Reverse-transcriptase polymerase chain reaction versus chest computed tomography for detecting early symptoms of COVID-19. A diagnostic accuracy systematic review and meta-analysis

Differences of the Chest Images Between Coronavirus Disease 2019 (COVID-19) Patients and Influenza Patients: A Systematic Review and Meta-analysis

Background: Coronavirus disease 2019 (COVID-19) and influenza are two infectious diseases that can pose a great threat to human health. We aimed to compare the differences in chest images between patients with COVID-19 and influenza to deepen the understanding of these two diseases. Methods: We searched PubMed, Embase and Web of Science for articles published before December 25, 2023, and performed a meta-analysis using Stata 14.0 with a random-effects model. The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Twenty-six articles with 2,159 COVID-19 patients and 1,568 influenza patients were included in the meta-analysis. By comparing chest computed tomography (CT) and chest X-ray, we found that COVID-19 patients had more peripheral lung lesions (OR=3.66, 95% CI: 1.84-7.31). Although COVID-19 patients had more bilateral lung involvement (OR=1.74, 95% CI: 0.90-3.38) and less unilateral lung involvement (OR=0.67, 95% CI: 0.44-1.02), these two results were not statistically significant. Patients with COVID-19 showed more ground-glass opacities (OR=2.83, 95% CI: 1.85-4.32), reverse halo signs (OR=3.47, 95% CI: 2.37-5.08), interlobular septal thickening (OR=2.16, 95% CI: 1.55-3.01), vascular enlargement (OR=5.00, 95% CI: 1.80-13.85) and crazy-paving patterns (OR=2.63, 95% CI: 1.57-4.41) on chest images than patients with influenza. We also found that compared with influenza patients, pleural effusion was rare in COVID-19 patients (OR=0.15, 95% CI: 0.07-0.31). Conclusions: There are some differences in the manifestations and distributions of lesions between patients with COVID-19 and influenza on chest images, which is helpful to distinguish these two infectious diseases.

Cost-effectiveness analysis of COVID-19 tests in the unified health system

BACKGROUND

To evaluate the cost-effectiveness ratio and economic impact of the Rapid Antigen Test (TR-Ag) to replace RT-PCR for the detection of the new Coronavirus in the Unified Health System (SUS).

METHODS

This is a cost-effectiveness analysis. Clinical protocols were used for the diagnosis of COVID-19 at the São José Municipal Hospital, located in the city of Itaberá-SP. The Incremental Cost-Effectiveness Ratio (ICER) was divided into two scenarios. In the first, the accuracy reported by the test manufacturers was included, and in the second, the cost resulting from a systematic review. Both were compared with the performance of the RT-PCR test. The increase in diagnoses was chosen as a health outcome and absenteeism was used as a criterion for assessing the economic impact.

RESULTS

The analysis resulted in incremental cost-effectiveness ratios of R$ 42,136.67 and R$ 68,329.73 for every thousand tests, according to the accuracy of the manufacturers' TR-Ag tests and what is reported in the literature in relation to RT-PCR, respectively. The average value found for the RT-PCR test (R$ 202.87) represents an increase of 165.32% in cost in relation to the value found for the TR-Ag. 4,305 tests were performed between April 2020 and December 2021 at the referral hospital. Also, maintaining the use of RT-PCR as the first choice for diagnosing COVID-19 and regulating absenteeism in the economically active population could have an impact of up to R$ 1,022,779.68 on municipal management.

CONCLUSION

It is concluded that the TR-Ag are configured as a cost-effective alternative for the SUS in the detection of the new Coronavirus. The strategy becomes economically favorable for the expansion of testing, combating the COVID-19 pandemic and reducing the impact on the local economy. However, studies are needed to validate the accuracy of the tests so that economic evaluations on the subject are more assertive.

A Review of Crucial Radiological Investigations in the Management of COVID-19 Cases

Chest X-ray, chest CT, and lung ultrasound are the most common radiological interventions used in the diagnosis and management of coronavirus disease 2019 (COVID-19) patients. The purpose of this literature review, which was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, is to determine which radiological investigation is crucial for that purpose. PubMed, Medline, American Journal of Radiology (AJR), Public Library of Science (PLOS), Elsevier, National Center for Biotechnology Information (NCBI), and ScienceDirect were explored. Seventy-two articles were reviewed for potential inclusion, including 50 discussing chest CT, 15 discussing chest X-ray, five discussing lung ultrasound, and two discussing COVID-19 epidemiology. The reported sensitivities and specificities for chest CT ranged from 64 to 98% and 25 to 88%, respectively. The reported sensitivities and specificities for chest X-rays ranged from 33 to 89% and 11.1 to 88.9%, respectively. The reported sensitivities and specificities for lung ultrasound ranged from 93 to 96.8% and 21.3 to 95%, respectively. The most common findings on chest CT include ground glass opacities and consolidation. The most common findings on chest X-rays include opacities, consolidation, and pleural effusion. The data indicate that chest CT is the most effective radiological tool for the diagnosis and management of COVID-19 patients. The authors support the continued use of reverse transcription polymerase chain reaction (RT-PCR), along with physical examination and contact history, for such diagnosis. Chest CT could be more appropriate in emergency situations when quick triage of patients is necessary before RT-PCR results are available. CT can also be used to visualize the progression of COVID-19 pneumonia and to identify potential false positive RT-PCR results. Chest X-ray and lung ultrasound are acceptable in situations where chest CT is unavailable or contraindicated.

Progress and Challenges of Point-of-Need Photonic Biosensors for the Diagnosis of COVID-19 Infections and Immunity

The new coronavirus disease, COVID-19, caused by SARS-CoV-2, continues to affect the world and after more than two years of the pandemic, approximately half a billion people are reported to have been infected. Due to its high contagiousness, our life has changed dramatically, with consequences that remain to be seen. To prevent the transmission of the virus, it is crucial to diagnose COVID-19 accurately, such that the infected cases can be rapidly identified and managed. Currently, the gold standard of testing is polymerase chain reaction (PCR), which provides the highest accuracy. However, the reliance on centralized rapid testing modalities throughout the COVID-19 pandemic has made access to timely diagnosis inconsistent and inefficient. Recent advancements in photonic biosensors with respect to cost-effectiveness, analytical performance, and portability have shown the potential for such platforms to enable the delivery of preventative and diagnostic care beyond clinics and into point-of-need (PON) settings. Herein, we review photonic technologies that have become commercially relevant throughout the COVID-19 pandemic, as well as emerging research in the field of photonic biosensors, shedding light on prospective technologies for responding to future health outbreaks. Therefore, in this article, we provide a review of recent progress and challenges of photonic biosensors that are developed for the testing of COVID-19, consisting of their working fundamentals and implementation for COVID-19 testing in practice with emphasis on the challenges that are faced in different development stages towards commercialization. In addition, we also present the characteristics of a biosensor both from technical and clinical perspectives. We present an estimate of the impact of testing on disease burden (in terms of Disability-Adjusted Life Years (DALYs), Quality Adjusted Life Years (QALYs), and Quality-Adjusted Life Days (QALDs)) and how improvements in cost can lower the economic impact and lead to reduced or averted DALYs. While COVID19 is the main focus of these technologies, similar concepts and approaches can be used and developed for future outbreaks of other infectious diseases.

Indications for accurate and appropriate use of personal protective equipment for healthcare professionals. A systematic review

BACKGROUND

The speed of the spread of coronavirus disease 2019 (COVID-19) has put enormous pressure on hospitals and other healthcare facilities. This, together with blockages in several countries, has hindered the availability and accessibility of the necessary personal protective equipment (PPE).

OBJECTIVE

To identify, systematically evaluate and summarize the available scientific evidence on the efficacy, safety, safe use and reuse of PPE for healthcare professionals, for preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

DESIGN AND SETTING

Systematic review of studies analyzing products for disinfecting and enabling reuse of PPE for coronavirus within the evidence-based health program of a federal university in São Paulo (SP), Brazil.

METHODS

A systematic search of the relevant literature was conducted in the PubMed, EMBASE, Cochrane Library, CINAHL, SCOPUS, Web of Science and LILACS databases, for articles published up to November 30, 2020.

RESULTS

Ten studies were selected. These analyzed the use of N95, surgical and cotton masks, face shields, flexible enclosures with plastic covers or polycarbonate intubation boxes and plastic curtains; and also PPE disinfection using several substances.

CONCLUSION

Combined use of a face shield with a N95 mask proved to be superior to other associations for protecting healthcare workers. Some products are useful for disinfecting PPE, such as 70% ethanol, 0.1% sodium hypochlorite and a mixture of quaternary ammonium and H2O2, and hydrogen peroxide. Ultraviolet light and dry heat at 70 °C can be used to decontaminate N95 masks.

REGISTRATION NUMBER

DOI: 10.17605/OSF.IO/4V5FD at the OPENSCIENCE Framework.

Computed tomography findings in 3,557 COVID-19 infected children: a systematic review

Background

Although it was assumed in the early stages of the coronavirus disease 2019 (COVID-19) outbreak that the novel coronavirus infection was uncommon among children, the number of infected children has since been increasing significantly. Real-time polymerase chain reaction (RT-PCR) is the gold standard modality for the diagnosis of COVID-19 infection. In adults, chest CT is performed as an adjunct for identifying suspected COVID-19 cases along with patients' management and follow-up. However, CT findings in COVID-19 children studies have shown a diverse incidence of abnormal CT and finding patterns that made CT scan necessity to have remained controversial. The aim of the present review was to comprehensively determine the imaging findings of chest CT scans of confirmed COVID-19-infected pediatric patients through a systematic review of the available published studies.

Methods

A systematic literature search was performed in the PubMed, Embase, Scopus, and Web of Science core collection databases (four databases including SSCI, SCIE, AHCI, and ESCI) to find original articles containing chest CT findings in children with COVID-19 through May 7, 2021. This review included 81 articles published in English that in total included 3,557 pediatric patients.

Results

This review included 81 articles published in English that in total included 3,557 pediatric patients. Among the total confirmed coronavirus-infected cases (via RT-PCR test), two-thirds had abnormal chest CT findings; among these patients, 549 (37.8%) had bilateral lung involvement, and 475 (32.7%) had unilateral disease. Regarding the types of lung lesions, ground glass opacities were observed in 794 (54.7%) of patients, and consolidation was observed in 10.2%; moreover, halo sign, discrete pulmonary nodules, interstitial abnormalities or reticulations, and vascular thickening shadows were reported in 7.4%, 2.6%, 9.7% and 1.7% of the patients, respectively.

Discussion

This review revealed that chest CT scan manifestations in majority of COVID-19 positive children are mild, so regarding the risk of radiation exposure, it is reasonable to confine CT scan to individual cases that its benefits outweigh the risks.

Diagnostic Test Accuracy of Deep Learning Detection of COVID-19: A Systematic Review and Meta-Analysis

RATIONALE AND OBJECTIVE

To perform a meta-analysis to compare the diagnostic test accuracy (DTA) of deep learning (DL) in detecting coronavirus disease 2019 (COVID-19), and to investigate how network architecture and type of datasets affect DL performance.

MATERIALS AND METHODS

We searched PubMed, Web of Science and Inspec from January 1, 2020, to December 3, 2020, for retrospective and prospective studies on deep learning detection with at least reported sensitivity and specificity. Pooled DTA was obtained using random-effect models. Sub-group analysis between studies was also carried out for data source and network architectures.

RESULTS

The pooled sensitivity and specificity were 91% (95% confidence interval [CI]: 88%, 93%; I2 = 69%) and 92% (95% CI: 88%, 94%; I2 = 88%), respectively for 19 studies. The pooled AUC and diagnostic odds ratio (DOR) were 0.95 (95% CI: 0.88, 0.92) and 112.5 (95% CI: 57.7, 219.3; I2 = 90%) respectively. The overall accuracy, recall, F1-score, LR+ and LR- are 89.5%, 89.5%, 89.7%, 23.13 and 0.13. Sub-group analysis shows that the sensitivity and DOR significantly vary with the type of network architectures and sources of data with low heterogeneity are (I2 = 0%) and (I2 = 18%) for ResNet architecture and single-source datasets, respectively.

CONCLUSION

The diagnosis of COVID-19 via deep learning has achieved incredible performance, and the source of datasets, as well as network architectures, strongly affect DL performance.

How did radiologists' diagnostic performance has changed in COVID-19 pneumonia: A single-centre retrospective study

AIMS

Delay and false positivity in PCR test results have necessitated accurate chest CT reporting for the management of patients with COVID-19-suspected symptoms. Pandemic related workload and level of experience on covid-dedicated chest CT scans might have affected the diagnostic performance of on-call radiologists. The aim of this study was to reveal the interpretation errors (IEs) in chest CT reports of COVID-19-suspected patients admitted to the Emergency Room (ER).

METHODS

Chest CT scans between March and June 2020 were re-evaluated and compared with the former reports and PCR test results. CT scan results were classified into four groups. Parenchymal involvement ratios, radiology departments' workload, COVID-19-related educational activities have been examined.

RESULTS

Out of 5721 Chest CT scans, 783 CTs belonging to 664 patients (340 female, 324 male) were included in this study. PCR test was positive in 398; negative in 385 cases. PCR positivity was found to be highest in "normal" and "typical for covid" groups whereas lowest in "atypical for covid" and "not covid" groups. 5%-25% parenchymal involvement ratio was found in 84.2% of the cases. Regarding the number of chest CT scans performed, radiologists' workload has found to be increased six-folds. With the re-evaluation, a total of 145 IEs (18.5%) have been found. IEs were mostly precipitated in the first two months (88.3%) and mostly in the "not covid" class (60%) regardless of PCR positivity. COVID-19 and radiology entitled educational activities along with the ER admission rates within the first two months of the pandemic have seemed to be related to the decline of IEs within time.

CONCLUSION

COVID-19 pandemic made a great impact on radiology departments with an inevitable burden of daily chest CT reporting. This workload and concomitant factors have effects on diagnostic challenges in COVID-19 pneumonia.

Chest computed tomography versus RT-PCR in early diagnostics of COVID-19 - a systematic review with meta-analysis

The purpose of this study was to compare the sensitivity and specificity of computed tomography (CT) scans of the chests of patients with the reference reverse-transcription real-time polymerase chain reaction (RT-PCR) in early diagnosis of COVID-19. A systematic review with meta-analysis for numerical outcomes was performed, including 10 studies (6528 patients). High risk of systematic bias (spectrum bias) was demonstrated in all studies, while in several studies research information bias was found to be possible. The sensitivity of CT examination ranged from 72% to 98%, and the specificity from 22% to 96%. The overall sensitivity of the CT scan was 91% and the specificity 87% (95% CI). Overall sensitivity of the RT-PCR reference test was lower (87%) than its specificity (99%) (95% CI). No clear conclusion could be drawn on the rationale of using CT scanning in the early diagnosis of COVID-19 in situations when specific clinical symptoms and epidemiological history would indicate coronavirus infection. The sensitivity of the CT test seems to be higher than that of the RT-PCR reference test, but this may be related to the mode of analysis and type of material analysed in genetic tests. CT scanning could be performed in symptomatic patients, with a defined time interval from symptom onset to performing CT or RT-PCR, and it should be explicitly included as an additional procedure when initial coronavirus genetic test results are negative, while clinical symptoms and epidemiological history indicate possible infection. However, a reference test showing the presence of coronavirus genetic material is essential throughout the diagnostic and treatment process.

A Comparison of Lung Ultrasound and Computed Tomography in the Diagnosis of Patients with COVID-19: A Systematic Review and Meta-Analysis

Background Lung ultrasound (LUS) and computed tomography (CT) can both be used for diagnosis of interstitial pneumonia caused by coronavirus disease 2019 (COVID-19), but the agreement between LUS and CT is unknown. Purpose to compare the agreement of LUS and CT in the diagnosis of interstitial pneumonia caused by COVID-19. Materials and Methods We searched PubMed, Cochrane library, Embase, Chinese Biomedicine Literature, and WHO COVID-19 databases to identify studies that compared LUS with CT in the diagnosis of interstitial pneumonia caused by COVID-19. We calculated the pooled overall, positive and negative percent agreements, diagnostic odds ratio (DOR) and the area under the standard receiver operating curve (SROC) for LUS in the diagnosis of COVID-19 compared with CT. Results We identified 1896 records, of which nine studies involving 531 patients were finally included. The pooled overall, positive and negative percentage agreements of LUS for the diagnosis of interstitial pneumonia caused by COVID-19 compared with CT were 81% (95% confidence interval [CI] 43–99%), 96% (95% CI, 80–99%, I² = 92.15%) and 80% (95%CI, 60–92%, I² = 92.85%), respectively. DOR was 37.41 (95% CI, 9.43–148.49, I² = 63.9%), and the area under the SROC curve was 0.94 (95% CI, 0.92–0.96). The quality of evidence for both specificity and sensitivity was low because of heterogeneity and risk of bias. Conclusion The level of diagnostic agreement between LUS and CT in the diagnosis of interstitial pneumonia caused by COVID-19 is high. LUS can be therefore considered as an equally accurate alternative for CT in situations where molecular tests are not available.

Estimating point prevalence of COVID-19 in Qatar's primary care registered population: an RT-PCR drive-through study protocol

BACKGROUND

The first COVID-19 cases in Qatar were reported on 29 February 2020. As the epidemic progresses, essential epidemiological information is needed to facilitate monitoring of COVID-19 in the population and plan the pandemic response in Qatar.

AIM

The primary aim of this cross-sectional study is to estimate the point prevalence of COVID-19 in Qatar's primary care registered population.

DESIGN & SETTING

A cross-sectional study design will be utilised. One publicly funded health centre from each of three geographical regions in Qatar will be identified as a study location and set up to facilitate a drive-through for the study.

METHOD

Primary Health Care Corporation (PHCC) is publicly funded and the largest primary care provider in Qatar. The study will include randomly selected individuals from the full list of PHCC's registered population on its electronic medical records system. The sample selection will be done using a proportional to size sampling technique stratified by age, sex, and nationality representative of the overall PHCC-registered population. Considering the total population registered in PHCC, a sample of 2080 is proposed. A questionnaire will be administered to collect sociodemographic information, and nasal and throat swab samples will be taken. Data will be analysed to report overall symptomatic and asymptomatic point prevalence of COVID-19.

CONCLUSION

This study, with the help of a randomly selected representative sample from Qatar's primary care registered population, will provide results that can be applied to the entire population. This study design will closely represent a real-world scenario of the outbreak and is likely to provide important data to guide COVID-19 pandemic planning and response in Qatar.

The Treaty of Influenza and SARS-CoV-2: Titans Versus Olympians

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