Prenatal Diagnosis of Aortic Coarctation: Prediction Algorithm according to Gestational Age

<b><i>Objectives:</i></b> The aim of the study was first to quantify the diagnostic accuracy of predictive anatomical factors of aortic coarctation (CoA) and second to design a postnatal CoA probability algorithm according to gestational age (GA) in prenatal period. <b><i>Methods:</i></b> Global and according to GA diagnostic performance of cardiac anatomical variables using the ROC curve were evaluated in a retrospective cohort of fetuses with suspicion of CoA (2004–2020). A serial testing strategy to predict postnatal CoA by fetal echocardiography was designed. <b><i>Results:</i></b> 114 fetuses were included. Isthmus-to-ductal (I/D) ratio provided the best discrimination between healthy fetuses and those with CoA (AUC 0.91, 95% CI: 0.86–0.96, I/D &#x3c; 0.74 sensitivity 96.3%, I/D &#x3c; 0.6, specificity 92.5%) with good classification capacity in both the second and third trimesters of gestation. Isthmus <i>z</i>-score and pulmonary/aortic valve ratio increased accuracy in fetuses &#x3e;28 and tricuspid/mitral valve ratio (TV/MV) in fetuses ≤28 weeks. Study of I/D plus TV/MV ratio in fetuses ≤28 and I/D ratio plus isthmus <i>z</i>-scores in fetuses &#x3e;28 weeks allowed to correctly classify 91.8% of fetuses as high or low probability of postnatal CoA. <b><i>Conclusions:</i></b> Diagnostic discrimination of anatomic predictive factors for CoA varies according to GA. Specific algorithms according to GA increase accuracy in CoA’s prenatal prediction.

147. Defining the Optimal Serial Testing Interval and Features for Identifying Patients with Early SARS-CoV-2 Infection

Background Serial testing for SARS-CoV-2 is necessary to prevent spread from patients early in infection. Testing intervals are largely derived from viral kinetic studies performed early in the COVID-19 pandemic. Laboratory and epidemiologic data accrued over the past year present an opportunity to use empiric models to define optimal serial testing intervals and features predictive of early infection. Methods Retrospective analysis of 15,314 inpatients within the Mass General Brigham healthcare system who had two tests within a 36-hour period between May 1 2020 and May 29 2021. Early infection was defined as having a negative test followed by a positive test. Patients with prior positive tests were excluded. The primary outcome was the proportion of patients in early infection over the total number tested serially, stratified by 4-hour testing intervals from the timestamp of the first test. Multivariate modeling was used to identify features predictive of early infection. Covariates included demographics, body site, PCR assay, location, community incidence, percent positivity, and median / skew of Ct value distributions. Results Of 19,971 test pairs, 193 (0.97%) were characterized as a negative followed by a positive within 36 hours. Bivariate analysis showed a close association between negative to positive test pairs during the first surge in spring 2020 that was not present during the winter surge. Negative to positive test pairs were most common in the 12 to 16 hour time interval (51/193, 26%, Figure 1). After controlling for covariates, the Roche cobas assay was more likely to identify patients with a negative to positive test pair relative to the Cepheid Xpert, Hologic Panther Fusion and Roche Liat assays. A second specimen from the lower respiratory tract was more likely to lead to a positive relative to other body sites. Community incidence and Ct value distributions were not predictive and there were no differences between nasal and nasopharyngeal swabs. All 4-hour time intervals from 16 to 36 hours were significant for predicting a negative to positive test pair (Table 1). Figure 1. Distribution of negative to positive test pairs by 4 hour time intervals Table 1. Multivariate regression predicting a negative to positive test pair Conclusion The likelihood of detecting early infection is dependent on PCR platform and body site of sampling. A range of time intervals between 16 to 36 hours after the initial test were likely to identify positive cases. Disclosures Sanjat Kanjilal, MD, MPH, GlaskoSmithKline (Advisor or Review Panel member)

416. Diagnostic Yield of Serial COVID-19 Testing in Hospitalized Patients

Background Accurate and rapid diagnosis of SARS-CoV-2 infection is essential to prevent nosocomial transmission. Patients with negative COVID-19 tests at admission may still be in the incubation phase during hospitalisation. False negative results can occur when patients are tested too early. The incidence of COVID-19 infections in Montréal, Canada started to increase in December 2020. Because of this rise, on January 4th, 2021, the Infection Control Service of the McGill University Health Centre (MUHC) recommended serial COVID-19 testing for all admitted patients on days 5 and 10 after admission. The aim of this study is to examine the diagnostic yield of serial COVID-19 testing. Methods We retrospectively analyzed SARS-CoV-2 test results for patients admitted to the MUHC between January 4, 2021, and April 30, 2021. Nasopharyngeal swabs were collected from patients for SARS-CoV-2 PCR testing. Multiple testing platforms were used (Roche Cobas 6800, Thermo ScientificTM King Fisher and Cepheid GeneXpert) because of the high volume of samples. Tests were classified as admission, day 5, and day 10 tests if they were done on days 0 to 2, 3 to 7, and 8 to 12 respectively. Patients positive for SARS-CoV-2 on admission were excluded from the analyses. The diagnostic yield of serial testing for patients admitted during each month was calculated by dividing the number of patients testing positive on day 5 or day 10 by the total number of patients who underwent serial testing during that month. Results There were 2945 admissions of 5 days or more and 1777 admissions of 10 days or more. Of these, 1509 patients and 841 patients respectively were serially tested for SARS-CoV-2 as recommended for a compliance rate of 51% at day 5 and 47% at day 10. Ten (0.7%) and 12 (1.4%) patients tested positive on days 5 and 10 respectively. The diagnostic yield of serial testing was highest for patients admitted in January 2021 at 2.2%, when the average daily incidence of COVID-19 was highest in Montréal (see Figure). The diagnostic yield of serial testing for each month, compared to the average daily COVID-19 incidence rate in Montréal, Québec, Canada. Conclusion The diagnostic yield of serial SARS-CoV-2 testing in hospitalized patients is low when the overall community incidence is low. However, diagnostic yield of serial testing increases when community incidence of COVID-19 is higher and should be considered in this situation. Disclosures All Authors: No reported disclosures

Application of a Serial Antigen Based Testing Strategy for SARS-CoV-2 and Student Adherence in a University Setting, Wisconsin — October–November 2020

Background Serial SARS-CoV-2 testing has been implemented at institutions of higher education (IHEs) and other settings. Testing strategies can include algorithms specifying confirmatory reverse transcription polymerase chain reaction (RT-PCR) testing after an antigen test. It is unknown how testing strategies perform detecting SARS-CoV-2, including individual adherence to serial testing requirements. Methods Student serial testing adherence was defined as completing ≥80% of weekly tests from October 5–November 14, 2020 and evaluated using logistic regression. Medical records were reviewed for all positive antigen test encounters and 10% of daily negative antigen test encounters during October 19–November 30, 2020. Results were used to estimate the proportion of individuals requiring only antigen tests, requiring and completing RT-PCR testing, and associated costs of tests. Results Two-thirds (66.5%; 1,166/1,754) of eligible on-campus students adhered to weekly testing; female students were more adherent (adjusted odds ratio [aOR]:2.07, 95% CI:1.66–2.59) than male students. Of all antigen test encounters, 11.5% (1,409/12,305) reported &gt;1 COVID-19 symptoms. Of non-COVID-19 exposed antigen test encounters, 88% (10,386/11,769) did not require confirmatory RT-PCR testing. Only 28% (390/1,387) of testing encounters had an associated recommended confirmatory RT-PCR test performed. We estimated the testing strategy captured 61% (235/389) of predicted RT-PCR positive specimens. Conclusions At this IHE, most students voluntarily adhered to serial testing. The majority of antigen test results did not require confirmatory RT-PCR testing, but when required, most students did not obtain it. Including strategies to increase the proportion of individuals obtaining indicated confirmatory testing might improve the testing program’s performance.

Comparative analyses of all FDA EUA-approved rapid antigen tests and RT-PCR for COVID-19 quarantine and surveillance-based isolation

Rapid antigen (RA) tests are being increasingly employed to detect COVID-19 infections in quarantine and surveillance. We conducted a comparative analysis of quarantine durations, testing frequencies, and false-positive rates for all of the 18 RA tests with emergency use authorization (EUA) from the FDA, and an RT-PCR test. For each test, we employed a mathematical model of imminent infections to calculate the effective reproductive number in the context of the test used for quarantine or serial testing. We informed the model with data on test specificity, temporal diagnostic sensitivity, and COVID-19 infectiousness. Our results demonstrate that the relative effectiveness of RA and RT-PCR tests in reducing post-quarantine transmission depends on the quarantine duration and the turnaround time of testing results. For quarantines shorter than five days, RA test on entry to and on exit from quarantine reduced onward transmission more than a single RT-PCR test conducted upon exit. Conducting surveillance via serial RT-PCR testing with a 24-h turnaround time, the minimum testing frequency paired with isolation of positives that is required to suppress the effective reproduction number (RE) below one was found to be every six days. RA tests reduce RE below one when conducted at a minimum frequency that ranges from every six days to every eight days. Our analysis also highlights that the risk of onward transmission during serial testing increases with the delay in obtaining the results. These RA test-specific results are an important component of the tool set for policy decision-making, and demonstrate that judicious selection of an appropriate RA test can supply a viable alternative to RT-PCR in efforts to control the spread of disease.

Efficacy of the Measures Adopted to Prevent COVID-19 Outbreaks in an Italian Correctional Facility for Inmates Affected by Chronic Diseases

Background: COVID-19 outbreaks in prisons and jails may affect both inmates and correctional workers. An observational study has been performed to investigate the efficacy of specific procedures and of a serial testing approach adopted for the COVID-19 prevention in an Italian correctional facility (Bari, Apulia) for inmates affected by chronic diseases.Methods: Two SARS-CoV-2 antigen testing campaigns were carried out for all the prisoners and correctional workers, including correctional officers (CO), administrative staff (AS), correctional health care workers (HCW), and operators working with people completing their sentence outside the prison (OOP). Antigen testing was conducted on nasopharyngeal swab specimens, using a fluorescence immunoassay for the qualitative detection of nucleocapsid SARS-CoV-2 antigen. All subjects positive to the antigen test underwent confirmation by rRT-PCR test.Results: In total, 426 new and residential inmates were tested during the first campaign and 480 during the second campaign. Only two new inmates resulted positive at the first campaign, while no positive cases were observed at the second campaign or outside of the testing campaigns. In total, 367 correctional workers were tested at the first campaign and 325 at the second. At the first, 4 CO and 2 HCW showed positive test results, while no new positive cases were observed at the second. Moreover, 1 CO and 1 HCW resulted positive outside of the testing campaigns for the onset of symptoms while at home.Conclusion: The implementation of a full risk management plan in a correctional facility, including both a strict protocol for the application of preventive measures and a serial testing approach, seems to be able to prevent COVID-19 outbreaks in both inmates and correctional workers.

Molecular Epidemiology of Large COVID-19 Clusters at an Academic Medical Center, March–October 2020

Background: COVID-19 in hospitalized patients may be the result of community acquisition or in-hospital transmission. Molecular epidemiology can help confirm hospital COVID-19 transmission and outbreaks. We describe large COVID-19 clusters identified in our hospital and apply molecular epidemiology to confirm outbreaks. Methods: The University of Iowa Hospitals and Clinics is an 811-bed academic medical center. We identified large clusters involving patients with hospital onset COVID-19 detected during March–October 2020. Large clusters included ≥10 individuals (patients, visitors, or HCWs) with a laboratory confirmed COVID-19 diagnosis (RT-PCR) and an epidemiologic link. Epidemiologic links were defined as hospitalization, work, or visiting in the same unit during the incubation or infectious period for the index case. Hospital onset was defined as a COVID-19 diagnosis ≥14 days from admission date. Admission screening has been conducted since May 2020 and serial testing (every 5 days) since July 2020. Nasopharyngeal swab specimens were retrieved for viral whole-genome sequencing (WGS). Cluster patients with a pairwise difference in ≤5 mutations were considered part of an outbreak. WGS was performed using Oxford Nanopore Technology and protocols from the ARTIC network. Results: We identified 2 large clusters involving patients with hospital-onset COVID-19. Cluster 1: 2 hospital-onset cases were identified in a medical-surgical unit in June 2020. Source and contact tracing revealed 4 additional patients, 1 visitor, and 13 employees with COVID-19. Median age for patients was 62 (range, 38–79), and all were male. In total, 17 samples (6 patients, 1 visitor, and 10 HCWs) were available for WGS. Cluster 2: A hospital-onset case was identified via serial testing in a non–COVID-19 intensive care unit in September 2020. Source investigation, contact tracing, and serial testing revealed 3 additional patients, and 8 HCWs. One HCW also had a community exposure. Patient median age was 60 years (range, 48–68) and all were male. In total, 11 samples (4 patients and 7 HCWs) were sequenced. Using WGS, cluster 1 was confirmed to be an outbreak: WGS showed 0–5 mutations in between samples. Cluster 2 was also an outbreak: WGS showed less diversity (0–3 mutations) and ruled out the HCW with a community exposure (20 mutations of difference). Conclusion: Whole-genome sequencing confirmed the outbreaks identified using classic epidemiologic methods. Serial testing allowed for early outbreak detection. Early outbreak detection and implementation of control measures may decrease outbreak size and genetic diversity.Funding: NoDisclosures: None