300. Long COVID in Cancer Patients: Preponderance of Symptoms in Majority of Patients Over Long Time Period

Abstract Background An increasing number of observational studies have reported the persistence of symptoms following recovery from acute COVID-19 disease. The long-term consequences of COVID-19 are not fully understood and there is no clear consensus on the definition of post-acute sequelae of SARS-CoV-2 infection (PASC). The reported prevalence of PASC widely varies from 10% up to 87%. The purpose of this study is to assess PASC in cancer patients following acute COVID-19 recovery. Methods We assessed cancer patients at MD Anderson Cancer Center who were diagnosed with COVID-19 disease between March 1, 2020 and Sept 1, 2020. Using patient questionnaires and medical chart reviews we followed these patients from March 2020 till May 2021. Patient questionnaires were sent out remotely daily for 14 days after COVID-19 diagnosis then weekly for 3 months, and then monthly thereafter. Chart reviews were conducted for each patient hospital re-admission and emergency department visit. These admissions were classified as either COVID-19 related or non-related. The persistence or emergence of new COVID19-related symptoms were captured at each COVID-19 related admission. Results We included 312 cancer patients with a median age of 57 years (18-86). The majority of patients had solid tumors (75%). Of the 312 patients, 188 (60%) reported long COVID-19 symptoms with a median duration of 7 months and up to 14 months after COVID-19 diagnosis. The most common symptoms reported included fatigue (82%), sleep disturbances (78%), myalgias (67%) and gastrointestinal symptoms (61%), followed by headache, altered smell or taste, dyspnea (47%) and cough (46%). A higher number of females reported a persistence of symptoms compared to males (63% vs 37%; p=0.036). Cancer type, neutropenia, lymphocytopenia, and hospital admission during acute COVID-19 disease were comparable in both groups and did not seem to contribute to a higher number of long-COVID-19 patients in our study group. Conclusion Long-COVID occurs in 60% of cancer patients and may persist up to 14 months after acute illness. The most common symptoms are fatigue, sleep disturbance, myalgia and gastro-intestinal symptoms. Disclosures Fareed Khawaja, MBBS, Eurofins Viracor (Research Grant or Support)

Background. There are multiple mechanisms for the interconnection between obesity and adverse outcomes in COVID-19. Body mass index (BMI) has historically been used to delineate body fatness, but does not include age, which could influence the relationship between body fat and BMI. Ideal body weight (IBW) equations predict a single IBW, which could allow improved recognition of adults with excess weight at increased risk of death from COVID-19. The purpose of our study was to determine whether an association exists between excess weight and in-hospital mortality in COVID-19 patients.
Methods. This was a multicenter, retrospective chart review of hospitalized patients with COVID-19. Patients were separated in two groups based on the difference between actual body weight (ABW) and IBW (ABW/IBW ≤ 120% and ABW/IBW > 120%) to compare rates of in-hospital mortality and length of stay (LOS). A subgroup analysis of patients with ABW/IBW > 120% was conducted to compare in-hospital mortality between patients with ABW/IBW 121-149%, ABW/IBW 150-199%, and ABW/IBW ≥ 200%.
Conclusion. In-hospital mortality and LOS were not significantly higher among COVID-19 patients with excess weight, defined by ABW/IBW > 120%, when compared to those with ABW/IBW ≤ 120%. Further research is needed to compare COVID-19 outcomes when BMI and ABW/IBW are used to define excess weight.
Disclosures. All Authors: No reported disclosures

D-dimer as an ICU Admission Risk Predictor in COVID-19 Patients, A Prospective Study
Oriana Narváez -Ramírez, n/a 1 ; Lina Morales-Cely, n/a 1 ; Ingrid G. Background. Since the onset of the 2019 coronavirus disease 2019 (COVID-19) pandemic, the rapid increase in community-acquired pneumonia (CAP) cases has led to an excessive rate of intensive care units (ICU) admissions, a rate varying between 5-18%, depending on the country. Consequently, the study of serum biomarkers, such as D-dimer, have been utilized to identify patient with severe disease. However, further data is needed to confirm the association between this serum concentration of D-dimer and the risk of ICU admission. Thus, the aim of this study was to determine if serum concentration of D-dimer predict the risk of ICU admission in patients with COVID-19 and CAP.
Methods. A prospective observational study was carried out at the Clinica Universidad de La Sabana, Colombia. Patients older than 18 years old, hospitalized for COVID-19 or CAP were included. Then, patients were stratified into ICU and non-ICU patients. Plasma samples were collected within the first 24 hours of hospital admission to quantify D-dimer using the PATHFAST system. Concentrations were compared among groups and to assess the biomarker capacity to predict ICU admission risk, ROC curves were used. Finally, a DeLong test was applied to compare their differences.
Results. A total of 240 patients diagnosed with lower respiratory tract infection were included in the study. 88 patients were COVID-19 negative (CAP) and 152 were positive. Plasma concentrations of D-dimer (µg/ml) were significantly higher in COVID-19 patients admitted to the ICU when compared with non-ICU COVID-19 admitted patients ( Conclusion. D-dimer seems to be a promising tool to identify COVID-19 patients with disease. However, this predicting capacity was not observed in CAP patients. Further studies are needed to identify the mechanisms underling the elevation of D-dimer in COVID-19 patients.
Disclosures. All Authors: No reported disclosures