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COVID-19 and cancer: A guide with suggested COVID-19 rule-out criteria to support clinical decision-making.

ABSTRACT: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious zoonotic pathogen that has exacted heavy public health, social and economic tolls. In February 2020, the World Health Organization acronymed the disease caused by SARS-CoV-2 as COVID-19, for coronavirus disease 2019. The number of confirmed COVID-19 infections, which has been detected in at least 103 countries, has reached 1,970,225 worldwide as of April 14, 2020 with 124,544 deaths, according to the U.S. Centers for Disease Control and Prevention (CDC). Many cases of COVID-19 resolve quickly. However, the disease, which, like other respiratory pathogens that cause common cold symptoms is believed to be transmitted through respiratory droplets. Infection with COVID-19 can also lead to significant morbidity and death; this is particularly the case for cancer patients. Moreover, because the signs and symptoms of COVID-19 are easily misattributed to the sequelae of cancer itself, such as pulmonary embolism, or its treatment, such as nausea and diarrhea, diagnosis may be delayed or missed. Potential COVID-19 rule out criteria, based on the Wells' criteria for pulmonary embolism, another protean disease entity, are provided as a decision-making aid. This review summarizes the current understanding of the transmission, clinical presentation, diagnosis and differential diagnosis, pathogenesis, rationale to treat the cancer or not, treatment and prevention of COVID-19 with an emphasis on implications in cancer.

SUBMITTER: Larson C

PROVIDER: S-EPMC7438345 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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COVID-19 and cancer: A guide with suggested COVID-19 rule-out criteria to support clinical decision-making.

Larson Christopher C Oronsky Bryan B Goyal Sharad S Ray Carolyn C Hedjran Farah F Hammond Terese C TC Kesari Santosh S Caroen Scott S Lybeck Michelle M Dobalian Vaughn E VE Oronsky Arnold A Reid Tony T

Biochimica et biophysica acta. Reviews on cancer 20200820 2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious zoonotic pathogen that has exacted heavy public health, social and economic tolls. In February 2020, the World Health Organization acronymed the disease caused by SARS-CoV-2 as COVID-19, for coronavirus disease 2019. The number of confirmed COVID-19 infections, which has been detected in at least 103 countries, has reached 1,970,225 worldwide as of April 14, 2020 with 124,544 deaths, according to the U.S. Centers ...[more]

PMID: 32827582

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Project description:BackgroundThe COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of this manuscript are to describe the structure and technologies used to construct a COVID-19 Data Mart architecture and to present how a large hospital has tackled the challenge of supporting daily management of COVID-19 pandemic emergency, by creating a strong retrospective knowledge base, a real time environment and integrated information dashboard for daily practice and early identification of critical condition at patient level. This framework is also used as an informative, continuously enriched data lake, which is a base for several on-going predictive studies.MethodsThe information technology framework for clinical practice and research was described. It was developed using SAS Institute software analytics tool and SAS® Vyia® environment and Open-Source environment R ® and Python ® for fast prototyping and modeling. The included variables and the source extraction procedures were presented.ResultsThe Data Mart covers a retrospective cohort of 5528 patients with SARS-CoV-2 infection. People who died were older, had more comorbidities, reported more frequently dyspnea at onset, had higher d-dimer, C-reactive protein and urea nitrogen. The dashboard was developed to support the management of COVID-19 patients at three levels: hospital, single ward and individual care level.InterpretationThe COVID-19 Data Mart based on integration of a large collection of clinical data and an AI-based integrated framework has been developed, based on a set of automated procedures for data mining and retrieval, transformation and integration, and has been embedded in the clinical practice to help managing daily care. Benefits from the availability of a Data Mart include the opportunity to build predictive models with a machine learning approach to identify undescribed clinical phenotypes and to foster hospital networks. A real-time updated dashboard built from the Data Mart may represent a valid tool for a better knowledge of epidemiological and clinical features of COVID-19, especially when multiple waves are observed, as well as for epidemic and pandemic events of the same nature (e. g. with critical clinical conditions leading to severe pulmonary inflammation). Therefore, we believe the approach presented in this paper may find several applications in comparable situations even at region or state levels. Finally, models predicting the course of future waves or new pandemics could largely benefit from network of DataMarts.

Project description:PLAIN ENGLISH SUMMARY:For the elderly to get the care and services they need, they may need to make the difficult decision about staying in their home or moving to another home. Many other people may be involved in their care too (friends, family and healthcare providers), and can support them in making the decision. We asked informal caregivers of elderly people to help us develop a decision guide to support them and their loved ones in making this decision. This guide will be used by health providers in home care who are trained to help people make decisions. The guide is in French and English. To design and test this decision guide we involved elderly people, their caregivers and health administrators. We first asked them what they needed for making the decision, and then designed a first version of the guide. Then we asked them to look at it and give feedback, which was used to make the final version. We then used scientific criteria to check its content and the language used. The final decision guide was acceptable to the caregivers, their elderly loved ones, and the health administrators. The guide is currently being evaluated in a large research project with home care teams in the province of Quebec. ABSTRACT:Background As they grow older, many elderly people are faced with the difficult and preference-sensitive decision about staying in their home or moving to a residence better adapted to their evolving care needs. We aimed to develop an English and French decision aid (DA) for elderly people facing this decision, and to involve end-users in all phases of the development process. Methods A three-cycle design with involvement of end-users in Quebec. End-users were elderly people (n?=?4) caregivers of the elderly (n?=?5), health administrators involved in home-care service delivery or policy (n?=?6) and an interprofessional research team (n?=?19). Cycle 1: Decisional needs assessment and development of the first prototype based on existing tools and input from end-users; overview of reviews examining the impact of location of care on elderly people's health outcomes. Cycle 2: Usability testing with end-users, adaptation of prototype. Cycle 3: Refinement of the prototype with a linguist, graphic designer and end-users. The final prototype underwent readability testing and an International Patient Decision Aids (IPDAS) criteria compatibility assessment to verify minimal requirements for decision aids and was tested for usability by the elderly. ResultsCycle 1: We used the Ottawa Personal Decision Guide to design a first prototype. As the overview of reviews did not find definitive evidence regarding optimal locations of care for elderly people, we were not able to add evidence-based advantages and disadvantages to the guide. Cycle 2: Overall, the caregivers and health administrators who evaluated the prototype (n?=?10) were positive. In response to their suggestions, we deleted some elements (overview of pros, cons, and consequences of the options) that were necessary to qualify the tool as a DA and renamed it a "decision guide". Cycle 3: We developed French and English versions of the guide, readable at a primary school level. The elderly judged the guide as acceptable. Conclusion We developed a decision guide to support elderly people and their caregivers in decision making about location of care. This paper is one of few to report on a fully collaborative approach to decision guide development that involves end-users at every stage (caregivers and health administrators early on, the frail elderly in the final stages). The guide is currently being evaluated in a cluster randomized trial. Trial registration: NCT02244359.

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COVID-19 and cancer: A guide with suggested COVID-19 rule-out criteria to support clinical decision-making.

Publications

COVID-19 and cancer: A guide with suggested COVID-19 rule-out criteria to support clinical decision-making.

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