Positive RT-PCR test results after consecutively negative results in patients with COVID-19

SARS-CoV-2 re-infection versus prolonged shedding: A case series

Since the start of the SARS‐CoV‐2 pandemic, it has been difficult to differentiate between SARS‐CoV‐2 re‐infection and prolonged RNA shedding. In this report, we identified patients with positive RT‐PCR results for SARS‐CoV‐2 ≥70 days apart. Clinical and laboratory data were collected and criteria were applied to discern whether the presentation was consistent with SARS‐CoV‐2 re‐infection or prolonged viral RNA shedding. Eleven individuals met the initial testing criteria, of which, seven met at least one criteria for re‐infection and four were consistent with prolonged RNA shedding. These data demonstrate the need for criteria to differentiate SARS‐CoV‐2 re‐infection from prolonged RNA shedding.

Characteristics of COVID-19 Recurrence: A Systematic Review and Meta-Analysis

Background:

Previous studies reported the recurrence of coronavirus disease 2019 (COVID-19) among discharge patients. This study aimed to examine the characteristic of COVID-19 recurrence cases by performing a systematic review and meta-analysis.

Methods:

A systematic search was performed in PubMed and Embase and gray literature up to September 19, 2020. A random-effects model was applied to obtain the pooled prevalence of disease recurrence among recovered patients and the prevalence of subjects underlying comorbidity among recurrence cases. The other characteristics were calculated based on the summary data of individual studies.

Results:

A total of 41 studies were included in the final analysis, we have described the epidemiological characteristics of COVID-19 recurrence cases. Of 3,644 patients recovering from COVID-19 and being discharged, an estimate of 15% (95% CI, 12% to 19%) patients was re-positive with SARS-CoV-2 during the follow-up. This proportion was 14% (95% CI, 11% to 17%) for China and 31% (95% CI, 26% to 37%) for Korea. Among recurrence cases, it was estimated 39% (95% CI, 31% to 48%) subjects underlying at least one comorbidity. The estimates for times from disease onset to admission, from admission to discharge, and from discharge to RNA positive conversion were 4.8, 16.4, and 10.4 days, respectively.

Conclusion:

This study summarized up-to-date evidence from case reports, case series, and observational studies for the characteristic of COVID-19 recurrence cases after discharge. It is recommended to pay attention to follow-up patients after discharge, even if they have been in discharge quarantine.

Clinical predictors of COVID-19 disease progression and death: Analysis of 214 hospitalised patients from Wuhan, China

INTRODUCTION

COVID-19 has spread rapidly worldwide and has been declared a pandemic.

OBJECTIVES

To delineate clinical features of COVID-19 patients with different severities and prognoses and clarify the risk factors for disease progression and death at an early stage.

METHODS

Medical history, laboratory findings, treatment and outcome data from 214 hospitalised patients with COVID-19 pneumonia admitted to Eastern Campus of Renmin Hospital, Wuhan University in China were collected from 30 January 2020 to 20 February 2020, and risk factors associated with clinical deterioration and death were analysed. The final date of follow-up was 21 March 2020.

RESULTS

Age, comorbidities, higher neutrophil cell counts, lower lymphocyte counts and subsets, impairment of liver, renal, heart, coagulation systems, systematic inflammation and clinical scores at admission were significantly associated with disease severity. Ten (16.1%) moderate and 45 (47.9%) severe patients experienced deterioration after admission, and median time from illness onset to clinical deterioration was 14.7 (IQR 11.3-18.5) and 14.5 days (IQR 11.8-20.0), respectively. Multivariate analysis showed increased Hazards Ratio of disease progression associated with older age, lymphocyte count <1.1 × 10⁹/L, blood urea nitrogen (BUN)> 9.5 mmol/L, lactate dehydrogenase >250 U/L and procalcitonin >0.1 ng/mL at admission. These factors were also associated with the risk of death except for BUN. Prediction models in terms of nomogram for clinical deterioration and death were established to illustrate the probability.

CONCLUSIONS

These findings provide insights for early detection and management of patients at risk of disease progression or even death, especially older patients and those with comorbidities.

Development and clinical application of a rapid SARS-CoV-2 antibody test strip: A multi-center assessment across China

BACKGROUND

The ongoing coronavirus disease 19 (COVID-19) is posing a threat to the public health globally. Serological test for SARS-CoV-2 antibody can improve early diagnosis of COVID-19 and serves as a valuable supplement to RNA detection.

METHOD

A SARS-CoV-2 IgG/IgM combined antibody test strip based on colloidal gold immunochromatography assay was developed, with both spike protein and nucleocapsid protein of SARS-CoV-2 antigen used for antibody detection. From 3 medical institutions across China, serum or plasma of 170 patients with confirmed COVID-19 diagnosis and 300 normal controls were collected and tested with the strip. Sensitivity, specificity, kappa coefficient, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were analyzed. Positive rates in different medical centers, age group, gender, and different disease course were compared.

RESULTS

158 out 170 samples from confirmed COVID-19 patients had positive results from the test, and 296 out of 300 samples from normal controls had negative results. The kit was 92.9% sensitive and 98.7% specific. The positive rate was 77.3% during the first week after disease onset, but reached 100% since day 9. AUC and kappa coefficient were 0.958 and 0.926, respectively, which showed the consistency of the test results with the standard diagnosis. Age or gender caused little variations in the kit sensitivity.

CONCLUSION

The rapid, easy-to-use SARS-CoV-2 IgG/IgM combined antibody test kit has a superior performance, which can help with accurate diagnosis and thus timely treatment and isolation of COVID-19 patients, that contributes to the better control of the global pandemic.

Population Risk Factors for COVID-19 Mortality in 93 Countries

Death rates due to COVID-19 pandemic vary considerably across regions and countries. Case Mortality Rates (CMR) per 100,000 population are more reliable than case-fatality rates per 100 test-positive cases, which are heavily dependent on the extent of viral case testing carried out in a country. We aimed to study the variations in CMR against population risk factors such as aging, underlying chronic diseases and social determinants such as poverty and overcrowding. Data on COVID-19 CMR in 93 countries was analyzed for associations with preexisting prevalence rates of eight diseases [asthma, lung cancer, Chronic Obstructive Pulmonary Disease (COPD), Alzheimer's Disease (AD), hypertension, ischemic heart disease, depression and diabetes], and six socio-demographic factors [Gross Domestic Product (GDP) per capita, unemployment, age over 65 years, urbanization, population density, and socio-demographic index]. These data were analyzed in three steps: correlation analysis, bivariate comparison of countries, and multivariate modelling. Bivariate analysis revealed that COVID-19 CMR were higher in countries that had high prevalence of population risk factors such as AD, lung cancer, asthma and COPD. On multivariate modeling however, AD, COPD, depression and higher GDP predicted increased death rates. Comorbid illnesses such as AD and lung diseases may be more influential than aging alone.

Perioperative management of COVID-19 patients undergoing cardiac surgery with cardiopulmonary bypass

Coronavirus disease 2019 (COVID-19) is a serious health concern which affects all healthcare professionals worldwide. The pandemic puts health services, including cardiac surgery units, under escalating pressure. There are significant challenges caused by this novel virus and ensuing disease that leads to great uncertainty. While it has been advocated to delay elective surgeries, most cardiac surgical patients present in a more urgent manner which elevates the critical nature for intervention, which may make the surgical decision inevitable. To date, no definitive treatments to the pandemic have been promoted. Cardiac surgical centers may experience an increasing number of COVID-19 patients in clinical practice. Preparation for managing these patients will require a change in the current modalities for perioperative care. Therefore, the goal of this report is to share our own experiences, combined with a review of the emerging literature, by highlighting principles for the adult cardiac surgery community regarding treatment of patients scheduled for surgery. The following report will recommend perioperative guidance in patient management to include safety precautions for the heart team, the conduct of extracorporeal circulation and related equipment, and covering the early period in intensive care in the context of the current pandemic.

Antibody tests for identification of current and past infection with SARS-CoV-2

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection.

OBJECTIVES

To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys.

SEARCH METHODS

We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020.

SELECTION CRITERIA

We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria).

DATA COLLECTION AND ANALYSIS

We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs).

MAIN RESULTS

We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands.

AUTHORS' CONCLUSIONS

The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.