Positive COVID-19 Test Research Articles

CA-125 monitoring in gynecologic cancer patients with COVID-19: A case series (413)

Objectives: CA-125 has long been utilized as a marker for gynecologic malignancies but can be elevated in many other inflammatory conditions, including lung disease. A retrospective study of tumor markers in non-cancer patients saw a rise in CA-125 values during severe COVID-19 infections. Similarly, a case report published on June 17, 2020, described a significant rise in CA-125 values during an ovarian cancer patient’s COVID-19 infection without evidence of disease progression. Given the potential confounding effect this could have on surveillance and treatment planning, we sought to describe the impact of COVID-19 infections on CA-125 trends in a gynecologic oncology patient population.Methods: We conducted a retrospective chart review of patients treated at a UPMC hospital during the COVID-19 pandemic from March 2020 through July 2021. Patients were included for analysis if they had a confirmed gynecologic malignancy, a COVID-19 infection, and had more than one CA-125 value drawn. The CA-125 values were plotted against the timeline of their COVID-19 infections to assess for trends in CA-125 values during and after infection.Results: There were 78 individuals identified with a COVID-19 infection and a CA-125 drawn following their positive COVID-19 test. Of these 78 patients, 18 had both gynecologic malignancy and more than one CA-125 drawn. Of these 18 patients, only one had an appreciable rise in their CA-125 values at the time of their COVID-19 diagnosis that resolved following their infection and could not be attributed to disease progression. Four patients were diagnosed with cancer at the time of COVID-19 diagnosis and had elevated CA-125 values. One patient passed before receiving treatment, and the other three had CA-125 values that trended down as they received treatment for their cancer. Two patients were noted to have a mild rise in their CA-125 at the time of their COVID-19 infection that continued to rise as they were diagnosed with the progression of their cancer. Most of the 18 patients (n=11, 61.1%) did not show an increase in CA-125 coinciding with their COVID-19 infection. They had either stable or decreasing CA-125 at the time of and following their COVID-19 diagnosis.Conclusions: This case series illustrates that while CA-125 values may increase during acute COVID-19 infection, cancer remains the most likely cause of a CA-125 increase. Clinical suspicion should remain high for a possible change in cancer status.

An Evaluation of the Impact of COVID-19 on Cardiovascular Surgery

Introduction: We aimed to describe the impact of COVID-19 among the patients who had cardiac surgery, with particular emphasis on pulmonary complications and 30-day mortality. Patients and Methods: From March 2020 to June 2021, a total of 2267 patients underwent cardiovascular surgery at Koşuyolu High Specialization Training and Research Hospital.. Patients who tested SARSCoV-2-positive by PCR perioperatively (seven days before or 30 days after surgery), despite testing negative at admission, were included. The primary endpoint of the study was 30-day mortality following surgery. The secondary endpoint was the development of pulmonary complications including acute respiratory distress syndrome (ARDS) or respiratory failure, which were defined according to the Berlin definition, and the need for mechanical ventilation for >48 h after the operation or the need for re-intubation after extubation. Results: Eleven patients out of 2267 (0.48%) had a positive PCR test for COVID-19. In the postoperative period, seven patients were diagnosed with COVID-19 in the clinical wards, of whom three patients were readmitted to the ICU. Nine patients had radiological pulmonary involvement. Five patients (45.5%) developed ARDS within four to seven days after a positive PCR test. Eight patients (72.7%) developed respiratory failure and required re-intubation, of whom two could not be extubated. Five patients (45.5%) died within 30 days, and seven (63.6) died during their hospital stay. Conclusion: COVID-19 has a severe negative impact on the postoperative course of cardiac surgery patients in terms of cardiovascular outcomes, pulmonary complications, and mortality. Given the dramatic impact of COVID-19 infection on postoperative outcomes, it appears that deferring cardiovascular surgeries may be more suitable if COVID-19 positivity is detected.

Race may modify the association between blood type and COVID-19 infection.

This study aims to investigate the race/ethnicity‐specific association between blood type and COVID‐19 susceptibility during March, 2020 and December, 2021 using data from the electronic health record at the University of Chicago Medicine. The study population was stratified into four groups: non‐Hispanic White, non‐Hispanic Black, Hispanic, and other. Log‐binomial generalized mixed model was used to estimate the relative risk (RR) and 95% confidence interval (CI). When compared to blood type O, type B was associated with positive COVID‐19 test in Blacks (RR = 1.12, 95% CI: 1.02–1.23), Whites (RR = 1.28, 95% CI: 0.99–1.66), and Hispanic (RR = 1.36, 95% CI: 0.97–1.92).

COVID-19 School vs. Community-Based Outbreak Trends among New Jersey K-12 Schools during the 2020-2021 School Year.

Identifying potential rapid methods to track COVID-19 trends within schools has become a necessity in understanding how to provide both education and maintain health and safety during a pandemic. This study examined COVID-19 trends and sociodemographic information in New Jersey (NJ) schools during the 2020–2021 school year. A database was compiled for this study in Microsoft Excel using various state and federal resources. Data used in the study are a combination of extracted data from weekly NJ Spotlight reports, weekly NJ COVID-19 Activity Level Index (NJ CALI) reports, and reports of school-based outbreaks via the NJ Department of Health (NJDOH). In 2020–2021, in NJ K–12 schools, the NJDOH defined a school-based outbreak incidence as two or more students and/or adult staff with a laboratory-confirmed positive molecular test for COVID-19 based on transmission occurring on campus. Data were organized into six regions across 21 counties within NJ (3–4 counties per region per NJDOH). COVID-19 trends in NJ schools mirrored trends in their districts, i.e., communities, within the state’s region; noticeably, there were consistently high trends during the winter holiday season (November 2020–January 2021). The cumulative number of incidences of school-based outbreaks remained relatively low but, nevertheless, increased throughout the 2020–2021 school year. This study recommends increased accessibility to COVID-19 reports for school and public health officials, and in the future for data to be reported to identify rates of transmission of other communicable diseases within K–12 students, and to further reinforce established mandates and other preventative measures in public while traveling during holiday seasons.

User perceptions about sharing exposure notification information for communicable diseases.

BackgroundThe (GuideSafe™) Exposure Notification System (ENS) was built and deployed in (Alabama) for anonymous sending and receiving of COVID-19 exposure alerts to people who have been in close contact with someone who later reports a positive COVID-19 test. Little is known about how the demographic groups perceive recent privacy-preserving the ENS innovations, including their usability, usefulness, satisfaction, and continued interest in sharing COVID-19 exposure information. The purpose of this study was to investigate how users across the demographic groups perceive the sharing of exposure information with various types of organizations and to investigate how end-user perceptions of the ENS usability, usefulness, and satisfaction differ across the demographic groups within the context of a statewide deployment of an exposure notification system.MethodsA survey was administered to (state residents blinded for review) (N = 1,049) to assess propensity to share COVID-19 infection data and evaluate end-user perceptions about usability, usefulness, and satisfaction with the (Alabama) ENS. The ANOVA and the Tukey's Honestly Significant Difference (HSD) post-hoc tests were conducted to assess the demographic group differences.ResultsThe ENS survey participants had a high awareness of contact tracing, exposure notifications, and the (GuideSafe™) ENS and reported having downloaded the app. Survey results revealed the majority of participants rated the app as useful (n = 490, 79%), easy to use (n = 490, 79%), and reported satisfaction with its use (n = 546, 88%). Other results suggest that ethnicity and age may be important factors for trust in sharing exposure information.ConclusionThe (GuideSafe™) system was one integrated component of comprehensive education and work re-entry strategy across (Alabama) that reached a broad user base. Users across the different demographic groups perceive the sharing of information about their communicable disease exposures differently. Furthermore, demographic factors play a role in which types of organizations individuals are willing to share their communicable disease exposure information. Public health institutions, employers, schools, healthcare providers, and technology designers may want to consider these findings as they construct technologies and perform outreach campaigns aimed at reducing infection rates with the ENS and related technologies.

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada.

Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global Moran's I spatial autocorrelation, and Local Moran's I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results: This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities). Conclusions: Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing.

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada

Introduction: This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. Methods: COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections. Daily cases were aggregated according to designated forward sortation area (FSA), and postal codes (PC) in municipal regions Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, and Windsor/Essex county. Hotspots were identified with area-to-area tests including Getis-Ord Gi*, Global Moran’s I spatial autocorrelation, and Local Moran’s I asymmetric clustering and outlier analyses. Case counts were also interpolated across geographic regions by Empirical Bayesian Kriging, which localizes high concentrations of COVID-19 positive tests, independent of FSA or PC boundaries. The Geostatistical Disease Epidemiology Toolbox, which is freely-available software, automates the identification of these regions and produces digital maps for public health professionals to assist in pandemic management of contact tracing and distribution of other resources. Results: This study provided indicators in real-time of likely, community-level disease transmission through innovative geospatial analyses of COVID-19 incidence data. Municipal and provincial results were validated by comparisons with known outbreaks at long-term care and other high density residences and on farms. PC-level analyses revealed hotspots at higher geospatial resolution than public reports of FSAs, and often sooner. Results of different tests and kriging were compared to determine consistency among hotspot assignments. Concurrent or consecutive hotspots in close proximity suggested potential community transmission of COVID-19 from cluster and outlier analysis of neighboring PCs and by kriging. Results were also stratified by population based-categories (sex, age, and presence/absence of comorbidities). Conclusions: Earlier recognition of hotspots could reduce public health burdens of COVID-19 and expedite contact tracing.

Racial/Ethnic, Biomedical, and Sociodemographic Risk Factors for COVID-19 Positivity and Hospitalization in the San Francisco Bay Area.

The COVID-19 pandemic has uncovered clinically meaningful racial/ethnic disparities in COVID-19-related health outcomes. Current understanding of the basis for such an observation remains incomplete, with both biomedical and social/contextual variables proposed as potential factors. Using a logistic regression model, we examined the relative contributions of race/ethnicity, biomedical, and socioeconomic factors to COVID-19 test positivity and hospitalization rates in a large academic health care system in the San Francisco Bay Area prior to the advent of vaccination and other pharmaceutical interventions for COVID-19. Whereas socioeconomic factors, particularly those contributing to increased social vulnerability, were associated with test positivity for COVID-19, biomedical factors and disease co-morbidities were the major factors associated with increased risk of COVID-19 hospitalization. Hispanic individuals had a higher rate of COVID-19 positivity, while Asian persons had higher rates of COVID-19 hospitalization. The excess hospitalization risk attributed to Asian race was not explained by differences in the examined biomedical or sociodemographic variables. Diabetes was an important risk factor for COVID-19 hospitalization, particularly among Asian patients, for whom diabetes tended to be more frequently undiagnosed and higher in severity. We observed that biomedical, racial/ethnic, and socioeconomic factors all contributed in varying but distinct ways to COVID-19 test positivity and hospitalization rates in a large, multi-racial, socioeconomically diverse metropolitan area of the United States. The impact of a number of these factors differed according to race/ethnicity. Improving overall COVID-19 health outcomes and addressing racial and ethnic disparities in COVID-19 outcomes will likely require a comprehensive approach that incorporates strategies that target both individual-specific and group contextual factors.

Anxiety and insecurity in medical interns: the impact of the pandemic COVID-19

Purpose: We aimed to assess anxiety among medical interns and to identify changes regarding their perspective about the profession during the pandemic period in Brazil, between November 2020 and February 2021. Methods: This is a cross-sectional descriptive study which medical interns answered an online survey questionnaire. The assessment was performed using the validated questionnaire General Anxiety Disorder Scale (GAD-7).Results: 162 responses were collected, mean age of 24.9 years, majority female (66.7%); 83.3% had the option of returning to practical assistance. Among these, 35% claimed to have had contact with suspects COVID-19 patients and 13% had a positive test for COVID-19. GAD-7 scores showed that 33.4% were qualified as “Normal”, while mild (37%), moderate (22.8%) or severe symptoms of anxiety (6.8%). A GAD-7 score positive for TAG was found in 29.6% of them. Anxiety was significantly associated (p=0.013) with questioning the choice of Medicine as a profession. Conclusions: We found a high frequency of interns with symptoms of anxiety, higher compared to similar studies prior to the pandemic. In addition, medical interns with anxiety were the ones who most questioned the choice of profession.

Initiation of antihypertensive drugs to patients with confirmed COVID-19-A population-based cohort study in Sweden.

PurposeHypertension is an important risk factor for severe outcomes in patients with COVID‐19, and antihypertensive drugs may have a protective effect. However, the pandemic may have negatively impacted health care services for chronic diseases. The aim of this study was to assess initiations of antihypertensive medicines in patients infected by COVID‐19.MethodsA cohort study including all Swedish residents 20–80 years old with a COVID‐19 positive test compared with an unexposed group without COVID‐19 matched for age, sex, and index date (date of confirmed COVID‐19). Data were collected within SCIFI‐PEARL, a study including linked data on COVID tests, hospital diagnoses, dispensed prescriptions, and socioeconomic data from Swedish national registers. Initiations of different antihypertensive drugs were studied from March 2020 until October 2020. Associations between COVID‐19 and initiation of antihypertensives were assessed by a multivariable Cox proportional hazards model.ResultsA total of 224 582 patients (exposed and unexposed) were included. After adjusting for cardiovascular comorbidities and education level, ACEi was the most commonly initiated antihypertensive agent to patients with COVID‐19. Hazard ratio and 95% confidence interval for initiation of drug therapy was 1.83 [1.53–2.19] for ACEi, followed by beta‐blockers 1.74 [1.55–1.95], calcium channel blockers 1.61 [1.41–1.83], angiotensin receptor blockers 1.61 [1.40–1.86], and diuretics 1.53 [1.32–1.77].ConclusionAll antihypertensive medicines were initiated more frequently in COVID‐19 patients. This can either be associated with hypertension caused by the COVID‐19 infection, more frequent diagnosis of hypertension among people with COVID‐19 since they consult health care, or residual confounding factors not adjusted for in the study.

Associations of air pollution with COVID-19 positivity, hospitalisations, and mortality: Observational evidence from UK Biobank

Individual-level studies with adjustment for important COVID-19 risk factors suggest positive associations of long-term air pollution exposure (particulate matter and nitrogen dioxide) with COVID-19 infection, hospitalisations and mortality. The evidence, however, remains limited and mechanisms unclear. We aimed to investigate these associations within UK Biobank, and to examine the role of underlying chronic disease as a potential mechanism. UK Biobank COVID-19 positive laboratory test results were ascertained via Public Health England and general practitioner record linkage, COVID-19 hospitalisations via Hospital Episode Statistics, and COVID-19 mortality via Office for National Statistics mortality records from March–December 2020. We used annual average outdoor air pollution modelled at 2010 residential addresses of UK Biobank participants who resided in England (n = 424,721). We obtained important COVID-19 risk factors from baseline UK Biobank questionnaire responses (2006–2010) and general practitioner record linkage. We used logistic regression models to assess associations of air pollution with COVID-19 outcomes, adjusted for relevant confounders, and conducted sensitivity analyses. We found positive associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with COVID-19 positive test result after adjustment for confounders and COVID-19 risk factors, with odds ratios of 1.05 (95% confidence intervals (CI) = 1.02, 1.08), and 1.05 (95% CI = 1.01, 1.08), respectively. PM 2.5 and NO 2 were positively associated with COVID-19 hospitalisations and deaths in minimally adjusted models, but not in fully adjusted models. No associations for PM10 were found. In analyses with additional adjustment for pre-existing chronic disease, effect estimates were not substantially attenuated, indicating that underlying chronic disease may not fully explain associations. We found some evidence that long-term exposure to PM2.5 and NO2 was associated with a COVID-19 positive test result in UK Biobank, though not with COVID-19 hospitalisations or deaths.

Identification of risk factors that increase household transmission of COVID-19 in Afyonkarahisar, Turkey.

COVID-19 is the greatest pandemic of the 21st century. This cross-sectional study determined the factors that cause COVID-19 transmission in the household, increase in susceptibility of contacts, and increase in contagiousness of the primary case, and developed predictive calculations for determining secondary attack rate in the household. A total of 701 households with positive COVID-19 test cases, and 1813 adults living in these households, were studied from August 24-31, 2020 in Afyonkarahisar, Turkey. All the participants were interviewed by phone. The participants were divided into two groups: positives included those with positive Polymerase Chain Reaction (PCR) tests, negatives included those with a negative test and those who were without a PCR test. Descriptive statistics, Chi-square test, and multivariate logistic regression analysis were performed. The secondary attack rate was 31.5%. Being male, having an education level > 8 years, living in the city, low number of people living in the household, having a severe illness, non-compliance with isolation requirement, and nonadherence to wearing masks increased contagiousness. The factors that increased the sensitivity of the household were determined as being female, having an education level of over 8 years, and being obese. The secondary attack rate (SAR) was higher in Turkey than in other countries and there was limited compliance with quarantine and isolation measures. Household transmission can be reduced by interventions such as masks, isolation, and quarantine. The transmission of COVID-19 in households can be reduced if preventive measures are taken in the early stages of infection.

O-019 Covid 19 and male infertility-how long should fertility treatment be deferred to overcome the postcovid changes in semen parameters and to restore male fertility?

Study questionMale recovered from covid19 showed negative impact on sperm quality- are these changes reversible and are antioxidant therapy beneficial to overcome sperm quality changes?Summary answerOxidative stress created by the proinflammatory cytokine storm by covid19 virion might interect with spermatozoa to cause changes in spermiogram and antioxidant is the treatmentWhat is known alreadyCovid19 virion might interect with human spermatozoa and disrupt male fertility. Suppression of semen volume, progressive motility, morphology, sperm number and DNA integrity as a result of covid19 infection were correlated with markers of oxidative stress and inflammation. Sperm DNA damage is the key feature of the disease but the effect on semen quality seem to subside with the passage of time although further studies are needed to substantiate this point. My study is to determine whether the proposed antioxidant treatment to restore the negative impact of covid19 on sperm vitality is beneficial or not.Study design, size, durationThe study included 20 male aged 20-45yrs among those couples who were undergoing infertility treatment at Shristi Healthcare between April/2020 to October/2020 with a positive covid19 test and has recovered from the disease atleast 3-5months earlier and who had undergone spermiogram test before the onset of the disease. Semen samples were taken3-5months after recovery from covid19 and after 3 months treatment with antioxidant(CoenzQ10/300mg).Participants/materials, setting, methodsInclusion criteria: precovid normal spermiogram, with mild to moderate covid symptoms without hospitalisation. Exclusion criteria: those with precovid oligospermia or azooospermia, h/o steroid therapy for covid, h/o hormonal drug use that could affect spermiogenesis, with severe covid symptoms requiring ICU treatment. Time between last negative nasal swab test to semen analysis was 120-150days. Antioxidant(CoenzQ10/300mg)given as once daily dose for 3months after recovery from covid and semen test reviewed after treatment and compared with precovid data.Main results and the role of chanceThe mean age of participants were 30.4±4.8yrs and smoking status, BMI, medical history, presence of varicocele were recorded. Semen samples were processed according to WHO guidelines(2010, 5th edition). Statistical analysis was done by paired t test for paired samples and p value <0.05 was considered statistically significant. When semen samples before and after covid19 were evaluated, it showed marked decline in sperm volume/ml(precovid 3(2.5-3.5) to postcovid 1.5(1-2), p < 0.005); total sperm count x10^6per ejaculate(precovid 42(25-65) to postcovid 5(1-10), p < 0.005); progressive motility% (precovid 55.1±21.7 to postcovid 15.1±5.7, p < 0.001); sperm morphology%(precovid 45(30-60)to postcovid10(5-25), p < 0.001).After 3months CoenzQ10/300mg treatment semen showed significant improvement in all 3 parameters eg sperm count (3.15±3.38-20.9±2.11, p < 0.001), sperm motility(5.25±3.25- 42.85±3.30, p < 0.001) sperm morphology(7.81±2.26- 25.89±7.05, p < 0.001). All previous studies about postcovid semen changes used normal male as reference but strength of my study was precovid semen profile of same participant was available as a reference point. It was seen that fertility of male restores between3-6months postcovid with antioxidant treatment and can resume planning pregnancy.Limitations, reasons for cautionSmall sample size, interpatient variation in the severity of covid19, inadequate study design and retrospective nature. All patient examined had mild to moderate symptoms and none suffered from severe covid19 symptoms or needed ICU treatment so no data available to comment on severe postcovid19 case semen changes.Wider implications of the findingsMany couples initially deferred fertility care due to concern about covid19 disease. Globally many fertility centre has resumed delivering care. Men and their partners must be appropriately counselled regarding what is known and remains unknown about covid19 and male reproductive health.Trial registration numbernot applicable

Diagnosis and Prognosis of COVID-19 Disease Using Routine Blood Values and LogNNet Neural Network.

Since February 2020, the world has been engaged in an intense struggle with the COVID-19 disease, and health systems have come under tragic pressure as the disease turned into a pandemic. The aim of this study is to obtain the most effective routine blood values (RBV) in the diagnosis and prognosis of COVID-19 using a backward feature elimination algorithm for the LogNNet reservoir neural network. The first dataset in the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 tests. The LogNNet-model achieved the accuracy rate of 99.5% in the diagnosis of the disease with 46 features and the accuracy of 99.17% with only mean corpuscular hemoglobin concentration, mean corpuscular hemoglobin, and activated partial prothrombin time. The second dataset consists of a total of 3899 patients with a diagnosis of COVID-19 who were treated in hospital, of which 203 were severe patients and 3696 were mild patients. The model reached the accuracy rate of 94.4% in determining the prognosis of the disease with 48 features and the accuracy of 82.7% with only erythrocyte sedimentation rate, neutrophil count, and C reactive protein features. Our method will reduce the negative pressures on the health sector and help doctors to understand the pathogenesis of COVID-19 using the key features. The method is promising to create mobile health monitoring systems in the Internet of Things.

Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction

IntroductionIncluding race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic disease severity (assessed using cardiometabolic disease staging) and COVID-19 hospitalization.MethodsElectronic medical record data on patients with a positive COVID-19 polymerase chain reaction test in 2020 and a previous encounter in the electronic medical record where cardiometabolic disease staging clinical data (BMI, blood glucose, blood pressure, high-density lipoprotein cholesterol, and triglycerides) were available from 2017 to 2020, were analyzed in 2021. Associations between cardiometabolic disease staging and COVID-19 hospitalization adding race and SDoH (individual and neighborhood level [e.g., Social Vulnerability Index]) in different models were examined. Area under the curve was used to assess predictive performance.ResultsA total of 2,745 patients were included (mean age of 58 years, 59% female, 47% Black). In the cardiometabolic disease staging model, area under the curve was 0.767 vs 0.777 when race was included. Adding SDoH to the cardiometabolic model improved the area under the curve to 0.809 (p<0.001), whereas the addition of SDoH and race increased the area under the curve to 0.811. In race-stratified models, the area under the curve for non-Hispanic Blacks was 0.781, whereas the model for non-Hispanic Whites performed better with an area under the curve of 0.821.ConclusionsCardiometabolic disease staging was predictive of hospitalization after a positive COVID-19 test. Adding race did not markedly increase the predictive ability; however, adding SDoH to the model improved the area under the curve to ≥0.80. Future research should include SDoH with biological variables in prediction modeling to capture social experience of race.

Increased Risk of Postoperative Mortality Associated With Prior COVID-19 Infection

IntroductionThe impact of COVID-19 infection on surgical patients is largely described by small-cohort studies. This study characterized the risk factors for postoperative mortality among patients with preoperative COVID-19 infection.MethodsData were abstracted from the electronic medical record for patients who tested positive for COVID-19 before surgery, excluding procedures related to extracorporeal membrane oxygenation (case, March 2020–April 2021). Mortality was compared with that for patients from the American College of Surgeons National Surgical Quality Improvement Program database (control, January 2018‒February 2020) with chi-square, t test, and multivariable regression.ResultsThere were 5,209 patients in the control cohort. Among 1,072 patients with positive COVID-19 testing before surgery, 589 had surgeries with specialties tracked by the American College of Surgeons National Surgical Quality Improvement Program (General Surgery, Gynecology, Neurosurgery, Orthopedics, Thoracic, Vascular). Patients with previous COVID-19 infection were younger (age 48 vs 59 years, p<0.001), were more likely to be Black (42% vs 28%, p<0.001), and underwent fewer elective surgeries (55% vs 83%, p<0.001). Postoperative mortality was greater among the case cohort (4.4% vs 1%, p<0.001). On multivariable logistic regression, postoperative mortality increased with age (OR=1.02), emergent surgeries (OR=2.6), and previous COVID-19 infection (OR=3.8). Among patients with previous COVID-19 infection, postoperative mortality was associated with male sex (OR=2.7), higher American Society of Anesthesiologists Physical Status Classification Score (OR=4.8), and smoking history (OR=3.7).ConclusionsAlthough data abstraction was limited by the electronic medical record, postoperative mortality is nearly 6 times higher for patients infected with COVID-19 within 2 weeks before surgery when adjusting for patient- and procedure-level factors. Among those with previous COVID-19 infection, postoperative mortality is associated with male sex, American Society of Anesthesiologists Physical Status Classification Score, and smoking history.

Abstract 5273: The peripheral proinflammatory responses in COVID-19: Clinical spectrum and outcome in patients with and without cancer

Abstract Background: A meta-analysis of COVID-19 shows that the pooled prevalence of cancer is 1.4%. Febrile illness during COVID-19 is caused by cytokine release syndrome energized by innate inflammatory immune cells, neutrophils, monocytes, and macrophages. Cancer has a worse clinical outcome with COVID-19 due to a potential contribution of the disordered inflammatory microenvironment and immune system. This study aimed to determine the impact of peripheral inflammatory responses on clinical outcome and severity of COVID-19 patients with and without cancer and compare their clinical spectra. Methodology: This IRB-approved, retrospective chart review performed at PNOC included patients 18 years or older with PCR-confirmed COVID-19 from April 2020 to April 2021. Histopathology-confirmed cases identified excluded cranial metastases, pregnancy, or ICU-ineligible due to advanced malignancy or missing data. We collected the first clinical encounter data following a positive COVID-19 test, including CDC-defined COVID-19 symptoms, co-morbidities, cancer status, and treatment—clinical outcomes and death from any cause within30 days of COVID-19 diagnosis. We determined peripheral blood inflammatory cells of neutrophils, lymphocytes, monocytes, platelets and the ratios between lymphocytes and the other three. According to INH guidelines, we ranked clinical severity as presymptomatic, mild, moderate, severe, or critical. Results: Of 3745 people with PCR-confirmed COVID-19, 65 (1.7%) had cancer. We randomly selected 130 non-cancer subjects, homogeneously distributed across each month. The median age was 59 years. Of all, 52.3% were women, 43% were diabetic, 45% were hypertensive, and 35% had the cardiopulmonary disease. Dyspnea occurs in 30.8% of those with cancer but in 59.2% of those without cancer (P &amp;lt; .001). High neutrophil was significantly associated with severity (P = .038), but there was no significant difference between cancer and non-cancer groups. High lymphocytes, MPV, and Neutrophil/Lymphocyte ratio were associated with symptoms but not outcome or severity. Death from any cause was more in the group with cancer 23.1% vs. 6.9%, P= .001. Only 2% of study participants with cancer continued chemotherapy after the diagnosis of COVID-19 was confirmed. Conclusion: Mortality significantly remains higher when cancer is comorbid with COVID-19, as seen in international groups. Further studies are needed to confirm whether cancer immunomodulation is a factor. Peripheral inflammatory response modestly predicts a worse outcome, particularly with elevated neutrophils, known for its proinflammatory rule by polarization and neutrophil extracellular trap (NET) formation with platelet activation. There was a modest increase in symptoms severity in non-cancer COVID19 but more mortality in cancer comorbid COVID-19 Citation Format: Amer N. Radwi, Zahra H. Alshardi, Rakan H. Alelyani, Raha M. Garout, Lojain N. Alruwaili, Muhammad T. Bakhsh. The peripheral proinflammatory responses in COVID-19: Clinical spectrum and outcome in patients with and without cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5273.

Predictive factors for severe COVID-19 infection in Terengganu state of Malaysia

Background: COVID-19 has a varied clinical presentation and may progress to severe form which could be fatal. Determination of risk factors for severe infection would be beneficial in averting COVID-19 mortality in Terengganu setting.Materials and Methods: A casecontrol study between mild and severe COVID-19 groups was conducted in Terengganu state from 1st March 2020 until 31st January 2021 based on retrospective record review. Individuals with laboratory RT-PCR confirmed positive test for COVID-19 were included as study samples. Descriptive statistics, simple and multiple logistic regression analyses were employed for statistical analysis.Results: There were 2142 COVID-19 cases in Terengganu during the studied period. The proportion of severe COVID-19 infection was 2.1% (95%CI: 0.01, 0.03). Among the severe COVID-19 cases, their mean (±SD) age was 52 (±16) and majority of them were male (59.1%) and had comorbidity (56.8%). The common symptoms among severe COVID-19 cases included fever (68.2%), cough (63.6%), coryza (22.7%), sore throat (13.6%) and anosmia (11.4%). Multiple logistic regression revealed older age, presence of comorbidity, having symptoms of fever, cough and anosmia as the significant associated factors for severe COVID-19 with adjusted odds ratio (AOR) of 1.07 (95%CI: 1.03, 1.11), p&lt;0.001; AOR 5.97 (95%CI: 2.09, 17.01), p=0.001; AOR 4.78 (95%CI: 1.63, 14.05), p=0.004; AOR 4.81 (95%CI: 1.70, 13.60), p=0.003; and AOR 8.39 (95%CI: 1.39, 50.33), p=0.020,respectively.Conclusion: Knowing the predictive factors for severe COVID-19 would facilitate clinicians in timely identification of high-risk cases for delivering prompt treatment and intervention.International Journal of Human and Health Sciences Vol. 06 No. 03 July’22 Page: 269-274

COVID-19 Surveillance in the Biobank at the Colorado Center for Personalized Medicine: Observational Study.

BackgroundCharacterizing the experience and impact of the COVID-19 pandemic among various populations remains challenging due to the limitations inherent in common data sources, such as electronic health records (EHRs) or cross-sectional surveys.ObjectiveThis study aims to describe testing behaviors, symptoms, impact, vaccination status, and case ascertainment during the COVID-19 pandemic using integrated data sources.MethodsIn summer 2020 and 2021, we surveyed participants enrolled in the Biobank at the Colorado Center for Personalized Medicine (CCPM; N=180,599) about their experience with COVID-19. The prevalence of testing, symptoms, and impacts of COVID-19 on employment, family life, and physical and mental health were calculated overall and by demographic categories. Survey respondents who reported receiving a positive COVID-19 test result were considered a “confirmed case” of COVID-19. Using EHRs, we compared COVID-19 case ascertainment and characteristics in EHRs versus the survey. Positive cases were identified in EHRs using the International Statistical Classification of Diseases, 10th revision (ICD-10) diagnosis codes, health care encounter types, and encounter primary diagnoses.ResultsOf the 25,063 (13.9%) survey respondents, 10,661 (42.5%) had been tested for COVID-19, and of those, 1366 (12.8%) tested positive. Nearly half of those tested had symptoms or had been exposed to someone who was infected. Young adults (18-29 years) and Hispanics were more likely to have positive tests compared to older adults and persons of other racial/ethnic groups. Mental health (n=13,688, 54.6%) and family life (n=12,233, 48.8%) were most negatively affected by the pandemic and more so among younger groups and women; negative impacts on employment were more commonly reported among Black respondents. Of the 10,249 individuals who responded to vaccination questions from version 2 of the survey (summer 2021), 9770 (95.3%) had received the vaccine. After integration with EHR data up to the time of the survey completion, 1006 (4%) of the survey respondents had a discordant COVID-19 case status between EHRs and the survey. Using all longitudinal EHR and survey data, we identified 11,472 (6.4%) COVID-19-positive cases among Biobank participants. In comparison to COVID-19 cases identified through the survey, EHR-identified cases were younger and more likely to be Hispanic.ConclusionsWe found that the COVID-19 pandemic has had far-reaching and varying effects among our Biobank participants. Integrated data assets, such as the Biobank at the CCPM, are key resources for population health monitoring in response to public health emergencies, such as the COVID-19 pandemic.

Associations between COVID-19 testing status, non-communicable diseases and HIV status among residents of sub-Saharan Africa during the first wave of the pandemic

BackgroundThis study determined if non-communicable disease status, HIV status, COVID-19 status and co-habiting were associated with COVID-19 test status in sub-Saharan Africa.MethodsData of 5945 respondents age 18-years-old and above from 31 countries in sub-Saharan Africa collected through an online survey conducted between June and December 2020, were extracted. The dependent variable was COVID-19 status (testing positive for COVID-19 and having symptoms of COVID-19 but not getting tested). The independent variables were non-communicable disease status (hypertension, diabetes, cancer, heart conditions, respiratory conditions, depression), HIV positive status, COVID-19 status (knowing a close friend who tested positive for COVID-19 and someone who died from COVID-19) and co-habiting (yes/no). Two binary logistic regression models developed to determine associations between the dependent and independent variables were adjusted for age, sex, employment, sub region and educational status.ResultsHaving a close friend who tested positive for COVID-19 (AOR:6.747), knowing someone who died from COVID-19 infection (AOR:1.732), and living with other people (AOR:1.512) were significantly associated with higher odds of testing positive for COVID-19 infection, while living with HIV was associated with significantly lower odds of testing positive for COVID-19 infection (AOR:0.284). Also, respondents with respiratory conditions (AOR:2.487), self-reported depression (AOR:1.901), those who had a close friend who tested positive for COVID-19 infection (AOR:2.562) and who knew someone who died from COVID-19 infection (AOR:1.811) had significantly higher odds of having symptoms of COVID-19 infection but not getting tested.ConclusionNon-communicable diseases seem not to increase the risk for COVID-19 positive test while cohabiting seems to reduce this risk. The likelihood that those who know someone who tested positive to or who died from COVID-19 not getting tested when symptomatic suggests there is poor contact tracing in the region. People with respiratory conditions and depression need support to get tested for COVID-19.