Added value of chest computed tomography in suspected COVID-19: an analysis of 239 patients

Detection of Virus SARS-CoV-2 Using a Surface Plasmon Resonance Device Based on BiFeO3-Graphene Layers

Coronavirus disease (COVID-19) pandemic outbreak is being investigated by severe respirational syndrome coronavirus-2 (SARS-CoV-2) as a global health issue. It is crucial to propose sensitive and rapid coronavirus detectors. Herein, we propose a biosensor based on surface plasmon resonance (SPRE) for the detection of SARS-CoV-2 virus. To achieve improved sensitivity, a BiFeO3 layer is inserted between a metal (Ag) thin film and a graphene layer in the proposed SPRE device so that it has the structure BK7 prism/ Ag/ BiFeO3/ graphene/ analyte. It has been demonstrated that a small variation in the refractive index of the analyte can cause a considerable shift in the resonance angle caused by the remarkable dielectric properties of the BiFeO3 layer, which include a high index of refraction and low loss. The proposed device has shown an extremely high sensitivity of 293 deg/RIU by optimizing the thicknesses of Ag, BiFeO3, and the number of graphene sheets. The proposed SPRE-based sensor is encouraging for use in various sectors of biosensing because of its high sensitivity.

Refractive index based optically transparent biosensor device design for early detection of coronavirus

For the quick detection of the new Coronavirus (COVID-19), a highly sensitive D-shaped gold-coated surface Plasmon resonance (SPR) biosensor is presented. The COVID-19 virus may be quickly and accurately identified using the SPR-based biosensor, which is essential for halting the spread of this excruciating epidemic. The suggested biosensor is used for detection of the IBV i.e. infectious bronchitis viruses contaminated cell that belongs to the family of COVID-19 having a refractive index of - 0.96, - 0.97, - 0.98, - 0.99, - 1 that is observed with the change in EID concentration. Some important optical parameter variations are examined in the investigation process. Multiphysics version 5.3 with the Finite element method is used for the proposed biosensor. The proposed sensor depicts maximum wavelength sensitivity of 40,141.76 nm/RIU. Some other parameters such as confinement loss, crosstalk, and insertion loss are also analyzed for the proposed sensor. The reported minimum insertion loss for the refractive index (RI) - 1 is 2.9 dB. Simple design, good sensitivity, and lower value of losses make the proposed sensor proficient for the detection of infectious bronchitis viruses belonging to COVID-19.

Graphical abstract

An Umbrella Review With Meta-Analysis of Chest Computed Tomography for Diagnosis of COVID-19: Considerations for Trauma Patient Management

Background

RT-PCR testing is the standard for diagnosis of COVID-19, although it has its suboptimal sensitivity. Chest computed tomography (CT) has been proposed as an additional tool with diagnostic value, and several reports from primary and secondary studies that assessed its diagnostic accuracy are already available. To inform recommendations and practice regarding the use of chest CT in the in the trauma setting, we sought to identify, appraise, and summarize the available evidence on the diagnostic accuracy of chest CT for diagnosis of COVID-19, and its application in emergency trauma surgery patients; overcoming limitations of previous reports regarding chest CT accuracy and discussing important considerations regarding its role in this setting.

Methods

We conducted an umbrella review using Living Overview of Evidence platform for COVID-19, which performs regular automated searches in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and more than 30 other sources. The review was conducted following the JBI methodology for systematic reviews. The Grading of Recommendations, Assessment, Development, and Evaluation approach for grading the certainty of the evidence is reported (registered in International Prospective Register of Systematic Reviews, CRD42020198267).

Results

Thirty studies that fulfilled selection criteria were included; 19 primary studies provided estimates of sensitivity (0.91, 95%CI = [0.88–0.93]) and specificity (0.73, 95%CI = [0.61; 0.82]) of chest CT for COVID-19. No correlation was found between sensitivities and specificities (ρ = 0.22, IC95% [–0.33; 0.66]). Diagnostic odds ratio was estimated at: DOR = 27.5, 95%CI (14.7; 48.5). Evidence for sensitivity estimates was graded as MODERATE, and for specificity estimates it was graded as LOW.

Conclusion

The value of chest CT appears to be that of an additional screening tool that can easily detect PCR false negatives, which are reportedly highly frequent. Upon the absence of PCR testing and impossibility to perform RT-PCR in trauma patients, chest CT can serve as a substitute with increased value and easy implementation.

Systematic Review Registration

[www.crd.york.ac.uk/prospero], identifier [CRD42020198267].

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2-Infected Pakistani Patients

SARS-CoV-2 is a causative agent for COVID-19 disease, initially reported from Wuhan, China. The infected patients experienced mild to severe symptoms, resulting in several fatalities due to a weak understanding of its pathogenesis, which is the same even to date. This cross-sectional study has been designed on 452 symptomatic mild-to-moderate and severe/critical patients to understand the epidemiology and clinical characteristics of COVID-19 patients with their comorbidities and response to treatment. The mean age of the studied patients was 58 ± 14.42 years, and the overall male to female ratio was 61.7 to 38.2%, respectively. In total, 27.3% of the patients had a history of exposure, and 11.9% had a travel history, while for 60% of patients, the source of infection was unknown. The most prevalent signs and symptoms in ICU patients were dry cough, myalgia, shortness of breath, gastrointestinal discomfort, and abnormal chest X-ray (p < 0.001), along with a high percentage of hypertension (p = 0.007) and chronic obstructive pulmonary disease (p = 0.029) as leading comorbidities. The complete blood count indicators were significantly disturbed in severe patients, while the coagulation profile and D-dimer values were significantly higher in mild-to-moderate (non-ICU) patients (p < 0.001). The serum creatinine (1.22 μmol L^-1; p = 0.016) and lactate dehydrogenase (619 μmol L^-1; p < 0.001) indicators were significantly high in non-ICU patients, while raised values of total bilirubin (0.91 μmol L^-1; p = 0.054), C-reactive protein (84.68 mg L^-1; p = 0.001), and ferritin (996.81 mg L^-1; p < 0.001) were found in ICU patients. The drug dexamethasone was the leading prescribed and administrated medicine to COVID-19 patients, followed by remdesivir, meropenem, heparin, and tocilizumab, respectively. A characteristic pattern of ground glass opacities, consolidation, and interlobular septal thickening was prominent in severely infected patients. These findings could be used for future research, control, and prevention of SARS-CoV-2-infected patients.

Diagnostic Performance of Antigen Rapid Diagnostic Tests, Chest Computed Tomography, and Lung Point-of-Care-Ultrasonography for SARS-CoV-2 Compared with RT-PCR Testing: A Systematic Review and Network Meta-Analysis

(1) Background: The comparative performance of various diagnostic methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains unclear. This study aimed to investigate the comparison of the 3 index test performances of rapid antigen diagnostic tests (RDTs), chest computed tomography (CT), and lung point-of-care-ultrasonography (US) with reverse transcription-polymerase chain reaction (RT-PCR), the reference standard, to provide more evidence-based data on the appropriate use of these index tests. (2) Methods: We retrieved data from electronic literature searches of PubMed, Cochrane Library, and EMBASE from 1 January 2020, to 1 April 2021. Diagnostic performance was examined using bivariate random-effects diagnostic test accuracy (DTA) and Bayesian network meta-analysis (NMA) models. (3) Results: Of the 3992 studies identified in our search, 118 including 69,445 participants met our selection criteria. Among these, 69 RDT, 38 CT, and 15 US studies in the pairwise meta-analysis were included for DTA with NMA. CT and US had high sensitivity of 0.852 (95% credible interval (CrI), 0.791–0.914) and 0.879 (95% CrI, 0.784–0.973), respectively. RDT had high specificity, 0.978 (95% CrI, 0.960–0.996). In accuracy assessment, RDT and CT had a relatively higher than US. However, there was no significant difference in accuracy between the 3 index tests. (4) Conclusions: This meta-analysis suggests that, compared with the reference standard RT-PCR, the 3 index tests (RDTs, chest CT, and lung US) had similar and complementary performances for diagnosis of SARS-CoV-2 infection. To manage and control COVID-19 effectively, future large-scale prospective studies could be used to obtain an optimal timely diagnostic process that identifies the condition of the patient accurately.

Thoracic imaging tests for the diagnosis of COVID-19

BACKGROUND

Our March 2021 edition of this review showed thoracic imaging computed tomography (CT) to be sensitive and moderately specific in diagnosing COVID-19 pneumonia. This new edition is an update of the review.

OBJECTIVES

Our objectives were to evaluate the diagnostic accuracy of thoracic imaging in people with suspected COVID-19; assess the rate of positive imaging in people who had an initial reverse transcriptase polymerase chain reaction (RT-PCR) negative result and a positive RT-PCR result on follow-up; and evaluate the accuracy of thoracic imaging for screening COVID-19 in asymptomatic individuals. The secondary objective was to assess threshold effects of index test positivity on accuracy.

SEARCH METHODS

We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 17 February 2021. We did not apply any language restrictions.

SELECTION CRITERIA

We included diagnostic accuracy studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19. Studies had to assess chest CT, chest X-ray, or ultrasound of the lungs for the diagnosis of COVID-19, use a reference standard that included RT-PCR, and report estimates of test accuracy or provide data from which we could compute estimates. We excluded studies that used imaging as part of the reference standard and studies that excluded participants with normal index test results.

DATA COLLECTION AND ANALYSIS

The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using QUADAS-2. We presented sensitivity and specificity per study on paired forest plots, and summarized pooled estimates in tables. We used a bivariate meta-analysis model where appropriate.

MAIN RESULTS

We included 98 studies in this review. Of these, 94 were included for evaluating the diagnostic accuracy of thoracic imaging in the evaluation of people with suspected COVID-19. Eight studies were included for assessing the rate of positive imaging in individuals with initial RT-PCR negative results and positive RT-PCR results on follow-up, and 10 studies were included for evaluating the accuracy of thoracic imaging for imagining asymptomatic individuals. For all 98 included studies, risk of bias was high or unclear in 52 (53%) studies with respect to participant selection, in 64 (65%) studies with respect to reference standard, in 46 (47%) studies with respect to index test, and in 48 (49%) studies with respect to flow and timing. Concerns about the applicability of the evidence to: participants were high or unclear in eight (8%) studies; index test were high or unclear in seven (7%) studies; and reference standard were high or unclear in seven (7%) studies. Imaging in people with suspected COVID-19 We included 94 studies. Eighty-seven studies evaluated one imaging modality, and seven studies evaluated two imaging modalities. All studies used RT-PCR alone or in combination with other criteria (for example, clinical signs and symptoms, positive contacts) as the reference standard for the diagnosis of COVID-19. For chest CT (69 studies, 28285 participants, 14,342 (51%) cases), sensitivities ranged from 45% to 100%, and specificities from 10% to 99%. The pooled sensitivity of chest CT was 86.9% (95% confidence interval (CI) 83.6 to 89.6), and pooled specificity was 78.3% (95% CI 73.7 to 82.3). Definition for index test positivity was a source of heterogeneity for sensitivity, but not specificity. Reference standard was not a source of heterogeneity. For chest X-ray (17 studies, 8529 participants, 5303 (62%) cases), the sensitivity ranged from 44% to 94% and specificity from 24 to 93%. The pooled sensitivity of chest X-ray was 73.1% (95% CI 64. to -80.5), and pooled specificity was 73.3% (95% CI 61.9 to 82.2). Definition for index test positivity was not found to be a source of heterogeneity. Definition for index test positivity and reference standard were not found to be sources of heterogeneity. For ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases), the sensitivity ranged from 73% to 94% and the specificity ranged from 21% to 98%. The pooled sensitivity of ultrasound was 88.9% (95% CI 84.9 to 92.0), and the pooled specificity was 72.2% (95% CI 58.8 to 82.5). Definition for index test positivity and reference standard were not found to be sources of heterogeneity. Indirect comparisons of modalities evaluated across all 94 studies indicated that chest CT and ultrasound gave higher sensitivity estimates than X-ray (P = 0.0003 and P = 0.001, respectively). Chest CT and ultrasound gave similar sensitivities (P=0.42). All modalities had similar specificities (CT versus X-ray P = 0.36; CT versus ultrasound P = 0.32; X-ray versus ultrasound P = 0.89). Imaging in PCR-negative people who subsequently became positive For rate of positive imaging in individuals with initial RT-PCR negative results, we included 8 studies (7 CT, 1 ultrasound) with a total of 198 participants suspected of having COVID-19, all of whom had a final diagnosis of COVID-19. Most studies (7/8) evaluated CT. Of 177 participants with initially negative RT-PCR who had positive RT-PCR results on follow-up testing, 75.8% (95% CI 45.3 to 92.2) had positive CT findings. Imaging in asymptomatic PCR-positive people For imaging asymptomatic individuals, we included 10 studies (7 CT, 1 X-ray, 2 ultrasound) with a total of 3548 asymptomatic participants, of whom 364 (10%) had a final diagnosis of COVID-19. For chest CT (7 studies, 3134 participants, 315 (10%) cases), the pooled sensitivity was 55.7% (95% CI 35.4 to 74.3) and the pooled specificity was 91.1% (95% CI 82.6 to 95.7).

AUTHORS' CONCLUSIONS

Chest CT and ultrasound of the lungs are sensitive and moderately specific in diagnosing COVID-19. Chest X-ray is moderately sensitive and moderately specific in diagnosing COVID-19. Thus, chest CT and ultrasound may have more utility for ruling out COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. The uncertainty resulting from high or unclear risk of bias and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.

[Korean Clinical Imaging Guidelines for Justification of Diagnostic Imaging Study for COVID-19]

To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered. In addition to clinical evaluations and laboratory tests, chest imaging may be contemplated to determine hospital admission for asymptomatic or mildly symptomatic unhospitalized patients with confirmed COVID-19. In hospitalized patients with confirmed COVID-19, chest imaging may be advised to determine or modify treatment alternatives. CT angiography may be considered if hemoptysis or pulmonary embolism is clinically suspected in a patient with confirmed COVID-19. For COVID-19 patients with improved symptoms, chest imaging is not recommended to make decisions regarding hospital discharge. For patients with functional impairment after recovery from COVID-19, chest imaging may be considered to distinguish a potentially treatable disease.

The role of chest imaging in the diagnosis, management, and monitoring of coronavirus disease 2019 (COVID-19)

Coronavirus disease 2019 (COVID-19) pandemic has posed a major public health crisis all over the world. The role of chest imaging, especially computed tomography (CT), has evolved during the pandemic paralleling the accumulation of scientific evidence. In the early stage of the pandemic, the performance of chest imaging for COVID-19 has widely been debated especially in the context of comparison to real-time reverse transcription polymerase chain reaction. Current evidence is against the use of chest imaging for routine screening of COVID-19 contrary to the initial expectations. It still has an integral role to play, however, in its work up and staging, especially when assessing complications or disease progression. Chest CT is gold standard imaging modality for COVID-19 pneumonia; in some situations, chest X-ray or ultrasound may be an effective alternative. The most important role of radiologists in this context is to be able to identify those patients at greatest risk of imminent clinical decompensation by learning to stratify cases of COVID-19 on the basis of radiologic imaging in the most efficient and timely fashion possible. The present availability of multiple and more refined CT grading systems and classification is now making this task easier and thereby contributing to the recent improvements achieved in COVID-19 treatment and outcomes. In this article, evidence of chest imaging regarding diagnosis, management and monitoring of COVID-19 will be chronologically reviewed.

Assessment of Lung Reaeration at 2 Levels of Positive End-expiratory Pressure in Patients With Early and Late COVID-19-related Acute Respiratory Distress Syndrome

PURPOSE

Patients with novel coronavirus disease (COVID-19) frequently develop acute respiratory distress syndrome (ARDS) and need invasive ventilation. The potential to reaerate consolidated lung tissue in COVID-19-related ARDS is heavily debated. This study assessed the potential to reaerate lung consolidations in patients with COVID-19-related ARDS under invasive ventilation.

MATERIALS AND METHODS

This was a retrospective analysis of patients with COVID-19-related ARDS who underwent chest computed tomography (CT) at low positive end-expiratory pressure (PEEP) and after a recruitment maneuver at high PEEP of 20 cm H2O. Lung reaeration, volume, and weight were calculated using both CT scans. CT scans were performed after intubation and start of ventilation (early CT), or after several days of intensive care unit admission (late CT).

RESULTS

Twenty-eight patients were analyzed. The median percentages of reaerated and nonaerated lung tissue were 19% [interquartile range, IQR: 10 to 33] and 11% [IQR: 4 to 15] for patients with early and late CT scans, respectively (P=0.049). End-expiratory lung volume showed a median increase of 663 mL [IQR: 483 to 865] and 574 mL [IQR: 292 to 670] after recruitment for patients with early and late CT scans, respectively (P=0.43). The median decrease in lung weight attributed to nonaerated lung tissue was 229 g [IQR: 165 to 376] and 171 g [IQR: 81 to 229] after recruitment for patients with early and late CT scans, respectively (P=0.16).

CONCLUSIONS

The majority of patients with COVID-19-related ARDS undergoing invasive ventilation had substantial reaeration of lung consolidations after recruitment and ventilation at high PEEP. Higher PEEP can be considered in patients with reaerated lung consolidations when accompanied by improvement in compliance and gas exchange.

Mortality of patients with solid and haematological cancers presenting with symptoms of COVID-19 with vs without detectable SARS-COV-2: a French nationwide prospective cohort study

BACKGROUND

Over 30 million COVID-19 cases have been diagnosed worldwide from late 2019. Among frail persons, cancer patients are at high risk of death from COVID-19.

METHODS

The French prospective cohort ONCOVID-19 enrolled patients with solid or haematological tumour, receiving anticancer treatment and presenting with clinical symptoms suggestive of COVID-19. COVID-19 was confirmed through detectable SARS-CoV2 by RT-PCR (repeated twice if negative first) and/or specific CT-scan. The study aims to assess the 28-day mortality rate after the first COVID test.

RESULTS

From March 1st to May 21st 2020, 23 French cancer centres and hospitals enrolled 1230 cancer patients with suspicion of COVID-19, including 1162 (94.5%) matching the inclusion criteria. We identified 425 (36.6%) COVID-19 positive patients including 155 (13.3%) diagnosed with CT-scan only, while 737 (63.4%) patients were COVID-19 negative. Death at day-28 occurred in 116/425 (27.8%) COVID-19 positive patients, and in 118/737 (16.3%) COVID-19 negative patients (p < 0·0001). With a median follow-up of 2.1 (1.6-2.4) months, 310 (26.7%) deaths were reported including 143 (33.6%) in the COVID-19 positive population, and 167 (22.7%) in the COVID-19 negative patients. Male gender, age, metastatic disease, immunosuppressive treatments, lymphopenia, COVID-19 diagnosis and diabetes were independent risk factors for death.

CONCLUSION

Patients with solid and haematological cancers presenting COVID-19 symptoms with SARS-CoV-2 RT-PCR confirmed or not are both at high-risk of early mortality. COVID-19 is reported as the cause of death in 50% of COVID-19 positive patients with cancer.

CLINICAL TRIAL REGISTRATION

This trial is registered with ClinicalTrials.gov, number NCT04363632.

Antibodies Can Last for More Than 1 Year After SARS-CoV-2 Infection: A Follow-Up Study From Survivors of COVID-19

Background: COVID-19 is a global pandemic. The prevention of SARS-CoV-2 infection and the rehabilitation of survivors are currently the most urgent tasks. However, after patients with COVID-19 are discharged from the hospital, how long the antibodies persist, whether the lung lesions can be completely absorbed, and whether cardiopulmonary abnormalities exist remain unclear.

Methods: A total of 56 COVID-19 survivors were followed up for 12 months, with examinations including serum virus-specific antibodies, chest CT, and cardiopulmonary exercise testing.

Results: The IgG titer of the COVID-19 survivors decreased gradually, especially in the first 6 months after discharge. At 6 and 12 months after discharge, the IgG titer decreased by 68.9 and 86.0%, respectively. The IgG titer in patients with severe disease was higher than that in patients with non-severe disease at each time point, but the difference did not reach statistical significance. Among the patients, 11.8% were IgG negative up to 12 months after discharge. Chest CT scans showed that at 3 and 10 months after discharge, the lung opacity had decreased by 91.9 and 95.5%, respectively, as compared with that at admission. 10 months after discharge, 12.5% of the patients had an opacity percentage >1%, and 18.8% of patients had pulmonary fibrosis (38.5% in the severe group and 5.3% in the non-severe group, P < 0.001). Cardiopulmonary exercise testing showed that 22.9% of patients had FEV1/FVC%Pred <92%, 17.1% of patients had FEV1%Pred <80%, 20.0% of patients had a VO₂ AT <14 mlO₂/kg/min, and 22.9% of patients had a VE/VCO₂ slope >30%.

Conclusions: IgG antibodies in most patients with COVID-19 can last for at least 12 months after discharge. The IgG titers decreased significantly in the first 6 months and remained stable in the following 6 months. The lung lesions of most patients with COVID-19 can be absorbed without sequelae, and a few patients in severe condition are more likely to develop pulmonary fibrosis. Approximately one-fifth of the patients had cardiopulmonary dysfunction 6 months after discharge.

Design and Numerical Analysis of a Graphene-Coated SPR Biosensor for Rapid Detection of the Novel Coronavirus

In this paper, a highly sensitive graphene-based multiple-layer (BK7/Au/PtSe2/Graphene) coated surface plasmon resonance (SPR) biosensor is proposed for the rapid detection of the novel Coronavirus (COVID-19). The proposed sensor was modeled on the basis of the total internal reflection (TIR) technique for real-time detection of ligand-analyte immobilization in the sensing region. The refractive index (RI) of the sensing region is changed due to the interaction of different concentrations of the ligand-analyte, thus impacting surface plasmon polaritons (SPPs) excitation of the multi-layer sensor interface. The performance of the proposed sensor was numerically investigated by using the transfer matrix method (TMM) and the finite-difference time-domain (FDTD) method. The proposed SPR biosensor provides fast and accurate early-stage diagnosis of the COVID-19 virus, which is crucial in limiting the spread of the pandemic. In addition, the performance of the proposed sensor was investigated numerically with different ligand-analytes: (i) the monoclonal antibodies (mAbs) as ligand and the COVID-19 virus spike receptor-binding domain (RBD) as analyte, (ii) the virus spike RBD as ligand and the virus anti-spike protein (IgM, IgG) as analyte and (iii) the specific probe as ligand and the COVID-19 virus single-standard ribonucleic acid (RNA) as analyte. After the investigation, the sensitivity of the proposed sensor was found to provide 183.33°/refractive index unit (RIU) in SPR angle (θSPR) and 833.33THz/RIU in SPR frequency (SPRF) for detection of the COVID-19 virus spike RBD; the sensitivity obtained 153.85°/RIU in SPR angle and 726.50THz/RIU in SPRF for detection of the anti-spike protein, and finally, the sensitivity obtained 140.35°/RIU in SPR angle and 500THz/RIU in SPRF for detection of viral RNA. It was observed that whole virus spike RBD detection sensitivity is higher than that of the other two detection processes. Highly sensitive two-dimensional (2D) materials were used to achieve significant enhancement in the Goos-Hänchen (GH) shift detection sensitivity and plasmonic properties of the conventional SPR sensor. The proposed sensor successfully senses the COVID-19 virus and offers additional (1 + 0.55) × L times sensitivity owing to the added graphene layers. Besides, the performance of the proposed sensor was analyzed based on detection accuracy (DA), the figure of merit (FOM), signal-noise ratio (SNR), and quality factor (QF). Based on its performance analysis, it is expected that the proposed sensor may reduce lengthy procedures, false positive results, and clinical costs, compared to traditional sensors. The performance of the proposed sensor model was checked using the TMM algorithm and validated by the FDTD technique.

Head-to-head validation of six immunoassays for SARS-CoV-2 in hospitalized patients

BACKGROUND

Detecting SARS-CoV-2 antibodies may help to diagnose COVID-19. Head-to-head validation of different types of immunoassays in well-characterized cohorts of hospitalized patients remains needed.

METHODS

We validated three chemiluminescence immunoassays (CLIAs) (Liaison, Elecsys, and Abbott) and one single molecule array assay (SIMOA) (Quanterix) for automated analyzers, one rapid immunoassay RIA (AllTest), and one ELISA (Wantai) in parallel in first samples from 126 PCR confirmed COVID-19 hospitalized patients and 158 pre-COVID-19 patients. Specificity of the AllTest was also tested in 106 patients with confirmed parasitic and dengue virus infections. Specificity of the Wantai assay was not tested due to limitations in sample volumes.

RESULTS

Overall sensitivity in first samples was 70.6 % for the Liaison, 71.4 % for the Elecsys, 75.4 % for the Abbott, 70.6 % for the Quanterix, 77.8 % for the AllTest, and 88.9 % for the Wantai assay, respectively. Sensitivity was between 77.4 % (Liaison) and 94.0 % (Wantai) after 10 dpso. No false positive results were observed for the Elecsys and Abbott assays. Specificity was 91.1 % for the Quanterix, 96.2 % for the Liaison, and 98.1 % for the AllTest assay, respectively.

CONCLUSION

We conclude that low sensitivity of all immunoassays limits their use early after onset of illness in diagnosing COVID-19 in hospitalized patients. After 10 dpso, the Wantai ELISA has a relatively high sensitivity, followed by the point-of-care AllTest RIA that compares favorably with automated analyzer immunoassays.

Thoracic imaging tests for the diagnosis of COVID-19

BACKGROUND

The respiratory illness caused by SARS-CoV-2 infection continues to present diagnostic challenges. Our 2020 edition of this review showed thoracic (chest) imaging to be sensitive and moderately specific in the diagnosis of coronavirus disease 2019 (COVID-19). In this update, we include new relevant studies, and have removed studies with case-control designs, and those not intended to be diagnostic test accuracy studies.

OBJECTIVES

To evaluate the diagnostic accuracy of thoracic imaging (computed tomography (CT), X-ray and ultrasound) in people with suspected COVID-19.

SEARCH METHODS

We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 30 September 2020. We did not apply any language restrictions.

SELECTION CRITERIA

We included studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19 and that reported estimates of test accuracy or provided data from which we could compute estimates.

DATA COLLECTION AND ANALYSIS

The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using the QUADAS-2 domain-list. We presented the results of estimated sensitivity and specificity using paired forest plots, and we summarised pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. We presented the uncertainty of accuracy estimates using 95% confidence intervals (CIs).

MAIN RESULTS

We included 51 studies with 19,775 participants suspected of having COVID-19, of whom 10,155 (51%) had a final diagnosis of COVID-19. Forty-seven studies evaluated one imaging modality each, and four studies evaluated two imaging modalities each. All studies used RT-PCR as the reference standard for the diagnosis of COVID-19, with 47 studies using only RT-PCR and four studies using a combination of RT-PCR and other criteria (such as clinical signs, imaging tests, positive contacts, and follow-up phone calls) as the reference standard. Studies were conducted in Europe (33), Asia (13), North America (3) and South America (2); including only adults (26), all ages (21), children only (1), adults over 70 years (1), and unclear (2); in inpatients (2), outpatients (32), and setting unclear (17). Risk of bias was high or unclear in thirty-two (63%) studies with respect to participant selection, 40 (78%) studies with respect to reference standard, 30 (59%) studies with respect to index test, and 24 (47%) studies with respect to participant flow. For chest CT (41 studies, 16,133 participants, 8110 (50%) cases), the sensitivity ranged from 56.3% to 100%, and specificity ranged from 25.4% to 97.4%. The pooled sensitivity of chest CT was 87.9% (95% CI 84.6 to 90.6) and the pooled specificity was 80.0% (95% CI 74.9 to 84.3). There was no statistical evidence indicating that reference standard conduct and definition for index test positivity were sources of heterogeneity for CT studies. Nine chest CT studies (2807 participants, 1139 (41%) cases) used the COVID-19 Reporting and Data System (CO-RADS) scoring system, which has five thresholds to define index test positivity. At a CO-RADS threshold of 5 (7 studies), the sensitivity ranged from 41.5% to 77.9% and the pooled sensitivity was 67.0% (95% CI 56.4 to 76.2); the specificity ranged from 83.5% to 96.2%; and the pooled specificity was 91.3% (95% CI 87.6 to 94.0). At a CO-RADS threshold of 4 (7 studies), the sensitivity ranged from 56.3% to 92.9% and the pooled sensitivity was 83.5% (95% CI 74.4 to 89.7); the specificity ranged from 77.2% to 90.4% and the pooled specificity was 83.6% (95% CI 80.5 to 86.4). For chest X-ray (9 studies, 3694 participants, 2111 (57%) cases) the sensitivity ranged from 51.9% to 94.4% and specificity ranged from 40.4% to 88.9%. The pooled sensitivity of chest X-ray was 80.6% (95% CI 69.1 to 88.6) and the pooled specificity was 71.5% (95% CI 59.8 to 80.8). For ultrasound of the lungs (5 studies, 446 participants, 211 (47%) cases) the sensitivity ranged from 68.2% to 96.8% and specificity ranged from 21.3% to 78.9%. The pooled sensitivity of ultrasound was 86.4% (95% CI 72.7 to 93.9) and the pooled specificity was 54.6% (95% CI 35.3 to 72.6). Based on an indirect comparison using all included studies, chest CT had a higher specificity than ultrasound. For indirect comparisons of chest CT and chest X-ray, or chest X-ray and ultrasound, the data did not show differences in specificity or sensitivity.

AUTHORS' CONCLUSIONS

Our findings indicate that chest CT is sensitive and moderately specific for the diagnosis of COVID-19. Chest X-ray is moderately sensitive and moderately specific for the diagnosis of COVID-19. Ultrasound is sensitive but not specific for the diagnosis of COVID-19. Thus, chest CT and ultrasound may have more utility for excluding COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. Future diagnostic accuracy studies should pre-define positive imaging findings, include direct comparisons of the various modalities of interest in the same participant population, and implement improved reporting practices.

Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis

PURPOSE

To determine the diagnostic performance of the COVID-19 Reporting and Data System (CO-RADS) and the Radiological Society of North America (RSNA) categorizations in patients with clinically suspected coronavirus disease 2019 (COVID-19) infection.

MATERIALS AND METHODS

In this meta-analysis, studies from 2020, up to August 24, 2020 were assessed for inclusion criteria of studies that used CO-RADS or the RSNA categories for scoring chest CT in patients with suspected COVID-19. A total of 186 studies were identified. After review of abstracts and text, a total of nine studies were included in this study. Patient information (n¸ age, sex), CO-RADS and RSNA scoring categories, and other study characteristics were extracted. Study quality was assessed with the QUADAS-2 tool. Meta-analysis was performed with a random effects model.

RESULTS

Nine studies (3283 patients) were included. Overall study quality was good, except for risk of non-performance of repeated reverse transcriptase polymerase chain reaction (RT-PCR) after negative initial RT-PCR and persistent clinical suspicion in four studies. Pooled COVID-19 frequencies in CO-RADS categories were: 1, 8.8%; 2, 11.1%; 3, 24.6%; 4, 61.9%; and 5, 89.6%. Pooled COVID-19 frequencies in RSNA classification categories were: negative 14.4%; atypical, 5.7%; indeterminate, 44.9%; and typical, 92.5%. Pooled pairs of sensitivity and specificity using CO-RADS thresholds were the following: at least 3, 92.5% (95% CI: 87.1, 95.7) and 69.2% (95%: CI: 60.8, 76.4); at least 4, 85.8% (95% CI: 78.7, 90.9) and 84.6% (95% CI: 79.5, 88.5); and 5, 70.4% (95% CI: 60.2, 78.9) and 93.1% (95% CI: 87.7, 96.2). Pooled pairs of sensitivity and specificity using RSNA classification thresholds for indeterminate were 90.2% (95% CI: 87.5, 92.3) and 75.1% (95% CI: 68.9, 80.4) and for typical were 65.2% (95% CI: 37.0, 85.7) and 94.9% (95% CI: 86.4, 98.2).

CONCLUSION

COVID-19 infection frequency was higher in patients categorized with higher CORADS and RSNA classification categories.

Severe Acute Respiratory Infection Surveillance during the Initial Phase of the COVID-19 Outbreak in North India: A Comparison of COVID-19 to Other SARI Causes

Introduction

World Health Organization proposes severe acute respiratory infection (SARI) case definition for coronavirus disease 2019 (COVID-19) surveillance; however, early differentiation between SARI etiologies remains challenging. We aimed to investigate the spectrum and outcome of SARI and compare COVID-19 to non-COVID-19 causes.

Patients and methods

A prospective cohort study was conducted between March 15, 2020, to August 15, 2020, at an adult medical emergency in North India. SARI was diagnosed using a “modified” case definition—febrile respiratory symptoms or radiographic evidence of pneumonia or acute respiratory distress syndrome of ≤14 days duration, along with a need for hospitalization and in the absence of an alternative etiology that fully explains the illness. COVID-19 was diagnosed with reverse transcription-polymerase chain reaction testing.

Results

In total, 95/212 (44.8%) cases had COVID-19. Community-acquired pneumonia (n = 57), exacerbation of chronic lung disease (n = 11), heart failure (n = 11), tropical febrile illnesses (n = 10), and influenza A (n = 5) were common non-COVID-19 causes. No between-group differences were apparent in age ≥60 years, comorbidities, oxygenation, leukocytosis, lymphopenia, acute physiology and chronic health evaluation (APACHE)-II score, CURB-65 score, and ventilator requirement at 24-hour. Bilateral lung distribution and middle-lower zones involvement in radiography predicted COVID-19. The median hospital stay was longer with COVID-19 (12 versus 5 days, p = 0.000); however, mortality was similar (31.6% versus 28.2%, p = 0.593). Independent mortality predictors were higher mean APACHE II in COVID-19 and early ventilator requirement in non-COVID-19 cases.

Conclusions

COVID-19 has similar severity and mortality as non-COVID-19 SARI but requires an extended hospital stay. Including radiography in the SARI definition might improve COVID-19 surveillance.

How to cite this article

Pannu AK, Kumar M, Singh P, Shaji A, Ghosh A, Behera A, et al. Severe Acute Respiratory Infection Surveillance during the Initial Phase of the COVID-19 Outbreak in North India: A Comparison of COVID-19 to Other SARI Causes. Indian J Crit Care Med 2021;25(7):761–767.