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Annals of Oncology ; 32:S1150, 2021.
Article in English | EMBASE | ID: covidwho-1432900


Background: Cancer patients are at increased risk of severe COVID-19 illness because of their systemic immunosuppressive state. The potential effects of cancer and/or anticancer treatments on COVID-19 vaccine response, adverse events and progression are unknown. Moreover, the impacts of financial, familial and societal stressors during the pandemic on health-related quality of life are unclear. To address these concerns, we report data from the ongoing U.S. NCI-funded SeroNet COVID-19 Risk Associations and Longitudinal Evaluation Study (CORALE) at a large health care system in Los Angeles. Methods: Cancer patients are invited to complete questionnaires, donate blood specimens and engage in long-term follow-up with repeat questionnaires and biosampling. Patient-reported outcomes are assessed at baseline, post-vaccination, 6, 12 and 24 months. Clinical information on cancer type, stage, treatment, dates, medications and outcomes (adverse events, SARS-CoV-2 infection, COVID-19 vaccination and cancer-related outcomes) are extracted from electronic medical records. Results: From December 2019-May 2020, we enrolled 317 patients with malignancies or hematologic disorders (70.0% response rate). The median age was 63 (interquartile range (IQR)=54-73) years, 47% were women, 30% self-identified as non-White minorities and 18% were unable to work due to health status. 3% were known to been infected with SARS-CoV-2. An overall COVID-19 vaccine acceptance rate of 80% was reported. Among unvaccinated patients, women expressed more hesitancy than men (p=0.045). Concerns about adverse events (56%), rushed vaccine development (44%), and insufficient knowledge (44%) were reported. Self-reported symptoms after the first dose included injection site pain (21%) and fatigue (11%). We observed low levels of depression and high emotional support. Enrollment is ongoing. Conclusions: Individuals with cancer are a complex and extremely diverse population with a multitude of considerations for both immediate clinical care and long-term survivorship. Updated results including findings on antibody response to vaccination across cancer types/treatment protocols will be presented. Legal entity responsible for the study: Cedars-Sinai Medical Center. Funding: U.S. National Cancer Institute. Disclosure: All authors have declared no conflicts of interest.

Journal of the American Geriatrics Society ; 69(SUPPL 1):S74, 2021.
Article in English | EMBASE | ID: covidwho-1214838


Background: Coronavirus 2019 (COVID-19), also known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), infection is a pandemic that causes acute respiratory injury, hospital admission and death. Older adults are at a higher risk of serious illness and death from this pandemic. Many COVID-19 patients have a pre-existing cardiovascular disease (CVD). We aim to develop a risk factor stratification tool, using Artificial Intelligence (AI) method, to predict mortality, ICU admission, and length of hospital stay, in patients with CVD during this pandemic. Methods: This is a retrospective cohort study. An IRB approval was obtained. Patients with confirmed (SARS-Cov-2) test, age more than 60 and older, who were admitted to the Sparrow hospital between March 2020 and October 2020 were included. CV risk factors including Hypertension (HTN), Chronic Ischemic Heart Disease (CHD), Heart Failure (HF), and Cardiac Arrhythmia (CA) were used. Results: Of the 426 patients with COVID-19(mean age:74.5 years), at least 1 CVD was identified in most patients. HTN being the most common (55%), followed by CHD (22%), HF (20%) and CA (3%). Multivariable logistic regression has been conducted to identify risk factors for adverse outcomes and competing risk survival analysis for mortality. Outcomes measures included hospital stay > 7 days, ICU admission, and death. Discussion: Our data suggests patients with HTN required longer hospital stay, had higher ICU admissions and death rate. Conclusion: CV risk factors are common in older adults. HTN is the commonest CVD in this population. Several CV risk factors may contribute to the severity of COVID19 and its impact on older adults. Our study suggests that CV risk factors including HTN, HF, CHD, and CA have major impact on COVID-19 infection in hospitalized geriatric populations - see graph 1. Patients with HTN, had longer hospital stay, ICU admission, and mortality. Based on this work, we suggest that a large data sample might be required to develop an AI software that can help predict outcomes and the need for certain resources for older patients.

Journal of the American Geriatrics Society ; 69:S148-S148, 2021.
Article in English | Web of Science | ID: covidwho-1195029
American Journal of Gastroenterology ; 115:S537-S537, 2020.
Article in English | Web of Science | ID: covidwho-1070201