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Background: Coronavirus-2 has profound effects on patients (pts) with Multiple myeloma (MM). At the beginning of the pandemic, COVID-19 infection resulted an overall mortality around 54% (cook et al. BMJ 2020). Here, we report an updated morbidity and fatality for MM. Methods: After obtaining IRB approvals from each participating institute, retrospectively, between January 1, 2021 and August 30, 2021, we identified pts with MM and COVID-19 in two myeloma centers (Levine Cancer Institute (LCI) & the University of Kansas medical center (KUMC). Results: We identified 162 MM pts who had COVID- 19 (LCI n=132, UKMC n=30), including 57% males, with median age of 64 years. Current or former smoking reported in 40% of pts. Most pts have associated comorbid conditions: hypertension (45%), hypogammaglobulinemia (32%), CKD (30%), DM (22%), obesity (16.6%), CHF (14%), and CAD (13.5%). Within 3 months prior to infection, treatment included immunomodulatory combinations in 35%, proteasome inhibitors in 28 %, and Daratumumab in 26.5%. Symptoms are summarized in table. 69% had Mild symptoms (no need for hospitalization), 20 % had moderate symptoms (requiring hospitalization), and 9.8% had severe symptoms (ICU level of care). The 18% of pts required oxygen: 6 pts required invasive oxygenation and 3 pts needed vasopressors. The 32% of pts had RRMM, 29.5% on maintenance, and 12% was getting induction. Regarding MM response: >VGPR in 45% and PD in 18%. The 78 pts had ASCT prior to COVID-19 infection: only 3 pts < 1 year and 3 pts < 6 months. MM response or ASCT did not affect hospitalization or mortality.The case fatality rate (CFR) was 6%. In the univariate analysis, CKD, DM, HTN and hepatic dysfunction were associated with an increased risk of hospitalization. However, in multivariate analysis, only CKD, hepatic dysfunction, and Hypogammaglobulinemia significantly increased the risk of admission with only age and lymphopenia were associated with increased COVID-19 related fatatlity. Conclusions: With implementation of center-specific disease control measures and universal screening, pts might have lower case severity and fatality rate than was initially reported.
ABSTRACT
Background: Patients (pts) with malignancies are at increased risk of morbidity and mortality from COVID-19. Among these pts, some of the higher case fatality ratios (CFR) reported are among pts with myeloid malignancies, ranging from 37 to 50% (Mehta V, Cancer Discov 2020;Ferrara F, Leukemia 2020). Levine Cancer Institute (LCI) has a robust hematologic malignancy and cellular therapy program that serves many pts with myeloid malignancies, seeing nearly 100 new diagnoses of acute myeloid leukemia per year. A strategy to mitigate risks associated with COVID-19 was established at LCI in partnership with Atrium Health's (AH) Hospital at Home (HAH). HAH was a system wide platform using telemedicine and home health services to assess and monitor COVID-19 + pts at high risk of complications. To augment HAH for our medically complex cancer pts, a virtual health navigation process involving expertise from across LCI, including a specialized nurse navigation team, was developed to rapidly identify LCI pts + for SARS-CoV-2, monitor them under physician supervision, and escalate care as needed with AH HAH. Along with the navigation platform, data-driven guidelines for detecting, monitoring, and managing LCI pts + for SARS-CoV-2 were swiftly employed across the extensive LCI network. Herein we report on the outcomes for LCI pts with myeloid malignancies + for SARS-CoV-2 and outline the employed risk mitigation strategies and their potential impact on these outcomes. Methods: An automated daily list of LCI pts + for SARS-CoV-2 was provided by AH Information Services. Each pt's chart was reviewed by a nurse navigator for hematologic or oncologic diagnosis, outpatient or inpatient status, and COVID-19 symptoms. Pts without a cancer diagnosis were not assigned a navigator. If hospitalized, a pt was not assigned a navigator;following discharge, if enrolled in HAH, a navigator was assigned. In collaboration with HAH, an algorithm for directing care was utilized (Figure 1). A diagnosis-specific navigator contacted and screened the pt with an assessment tool, which scored pts for surveillance and treatment needs (Table 1). Documentation was forwarded to the primary hematologist/oncologist. Comprehensive guidelines for testing, scheduling, management of + pts, research, and process changes were created, disseminated, and actively updated through LCI's EAPathways. For outcome analysis for pts with myeloid malignancies, pt vital status was updated through data cutoff (7/3/21). Results: From inception on 3/20/20 to 12/2/20, 974 LCI patients were identified as SARS-CoV-2 + and reviewed for nurse navigation. Of the 974 pts, including pts with benign and malignant diagnoses, 488 were navigated. Among all SARS-CoV-2 + LCI pts, 145 (15%) had a hematologic malignancy, including 37 (4%) pts with myeloid malignancies. Characteristics are shown in Table 2. Of the 37 pts, 18 (49%) were navigated. 70% with myeloid malignancies were on active treatment at the time of + test. Nearly 50% of those on active treatment were navigated. 46% were hospitalized with COVID-19, with this being the main reason for no assigned navigator. 24% of hospitalized pts were eventually assigned a navigator. Only 3 pts had undergone allogeneic stem cell transplantation (allo-SCT) with a median time from transplant to detection of SARS-CoV-2 of 9 months (range, 7-23). 2 out of 3 cases post allo-SCT were asymptomatic. No pt died from COVID-19 following allo-SCT. Among the navigated pts with myeloid malignancies, there was no death related to COVID-19. 4 pts, all of whom were hospitalized, died from COVID-19 (N=2, myelodysplastic syndrome with 1 on azacitidine;N=2, myeloproliferative neoplasm, both on hydrea). A CFR of 11% was demonstrated for LCI pts with myeloid malignancies. Conclusions: A multidisciplinary response strategy liaising between AH HAH and LCI followed, assessed, and assisted cancer pts + for SARS-CoV-2. With our embedded nurse navigation team's specialized attention along with enhanced physician oversight and close collaboration with AH HAH, opportunities f r care escalation or adjustments in cancer-focused care were promptly identified. In this setting, among the high-risk population of pts with myeloid malignancies, a lower CFR than has been reported was observed. A virtual navigation platform with HAH capabilities is a feasible, safe, and effective way to monitor and care for this high-risk population. [Formula presented] Disclosures: Moyo: Seattle Genetics: Consultancy. Chai: Cardinal Health: Membership on an entity's Board of Directors or advisory committees. Avalos: JUNO: Membership on an entity's Board of Directors or advisory committees. Grunwald: Amgen: Consultancy;Agios: Consultancy;Astellas: Consultancy;Daiichi Sankyo: Consultancy;Stemline: Consultancy;Bristol Myers Squibb: Consultancy;PRIME: Other;Trovagene: Consultancy;Blueprint Medicines: Consultancy;AbbVie: Consultancy;Med Learning Group: Other;Pfizer: Consultancy;Sierra Oncology: Consultancy;Janssen: Research Funding;Incyte: Consultancy, Research Funding;Gilead: Consultancy;MDEdge: Other;PER: Other;Cardinal Health: Consultancy;Karius: Consultancy. Copelan: Amgen: Consultancy.
ABSTRACT
The world is getting advanced towards technology rapidly, therefore an updated and advanced traditional class room learning was required in this modern era of education which could provide easy and quality learning for students. A complete solution having all variety of applications was essentially needed through which students can attend lectures from their home as well in this pandemic era. A cost-effective solution was developed named as automated class lecture recording system, utilizing a low-cost minimal effort card, single sized board PC. The proposed research provides a platform through which students can attend and revise high quality lectures in their preferred time. The proposed research comprises of raspberry pi, operating system (noobs), pi-cam and framework. Videos were recorded and streamed using Pi cam. Raspberry pi was programmed in such a way that it is capable to process all data i.e., video frames and audio packets in an asynchronous way and at the end videos and audio are merged. After completion of lecture, recording the sound and video documents can be combined and sent to the referred/desired storage device from where instructor can upload it to location or on dedicated site from where students can access it. Thus, the proposed system, provided benefit to students if someone is absent or not attending lecture due to illness or some other reasons. The proposed research also provides the solution of increasing number of expenses for students as it can save travel expenses and accommodation costs. Although there are so many competitive solutions are available for the class lecture recording system but these systems cannot be acknowledged as cost-effective solution. Moreover, some free solutions are there but they don't provide high quality and merging mechanism with the video of the instructor and lecture as well. Therefore, the proposed research can be considered as the most cost effective and efficient solution for traditional class room teachings. Cost survey for lecture recording system was also completed to recognize the importance and significance of the proposed design which showed that the proposed solution providers cost in Pakistan. © 2021 IEEE.
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Background: SARS-CoV-2 virus has been shown to persist in respiratory tract in immunocompromised patients. However, such data are lacking for both asymptomatic and symptomatic SARS-CoV-2 infection in cancer patients. We share our single center experience on duration of SARS-CoV-2 viral presence in the upper respiratory tract of cancer patients with SARS-CoV-2 infection (asymptomatic and symptomatic) detected by viral PCR. Methods: This is retrospective review of cancer patients with documented SARS-CoV-2 infection and measurement of viral shedding at Levine Cancer Institute. Testing indications were COVID-19 symptomatic illness, pre-procedural and pre-chemo testing. Prolonged shedding was defined as presence of viral RNA beyond 30 days after first positive test. To document viral clearance, patients required 2 negative SARSCoV-2 PCR test separated by at least 24 hours and maximum 3 weeks apart either by nasopharyngeal or nasal PCR swab. Differences in distributions were identified between patients shedding virus more than 30 days and less than 30 days using uni- and multivariable logistic regression models. Statistical significance was set at p < 0.10 to enter the multivariable model, and p < 0.05 to remain. Results: Demographic data: median age 62 (range 20-93);58.5% females;70% White, 21% Black, and 7.4% Hispanics. Comorbidities included hypertension 43.2%, diabetes 16.7% and chronic lung disease 3.7%. Underlying malignancies were breast cancer 25%, hematologic cancer 22%, lung cancer 16% and genitourinary 11%. Chemotherapy was received by 26.5% patients within 4 weeks prior to testing. 162 patients were identified median duration of 18 days (range 4-90 days). Of these, 76% patients were tested for non-symptomatic indication with median duration of shedding 17 days (range 6-80) and 23% were tested for clinical symptoms with median duration of shedding 29 days (range 4-90) (p = < 0.001);50% of patients never developed symptoms, whereas 35% patients with non-symptomatic testing indication, subsequently developed symptoms. Viral clearance by day 30, day 45, day 60 and day 90 was 78%, 93%, 97% and 100% respectively. Univariate analysis did not show difference between patients with prolonged shedding vs those shedding less than 30 days for age, gender, race, ethnicity, underlying malignancy, co-morbidities including body mass index, diabetes, chronic lung conditions, hypertension, or receipt of cytotoxic chemo. Multivariable analysis showed that presence of symptoms at any point during SARS-CoV-2 infection (OR 5.9, 95% CI 2.4-14.5, p < 0.001) was associated with prolonged shedding. Conclusions: Symptomatic SARS-CoV-2 infection is associated with prolonged viral shedding in cancer patients. Cancer patients can have asymptomatic SARS-CoV-2 infection. More studies are warranted to understand viral kinetics and its clinical implications in cancer patients.
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Background: Cancer patients are more susceptible to developing severe disease associated with SARS-CoV-2 infection. Herein, data from a high-volume cancer center is presented highlighting risk factors associated with hospitalization with COVID-19 disease. Methods: Cancer patients in the Levine Cancer Institute COVID19 database who were tested for SARS-CoV-2 due to clinical illness from March 1, 2020 to October 29, 2020 with 90 days follow-up are described here. Patients' demographic and clinical information were retrospectively entered into a REDCap database from chart reviews. Differences in distributions were identified between hospitalized and nonhospitalized patients using the chi-squared test with uni- and multivariable logistic regression models. Statistical significance was set at p<0.05. Results: 228 patients with SARS-CoV-2 infection were identified, of whom 103 (45%) were hospitalized. Median age was 63 years (range 28-95). Race distribution for infection showed White 65%, followed by Black 26.8% and Hispanic ethnicity 16.7% , with a similar distribution for hospital admission. Median length of stay was 10 days (range 1-91) with no readmissions within 90 days. The most common underlying malignancies were breast (29.8%), hematologic (21.1%) and genitourinary (12.3%). The most common preexisting conditions included hypertension (55.7%), diabetes (27.2%) and cardiac disease (3.9%). The most common presenting symptoms were cough (50.2%), fever (38.4%), fatigue (37.8%) and shortness of breath (36.4%). Maximum oxygen requirements for hospitalized patients were ambient air (34%), nasal canula (34%), high/medium flow nasal canula (10%), non-invasive ventilation (13%) and mechanical ventilation (10%). Case fatality rate was 10% with diagnosis of COVID-19, including 21.4% of those admitted to the hospital and 51.7% of those admitted to the ICU. Univariable logistic regression analysis showed that age, sex, prior chemotherapy, upper gastrointestinal cancers, hematologic cancers, number of medical conditions, cardiac disease, chronic lung diseases, hypertension, and diabetes increased risk of hospitalization. Table shows results of multivariate analysis. Conclusions: The COVID-19 pandemic has caused high case fatality rates in our cancer patients. We identified age, cardiac disease, hematologic malignancy and receipt of chemotherapy within 4 weeks of diagnosis as risk factors for hospitalization. These data may help in prioritizing early intervention in vulnerable subgroups to improve survival outcomes.
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Background: Reports suggested cancer patients were at greater risk for increased morbidity and mortality from COVID-19. A process to mitigate these risks was established at Levine Cancer Institute (LCI) in partnership with Atrium Health's (AH) Hospital at Home (HAH) initiative. This virtual health navigation process employed expertise from the departments of Hematologic Oncology and Blood Disorders, Oncology, and Supportive Oncology, including a specialized nurse navigation team, to rapidly identify COVID-19 positive LCI patients, monitor them under physician supervision, and escalate care as needed with AH HAH program. Methods: AH Information Services created an automated list of LCI COVID-19 positive patients with a daily database. Each patient was reviewed by a nurse navigator. Review included hematologic or oncologic diagnosis, outpatient or inpatient status, and any COVID-19 symptoms. Once a malignant diagnosis was confirmed, a diagnosis-specific navigator contacted and screened the patient with a COVID assessment tool. Documentation was forwarded to the primary oncologist/hematologist. The tool scored patients for surveillance and treatment needs. A score of 0-2 prompted phone assessment every 48-72 hours, and score of 3-5 required every 24-48 hour calls with physician involvement when appropriate. If score of ≥6, care was escalated to LCI nurse/physician for admission to AH acute care HAH or conventional inpatient admission. Results: From inception on 3/20/2020 to data review date of 12/2/2020, 974 LCI patients were identified as COVID-19 positive and reviewed for nurse navigation (Table). Of the 974, 488 were navigated. Given limited resources, patients with benign conditions were not assigned a navigator, though a similar process was created for sickle cell disease. Of the 974, 75 are now deceased. Only 25 are deceased among the 488 navigated. Conclusions: The COVID-19 pandemic presented unprecedented circumstances to our patients and their clinicians. LCI expeditiously put policies and procedures in place to mitigate the intersection of COVID-19 and cancer. The multidisciplinary response strategy liaising between AH HAH and LCI followed, assessed, and assisted LCI COVID19 positive patients. With our embedded nurse navigation team's specialized attention along with enhanced physician oversight and close collaboration with AH HAH, opportunities for care escalation or adjustments in cancerfocused care were promptly identified. Analysis is ongoing to elucidate the lower mortality rate observed among navigated patients.
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Background: Background:: Immune modulation in patients with clinical features suggestive of a cytokine release syndrome (CRS) has become a pharmacologic target for potential treatment of COVID- 19 and prevention of ARDS. Tocilizumab is an IL-6 receptor blocker FDA-approved for chimeric antigen receptor (CAR) T cell-induced severe or life-threatening CRS. The objective of this study was to describe clinical outcomes associated with tocilizumab compared with those not receiving tocilizumab in critically ill patients with severe COVID-19. Methods: Methods: Retrospective case series of 49 adult patients admitted to an intensive care unit with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Patients receiving tocilizumab were compared with those not receiving tocilizumab. The primary outcome was clinical improvement (decrease in supplemental oxygen requirement, discharge from ICU, or live discharge from hospital). Secondary endpoints included mortality and frequency of extubation. All comparative endpoints were assessed at 2 weeks after ICU admission. Results: Results: 49 patients were identified with SARS-CoV-2 who were admitted to an ICU, 16 received tocilizumab. Baseline characteristics were similar;most were African American males with comorbidities such as obesity, cardiovascular disease, and diabetes. The time from symptom onset to positive test and subsequent intubation were similar (4 and 7 days, respectively). 75% received one dose (all received 8 mg/kg). The median time from symptom onset to tocilizumab administration was 11 days. In patients receiving tocilizumab compared with those not receiving tocilizumab, there were similar rates of clinical improvement (44% versus 61%, p=0.27), extubation (31% versus 45%, p=0.60), and mortality (18% versus 19%, p >0.99, respectively). 81% of the tocilizumab group had resolution of fever and 75% had improvement in C-reactive protein levels. Conclusion: Conclusion: In this study of patients with progressed disease, outcomes were similar regardless of receipt of tocilizumab. Randomized controlled trials are needed to assess the impact of earlier administration and identify clinical characteristics to assist with selection of appropriate patients who may benefit from tocilizumab.