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Article ; Online: Care and Precision Medicine Research in the Time of COVID-19.

Ison, Juliana M / Karlson, Elizabeth W / Jackson, Jonathan D / Hille, Alexander / McCloud, Cheryl / Bor, Meg / Zhou, Guohai / Clark, Cheryl R

Ethnicity & disease

2021 Volume 31, Issue 3, Page(s) 407–410

Abstract: Purpose: Enhancing the bidirectional benefit of precision medicine research infrastructure ... infrastructure to provide human-centered COVID-19 resources to participants as a part of their research ... received a COVID-19 check-in call.: Methods: Research assistants called participants during March-April ...

Abstract	Purpose: Enhancing the bidirectional benefit of precision medicine research infrastructure may advance equity in research participation for diverse groups. This study explores the use of research infrastructure to provide human-centered COVID-19 resources to participants as a part of their research participation. Design: The Participants: A total of 20,559 participants in the AoUNE consortium received a COVID-19 check-in call. Methods: Research assistants called participants during March-April 2020, distributed COVID-19 resources to interested participants, and subsequently rated call tone. Results: Of the total cohort participants called, 8,512 (41%) spoke with a research team member. The majority of calls were rated as positive or neutral; only 3% rated as negative. African American and Black as well as Hispanic populations requested COVID-19 resources at higher rates than other groups. Conclusions: Calls made to AoUNE participants were received positively by diverse groups. These findings may have implications for participant-centered engagement strategies in precision medicine research.
MeSH term(s)	COVID-19 ; Hispanic or Latino ; Humans ; Population Health ; Precision Medicine ; SARS-CoV-2
Language	English
Publishing date	2021-07-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	1274267-3
ISSN	1945-0826 ; 1049-510X
ISSN (online)	1945-0826
ISSN	1049-510X
DOI	10.18865/ed.31.3.407
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Article ; Online: Report from the Ready for the Next Round Thought-Leadership Roundtables on Building Resilience in Cancer Care and Control in Canada-Colorectal Cancer Canada; 2021.

Current oncology (Toronto, Ont.)

2022 Volume 29, Issue 3, Page(s) 1723–1743

Abstract: ... precision medicine approaches to care. (5) investing in training and hiring a robust supply of health care ... in cancer care delivery. (2) developing real-time data metrics, data sharing, and evidence-based ... 1) Background: The COVID-19 pandemic illuminated vulnerabilities in the Canadian health care ...

Abstract	(1) Background: The COVID-19 pandemic illuminated vulnerabilities in the Canadian health care system and exposed gaps and challenges across the cancer care continuum. Canada is experiencing significant disruptions to cancer-related services, and the impact these disruptions (delays/deferrals/cancellations) have on the health care system and patients are yet to be determined. Given the potential adverse ramifications, how can Canada's health care systems build resilience for future threats? (2) Methods: To answer this question, CCC facilitated a series of four thought-leadership roundtables, each representing the views of four different stakeholder groups: patients, physicians, health care system leaders, and researchers. (3) Results: Six themes of strength were identified to serve as a springboard for building resilience including, (1) advancing virtual care and digital health technologies to prevent future interruptions in cancer care delivery. (2) developing real-time data metrics, data sharing, and evidence-based decision-making. (3) enhancing public-private-non-profit partnerships to advance research and strengthen connections across the system. (4) advancing patient-centricity in cancer research to drive and encourage precision medicine approaches to care. (5) investing in training and hiring a robust supply of health care human resources. (6) implementing a national strategy and infrastructure to ensure inter-provincial collaborative data sharing (4). Conclusions: A resilient health care system that can respond to shocks and threats is not an emergency system; it is a robust everyday system that can respond to emergencies.
MeSH term(s)	COVID-19/epidemiology ; Canada ; Colorectal Neoplasms/therapy ; Humans ; Leadership ; Pandemics
Language	English
Publishing date	2022-03-07
Publishing country	Switzerland
Document type	Congress ; Research Support, Non-U.S. Gov't
ZDB-ID	1236972-x
ISSN	1718-7729 ; 1198-0052
ISSN (online)	1718-7729
ISSN	1198-0052
DOI	10.3390/curroncol29030143
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Article: From Precision Metapharmacology to Patient Empowerment: Delivery of Self-Care Practices for Epilepsy, Pain, Depression and Cancer Using Digital Health Technologies.

Bulaj, Grzegorz / Clark, Jacqueline / Ebrahimi, Maryam / Bald, Elizabeth

Frontiers in pharmacology

2021 Volume 12, Page(s) 612602

Abstract: ... COVID-19, and 4) just-in-time stressful and traumatic circumstances. Development and implementation ... patient-centered care, integrative medicine and digital health ecosystems. ... priorities of key stakeholders including patients, research communities, healthcare industry, regulatory and ...

Abstract	To improve long-term outcomes of therapies for chronic diseases, health promotion and lifestyle modifications are the most promising and sustainable strategies. In addition, advances in digital technologies provide new opportunities to address limitations of drug-based treatments, such as medication non-adherence, adverse effects, toxicity, drug resistance, drug shortages, affordability, and accessibility. Pharmaceutical drugs and biologics can be combined with digital health technologies, including mobile medical apps (digital therapeutics), which offer additional clinical benefits and cost-effectiveness. Promises of drug+digital combination therapies are recognized by pharmaceutical and digital health companies, opening opportunities for integrating pharmacotherapies with non-pharmacological interventions (metapharmacology). Herein we present unique features of digital health technologies which can deliver personalized self-care modalities such as breathing exercises, mindfulness meditation, yoga, physical activity, adequate sleep, listening to preferred music, forgiveness and gratitude. Clinical studies reveal how aforementioned complimentary practices may support treatments of epilepsy, chronic pain, depression, cancer, and other chronic diseases. This article also describes how digital therapies delivering "medicinal" self-care and other non-pharmacological interventions can also be personalized by accounting for: 1) genetic risks for comorbidities, 2) adverse childhood experiences, 3) increased risks for viral infections such as seasonal influenza, or COVID-19, and 4) just-in-time stressful and traumatic circumstances. Development and implementation of personalized pharmacological-behavioral combination therapies (precision metapharmacology) require aligning priorities of key stakeholders including patients, research communities, healthcare industry, regulatory and funding agencies. In conclusion, digital technologies enable integration of pharmacotherapies with self-care, lifestyle interventions and patient empowerment, while concurrently advancing patient-centered care, integrative medicine and digital health ecosystems.
Language	English
Publishing date	2021-04-23
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2021.612602
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Article ; Online: Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods

Pan, Pan / Li, Yichao / Xiao, Yongjiu / Han, Bingchao / Su, Longxiang / Su, Mingliang / Li, Yansheng / Zhang, Siqi / Jiang, Dapeng / Chen, Xia / Zhou, Fuquan / Ma, Ling / Bao, Pengtao / Xie, Lixin

Journal of Medical Internet Research, Vol 22, Iss 11, p e

Model Development and Validation

2020 Volume 23128

Abstract: BackgroundPatients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and ... of risk factors and prediction of mortality among ICU patients with COVID-19. MethodsIn this study, 123 patients ... with COVID-19 in the ICU of Vulcan Hill Hospital were retrospectively selected from the database, and ...

Abstract	BackgroundPatients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and methods to assess patients’ prognosis early and administer precise treatment are of great significance. ObjectiveThe aim of this study was to use machine learning to construct a model for the analysis of risk factors and prediction of mortality among ICU patients with COVID-19. MethodsIn this study, 123 patients with COVID-19 in the ICU of Vulcan Hill Hospital were retrospectively selected from the database, and the data were randomly divided into a training data set (n=98) and test data set (n=25) with a 4:1 ratio. Significance tests, correlation analysis, and factor analysis were used to screen 100 potential risk factors individually. Conventional logistic regression methods and four machine learning algorithms were used to construct the risk prediction model for the prognosis of patients with COVID-19 in the ICU. The performance of these machine learning models was measured by the area under the receiver operating characteristic curve (AUC). Interpretation and evaluation of the risk prediction model were performed using calibration curves, SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), etc, to ensure its stability and reliability. The outcome was based on the ICU deaths recorded from the database. ResultsLayer-by-layer screening of 100 potential risk factors finally revealed 8 important risk factors that were included in the risk prediction model: lymphocyte percentage, prothrombin time, lactate dehydrogenase, total bilirubin, eosinophil percentage, creatinine, neutrophil percentage, and albumin level. Finally, an eXtreme Gradient Boosting (XGBoost) model established with the 8 important risk factors showed the best recognition ability in the training set of 5-fold cross validation (AUC=0.86) and the verification queue (AUC=0.92). The calibration curve showed that the risk predicted by the model was in good agreement with the actual risk. In addition, using the SHAP ...
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
Subject code	310
Language	English
Publishing date	2020-11-01T00:00:00Z
Publisher	JMIR Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal

Patrício, André / Costa, Rafael S / Henriques, Rui

Journal of Medical Internet Research, Vol 23, Iss 4, p e

Longitudinal Cohort Study

2021 Volume 26075

Abstract: BackgroundIn the face of the current COVID-19 pandemic, the timely prediction of upcoming medical ... needs for infected individuals enables better and quicker care provision when necessary and management ... intensive care unit admissions, and respiratory assistance) and survivability of individuals testing positive for SARS ...

Abstract	BackgroundIn the face of the current COVID-19 pandemic, the timely prediction of upcoming medical needs for infected individuals enables better and quicker care provision when necessary and management decisions within health care systems. ObjectiveThis work aims to predict the medical needs (hospitalizations, intensive care unit admissions, and respiratory assistance) and survivability of individuals testing positive for SARS-CoV-2 infection in Portugal. MethodsA retrospective cohort of 38,545 infected individuals during 2020 was used. Predictions of medical needs were performed using state-of-the-art machine learning approaches at various stages of a patient’s cycle, namely, at testing (prehospitalization), at posthospitalization, and during postintensive care. A thorough optimization of state-of-the-art predictors was undertaken to assess the ability to anticipate medical needs and infection outcomes using demographic and comorbidity variables, as well as dates associated with symptom onset, testing, and hospitalization. ResultsFor the target cohort, 75% of hospitalization needs could be identified at the time of testing for SARS-CoV-2 infection. Over 60% of respiratory needs could be identified at the time of hospitalization. Both predictions had >50% precision. ConclusionsThe conducted study pinpoints the relevance of the proposed predictive models as good candidates to support medical decisions in the Portuguese population, including both monitoring and in-hospital care decisions. A clinical decision support system is further provided to this end.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2021-04-01T00:00:00Z
Publisher	JMIR Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Real-Time Crowd Monitoring and Management System for Social Distance Classification and Healthcare Using Deep Learning

Sangeeta Yadav / Preeti Gulia / Nasib Singh Gill / Jyotir Moy Chatterjee

Journal of Healthcare Engineering, Vol

2022 Volume 2022

Abstract: ... The observed results show its suitability for real-time deployment in public places for COVID-19 prevention ... This system significantly helps in COVID-19 prevention by social distance detection and classification ... by this notion, a real-time crowd monitoring and management system for social distance classification is ...

Abstract	Coronavirus born COVID-19 disease has spread its roots in the whole world. It is primarily spread by physical contact. As a preventive measure, proper crowd monitoring and management systems are required to be installed in public places to limit sudden outbreaks and impart improved healthcare. The number of new infections can be significantly reduced by adopting social distancing measures earlier. Motivated by this notion, a real-time crowd monitoring and management system for social distance classification is proposed in this research paper. In the proposed system, people are segregated from the background using the YOLO v4 object detection technique, and then the detected people are tracked by bounding boxes using the Deepsort technique. This system significantly helps in COVID-19 prevention by social distance detection and classification in public places using surveillance images and videos captured by the cameras installed in these places. The performance of this system has been assessed using mean average precision (mAP) and frames per second (FPS) metrics. It has also been evaluated by deploying it on Jetson Nano, a low-cost embedded system. The observed results show its suitability for real-time deployment in public places for COVID-19 prevention by social distance monitoring and classification.
Keywords	Medicine (General) ; R5-920 ; Medical technology ; R855-855.5
Subject code	006
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: ‘Containment, delay, mitigation’

Lisa Baraitser / Laura Salisbury

Wellcome Open Research, Vol

waiting and care in the time of a pandemic [version 1; peer review: 2 approved]

2020 Volume 5

Abstract: ... its effects – we offer a psychosocial reading that draws attention to the relation between time and care ... that is the management and mitigation of a future threat, but also a time of care in and for the present. ... people. In conditions of lockdown and what will be a long and drawn-out ‘after life’ of COVID-19 ...

Abstract	In this paper we take up three terms – containment, delay, mitigation – that have been used by the UK Government to describe their phased response to the COVID-19 pandemic. Although the terms refer to a political and public health strategy – contain the virus, flatten the peak of the epidemic, mitigate its effects – we offer a psychosocial reading that draws attention to the relation between time and care embedded in each term. We do so to call for the development of a form of care-ful attention under conditions that tend to prompt action rather than reflection, closing down time for thinking. Using Adriana Cavarero’s notion of ‘horrorism’, in which violence is enacted at precisely the point that care is most needed, we discuss the ever-present possibility of failures within acts of care. We argue that dwelling in the temporality of delay can be understood as an act of care if delaying allows us to pay care-ful attention to violence. We then circle back to a point in twentieth-century history – World War II – that was also concerned with an existential threat requiring a response from a whole population. Our purpose is not to invoke a fantasised narrative of ‘Blitz spirit’, but to suggest that the British psychoanalytic tradition born of that moment offers resources for understanding how to keep thinking while ‘under fire’ through containing unbearable anxiety and the capacity for violence in the intersubjective space and time between people. In conditions of lockdown and what will be a long and drawn-out ‘after life’ of COVID-19, this commitment to thinking in and with delay and containment might help to inhabit this time of waiting – waiting that is the management and mitigation of a future threat, but also a time of care in and for the present.
Keywords	Medicine ; R ; Science ; Q
Subject code	360
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	Wellcome
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: ‘Containment, delay, mitigation’

Lisa Baraitser / Laura Salisbury

Wellcome Open Research, Vol

waiting and care in the time of a pandemic [version 2; peer review: 2 approved]

2020 Volume 5

Abstract	In this paper, we take up three terms – containment, delay, mitigation – that have been used by the UK Government to describe their phased response to the COVID-19 pandemic. Although the terms refer to a political and public health strategy – contain the virus, flatten the peak of the epidemic, mitigate its effects – we offer a psychosocial reading that draws attention to the relation between time and care embedded in each term. We do so to call for the development of a form of care-ful attention under conditions that tend to prompt action rather than reflection, closing down time for thinking. Using Adriana Cavarero’s notion of ‘horrorism’, in which violence is enacted at precisely the point that care is most needed, we discuss the ever-present possibility of failures within acts of care. We argue that dwelling in the temporality of delay can be understood as an act of care if delaying allows us to pay care-ful attention to violence. We then circle back to a point in twentieth-century history – World War II – that was also concerned with an existential threat requiring a response from a whole population. Our purpose is not to invoke a fantasised narrative of ‘Blitz spirit’, but to suggest that the British psychoanalytic tradition born of that moment offers resources for understanding how to keep thinking while ‘under fire’ through containing unbearable anxiety and the capacity for violence in the intersubjective space and time between people. In conditions of lockdown and what will be a long and drawn-out ‘after life’ of COVID-19, this commitment to thinking in and with delay and containment might help to inhabit this time of waiting – waiting that is the management and mitigation of a future threat, but also a time of care in and for the present.
Keywords	Medicine ; R ; Science ; Q ; covid19
Subject code	360
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	Wellcome
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Situating 'best practice'

Mia Harrison / Tim Rhodes / Kari Lancaster

SSM: Qualitative Research in Health, Vol 4, Iss , Pp 100343- (2023)

Making healthcare familiar and good enough in the face of unknowns

2023

Abstract: ... and research of Covid-19 in a hospital in Sydney, Australia, we investigate how best practice is done ... that care during Covid-19 is made to work as ‘familiar’ practice, ‘good-enough’ practice, and ‘better ... in times of uncertainty and disruption, thus approaching ‘best practice’ as a situated concern. We find ...

Abstract	The relationship between ‘best practice’ as a set of evidence-informed principles and its actualization in situations of care has been the subject of significant critique across clinical and sociological health research. Precisely how ‘best practice’ gets done—in practice—is often not investigated in itself. Drawing from qualitative interviews with thirty-three healthcare workers involved in the care, management, and research of Covid-19 in a hospital in Sydney, Australia, we investigate how best practice is done in times of uncertainty and disruption, thus approaching ‘best practice’ as a situated concern. We find that care during Covid-19 is made to work as ‘familiar’ practice, ‘good-enough’ practice, and ‘better’ practice. Our analysis moves away from ideas of best practice as an act, prescription, or framework, towards best practice as processual and always in-the-making. Doing best practice is a situated yet iterative process of making care work in relation with what can be known, what can be done, and what can be done better (here, now, and for now).
Keywords	Best practice ; Healthcare ; Uncertainty ; Covid-19 ; Qualitative ; Situated practice ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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