cine CMR images from a clinically heterogeneous population (n = 217) were manually contoured by a team of experienced investigators. On the same images we derived automated contours using a ML algorithm. A contour quality scoring application randomly presented manual and automated contours to four blinded clinicians, who were asked to assign a quality score from a predefined rubric. Firstly, we analyzed the distribution of quality scores between the two contouring methods across all clinicians. Secondly, we analyzed the interobserver reliability between the raters. Finally, we examined whether there was a variation in scores based on the type of contour, SAX slice level, and underlying disease. Results The overall distribution of scores between the two methods was significantly different, with automated contours scoring better than the manual (OR (95% CI) = 1.17 (1.07–1.28), p = 0.001; n = 9401). There was substantial scoring agreement between raters for each contouring method independently, albeit it was significantly better for automated segmentation (automated: AC2 = 0.940, 95% CI, 0.937–0.943 vs manual: AC2 = 0.934, 95% CI, 0.931–0.937; p = 0.006). Next, the analysis of quality scores based on different factors was performed. Our approach helped identify trends patterns of lower segmentation quality as observed for left ventricle epicardial and basal contours with both methods. Similarly, significant differences in quality between the two methods were also found in dilated cardiomyopathy and hypertension. Conclusions Our results confirm the ability of our systematic scoring analysis to determine the clinical acceptability of automated contours. This approach focused on the contours' clinical utility could ultimately improve clinicians' confidence in artificial intelligence and its acceptability in the clinical workflow.
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Affiliation(s)
- Elisa Rauseo
- NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom
| | | | | | | | - Thu-Thao Le
- National Heart Centre Singapore, Singapore, Singapore
| | - Stuart Alexander Cook
- National Heart Centre Singapore, Singapore, Singapore.,Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore, Singapore, Singapore
| | - Derek John Hausenloy
- National Heart Centre Singapore, Singapore, Singapore.,Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore, Singapore, Singapore.,Yong Loo Lin School of Medicine, National University Singapore, Singapore, Singapore.,The Hatter Cardiovascular Institute, University College London, London, United Kingdom.,Cardiovascular Research Center, College of Medical and Health Sciences, Asia University, Taichung, Taiwan
| | - Briana Ang
- National Heart Centre Singapore, Singapore, Singapore
| | | | | | | | | | - Kenneth Fung
- NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom
| | - Jackie Cooper
- NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom
| | - Mohammed Yunus Khanji
- NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.,Department of Cardiology, Newham University Hospital, Barts Health NHS Trust, London, United Kingdom
| | - Nay Aung
- NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom
| | - Steffen Erhard Petersen
- NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom.,Health Data Research UK, London, United Kingdom.,Alan Turing Institute, London, United Kingdom
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14
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Vahabi M, Pui-Hing Wong J, Moosapoor M, Akbarian A, Fung K. Effects of Acceptance and Commitment Therapy (ACT) on Mental Health and Resiliency of Migrant Live-in Caregivers in Canada: Pilot Randomized Wait List Controlled Trial. JMIR Form Res 2022; 6:e32136. [PMID: 35084337 PMCID: PMC9090443 DOI: 10.2196/32136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/24/2021] [Accepted: 09/25/2021] [Indexed: 11/13/2022] Open
Abstract
Background
Temporary migrant live-in caregivers constitute a vulnerable stream of temporary foreign workers in Canada. This is because the majority are racialized women from the Global South, the gendered nature of caregiving work has historically been undervalued, and their working and living spheres are intertwined which makes application of labor laws and surveillance almost impossible. Their invisible position in the fabric of Canadian society along with their precarious employment and immigration status place their mental health at jeopardy. There is a paucity of research about psychological support for this population.
Objective
Our pilot study Women Empowerment—Caregiver Acceptance and Resilience E-Learning (WE2CARE) aimed to assess the efficacy of a 6-week online delivery of a psychological intervention based on acceptance and commitment therapy (ACT) in reducing psychological distress and promoting resiliency among live-in care givers in the Greater Toronto Area.
Methods
A pilot randomized wait list controlled design was used. Participants were recruited by two community peer champions working with community health organizations serving migrant live-in caregivers. A total of 36 participants were recruited and randomly assigned to the intervention and wait list control groups; 7 dropped out of the study due to competing life priorities. Standardized self-reported surveys were administered online pre-, post-, and 6-week postintervention to assess mental distress (DASS-21), psychological flexibility (AAQ-2), mindfulness (CAMS-R), and Multi-System Model of Resilience (MSMR-I). Independent and dependent t tests were used to compare study outcomes at pre, post, and 6-week follow-up across and within both arms of the study. Linear mixed effects models were created for each outcome of interest from baseline to postintervention among intervention and control participants. Self-reported impact of the WE2CARE intervention was examined using independent t tests across the study arms.
Results
Average age of participants was 38 years. Many were born in the Philippines (23/29, 79%). The data on the impact of the psychological intervention showed a lower level of depression, anxiety, and stress among the intervention group compared with the control. However, the differences were not significant due to small sample size and COVID-19 crisis (6.94 vs 9.50, P=.54; 6.94 vs 10.83, P=.20; 7.76 vs 10.33, P=.44, respectively). There was a significant improvement in mindful qualities and external resilience, particularly in life satisfaction and accessible support among the intervention group (37.18 vs 32.92, t22=2.35, P=.03; 20.29 vs 16.5, t21=2.98, P=.007; 8.47 vs 6.75, t14=2.41, P=.03; 7.59 vs 5.33, t16=.008, respectively).
Conclusions
WE2CARE is among the first studies exploring the efficacy of online delivery of ACT in addressing mental health challenges among live-in caregivers. While there are increased web-based ACT interventions, few use group videoconferencing to promote peer connection and mutual support. WE2CARE showed promising results in reducing psychological distress and promoting mindfulness and resiliency. The intervention highly motivated participants to engage collectively in building social support networks.
International Registered Report Identifier (IRRID)
RR2-10.2196/preprints.31211
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Affiliation(s)
- Mandana Vahabi
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | | | - Masoomeh Moosapoor
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | - Abdolreza Akbarian
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | - Kenneth Fung
- Toronto Western Hospital, University Health Network, Toronto, ON, Canada
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15
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Fung K, Liu JJ, Vahabi M, Li ATW, Zurowski M, Wong JPH. Pandemic Acceptance and Commitment to Empowerment Response (PACER) Training: Protocol for the Development and Rapid-Response Deployment. JMIR Res Protoc 2021; 10:e33495. [PMID: 34726602 PMCID: PMC8651179 DOI: 10.2196/33495] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/08/2021] [Accepted: 10/08/2021] [Indexed: 12/01/2022] Open
Abstract
Background During a global pandemic, it is critical to rapidly deploy a psychological intervention to support the mental health and resilience of highly affected individuals and communities. Objective This is the rationale behind the development and implementation of the Pandemic Acceptance and Commitment to Empowerment Response (PACER) Training, an online, blended, skills building intervention to increase the resilience and well-being of participants while promoting their individual and collective empowerment and capacity building. Methods Based on acceptance and commitment therapy (ACT) and social justice–based group empowerment psychoeducation (GEP), we developed the Acceptance and Commitment to Empowerment (ACE) model to enhance psychological resilience and collective empowerment. The PACER program consists of 6 online, interactive, self-guided modules complemented by 6 weekly, 90-minute, videoconference, facilitator-led, group sessions. Results As of August 2021, a total of 325 participants had enrolled in the PACER program. Participants include frontline health care providers and Chinese-Canadian community members. Conclusions The PACER program is an innovative intervention program with the potential for increasing resilience and empowerment while reducing mental distress during the pandemic. International Registered Report Identifier (IRRID) DERR1-10.2196/33495
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Affiliation(s)
- Kenneth Fung
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Jenny Jw Liu
- Toronto Western Hospital, University Health Network, Toronto, ON, Canada.,Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | - Mandana Vahabi
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | | | - Mateusz Zurowski
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Toronto Western Hospital, University Health Network, Toronto, ON, Canada
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16
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Palma D, Prisman E, Berthelet E, Tran E, Hamilton S, Wu J, Eskander A, Higgins K, Karam I, Poon I, Husain Z, Enepekides D, Hier M, Sultanem K, Richardson K, Mlynarek A, Johnson-Obaseki S, Eapen L, Odell M, Bayley A, Dowthwaite S, Jackson J, Dzienis M, O'Neil J, Chandarana S, Banerjee R, Hart R, Chung J, Tenenholz T, Krishnan S, Le H, Yoo J, Mendez A, Winquist E, Kuruvilla S, Stewart P, Warner A, Mitchell S, Chen J, Parker C, Wehrli B, Kwan K, Theurer J, Sathya J, Hammond J, Read N, Venkatesan V, MacNeil D, Fung K, Nichols A. A Randomized Trial of Radiotherapy vs. Trans-Oral Surgery for Treatment De-Escalation in HPV-Associated Oropharyngeal Squamous Cell Carcinoma (ORATOR2). Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.09.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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17
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Sato C, Adumattah A, Abulencia MK, Garcellano PD, Li ATW, Fung K, Poon MKL, Vahabi M, Wong JPH. COVID-19 Mental Health Stressors of Health Care Providers in the Pandemic Acceptance and Commitment to Empowerment Response (PACER) Intervention: A Qualitative Study (Preprint). JMIR Form Res 2021; 6:e35280. [PMID: 35138256 PMCID: PMC8942093 DOI: 10.2196/35280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/15/2022] [Accepted: 02/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background Objective Methods Results Conclusions
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Affiliation(s)
- Christa Sato
- Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada
| | - Anita Adumattah
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | | | | | - Alan Tai-Wai Li
- Regent Park Community Health Centre, Toronto, ON, Canada
- Committee for Accessible AIDS Treatment, Toronto, ON, Canada
| | - Kenneth Fung
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Mandana Vahabi
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
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18
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Zayed S, Lin C, Boldt G, Lang P, Read N, Venkatesan V, Sathya J, Fung K, MacNeil D, Mendez A, Yoo J, Warner A, Nichols A, Palma D. Survival Outcomes in Primary Head and Neck Adult Sarcoma: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.1115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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19
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Zayed S, Lin C, Boldt G, Lang P, Read N, Venkatesan V, Sathya J, Fung K, MacNeil D, Mendez A, Yoo J, Warner A, Nichols A, Palma D. Survival Outcomes in Primary Angiosarcoma of the Head and Neck: A Systematic Review and Meta-Analysis. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.984] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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20
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Simon J, Fung K, Raisi-Estabragh Z, Aung N, Khanji MY, Kolossvary M, Merkely B, Munroe PB, Harvey NC, Piechnik SK, Neubauer S, Petersen SE, Maurovich-Horvat P. Association of daily coffee consumption with cardiovascular health – results from the UK Biobank. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2416] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
There are conflicting reports on the association of coffee consumption with cardiovascular (CV) health. The UK Biobank is a prospective cohort study including data for half a million middle-aged individuals.
Purpose
We studied the association of daily coffee consumption with all-cause and CV mortality, and incidence of the major CV diseases in the UK Biobank. In a subgroup of participants who underwent cardiovascular magnetic resonance (CMR), we evaluated the association between regular coffee intake and cardiac structure and function parameters.
Methods
UK Biobank cohort of participants without clinically manifested heart disease at the time of recruitment were included. Regular coffee intake was categorized into 3 groups: zero, light-to-moderate (0.5–3 cups/day) and high (>3 cups/day) coffee drinkers. We estimated association of daily coffee consumption with incident outcomes using multivariable Cox-regression models (median follow-up of 11 years) and, in the subset with CMR data, with left and right ventricular (LV, RV) end-systolic and end-diastolic volumes, LV mass, and LV/RV stroke volume using multivariable linear regression. Models were adjusted for potential confounders and mediators, including: age, sex, non-European ethnicities, body mass index, smoking, physical activity, Townsend deprivation index, alcohol, meat, fruit and vegetable intake, hypertension, diabetes mellitus, and cholesterol level.
Results
We included 468,629 individuals (mean age 56.2±8.1 years, 44.2% male). Among them, 22.1% did not consume coffee on a regular basis, 58.4% had 0.5–3 cups per day and 19.5% had >3 cups per day. After adjustment for potential confounders and mediators, compared to non-coffee drinkers, light-to-moderate coffee drinking was associated with lower risk of all-cause mortality (HR=0.88, p<0.001), CV mortality (HR=0.83, p=0.006), and incident stroke (HR=0.79; p=0.037). CMR data were available in 30,650 participants. In multivariable analysis, compared to non-coffee drinkers, both the light-to-moderate and high coffee consuming categories, were associated with significantly increased LV and RV ventricular end-systolic (β=0.91 and 1.64 for LV and 1.10 and 1.72 for RV), end-diastolic (β=2.21 and 3.28 for LV and 2.24 and 3.35 for RV) and stroke volumes (β=1.31 and 1.64 for LV and 1.15 and 1.63 for RV), as well as greater LV mass (β=0.78 and 1.64; all p<0.001).
Conclusion
In this large study of the UK Biobank population, regular coffee consumption of up to 3 cups per day was associated with favorable cardiovascular outcomes, in particular, decreased all-cause and CV mortality and stroke incidence. Regular coffee consumption was also associated with a pattern of CMR metrics in keeping with the reverse of age-related cardiac alterations.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- J Simon
- Semmelweis University, MTA-SE Cardiovascular Research Group, Heart and Vascular Center, Budapest, Hungary
| | - K Fung
- Queen Mary University of London, 2William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, United Kingdom
| | - Z Raisi-Estabragh
- Queen Mary University of London, 2William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, United Kingdom
| | - N Aung
- Queen Mary University of London, 2William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, United Kingdom
| | - M Y Khanji
- Queen Mary University of London, 2William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, United Kingdom
| | - M Kolossvary
- Semmelweis University, MTA-SE Cardiovascular Research Group, Heart and Vascular Center, Budapest, Hungary
| | - B Merkely
- Semmelweis University, MTA-SE Cardiovascular Research Group, Heart and Vascular Center, Budapest, Hungary
| | - P B Munroe
- Queen Mary University of London, 2William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, United Kingdom
| | - N C Harvey
- University of Southampton, MRC Lifecourse Epidemiology Unit, Southampton, United Kingdom
| | - S K Piechnik
- University of Oxford, National Institute for Health Research, Oxford Biomedical Research Centre, Division of Cardiovascul, Oxford, United Kingdom
| | - S Neubauer
- University of Oxford, National Institute for Health Research, Oxford Biomedical Research Centre, Division of Cardiovascul, Oxford, United Kingdom
| | - S E Petersen
- Queen Mary University of London, 2William Harvey Research Institute, NIHR Barts Biomedical Research Centre, London, United Kingdom
| | - P Maurovich-Horvat
- Semmelweis University, MTA-SE Cardiovascular Research Group, Heart and Vascular Center, Budapest, Hungary
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21
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Fung K, Cheng SL, Ning X, Li ATW, Zhang J, Liu JJW, Hilario CT, Cheng X, Yu M, Jia CX, Gao J, Wong JPH. Mental Health Promotion and Stigma Reduction Among University Students Using the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) Framework: Protocol for a Mixed Methods Study. JMIR Res Protoc 2021; 10:e25592. [PMID: 34435956 PMCID: PMC8430866 DOI: 10.2196/25592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 05/05/2021] [Accepted: 05/12/2021] [Indexed: 12/03/2022] Open
Abstract
Background Rapid urbanization, academic pressures, and developmental life transition stressors contribute to mental health stress for postsecondary students in China. Effective prevention, early identification, and timely intervention are challenged by stigma, a lack of mental health literacy, and inadequate mental health resources. Objective Our implementation science (IS) research project is aimed at evaluating the use of an evidence-informed mental health promotion intervention named Acceptance and Commitment to Empowerment – Linking Youth and ‘Xin’ (hearts) (ACE-LYNX) to promote university student mental health in Jinan, China. Methods We will engage and collaborate with Shandong Mental Health Center, the provincial mental health center, and six local universities in different regions of Jinan. The ACE-LYNX intervention aims to reduce social stigma against mental illness, enhance mental health literacy, and improve access to quality mental health care by increasing interdisciplinary collaboration and forming a mental health network. It is based on two evidence-based approaches, Acceptance and Commitment Therapy (ACT) and Group Empowerment Psychoeducation (GEP), and it will be delivered through online learning and in-person group training. The project will train 90 interdisciplinary professionals using the model. They will in turn train 15 professionals and 20 students at each university. The project will adopt the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework, which provides a structure to examine the process and outcomes of implementation using mixed methods comprising quantitative and qualitative approaches along five dimensions: reach, efficacy, adoption, implementation, and maintenance. Results Over the course of the project, 720 champions will be directly trained. They will contribute to developing a formal and informal mental health network, strengthened by student-led mental health initiatives and professional-led initiatives to promote collaborative care and facilitated care pathways. We anticipate that our project will reach out to 11,000 to 18,000 students. Conclusions This IS protocol will outline our unique intervention model and key steps to contextualize, implement, and evaluate community-based mental health intervention. International Registered Report Identifier (IRRID) PRR1-10.2196/25592
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Affiliation(s)
- Kenneth Fung
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sheng-Li Cheng
- Department of Social Work, School of Philosophy and Social Development, Shandong University, Jinan, China
| | - Xuan Ning
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | | | | | - Jenny Jing-Wen Liu
- Daphne Cockwell School of Nursing, Ryerson University, Toronto, ON, Canada
| | | | | | - Miao Yu
- Department of Social Work, School of Philosophy and Social Development, Shandong University, Jinan, China
| | - Cun-Xian Jia
- Department of Epidemiology, Shandong University, Jinan, China
| | - Jianguo Gao
- Department of Social Work, School of Philosophy and Social Development, Shandong University, Jinan, China
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22
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Magnacca C, Thomson K, Marcinkiewicz A, Davis S, Steel L, Lunsky Y, Fung K, Vause T, Redquest B. A Telecommunication Model to Teach Facilitator to Deliver Acceptance and Commitment Training. Behav Anal Pract 2021; 15:730-751. [PMID: 34422238 PMCID: PMC8366160 DOI: 10.1007/s40617-021-00628-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/12/2021] [Indexed: 12/01/2022] Open
Abstract
Providing mediator training using a telecommunication format increases access to training by reducing geographical and financial barriers, while maintaining or increasing efficiency. Limited research has implemented this format to train facilitators in acceptance and commitment training (ACT), an empirically supported intervention. The aim of this research was to examine the efficacy of behavioral skills training via telecommunication for training novice facilitators to provide ACT to caregivers of individuals with neurodevelopmental disabilities. This two-part study involved concurrent multiple-baseline designs, each across four participants. Quantitative data on fidelity and confidence were collected at baseline, posttraining, and at 1-month follow-up. The results from this study provide preliminary support for the use of behavioral skills training via telecommunication to train ACT facilitators. Increasing the number of competently trained facilitators will help build capacity to increase access to ACT across geographical regions. Supplementary Information The online version contains supplementary material available at 10.1007/s40617-021-00628-x.
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Affiliation(s)
- Carly Magnacca
- Department of Applied Disability Studies, Brock University, St. Catharines, ON L2S 3A1 Canada
| | - Kendra Thomson
- Department of Applied Disability Studies, Brock University, St. Catharines, ON L2S 3A1 Canada.,Azrieli Adult Neuordevelopmental Centre (Centre for Addiction and Mental Health), Toronto, ON Canada
| | - Amanda Marcinkiewicz
- Azrieli Adult Neuordevelopmental Centre (Centre for Addiction and Mental Health), Toronto, ON Canada.,Department of Child and Youth Studies, Brock University, St. Catharines, ON Canada
| | - Sarah Davis
- Department of Child and Youth Studies, Brock University, St. Catharines, ON Canada
| | - Lee Steel
- Azrieli Adult Neuordevelopmental Centre (Centre for Addiction and Mental Health), Toronto, ON Canada
| | - Yona Lunsky
- Azrieli Adult Neuordevelopmental Centre (Centre for Addiction and Mental Health), Toronto, ON Canada
| | - Kenneth Fung
- Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Tricia Vause
- Department of Child and Youth Studies, Brock University, St. Catharines, ON Canada
| | - Brianne Redquest
- Azrieli Adult Neuordevelopmental Centre (Centre for Addiction and Mental Health), Toronto, ON Canada
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23
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Simon J, Fung K, Kolossváry M, Sanghvi MM, Aung N, Paiva JM, Lukaschuk E, Carapella V, Merkely B, Bittencourt MS, Karády J, Lee AM, Piechnik SK, Neubauer S, Maurovich-Horvat P, Petersen SE. Sex-specific associations between alcohol consumption, cardiac morphology, and function as assessed by magnetic resonance imaging: insights form the UK Biobank Population Study. Eur Heart J Cardiovasc Imaging 2021; 22:1009-1016. [PMID: 33313691 PMCID: PMC7613253 DOI: 10.1093/ehjci/jeaa242] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 08/03/2020] [Indexed: 12/19/2022] Open
Abstract
AIMS Data regarding the effects of regular alcohol consumption on cardiac anatomy and function are scarce. Therefore, we sought to determine the relationship between regular alcohol intake and cardiac structure and function as evaluated with cardiac magnetic resonance imaging. METHODS AND RESULTS Participants of the UK Biobank who underwent cardiac magnetic resonance were enrolled in our analysis. Data regarding regular alcohol consumption were obtained from questionnaires filled in by the study participants. Exclusion criteria were poor image quality, missing, or incongruent data regarding alcohol drinking habits, prior drinking, presence of heart failure or angina, and prior myocardial infarction or stroke. Overall, 4335 participants (61.5 ± 7.5 years, 47.6% male) were analysed. We used multivariate linear regression models adjusted for age, ethnicity, body mass index, smoking, hypertension, diabetes mellitus, physical activity, cholesterol level, and Townsend deprivation index to examine the relationship between regular alcohol intake and cardiac structure and function. In men, alcohol intake was independently associated with marginally increased left ventricular end-diastolic volume [β = 0.14; 95% confidence interval (CI) = 0.05-0.24; P = 0.004], left ventricular stroke volume (β = 0.08; 95% CI = 0.03-0.14; P = 0.005), and right ventricular stroke volume (β = 0.08; 95% CI = 0.02-0.13; P = 0.006). In women, alcohol consumption was associated with increased left atrium volume (β = 0.14; 95% CI = 0.04-0.23; P = 0.006). CONCLUSION Alcohol consumption is independently associated with a marginal increase in left and right ventricular volumes in men, but not in women, whereas alcohol intake showed an association with increased left atrium volume in women. Our results suggest that there is only minimal relationship between regular alcohol consumption and cardiac morphology and function in an asymptomatic middle-aged population.
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Affiliation(s)
- Judit Simon
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Márton Kolossváry
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Mihir M. Sanghvi
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Nay Aung
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Jose Miguel Paiva
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Elena Lukaschuk
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom
| | | | - Béla Merkely
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | | | - Júlia Karády
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Cardiac MR PET CT Program, Massachusetts General Hospital – Harvard Medical School, Boston, USA
| | - Aaron M Lee
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Stefan K. Piechnik
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom
| | - Stefan Neubauer
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary
- Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
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24
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Rauseo E, Lockhart L, Paiva JM, Fung K, Khanji MY, Raisi-Estabragh Z, Amir-Khalili A, Petersen SE. Automated myocardial segmentation in native t1-mapping cardiovascular magnetic resonance images based on machine learning: a validation study in the UK biobank"s covid-19 subset. Eur Heart J Cardiovasc Imaging 2021. [PMCID: PMC8344639 DOI: 10.1093/ehjci/jeab090.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Innovate UK Background Regional assessment of septal native T1 values with cardiovascular magnetic resonance (CMR) is used to characterise diffuse myocardial diseases. Previous studies suggest its potential role in detecting early pathological alterations, which may help identify high-risk subjects at early disease stages. Automated analysis of myocardial native T1 images may enable faster CMR analysis and reduce inter-observer variability of manual analysis. However, the technical performance of such methodologies has not been previously reported. Purpose We tested, in a subset of UK Biobank participants, the degree of agreement between CMR septal myocardial T1 values obtained from our machine learning (ML) algorithm and septal native T1 values computed from manual segmentations. Methods We analysed the first 292 participants who were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and had CMR imaging (1.5 Tesla, Siemens MAGNETOM Aera). T1 mapping was performed in a single mid-ventricular short axis (SAX) slice using ShMOLLI (WIP780B) sequences. Three experienced CMR readers independently measured native T1 values by manually placing a single region of interest (ROI) covering half of the anteroseptal and half of the inferoseptal wall using cvi42 post-processing software (version 5.11). A mean T1 value for each participant was then calculated. A ML algorithm developed by Circle Cardiovascular Imaging Inc. was then applied to the same images to derive the myocardium T1 values automatically. The algorithm was previously trained to segment myocardium from SAX T1 and non-T1 mapping images on two external CMR datasets. We compared the mean septal ROI T1 values to the mean myocardium T1 values predicted by the ML algorithm. Results Two studies were excluded after quality control. The ML-derived and the manually calculated mean T1 values were significantly correlated (r = 0.82, p < 0.001). The Bland-Altman analysis between the two methods showed a mean bias of 3.64 ms, with 95% limits of agreement of −38.88 to 53.46 ms, indicating good agreement (figure 1). Conclusions We demonstrated strong correlation and good agreement between native T1 values obtained from our automated analysis method and manual T1 septal analysis in a subset of UK Biobank participants. This algorithm may represent a valuable tool for clinicians allowing for fast and potentially less operator-dependent myocardial tissue characterisation. However, validation of more extensive datasets and quality control processes are needed.
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Affiliation(s)
- E Rauseo
- William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary, London, United Kingdom of Great Britain & Northern Ireland
| | - L Lockhart
- Circle Cardiovascular Imaging, Calgary, Canada
| | - JM Paiva
- Circle Cardiovascular Imaging, Calgary, Canada
| | - K Fung
- William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary, London, United Kingdom of Great Britain & Northern Ireland
| | - MY Khanji
- William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary, London, United Kingdom of Great Britain & Northern Ireland
| | - Z Raisi-Estabragh
- William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary, London, United Kingdom of Great Britain & Northern Ireland
| | | | - SE Petersen
- William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary, London, United Kingdom of Great Britain & Northern Ireland
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25
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Ricci F, Aung N, Thomson R, Boubertakh R, Camaioni C, Doimo S, Sanghvi MM, Fung K, Khanji MY, Lee A, Malcolmson J, Mantini C, Paiva J, Gallina S, Fedorowski A, Mohiddin SA, Aquaro GD, Petersen SE. Pulmonary blood volume index as a quantitative biomarker of haemodynamic congestion in hypertrophic cardiomyopathy. Eur Heart J Cardiovasc Imaging 2021; 20:1368-1376. [PMID: 31504370 PMCID: PMC6868494 DOI: 10.1093/ehjci/jez213] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 04/01/2019] [Accepted: 08/21/2019] [Indexed: 12/24/2022] Open
Abstract
Aims The non-invasive assessment of left ventricular (LV) diastolic function and filling pressure in hypertrophic cardiomyopathy (HCM) is still an open issue. Pulmonary blood volume index (PBVI) by cardiovascular magnetic resonance (CMR) has been proposed as a quantitative biomarker of haemodynamic congestion. We aimed to assess the diagnostic accuracy of PBVI for left atrial pressure (LAP) estimation in patients with HCM. Methods and results We retrospectively identified 69 consecutive HCM outpatients (age 58 ± 11 years; 83% men) who underwent both transthoracic echocardiography (TTE) and CMR. Guideline-based detection of LV diastolic dysfunction was assessed by TTE, blinded to CMR results. PBVI was calculated as the product of right ventricular stroke volume index and the number of cardiac cycles for a bolus of gadolinium to pass through the pulmonary circulation as assessed by first-pass perfusion imaging. Compared to patients with normal LAP, patients with increased LAP showed significantly larger PBVI (463 ± 127 vs. 310 ± 86 mL/m2, P < 0.001). PBVI increased progressively with worsening New York Heart Association functional class and echocardiographic stages of diastolic dysfunction (P < 0.001 for both). At the best cut-off point of 413 mL/m2, PBVI yielded good diagnostic accuracy for the diagnosis of LV diastolic dysfunction with increased LAP [C-statistic = 0.83; 95% confidence interval (CI): 0.73–0.94]. At multivariable logistic regression analysis, PBVI was an independent predictor of increased LAP (odds ratio per 10% increase: 1.97, 95% CI: 1.06–3.68; P = 0.03). Conclusion PBVI is a promising CMR application for assessment of diastolic function and LAP in patients with HCM and may serve as a quantitative marker for detection, grading, and monitoring of haemodynamic congestion.
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Affiliation(s)
- Fabrizio Ricci
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University, Via Luigi Polacchi, 11 - 66100 Chieti, Italy.,William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK.,Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-205 02 Malmö, Sweden.,Fondazione Villa Serena per la Ricerca, Viale Leonardo Petruzzi, 42 - 65013 Città Sant'Angelo, Italy
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Ross Thomson
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Redha Boubertakh
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Claudia Camaioni
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Sara Doimo
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK.,Cardiovascular Department, Azienda Sanitaria Universitaria Integrata, University of Trieste, via Pietro Valdoni, 7 - 34149 Trieste, Italy
| | - Mihir M Sanghvi
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Mohammed Y Khanji
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Aaron Lee
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - James Malcolmson
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Cesare Mantini
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University, Via Luigi Polacchi, 11 - 66100 Chieti, Italy
| | - José Paiva
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | - Sabina Gallina
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University, Via Luigi Polacchi, 11 - 66100 Chieti, Italy
| | - Artur Fedorowski
- Department of Clinical Sciences, Lund University, Skåne University Hospital, SE-205 02 Malmö, Sweden
| | - Saidi A Mohiddin
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
| | | | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.,Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London EC1A 7BE, UK
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Kirmayer LJ, Fernando S, Guzder J, Lashley M, Rousseau C, Schouler-Ocak M, Lewis-Fernández R, Fung K, Jarvis GE. A Call to Action on Racism and Social Justice in Mental Health: Un appel à l'action en matière de racisme et de justice sociale en santé mentale. Can J Psychiatry 2021; 66:590-593. [PMID: 32954813 PMCID: PMC8138735 DOI: 10.1177/0706743720964333] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Laurence J Kirmayer
- James McGill Professor and Director, Division of Social and Transcultural Psychiatry, McGill University, Montréal, Québec
| | - Suman Fernando
- Emeritus Professor in Social Sciences, London Metropolitan University, London
| | - Jaswant Guzder
- Professor, Division of Social and Transcultural Psychiatry, McGill University, Montréal, Québec
| | - Myrna Lashley
- Assistant Professor, Division of Social and Transcultural Psychiatry, McGill University, Montréal, Québec
| | - Cécile Rousseau
- Professor, Division of Social and Transcultural Psychiatry, McGill University, Montréal, Québec
| | - Meryam Schouler-Ocak
- Professor for Intercultural Psychiatry and Psychotherapy, Psychiatric University Clinic of Charité, Berlin; Chair of Section on Transcultural Psychiatry of World Psychiatric Association
| | - Roberto Lewis-Fernández
- Professor of Clinical Psychiatry, Columbia University; Director, NYS Center of Excellence for Cultural Competence, New York State Psychiatric Institute; President, World Association of Cultural Psychiatry
| | - Kenneth Fung
- Associate Professor, Psychotherapy, Humanities, and Psychosocial Interventions (PHPI) Division, Department of Psychiatry, University of Toronto; President, Society for the Study of Psychiatry and Culture
| | - G Eric Jarvis
- Associate Professor, Division of Social and Transcultural Psychiatry and Director, Cultural Consultation Service, McGill University, Montréal, Québec; Chair, Section on Transcultural Psychiatry, Canadian Psychiatric Association
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St-Amant O, Vahabi M, Wong JPH, Salami B, Fung K, Miholjcic J, Tan V. Invisible diaspora: A scoping review of migrant caregivers’ social integration trajectory. Int Health Trends & Persp 2021. [DOI: 10.32920/ihtp.v1i1.1419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Background: The Canadian Caregiver program, initiated in 1992, functions to conceal the inadequate public policy and programs on child and elder care in Canada. Consequently, migrant caregivers have become an invisible diaspora filling a domestic labour gap with few protections.
Aim and Methods: This scoping review aims to identify the systemic barriers that undermine social integration of migrant caregivers. We searched ten publication index databases from 2001-2020. We retrieved 1,624 articles, after accounting for exclusion criteria, 22 peer-reviewed articles were selected for this review representing migrant women across Canada who are and/or were part of the program.
Results: Four key barriers were identified: economic exploitation, deskilling and downward occupational mobility, asymmetrical accountability, and social isolation.
Conclusion: Discriminatory policies and hidden exploitative employment practices of the Canadian Caregiver program perpetuate a cycle of marginalization. This review also found that community support groups and alliances function to promote resilience among migrant caregivers through community advocacy.
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Raisi-Estabragh Z, McCracken C, Cooper J, Fung K, Paiva JM, Khanji MY, Rauseo E, Biasiolli L, Raman B, Piechnik SK, Neubauer S, Munroe PB, Harvey NC, Petersen SE. Adverse cardiovascular magnetic resonance phenotypes are associated with greater likelihood of incident coronavirus disease 2019: findings from the UK Biobank. Aging Clin Exp Res 2021; 33:1133-1144. [PMID: 33683678 PMCID: PMC7938275 DOI: 10.1007/s40520-021-01808-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 02/02/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) disproportionately affects older people. Observational studies suggest indolent cardiovascular involvement after recovery from acute COVID-19. However, these findings may reflect pre-existing cardiac phenotypes. AIMS We tested the association of baseline cardiovascular magnetic resonance (CMR) phenotypes with incident COVID-19. METHODS We studied UK Biobank participants with CMR imaging and COVID-19 testing. We considered left and right ventricular (LV, RV) volumes, ejection fractions, and stroke volumes, LV mass, LV strain, native T1, aortic distensibility, and arterial stiffness index. COVID-19 test results were obtained from Public Health England. Co-morbidities were ascertained from self-report and hospital episode statistics (HES). Critical care admission and death were from HES and death register records. We investigated the association of each cardiovascular measure with COVID-19 test result in multivariable logistic regression models adjusting for age, sex, ethnicity, deprivation, body mass index, smoking, diabetes, hypertension, high cholesterol, and prior myocardial infarction. RESULTS We studied 310 participants (n = 70 positive). Median age was 63.8 [57.5, 72.1] years; 51.0% (n = 158) were male. 78.7% (n = 244) were tested in hospital, 3.5% (n = 11) required critical care admission, and 6.1% (n = 19) died. In fully adjusted models, smaller LV/RV end-diastolic volumes, smaller LV stroke volume, and poorer global longitudinal strain were associated with significantly higher odds of COVID-19 positivity. DISCUSSION We demonstrate association of pre-existing adverse CMR phenotypes with greater odds of COVID-19 positivity independent of classical cardiovascular risk factors. CONCLUSIONS Observational reports of cardiovascular involvement after COVID-19 may, at least partly, reflect pre-existing cardiac status rather than COVID-19 induced alterations.
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Affiliation(s)
- Zahra Raisi-Estabragh
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, EC1A 7BE, UK
| | - Celeste McCracken
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Jackie Cooper
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, EC1A 7BE, UK
| | - José M Paiva
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Mohammed Y Khanji
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, EC1A 7BE, UK
| | - Elisa Rauseo
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, EC1A 7BE, UK
| | - Luca Biasiolli
- National Institute for Health Research Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Betty Raman
- National Institute for Health Research Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stefan K Piechnik
- National Institute for Health Research Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stefan Neubauer
- National Institute for Health Research Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Patricia B Munroe
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Nicholas C Harvey
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK.
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, EC1A 7BE, UK
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Liu JJW, Gervasio J, Fung K, Vickers K. The Effects of Visual Displays in Attenuating Discrepancies Between Self-Reported and Physiological Indexes of Stress. European Journal of Psychological Assessment 2021. [DOI: 10.1027/1015-5759/a000587] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Abstract. This study examined whether the relationship between subjective and physiological outcomes of stress, and the responsivity to stressors, are affected by whether participants can see a visual display of their physiological output. Participants were randomly assigned to have a visible view of their physiological output readings, or to a condition in which physiological output readings were out of view. Participants individually completed a 30-min laboratory study including the modified Trier Social Stress Task. Both physiological markers of stress (heart rate and blood pressure) and subjective evaluations of stress (visual analog scale) were measured. Results found little congruency across subjective and physiological measures of stress. The visible visual display condition had elevated physiological arousal, while no group differences were observed in self-reported stress. Findings from the study provide insight into the use of visual physiological displays and hold practical implications for both the measurement of stress in research, and the development of wearable technologies without accompanying response strategies.
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Affiliation(s)
- Jenny J. W. Liu
- Department of Psychology, Ryerson University, Toronto, ON, Canada
| | - Julia Gervasio
- Department of Psychology, Ryerson University, Toronto, ON, Canada
| | - Kenneth Fung
- Department of Psychiatry, University of Toronto, ON, Canada
| | - Kristin Vickers
- Department of Psychology, Ryerson University, Toronto, ON, Canada
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Kenawy A, Khanji MY, Chirvasa M, Fung K, Sojoudi A, Paiva JOSEM, Samy N, Farid W, Khalil TS, Petersen SE. Application of a machine learning contouring tool for the evaluation of left ventricular strain in clinical practice. Eur Heart J Cardiovasc Imaging 2021. [DOI: 10.1093/ehjci/jeaa356.259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): AK has been funded by the Egyptian cultural centre and educational bureau of the Egyptian embassy in London and the Ministry of higher education in Egypt. SEP acknowledges support from the “SmartHeart” EPSRC programme grant (www.nihr.ac.uk; EP/P001009/1) and the London Medical Imaging and AI Centre for Value-Based Healthcare. This new centre is one of the UK Centres supported by a £50m investment from the Data to Early Diagnosis and Precision Medicine strand of the government’s Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI). SEP acknowledges support from the CAP-AI programme, London’s first AI enabling programme focused on stimulating growth in the capital’s AI Sector. CAP-AI is led by Capital Enterprise in partnership with Barts Health NHS Trust and Digital Catapult and is funded by the European Regional Development Fund and Barts Charity. SEP also acts as a paid consultant to Circle Cardiovascular Imaging Inc., Calgary, Canada and Servier
onbehalf
Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London, UK
Background
Manual contouring of cardiovascular magnetic resonance (CMR) cine images remains common practice and the reference standard for left ventricular (LV) volumes and mass evaluation. However, it is time-consuming and machine learning (ML) may significantly reduce the time required for contouring. Accurate LV contours are the basis for reliable LV strain analysis using tissue tracking.
Purpose
To assess the impact of a ML contouring tool alone versus expert adjusted contours on LV strain.
Methods
We retrospectively selected 402 CMR studies with diagnoses of myocardial infarction (n = 108), myocarditis (n = 130) and healthy controls (n = 164) from the Barts BioResource between January 2015 to June 2018. CMR examinations were obtained using 1.5T and 3T scanners (Siemens Healthineers, Germany). We excluded 32 cases due to phase inconsistency between short (SAX) and long axes (LAX) cine images or suboptimal cine image quality. For the remaining 370 cases, steady state free precession cine images for LAX and SAX were analysed by the ML contouring tool (using CVI42 research prototype software 5.11). Manual expert adjustment for the contours was done for each case if considered suboptimal for strain analysis in the reference end-diastolic phase. Strain results from ML and expert adjusted ML methods were compared for strain agreement. Times taken by these methods were recorded and compared against the time taken for standard manual contouring.
Results
SAX and LAX derived strains by ML and expert adjusted ML methods showed good agreement by Bland-Altman analysis (Figure 1) with excellent coefficient of concordance using Kendall W which is 0.98 for global SAX, radial and circumferential strains (mean difference(MD) = -1.7% (lower and upper limits of agreement (UL,LL) -6.6,3.2), MD = 0.5% (-1.0,2.1)) and is 0.95 for global LAX derived strain (radial and longitudinal, MD = 0.7% (UL,LL -8.7 ,7.4),MD= 0.2% (-1.9,2.5), respectively). Time taken for adjustment of ML contours was significantly shorter than manual contouring (1.35 minutes vs 8.0 minutes, around 590% time saving in ML adjusted method).
Conclusions
ML contouring compared to expert manual adjustment has a clinically reasonable agreement when used for measuring LV strain. Also, using the ML tool with expert adjustment shows significant time saving for analysis and reporting time compared to entirely manual analysis, favouring its application in routine clinical practice.
Abstract Figure.
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Affiliation(s)
- A Kenawy
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, United Kingdom of Great Britain & Northern Ireland
| | - MY Khanji
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London, United Kingdom of Great Britain & Northern Ireland
| | - M Chirvasa
- Circle Cardiovascular Imaging Inc., , Calgary,AB, Canada
| | - K Fung
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, United Kingdom of Great Britain & Northern Ireland
| | - A Sojoudi
- Circle Cardiovascular Imaging Inc., , Calgary,AB, Canada
| | - JOSE M Paiva
- Circle Cardiovascular Imaging Inc., , Calgary,AB, Canada
| | - N Samy
- Faculty of medicine Menoufia university, Menoufia, Egypt
| | - W Farid
- Faculty of medicine Menoufia university, Menoufia, Egypt
| | - TS Khalil
- Faculty of medicine Menoufia university, Menoufia, Egypt
| | - SE Petersen
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, United Kingdom of Great Britain & Northern Ireland
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Omer M, Amir-Khalili A, Sojoudi A, Thao Le T, A Cook S, Faye Toh D, Bryant J, Chin C, Miguel Paiva J, Fung K, Aung N, Y Khanji M, Rauseo E, Cooper J, E Petersen S. Assessing automated CMR contouring algorithms using systematic contour quality scoring analysis. Eur Heart J Cardiovasc Imaging 2021. [DOI: 10.1093/ehjci/jeaa356.434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): SmartHeart EPSRC programme grant (www.nihr.ac.uk), London Medical Imaging and AI Centre for Value-Based Healthcare
Background
Quality measures for machine learning algorithms include clinical measures such as end-diastolic (ED) and end-systolic (ES) volume, volumetric overlaps such as Dice similarity coefficient and surface distances such as Hausdorff distance. These measures capture differences between manually drawn and automated contours but fail to capture the trust of a clinician to an automatically generated contour.
Purpose
We propose to directly capture clinicians’ trust in a systematic way. We display manual and automated contours sequentially in random order and ask the clinicians to score the contour quality. We then perform statistical analysis for both sources of contours and stratify results based on contour type.
Data
The data selected for this experiment came from the National Health Center Singapore. It constitutes CMR scans from 313 patients with diverse pathologies including: healthy, dilated cardiomyopathy (DCM), hypertension (HTN), hypertrophic cardiomyopathy (HCM), ischemic heart disease (IHD), left ventricular non-compaction (LVNC), and myocarditis. Each study contains a short axis (SAX) stack, with ED and ES phases manually annotated. Automated contours are generated for each SAX image for which manual annotation is available. For this, a machine learning algorithm trained at Circle Cardiovascular Imaging Inc. is applied and the resulting predictions are saved to be displayed in the contour quality scoring (CQS) application.
Methods: The CQS application displays manual and automated contours in a random order and presents the user an option to assign a contour quality score
1: Unacceptable, 2: Bad, 3: Fair, 4: Good. The UK Biobank standard operating procedure is used for assessing the quality of the contoured images. Quality scores are assigned based on how the contour affects clinical outcomes. However, as images are presented independent of spatiotemporal context, contour quality is assessed based on how well the area of the delineated structure is approximated. Consequently, small contours and small deviations are rarely assigned a quality score of less than 2, as they are not clinically relevant. Special attention is given to the RV-endo contours as often, mostly in basal images, two separate contours appear. In such cases, a score of 3 is given if the two disjoint contours sufficiently encompass the underlying anatomy; otherwise they are scored as 2 or 1.
Results
A total of 50991 quality scores (24208 manual and 26783 automated) are generated by five expert raters. The mean score for all manual and automated contours are 3.77 ± 0.48 and 3.77 ± 0.52, respectively. The breakdown of mean quality scores by contour type is included in Fig. 1a while the distribution of quality scores for various raters are shown in Fig. 1b.
Conclusion
We proposed a method of comparing the quality of manual versus automated contouring methods. Results suggest similar statistics in quality scores for both sources of contours.
Abstract Figure 1
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Affiliation(s)
- M Omer
- Circle Cardiovascular Imaging Inc., Calgary, Canada
| | | | - A Sojoudi
- Circle Cardiovascular Imaging Inc., Calgary, Canada
| | - T Thao Le
- National Heart Centre Singapore, Singapore, Singapore
| | - S A Cook
- National Heart Centre Singapore, Singapore, Singapore
| | - D Faye Toh
- National Heart Centre Singapore, Singapore, Singapore
| | - J Bryant
- National Heart Centre Singapore, Singapore, Singapore
| | - C Chin
- National Heart Centre Singapore, Singapore, Singapore
| | | | - K Fung
- Barts Heart Centre, London, United Kingdom of Great Britain & Northern Ireland
| | - N Aung
- Barts Heart Centre, London, United Kingdom of Great Britain & Northern Ireland
| | - M Y Khanji
- Barts Heart Centre, London, United Kingdom of Great Britain & Northern Ireland
| | - E Rauseo
- Barts Heart Centre, London, United Kingdom of Great Britain & Northern Ireland
| | - J Cooper
- Barts Heart Centre, London, United Kingdom of Great Britain & Northern Ireland
| | - S E Petersen
- Barts Heart Centre, London, United Kingdom of Great Britain & Northern Ireland
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32
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Kirmayer LJ, Fung K, Rousseau C, Lo HT, Menzies P, Guzder J, Ganesan S, Andermann L, McKenzie K. Guidelines for Training in Cultural Psychiatry. Can J Psychiatry 2021; 66:195-246. [PMID: 32345034 PMCID: PMC7918872 DOI: 10.1177/0706743720907505] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
This position paper has been substantially revised by the Canadian Psychiatric Association (CPA)'s Section on Transcultural Psychiatry and the Standing Committee on Education and approved for republication by the CPA's Board of Directors on February 8, 2019. The original position paper1 was first approved by the CPA Board on September 28, 2011.
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Affiliation(s)
- Laurence J Kirmayer
- James McGill Professor and Director, Division of Social and Transcultural Psychiatry, 5620McGill University, Montreal, Quebec; Director, Culture and Mental Health Research Unit, Jewish General Hospital, Montreal, Quebec
| | - Kenneth Fung
- Clinical Director, Asian Initiative in Mental Health, University Health Network, Toronto, Ontario; Associate Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario; President, Society for the Study of Psychiatry and Culture, Toronto, Ontario
| | - Cécile Rousseau
- Professor, Division of Social and Cultural Psychiatry, 5620McGill University, Montreal, Quebec
| | - Hung Tat Lo
- Director, Asian Clinic, Hong Fook Mental Health Association, Toronto, Ontario
| | - Peter Menzies
- Psychiatrist, Four Directions Therapeutic and Consulting Services, working with First Nations communities in northern Ontario
| | - Jaswant Guzder
- Professor, Department of Psychiatry, 5620McGill University, Montreal, Quebec; Senior Clinician, Cultural Consultation Service, Institute of Community and Family Psychiatry, Sir Mortimer B Davis Jewish General Hospital, Montreal, Quebec; Senior Clinician, Child Psychiatry, Jewish General Hospital, Montreal, Quebec
| | - Soma Ganesan
- Clinical Professor of Psychiatry, University of British Columbia, Vancouver, British Columbia; Director, Cross Cultural Psychiatry Program, University of British Columbia, Vancouver, British Columbia
| | - Lisa Andermann
- Psychiatrist, Mount Sinai Hospital, Toronto, Ontario; Associate Professor, Equity, Gender and Populations Division, Department of Psychiatry, University of Toronto, Toronto, Ontario
| | - Kwame McKenzie
- CEO, Wellesley Institute, Toronto, Ontario; Professor of Psychiatry, University of Toronto, Toronto, Ontario; Director, Department of Health Equity, Centre for Addiction and Mental Health, Toronto, Ontario
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Raisi-Estabragh Z, Biasiolli L, Cooper J, Aung N, Fung K, Paiva JM, Sanghvi MM, Thomson RJ, Curtis E, Paccou J, Rayner JJ, Werys K, Puchta H, Thomas KE, Lee AM, Piechnik SK, Neubauer S, Munroe PB, Cooper C, Petersen SE, Harvey NC. Poor Bone Quality is Associated With Greater Arterial Stiffness: Insights From the UK Biobank. J Bone Miner Res 2021; 36:90-99. [PMID: 32964541 PMCID: PMC7613252 DOI: 10.1002/jbmr.4164] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 07/26/2020] [Accepted: 08/05/2020] [Indexed: 12/20/2022]
Abstract
Osteoporosis and ischemic heart disease (IHD) represent important public health problems. Existing research suggests an association between the two conditions beyond that attributable to shared risk factors, with a potentially causal relationship. In this study, we tested the association of bone speed of sound (SOS) from quantitative heel ultrasound with (i) measures of arterial compliance from cardiovascular magnetic resonance (aortic distensibility [AD]); (ii) finger photoplethysmography (arterial stiffness index [ASI]); and (iii) incident myocardial infarction and IHD mortality in the UK Biobank cohort. We considered the potential mediating effect of a range of blood biomarkers and cardiometabolic morbidities and evaluated differential relationships by sex, menopause status, smoking, diabetes, and obesity. Furthermore, we considered whether associations with arterial compliance explained association of SOS with ischemic cardiovascular outcomes. Higher SOS was associated with lower arterial compliance by both ASI and AD for both men and women. The relationship was most consistent with ASI, likely relating to larger sample size available for this variable (n = 159,542 versus n = 18,229). There was no clear evidence of differential relationship by menopause, smoking, diabetes, or body mass index (BMI). Blood biomarkers appeared important in mediating the association for both men and women, but with different directions of effect and did not fully explain the observed effects. In fully adjusted models, higher SOS was associated with significantly lower IHD mortality in men, but less robustly in women. The association of SOS with ASI did not explain this observation. In conclusion, our findings support a positive association between bone and vascular health with consistent patterns of association in men and women. The underlying mechanisms are complex and appear to vary by sex. © 2020 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Zahra Raisi-Estabragh
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service (NHS) Trust, London, UK
| | - Luca Biasiolli
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Jackie Cooper
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service (NHS) Trust, London, UK
| | - Nay Aung
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service (NHS) Trust, London, UK
| | - Kenneth Fung
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service (NHS) Trust, London, UK
| | - José M Paiva
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Mihir M Sanghvi
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service (NHS) Trust, London, UK
| | - Ross J Thomson
- Department of Cardiology, Royal Free Hospital, Royal Free London NHS Foundation Trust, London, UK
| | - Elizabeth Curtis
- Medical Research Council (MRC) Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Julien Paccou
- Rheumatology Department, Lille University Hospital, CHU Lille, MABlab ULR 4490, 59037 Lille, France
| | - Jennifer J Rayner
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Konrad Werys
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Henrike Puchta
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Katharine E Thomas
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Aaron M Lee
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Stefan K Piechnik
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Patricia B Munroe
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Cyrus Cooper
- Medical Research Council (MRC) Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- National Institute for Health Research (NIHR) Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service (NHS) Foundation Trust, Southampton, UK
- National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Steffen E Petersen
- William Harvey Research Institute, National Institute for Health Research (NIHR) Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service (NHS) Trust, London, UK
| | - Nicholas C Harvey
- Medical Research Council (MRC) Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- National Institute for Health Research (NIHR) Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton National Health Service (NHS) Foundation Trust, Southampton, UK
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Ricci F, Aung N, Gallina S, Zemrak F, Fung K, Bisaccia G, Paiva JM, Khanji MY, Mantini C, Palermi S, Lee AM, Piechnik SK, Neubauer S, Petersen SE. Cardiovascular magnetic resonance reference values of mitral and tricuspid annular dimensions: the UK Biobank cohort. J Cardiovasc Magn Reson 2020; 23:5. [PMID: 33407573 PMCID: PMC7788733 DOI: 10.1186/s12968-020-00688-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 10/29/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Mitral valve (MV) and tricuspid valve (TV) apparatus geometry are essential to define mechanisms and etiologies of regurgitation and to inform surgical or transcatheter interventions. Given the increasing use of cardiovascular magnetic resonance (CMR) for the evaluation of valvular heart disease, we aimed to establish CMR-derived age- and sex-specific reference values for mitral annular (MA) and tricuspid annular (TA) dimensions and tethering indices derived from truly healthy Caucasian adults. METHODS 5065 consecutive UK Biobank participants underwent CMR using cine balanced steady-state free precession imaging at 1.5 T. Participants with non-Caucasian ethnicity, prevalent cardiovascular disease and other conditions known to affect cardiac chamber size and function were excluded. Absolute and indexed reference ranges for MA and TA diameters and tethering indices were stratified by gender and age (45-54, 55-64, 65-74 years). RESULTS Overall, 721 (14.2%) truly healthy participants aged 45-74 years (54% women) formed the reference cohort. Absolute MA and TA diameters, MV tenting length and MV tenting area, were significantly larger in men. Mean ± standard deviation (SD) end-diastolic and end-systolic MA diameters in the 3-chamber view (anteroposterior diameter) were 2.9 ± 0.4 cm (1.5 ± 0.2 cm/m2) and 3.3 ± 0.4 cm (1.7 ± 0.2 cm/m2) in men, and 2.6 ± 0.4 cm (1.6 ± 0.2 cm/m2) and 3.0 ± 0.4 cm (1.8 ± 0.2 cm/m2) in women, respectively. Mean ± SD end-diastolic and end-systolic TA diameters in the 4-chamber view were 3.2 ± 0.5 cm (1.6 ± 0.3 cm/m2) and 3.2 ± 0.5 cm (1.7 ± 0.3 cm/m2) in men, and 2.9 ± 0.4 cm (1.7 ± 0.2 cm/m2) and 2.8 ± 0.4 cm (1.7 ± 0.3 cm/m2) in women, respectively. With advancing age, end-diastolic TA diameter became larger and posterior MV leaflet angle smaller in both sexes. Reproducibility of measurements was good to excellent with an inter-rater intraclass correlation coefficient (ICC) between 0.92 and 0.98 and an intra-rater ICC between 0.90 and 0.97. CONCLUSIONS We described age- and sex-specific reference ranges of MA and TA dimensions and tethering indices in the largest validated healthy Caucasian population. Reference ranges presented in this study may help to improve the distinction between normal and pathological states, prompting the identification of subjects that may benefit from advanced cardiac imaging for annular sizing and planning of valvular interventions.
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Affiliation(s)
- Fabrizio Ricci
- Department of Neuroscience, Imaging and Clinical Sciences, "G.D'Annunzio" University, Chieti, Italy
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Casa Di Cura Villa Serena, 65013, Città Sant'Angelo, Pescara, Italy
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Sabina Gallina
- Department of Neuroscience, Imaging and Clinical Sciences, "G.D'Annunzio" University, Chieti, Italy
| | - Filip Zemrak
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Giandomenico Bisaccia
- Department of Neuroscience, Imaging and Clinical Sciences, "G.D'Annunzio" University, Chieti, Italy
| | - Jose Miguel Paiva
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Mohammed Y Khanji
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Cesare Mantini
- Department of Neuroscience, Imaging and Clinical Sciences, "G.D'Annunzio" University, Chieti, Italy
| | - Stefano Palermi
- Department of Neuroscience, Imaging and Clinical Sciences, "G.D'Annunzio" University, Chieti, Italy
| | - Aaron M Lee
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK
| | - Stefan K Piechnik
- Division of Cardiovascular Medicine, NIHR BRC Oxford, Radcliffe Department of Medicine, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, NIHR BRC Oxford, Radcliffe Department of Medicine, University of Oxford, Level 6, West Wing, John Radcliffe Hospital, Headington, Oxford, OX3 9DU, UK
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK.
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Zheng Q, Delingette H, Fung K, Petersen SE, Ayache N. Pathological Cluster Identification by Unsupervised Analysis in 3,822 UK Biobank Cardiac MRIs. Front Cardiovasc Med 2020; 7:539788. [PMID: 33313075 PMCID: PMC7701336 DOI: 10.3389/fcvm.2020.539788] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 08/12/2020] [Indexed: 12/12/2022] Open
Abstract
We perform unsupervised analysis of image-derived shape and motion features extracted from 3,822 cardiac Magnetic resonance imaging (MRIs) of the UK Biobank. First, with a feature extraction method previously published based on deep learning models, we extract from each case 9 feature values characterizing both the cardiac shape and motion. Second, a feature selection is performed to remove highly correlated feature pairs. Third, clustering is carried out using a Gaussian mixture model on the selected features. After analysis, we identify 2 small clusters that probably correspond to 2 pathological categories. Further confirmation using a trained classification model and dimensionality reduction tools is carried out to support this finding. Moreover, we examine the differences between the other large clusters and compare our measures with the ground truth.
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Affiliation(s)
- Qiao Zheng
- Université Côte d'Azur, Inria, Sophia Antipolis, Valbonne, France
| | - Hervé Delingette
- Université Côte d'Azur, Inria, Sophia Antipolis, Valbonne, France
| | - Kenneth Fung
- National Institute for Health Research Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service Trust, London, United Kingdom
| | - Steffen E. Petersen
- National Institute for Health Research Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
- Barts Heart Centre, St Bartholomew's Hospital, Barts Health National Health Service Trust, London, United Kingdom
| | - Nicholas Ayache
- Université Côte d'Azur, Inria, Sophia Antipolis, Valbonne, France
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36
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Kassirian S, Dzioba A, Hamel S, Patel K, Sahovaler A, Palma DA, Read N, Venkatesan V, Nichols AC, Yoo J, Fung K, Mendez A, MacNeil SD. Delay in diagnosis of patients with head-and-neck cancer in Canada: impact of patient and provider delay. Curr Oncol 2020; 27:e467-e477. [PMID: 33173386 PMCID: PMC7606041 DOI: 10.3747/co.27.6547] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Background Head-and-neck cancers (hncs) often present at an advanced stage, leading to poor outcomes. Late presentation might be attributable to patient delays (reluctance to seek treatment, for instance) or provider delays (misdiagnosis, prolonged wait time for consultation, for example). The objective of the present study was to examine the length and cause of such delays in a Canadian universal health care setting. Methods Patients presenting for the first time to the hnc multidisciplinary team (mdt) with a biopsy-proven hnc were recruited to this study. Patients completed a survey querying initial symptom presentation, their previous medical appointments, and length of time between appointments. Clinical and demographic data were collected for all patients. Results The average time for patients to have their first appointment at the mdt clinic was 15.1 months, consisting of 3.9 months for patients to see a health care provider (hcp) for the first time since symptom onset and 10.7 months from first hcp appointment to the mdt clinic. Patients saw an average of 3 hcps before the mdt clinic visit (range: 1-7). No significant differences in time to presentation were found based on stage at presentation or anatomic site. Conclusions At our tertiary care cancer centre, a patient's clinical pathway to being seen at the mdt clinic shows significant delays, particularly in the time from the first hcp visit to mdt referral. Possible methods to mitigate delay include education about hnc for patients and providers alike, and a more streamlined referral system.
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Affiliation(s)
- S Kassirian
- Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - A Dzioba
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - S Hamel
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - K Patel
- Department of Otolaryngology, Moffitt Cancer Center and Research Institute, University of South Florida, Tampa, FL, U.S.A
| | - A Sahovaler
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - D A Palma
- Department of Radiation Oncology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - N Read
- Department of Radiation Oncology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - V Venkatesan
- Department of Radiation Oncology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - A C Nichols
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - J Yoo
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - K Fung
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - A Mendez
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
| | - S D MacNeil
- Department of Otolaryngology, Schulich School of Medicine and Dentistry, Western University, London Health Sciences Centre, London, ON
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Bai W, Suzuki H, Huang J, Francis C, Wang S, Tarroni G, Guitton F, Aung N, Fung K, Petersen SE, Piechnik SK, Neubauer S, Evangelou E, Dehghan A, O'Regan DP, Wilkins MR, Guo Y, Matthews PM, Rueckert D. A population-based phenome-wide association study of cardiac and aortic structure and function. Nat Med 2020; 26:1654-1662. [PMID: 32839619 PMCID: PMC7613250 DOI: 10.1038/s41591-020-1009-y] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 07/07/2020] [Indexed: 12/14/2022]
Abstract
Differences in cardiac and aortic structure and function are associated with cardiovascular diseases and a wide range of other types of disease. Here we analyzed cardiovascular magnetic resonance images from a population-based study, the UK Biobank, using an automated machine-learning-based analysis pipeline. We report a comprehensive range of structural and functional phenotypes for the heart and aorta across 26,893 participants, and explore how these phenotypes vary according to sex, age and major cardiovascular risk factors. We extended this analysis with a phenome-wide association study, in which we tested for correlations of a wide range of non-imaging phenotypes of the participants with imaging phenotypes. We further explored the associations of imaging phenotypes with early-life factors, mental health and cognitive function using both observational analysis and Mendelian randomization. Our study illustrates how population-based cardiac and aortic imaging phenotypes can be used to better define cardiovascular disease risks as well as heart-brain health interactions, highlighting new opportunities for studying disease mechanisms and developing image-based biomarkers.
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Affiliation(s)
- Wenjia Bai
- Data Science Institute, Imperial College London, London, UK. .,Department of Brain Sciences, Imperial College London, London, UK.
| | - Hideaki Suzuki
- Department of Brain Sciences, Imperial College London, London, UK.,Department of Cardiovascular Medicine, Tohoku University Hospital, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Jian Huang
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.,UK Dementia Research Institute, Imperial College London, London, UK
| | - Catherine Francis
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Shuo Wang
- Data Science Institute, Imperial College London, London, UK
| | - Giacomo Tarroni
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.,CitAI Research Centre, Department of Computer Science, City University of London, London, UK
| | | | - Nay Aung
- NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Kenneth Fung
- NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Steffen E Petersen
- NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Stefan K Piechnik
- NIHR Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stefan Neubauer
- NIHR Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Evangelos Evangelou
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.,Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Abbas Dehghan
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.,UK Dementia Research Institute, Imperial College London, London, UK
| | - Declan P O'Regan
- MRC London Institute of Medical Sciences, Imperial College London, London, UK
| | - Martin R Wilkins
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Yike Guo
- Data Science Institute, Imperial College London, London, UK
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, UK.,UK Dementia Research Institute, Imperial College London, London, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK
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38
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Chen C, Bai W, Davies RH, Bhuva AN, Manisty CH, Augusto JB, Moon JC, Aung N, Lee AM, Sanghvi MM, Fung K, Paiva JM, Petersen SE, Lukaschuk E, Piechnik SK, Neubauer S, Rueckert D. Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images. Front Cardiovasc Med 2020; 7:105. [PMID: 32714943 PMCID: PMC7344224 DOI: 10.3389/fcvm.2020.00105] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Accepted: 05/20/2020] [Indexed: 11/22/2022] Open
Abstract
Background: Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g., same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. Methods: We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). Results: The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium, and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. Conclusions: The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task.
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Affiliation(s)
- Chen Chen
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Wenjia Bai
- Data Science Institute, Imperial College London, London, United Kingdom.,Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Rhodri H Davies
- Institute of Cardiovascular Science, University College London, London, United Kingdom.,Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Anish N Bhuva
- Institute of Cardiovascular Science, University College London, London, United Kingdom.,Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Charlotte H Manisty
- Institute of Cardiovascular Science, University College London, London, United Kingdom.,Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Joao B Augusto
- Institute of Cardiovascular Science, University College London, London, United Kingdom.,Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - James C Moon
- Institute of Cardiovascular Science, University College London, London, United Kingdom.,Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom
| | - Nay Aung
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Aaron M Lee
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Mihir M Sanghvi
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Kenneth Fung
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Jose Miguel Paiva
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Steffen E Petersen
- Department of Cardiovascular Imaging, Barts Heart Centre, St Bartholomew's Hospital, London, United Kingdom.,NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, United Kingdom
| | - Elena Lukaschuk
- NIHR BRC Oxford, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, London, United Kingdom
| | - Stefan K Piechnik
- NIHR BRC Oxford, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, London, United Kingdom
| | - Stefan Neubauer
- NIHR BRC Oxford, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, London, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
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Sommer DD, Engels PT, Weitzel EK, Khalili S, Corsten M, Tewfik MA, Fung K, Cote D, Gupta M, Sne N, Brown TFE, Paul J, Kost KM, Witterick IJ. Recommendations from the CSO-HNS taskforce on performance of tracheotomy during the COVID-19 pandemic. J Otolaryngol Head Neck Surg 2020; 49:23. [PMID: 32340627 PMCID: PMC7184547 DOI: 10.1186/s40463-020-00414-9] [Citation(s) in RCA: 106] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 04/13/2020] [Indexed: 01/08/2023] Open
Abstract
INTRODUCTION The performance of tracheotomy is a common procedural request by critical care departments to the surgical services of general surgery, thoracic surgery and otolaryngology - head & neck surgery. A Canadian Society of Otolaryngology - Head & Neck Surgery (CSO-HNS) task force was convened with multi-specialty involvement from otolaryngology-head & neck surgery, general surgery, critical care and anesthesiology to develop a set of recommendations for the performance of tracheotomies during the COVID-19 pandemic. MAIN BODY The tracheotomy procedure is highly aerosol generating and directly exposes the entire surgical team to the viral aerosol plume and secretions, thereby increasing the risk of transmission to healthcare providers. As such, we believe extended endotracheal intubation should be the standard of care for the entire duration of ventilation in the vast majority of patients. Pre-operative COVID-19 testing is highly recommended for any non-emergent procedure. CONCLUSION The set of recommendations in this document highlight the importance of avoiding tracheotomy procedures in patients who are COVID-19 positive if at all possible. Recommendations for appropriate PPE and environment are made for COVID-19 positive, negative and unknown patients requiring consideration of tracheotomy. The safety of healthcare professionals who care for ill patients and who keep critical infrastructure operating is paramount.
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Affiliation(s)
- D D Sommer
- Division of Otolaryngology - Head & Neck Surgery - Department of Surgery, McMaster University Medical Centre, McMaster University, 3V1 Clinic, 1200 Main St West, Hamilton, ON, L8N 3Z5, Canada.
| | - P T Engels
- Department of Surgery and Critical Care, McMaster University, Hamilton, ON, Canada
| | - E K Weitzel
- United States Army Institute of Surgical Research, Fort Sam Houston, TX, USA
| | - S Khalili
- Aurora Neuroscience Innovation Institute, Milwaukee, WI, USA
| | - M Corsten
- Division of Otolaryngology - Head & Neck Surgery, Dalhousie University, Halifax, NS, Canada
| | - M A Tewfik
- Department of Otolaryngology - Head and Neck Surgery, McGill University, Montreal, QC, Canada
| | - K Fung
- Department of Otolaryngology - Head and Neck Surgery, Western University, London, ON, Canada
| | - D Cote
- Division of Otolaryngology - Head and Neck Surgery, University of Alberta, Edmonton, AB, Canada
| | - M Gupta
- Division of Otolaryngology - Head & Neck Surgery - Department of Surgery, McMaster University Medical Centre, McMaster University, 3V1 Clinic, 1200 Main St West, Hamilton, ON, L8N 3Z5, Canada
| | - N Sne
- Department of Surgery and Critical Care, McMaster University, Hamilton, ON, Canada
| | - T F E Brown
- Division of Otolaryngology - Head & Neck Surgery, Dalhousie University, Halifax, NS, Canada
| | - J Paul
- Department of Anesthesia, McMaster University, Hamilton, ON, Canada
| | - K M Kost
- Department of Otolaryngology - Head and Neck Surgery, McGill University, Montreal, QC, Canada
| | - I J Witterick
- Department of Otolaryngology - Head & Neck Surgery, University of Toronto, Toronto, ON, Canada
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40
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Ferdian E, Suinesiaputra A, Fung K, Aung N, Lukaschuk E, Barutcu A, Maclean E, Paiva J, Piechnik SK, Neubauer S, Petersen SE, Young AA. Fully Automated Myocardial Strain Estimation from Cardiovascular MRI-tagged Images Using a Deep Learning Framework in the UK Biobank. Radiol Cardiothorac Imaging 2020; 2:e190032. [PMID: 32715298 PMCID: PMC7051160 DOI: 10.1148/ryct.2020190032] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 07/19/2019] [Accepted: 08/21/2019] [Indexed: 11/25/2022]
Abstract
PURPOSE To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac MRI-tagged images. MATERIALS AND METHODS In this retrospective cross-sectional study, 4508 cases from the U.K. Biobank were split randomly into 3244 training cases, 812 validation cases, and 452 test cases. Ground truth myocardial landmarks were defined and tracked by manual initialization and correction of deformable image registration using previously validated software with five readers. The fully automatic framework consisted of (a) a convolutional neural network (CNN) for localization and (b) a combination of a recurrent neural network (RNN) and a CNN to detect and track the myocardial landmarks through the image sequence for each slice. Radial and circumferential strain were then calculated from the motion of the landmarks and averaged on a slice basis. RESULTS Within the test set, myocardial end-systolic circumferential Green strain errors were -0.001 ± 0.025, -0.001 ± 0.021, and 0.004 ± 0.035 in the basal, mid-, and apical slices, respectively (mean ± standard deviation of differences between predicted and manual strain). The framework reproduced significant reductions in circumferential strain in participants with diabetes, hypertensive participants, and participants with a previous heart attack. Typical processing time was approximately 260 frames (approximately 13 slices) per second on a GPU with 12 GB RAM compared with 6-8 minutes per slice for the manual analysis. CONCLUSION The fully automated combined RNN and CNN framework for analysis of myocardial strain enabled unbiased strain evaluation in a high-throughput workflow, with similar ability to distinguish impairment due to diabetes, hypertension, and previous heart attack.Published under a CC BY 4.0 license. Supplemental material is available for this article.
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Affiliation(s)
- Edward Ferdian
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Avan Suinesiaputra
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Kenneth Fung
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Nay Aung
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Elena Lukaschuk
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Ahmet Barutcu
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Edd Maclean
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Jose Paiva
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Stefan K. Piechnik
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Stefan Neubauer
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Steffen E. Petersen
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
| | - Alistair A. Young
- From the Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand (E.F., A.S., A.A.Y.); William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, England (K.F., N.A., E.M., J.P., S.E.P.); and Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, England (E.L., A.B., S.K.P., S.N.); Department of Biomedical Engineering, King’s College London, 5th Floor Becket House, 1 Lambeth Palace Rd, London SE1 7EU, England (A.A.Y.)
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Fung K, Biasiolli L, Hann E, Ramirez J, Lukaschuk E, Aung N, Paiva J, Werys K, Sanghvi M, Thomson R, Rayner J, Puchta H, Moon N, Thomas K, Lee A, Piechnik S, Neubauer S, Petersen S, Munroe P. 3.2 First Genome-Wide Association Study of Cardiovascular Magnetic Resonance Derived Aortic Distensibility Reveals 7 Loci. Artery Res 2020. [DOI: 10.2991/artres.k.191224.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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Khanji MY, Jensen MT, Kenawy AA, Raisi-Estabragh Z, Paiva JM, Aung N, Fung K, Lukaschuk E, Zemrak F, Lee AM, Barutcu A, Maclean E, Cooper J, Piechnik SK, Neubauer S, Petersen SE. Association Between Recreational Cannabis Use and Cardiac Structure and Function. JACC Cardiovasc Imaging 2019; 13:886-888. [PMID: 31864983 DOI: 10.1016/j.jcmg.2019.10.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 10/02/2019] [Accepted: 10/11/2019] [Indexed: 01/11/2023]
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Fung K, Cheshire C, Cooper JA, Catarino P, Piechnik SK, Neubauer S, Bhagra S, Pettit S, Petersen SE. Validation of Cardiovascular Magnetic Resonance-Derived Equation for Predicted Left Ventricular Mass Using the UK Biobank Imaging Cohort: Tool for Donor-Recipient Size Matching. Circ Heart Fail 2019; 12:e006362. [PMID: 31805784 PMCID: PMC6922072 DOI: 10.1161/circheartfailure.119.006362] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Current guidance from International Society for Heart and Lung Transplantation recommends using body weight for donor-recipient size matching for heart transplantation. However, recent studies have shown that predicted heart mass, using body weight, height, age, and sex, may represent a better method of size matching. We aim to validate a cardiovascular magnetic resonance (CMR)-derived equation for predicted left ventricular mass (LVM) in a cohort of normal individuals in the United Kingdom. METHODS This observational study was conducted in 5065 middle-aged (44-77 years old) UK Biobank participants who underwent CMR imaging in 2014 to 2015. Individuals with cancer diagnosis in the previous 12 months or history of cardiovascular disease were excluded. Predicted LVM was calculated based on participants' sex, height, and weight recorded at the time of imaging. Correlation analyses were performed between the predicted LVM and the LVM obtained from manual contouring of CMR cine images. The analysis included 3398 participants (age 61.5±7.5 years, 47.8% males). RESULTS Predicted LVM was considerably higher than CMR-derived LVM (mean±SD of 138.8±28.9 g versus 86.3±20.9 g). However, there was a strong correlation between the 2 measurements (Spearman correlation coefficient 0.802, P<0.0001). CONCLUSIONS Predicted LVM calculated using a CMR-derived equation that incorporates height, weight, and sex has a strong correlation with CMR LVM in large cohort of normal individuals in the United Kingdom. Our findings suggest that predicted heart mass equations may be a valid tool for donor-recipient size matching for heart transplantation in the United Kingdom.
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Affiliation(s)
- Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, United Kingdom (K.F., J.A.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (K.F., S.E.P.)
| | - Caitlin Cheshire
- Advanced Heart Failure and Transplant Unit, Royal Papworth Hospital NHS Foundation Trust, Cambridge, United Kingdom (C.C., P.C., S.B., S.P.)
| | - Jackie A. Cooper
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, United Kingdom (K.F., J.A.C., S.E.P.)
| | - Pedro Catarino
- Advanced Heart Failure and Transplant Unit, Royal Papworth Hospital NHS Foundation Trust, Cambridge, United Kingdom (C.C., P.C., S.B., S.P.)
| | - Stefan K. Piechnik
- NIHR Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, University of Oxford, United Kingdom (S.K.P., S.N.)
| | - Stefan Neubauer
- NIHR Oxford Biomedical Research Centre, Division of Cardiovascular Medicine, University of Oxford, United Kingdom (S.K.P., S.N.)
| | - Sai Bhagra
- Advanced Heart Failure and Transplant Unit, Royal Papworth Hospital NHS Foundation Trust, Cambridge, United Kingdom (C.C., P.C., S.B., S.P.)
| | - Stephen Pettit
- Advanced Heart Failure and Transplant Unit, Royal Papworth Hospital NHS Foundation Trust, Cambridge, United Kingdom (C.C., P.C., S.B., S.P.)
| | - Steffen E. Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, United Kingdom (K.F., J.A.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (K.F., S.E.P.)
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Aung N, Vargas JD, Yang C, Cabrera CP, Warren HR, Fung K, Tzanis E, Barnes MR, Rotter JI, Taylor KD, Manichaikul AW, Lima JA, Bluemke DA, Piechnik SK, Neubauer S, Munroe PB, Petersen SE. Genome-Wide Analysis of Left Ventricular Image-Derived Phenotypes Identifies Fourteen Loci Associated With Cardiac Morphogenesis and Heart Failure Development. Circulation 2019; 140:1318-1330. [PMID: 31554410 PMCID: PMC6791514 DOI: 10.1161/circulationaha.119.041161] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND The genetic basis of left ventricular (LV) image-derived phenotypes, which play a vital role in the diagnosis, management, and risk stratification of cardiovascular diseases, is unclear at present. METHODS The LV parameters were measured from the cardiovascular magnetic resonance studies of the UK Biobank. Genotyping was done using Affymetrix arrays, augmented by imputation. We performed genome-wide association studies of 6 LV traits-LV end-diastolic volume, LV end-systolic volume, LV stroke volume, LV ejection fraction, LV mass, and LV mass to end-diastolic volume ratio. The replication analysis was performed in the MESA study (Multi-Ethnic Study of Atherosclerosis). We identified the candidate genes at genome-wide significant loci based on the evidence from extensive bioinformatic analyses. Polygenic risk scores were constructed from the summary statistics of LV genome-wide association studies to predict the heart failure events. RESULTS The study comprised 16 923 European UK Biobank participants (mean age 62.5 years; 45.8% men) without prevalent myocardial infarction or heart failure. We discovered 14 genome-wide significant loci (3 loci each for LV end-diastolic volume, LV end-systolic volume, and LV mass to end-diastolic volume ratio; 4 loci for LV ejection fraction, and 1 locus for LV mass) at a stringent P<1×10-8. Three loci were replicated at Bonferroni significance and 7 loci at nominal significance (P<0.05 with concordant direction of effect) in the MESA study (n=4383). Follow-up bioinformatic analyses identified 28 candidate genes that were enriched in the cardiac developmental pathways and regulation of the LV contractile mechanism. Eight genes (TTN, BAG3, GRK5, HSPB7, MTSS1, ALPK3, NMB, and MMP11) supported by at least 2 independent lines of in silico evidence were implicated in the cardiac morphogenesis and heart failure development. The polygenic risk scores of LV phenotypes were predictive of heart failure in a holdout UK Biobank sample of 3106 cases and 224 134 controls (odds ratio 1.41, 95% CI 1.26 - 1.58, for the top quintile versus the bottom quintile of the LV end-systolic volume risk score). CONCLUSIONS We report 14 genetic loci and indicate several candidate genes that not only enhance our understanding of the genetic architecture of prognostically important LV phenotypes but also shed light on potential novel therapeutic targets for LV remodeling.
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Affiliation(s)
- Nay Aung
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health National Health Service Trust, West Smithfield, London, United Kingdom (N.A., K.F., S.E.P.)
| | - Jose D. Vargas
- Medstar Heart and Vascular Institute, Medstar Georgetown University Hospital, Washington, DC (J.D.V.)
| | - Chaojie Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville (C.Y., A.W.M.)
| | - Claudia P. Cabrera
- Centre for Translational Bioinformatics (C.P.C., E.T., M.R.B.), Queen Mary University of London, United Kingdom
| | - Helen R. Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
| | - Kenneth Fung
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health National Health Service Trust, West Smithfield, London, United Kingdom (N.A., K.F., S.E.P.)
| | - Evan Tzanis
- Centre for Translational Bioinformatics (C.P.C., E.T., M.R.B.), Queen Mary University of London, United Kingdom
| | - Michael R. Barnes
- Centre for Translational Bioinformatics (C.P.C., E.T., M.R.B.), Queen Mary University of London, United Kingdom
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Division of Genomics Outcomes, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles, Medical Center, Torrance, CA (J.I.R., K.D.T.)
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Division of Genomics Outcomes, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles, Medical Center, Torrance, CA (J.I.R., K.D.T.)
| | - Ani W. Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville (C.Y., A.W.M.)
| | - Joao A.C. Lima
- Division of Cardiology, Johns Hopkins University, Baltimore, MD (J.AC.L.)
| | - David A. Bluemke
- Department of Radiology, University of Wisconsin, Madison (D.A.B.)
| | - Stefan K. Piechnik
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom (S.K.P., S.N.)
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, United Kingdom (S.K.P., S.N.)
| | - Patricia B. Munroe
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
| | - Steffen E. Petersen
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- National Institute for Health Research, Barts Cardiovascular Biomedical Research Centre (N.A., H.R.W., K.F., P.B.M., S.E.P.), Queen Mary University of London, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health National Health Service Trust, West Smithfield, London, United Kingdom (N.A., K.F., S.E.P.)
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Palma D, Theurer J, Prisman E, Read N, Berthelet E, Fung K, de Almeida J, Bayley A, Richardson K, Mlynarek A, Krishnan S, Le H, Mitchell S, Chen J, Corsten M, Johnson-Obaseki S, Odell M, Parker C, Kwan K, Nichols A. Radiotherapy vs. Trans-Oral Robotic Surgery for Oropharyngeal Squamous Cell Carcinoma (OPSCC): Results of a Randomized Trial. Int J Radiat Oncol Biol Phys 2019. [DOI: 10.1016/j.ijrobp.2019.06.485] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Jensen MT, Fung K, Aung N, Sanghvi MM, Chadalavada S, Paiva JM, Khanji MY, de Knegt MC, Lukaschuk E, Lee AM, Barutcu A, Maclean E, Carapella V, Cooper J, Young A, Piechnik SK, Neubauer S, Petersen SE. Changes in Cardiac Morphology and Function in Individuals With Diabetes Mellitus: The UK Biobank Cardiovascular Magnetic Resonance Substudy. Circ Cardiovasc Imaging 2019; 12:e009476. [PMID: 31522551 PMCID: PMC7099857 DOI: 10.1161/circimaging.119.009476] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 07/18/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND Diabetes mellitus (DM) is associated with increased risk of cardiovascular disease. Detection of early cardiac changes before manifest disease develops is important. We investigated early alterations in cardiac structure and function associated with DM using cardiovascular magnetic resonance imaging. METHODS Participants from the UK Biobank Cardiovascular Magnetic Resonance Substudy, a community cohort study, without known cardiovascular disease and left ventricular ejection fraction ≥50% were included. Multivariable linear regression models were performed. The investigators were blinded to DM status. RESULTS A total of 3984 individuals, 45% men, (mean [SD]) age 61.3 (7.5) years, hereof 143 individuals (3.6%) with DM. There was no difference in left ventricular (LV) ejection fraction (DM versus no DM; coefficient [95% CI]: -0.86% [-1.8 to 0.5]; P=0.065), LV mass (-0.13 g/m2 [-1.6 to 1.3], P=0.86), or right ventricular ejection fraction (-0.23% [-1.2 to 0.8], P=0.65). However, both LV and right ventricular volumes were significantly smaller in DM, (LV end-diastolic volume/m2: -3.46 mL/m2 [-5.8 to -1.2], P=0.003, right ventricular end-diastolic volume/m2: -4.2 mL/m2 [-6.8 to -1.7], P=0.001, LV stroke volume/m2: -3.0 mL/m2 [-4.5 to -1.5], P<0.001; right ventricular stroke volume/m2: -3.8 mL/m2 [-6.5 to -1.1], P=0.005), LV mass/volume: 0.026 (0.01 to 0.04) g/mL, P=0.006. Both left atrial and right atrial emptying fraction were lower in DM (right atrial emptying fraction: -6.2% [-10.2 to -2.1], P=0.003; left atrial emptying fraction:-3.5% [-6.9 to -0.1], P=0.043). LV global circumferential strain was impaired in DM (coefficient [95% CI]: 0.38% [0.01 to 0.7], P=0.045). CONCLUSIONS In a low-risk general population without known cardiovascular disease and with preserved LV ejection fraction, DM is associated with early changes in all 4 cardiac chambers. These findings suggest that diabetic cardiomyopathy is not a regional condition of the LV but affects the heart globally.
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Affiliation(s)
- Magnus T. Jensen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
- Department of Cardiology, Copenhagen University Hospital Herlev- Gentofte, Hellerup, Denmark (M.T.J.)
- Department of Cardiology, Copenhagen University Hospital Rigshospitalet, Denmark (M.T.J.)
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Mihir M. Sanghvi
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Sucharitha Chadalavada
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Jose M. Paiva
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Mohammed Y. Khanji
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Martina C. de Knegt
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Elena Lukaschuk
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, United Kingdom (E.L., A.B., V.C., S.K.P., S.N.)
| | - Aaron M. Lee
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
| | - Ahmet Barutcu
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, United Kingdom (E.L., A.B., V.C., S.K.P., S.N.)
| | - Edd Maclean
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
| | - Valentina Carapella
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, United Kingdom (E.L., A.B., V.C., S.K.P., S.N.)
| | - Jackie Cooper
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
| | - Alistair Young
- Department of Biomedical Engineering, King’s College London, United Kingdom (A.Y.)
| | - Stefan K. Piechnik
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, United Kingdom (E.L., A.B., V.C., S.K.P., S.N.)
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, United Kingdom (E.L., A.B., V.C., S.K.P., S.N.)
| | - Steffen E. Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., E.M., J.C., S.E.P.)
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, London, United Kingdom (M.T.J., K.F., N.A., M.M.S., S.C., J.M.P., M.Y.K., M.C.d.K., A.M.L., S.E.P.)
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Mauger C, Gilbert K, Lee AM, Sanghvi MM, Aung N, Fung K, Carapella V, Piechnik SK, Neubauer S, Petersen SE, Suinesiaputra A, Young AA. Right ventricular shape and function: cardiovascular magnetic resonance reference morphology and biventricular risk factor morphometrics in UK Biobank. J Cardiovasc Magn Reson 2019; 21:41. [PMID: 31315625 PMCID: PMC6637624 DOI: 10.1186/s12968-019-0551-6] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 06/14/2019] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND The associations between cardiovascular disease (CVD) risk factors and the biventricular geometry of the right ventricle (RV) and left ventricle (LV) have been difficult to assess, due to subtle and complex shape changes. We sought to quantify reference RV morphology as well as biventricular variations associated with common cardiovascular risk factors. METHODS A biventricular shape atlas was automatically constructed using contours and landmarks from 4329 UK Biobank cardiovascular magnetic resonance (CMR) studies. A subdivision surface geometric mesh was customized to the contours using a diffeomorphic registration algorithm, with automatic correction of slice shifts due to differences in breath-hold position. A reference sub-cohort was identified consisting of 630 participants with no CVD risk factors. Morphometric scores were computed using linear regression to quantify shape variations associated with four risk factors (high cholesterol, high blood pressure, obesity and smoking) and three disease factors (diabetes, previous myocardial infarction and angina). RESULTS The atlas construction led to an accurate representation of 3D shapes at end-diastole and end-systole, with acceptable fitting errors between surfaces and contours (average error less than 1.5 mm). Atlas shape features had stronger associations than traditional mass and volume measures for all factors (p < 0.005 for each). High blood pressure was associated with outward displacement of the LV free walls, but inward displacement of the RV free wall and thickening of the septum. Smoking was associated with a rounder RV with inward displacement of the RV free wall and increased relative wall thickness. CONCLUSION Morphometric relationships between biventricular shape and cardiovascular risk factors in a large cohort show complex interactions between RV and LV morphology. These can be quantified by z-scores, which can be used to study the morphological correlates of disease.
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Affiliation(s)
- Charlène Mauger
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Kathleen Gilbert
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Aaron M. Lee
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Mihir M. Sanghvi
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Valentina Carapella
- Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stefan K. Piechnik
- Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stefan Neubauer
- Oxford NIHR Biomedical Research Centre, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Steffen E. Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK
| | - Avan Suinesiaputra
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
| | - Alistair A. Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Department of Biomedical Engineering, King’s College London, London, UK
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48
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Fung K, Vivier D, Price E, Zeglis B. Development of a MUC1-targeting PET probe for ovarian cancer. Nucl Med Biol 2019. [DOI: 10.1016/s0969-8051(19)30346-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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49
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Woodbridge SP, Aung N, Paiva JM, Sanghvi MM, Zemrak F, Fung K, Petersen SE. Physical activity and left ventricular trabeculation in the UK Biobank community-based cohort study. Heart 2019; 105:990-998. [PMID: 30723101 PMCID: PMC6582810 DOI: 10.1136/heartjnl-2018-314155] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Revised: 01/08/2019] [Accepted: 01/14/2019] [Indexed: 01/22/2023] Open
Abstract
OBJECTIVE Vigorous physical activity (PA) in highly trained athletes has been associated with heightened left ventricular (LV) trabeculation extent. It has therefore been hypothesised that LV trabeculation extent may participate in exercise-induced physiological cardiac remodelling. Our cross-sectional observational study aimed to ascertain whether there is a 'dose-response' relationship between PA and LV trabeculation extent and whether this could be identified at opposite PA extremes. METHODS In a cohort of 1030 individuals from the community-based UK Biobank study (male/female ratio: 0.84, mean age: 61 years), PA was measured via total metabolic equivalent of task (MET) min/week and 7-day average acceleration, and trabeculation extent via maximal non-compaction/compaction ratio (NC/C) in long-axis images of cardiovascular magnetic resonance studies. The relationship between PA and NC/C was assessed by multivariate regression (adjusting for potential confounders) as well as between demographic, anthropometric and LV phenotypic parameters and NC/C. RESULTS There was no significant linear relationship between PA and NC/C (full adjustment, total MET-min/week: ß=-0.0008, 95% CI -0.039 to -0.037, p=0.97; 7-day average acceleration: ß=-0.047, 95% CI -0.110 to -0.115, p=0.13, per IQR increment in PA), or between extreme PA quintiles (full adjustment, total MET-min/week: ß=-0.026, 95% CI -0.146 to -0.094, p=0.67; 7-day average acceleration: ß=-0.129, 95% CI -0.299 to -0.040, p=0.49), across all adjustment levels. A negative relationship was identified between left ventricular ejection fraction and NC/C, significantly modified by PA (ß difference=-0.006, p=0.03). CONCLUSIONS In a community-based general population cohort, there was no relationship at, or between, extremes, between PA and NC/C, suggesting that at typical general population PA levels, trabeculation extent is not influenced by PA changes.
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Affiliation(s)
- Simon P Woodbridge
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Nay Aung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Jose M Paiva
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Mihir M Sanghvi
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Filip Zemrak
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Kenneth Fung
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
| | - Steffen E Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK
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50
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Bernard C, Soklaridis S, Paton M, Fung K, Fefergrad M, Andermann L, Johnson A, Ferguson G, Iglar K, Whitehead CR. Family physicians and health advocacy: Is it really a difficult fit? Can Fam Physician 2019; 65:491-496. [PMID: 31300435 PMCID: PMC6738460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
OBJECTIVE To examine whether family medicine residents and faculty members appreciate the full spectrum of health advocacy as described in articles published in Canadian Family Physician in 2016 and to identify the perceived challenges and enablers of advocating across the entire spectrum. DESIGN Analysis of a subset of data from a qualitative study using semistructured interviews and focus groups. SETTING University of Toronto in Ontario. PARTICIPANTS A total of 9 family medicine faculty members and 6 family medicine residents. METHODS A subset of transcripts from a 2015 qualitative study that explored family medicine and psychiatry residents' and faculty members' understanding of the CanMEDS-Family Medicine health advocate role were reviewed, guided by interpretive descriptive methodology. MAIN FINDINGS Results indicated that family medicine physicians and residents were able to identify the full spectrum of advocacy described in the Canadian Family Physician articles and that they valued the role. Further, there was widespread agreement that being a health advocate was linked with their identities as health professionals. The time it takes to be a health advocate was seen as a barrier to being effective in the role, and the work was seen as extremely challenging owing to system constraints. Participants also described a gap in training relating to advocacy at the system level as a challenge. CONCLUSION Team-based care was seen as one of the most important enablers for becoming involved in the full spectrum of advocacy, as was time for personal reflection.
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Affiliation(s)
- Carrie Bernard
- Assistant Professor and Associate Program Director of Curriculum and Remediation for the postgraduate program in the Department of Family and Community Medicine at the University of Toronto in Ontario and Assistant Clinical Professor in the Department of Family Medicine at McMaster University in Hamilton, Ont.
| | - Sophie Soklaridis
- Independent Scientist and Interim Director of Education Research at the Centre for Addiction and Mental Health in Toronto and Assistant Professor in the Department of Psychiatry at the University of Toronto
| | - Morag Paton
- Doctoral candidate in the Ontario Institute for Studies in Education at the University of Toronto and Education Research Coordinator for Continuing Professional Development in the Faculty of Medicine at the University of Toronto
| | - Kenneth Fung
- Clinical Director for the Asian Initiative in Mental Health and Associate Professor in the Equity, Gender, and Population Division of the Department of Psychiatry at the University of Toronto
| | - Mark Fefergrad
- Assistant Professor and Program Director of Postgraduate Education in the Department of Psychiatry at the University of Toronto
| | - Lisa Andermann
- Associate Professor in the Equity, Gender, and Population Division of the Department of Psychiatry at the University of Toronto
| | - Andrew Johnson
- Manager of Client and Family Education and CAMH Publications Education at the Centre for Addiction and Mental Health
| | - Genevieve Ferguson
- Was Research coordinator for this project through the Centre for Addiction and Mental Health
| | - Karl Iglar
- Associate Professor in the Department of Family and Community Medicine at the University of Toronto
| | - Cynthia R Whitehead
- Associate Professor in the Department of Family and Community Medicine at the University of Toronto, Director and Scientist at the Wilson Centre for Research and Education, Vice President of Education at Women's College Hospital, and the BMO Financial Group Chair in Health Professions Research at University Health Network
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