Chest CT versus RT-PCR for the detection of COVID-19: systematic review and meta-analysis of comparative studies

Diagnostic accuracy of a set of clinical and radiological criteria for screening of COVID-19 using RT-PCR as the reference standard

BACKGROUND

The gold-standard method for establishing a microbiological diagnosis of COVID-19 is reverse-transcriptase polymerase chain reaction (RT-PCR). This study aimed to evaluate the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of a set of clinical-radiological criteria for COVID-19 screening in patients with severe acute respiratory failure (SARF) admitted to intensive care units (ICUs), using reverse-transcriptase polymerase chain reaction (RT-PCR) as the reference standard.

METHODS

Diagnostic accuracy study including a historical cohort of 1009 patients consecutively admitted to ICUs across six hospitals in Curitiba (Brazil) from March to September, 2020. The sample was stratified into groups by the strength of suspicion for COVID-19 (strong versus weak) using parameters based on three clinical and radiological (chest computed tomography) criteria. The diagnosis of COVID-19 was confirmed by RT-PCR (referent).

RESULTS

With respect to RT-PCR, the proposed criteria had 98.5% (95% confidence interval [95% CI] 97.5-99.5%) sensitivity, 70% (95% CI 65.8-74.2%) specificity, 85.5% (95% CI 83.4-87.7%) accuracy, PPV of 79.7% (95% CI 76.6-82.7%) and NPV of 97.6% (95% CI 95.9-99.2%). Similar performance was observed when evaluated in the subgroups of patients admitted with mild/moderate respiratory disfunction, and severe respiratory disfunction.

CONCLUSION

The proposed set of clinical-radiological criteria were accurate in identifying patients with strong versus weak suspicion for COVID-19 and had high sensitivity and considerable specificity with respect to RT-PCR. These criteria may be useful for screening COVID-19 in patients presenting with SARF.

Conventional and Novel Diagnostic Tools for the Diagnosis of Emerging SARS-CoV-2 Variants

Accurate identification at an early stage of infection is critical for effective care of any infectious disease. The "coronavirus disease 2019 (COVID-19)" outbreak, caused by the virus "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)", corresponds to the current and global pandemic, characterized by several developing variants, many of which are classified as variants of concern (VOCs) by the "World Health Organization (WHO, Geneva, Switzerland)". The primary diagnosis of infection is made using either the molecular technique of RT-PCR, which detects parts of the viral genome's RNA, or immunodiagnostic procedures, which identify viral proteins or antibodies generated by the host. As the demand for the RT-PCR test grew fast, several inexperienced producers joined the market with innovative kits, and an increasing number of laboratories joined the diagnostic field, rendering the test results increasingly prone to mistakes. It is difficult to determine how the outcomes of one unnoticed result could influence decisions about patient quarantine and social isolation, particularly when the patients themselves are health care providers. The development of point-of-care testing helps in the rapid in-field diagnosis of the disease, and such testing can also be used as a bedside monitor for mapping the progression of the disease in critical patients. In this review, we have provided the readers with available molecular diagnostic techniques and their pitfalls in detecting emerging VOCs of SARS-CoV-2, and lastly, we have discussed AI-ML- and nanotechnology-based smart diagnostic techniques for SARS-CoV-2 detection.

COVID-19 lung infection segmentation from chest CT images based on CAPA-ResUNet

Coronavirus disease 2019 (COVID-19) epidemic has devastating effects on personal health around the world. It is significant to achieve accurate segmentation of pulmonary infection regions, which is an early indicator of disease. To solve this problem, a deep learning model, namely, the content-aware pre-activated residual UNet (CAPA-ResUNet), was proposed for segmenting COVID-19 lesions from CT slices. In this network, the pre-activated residual block was used for down-sampling to solve the problems of complex foreground and large fluctuations of distribution in datasets during training and to avoid gradient disappearance. The area loss function based on the false segmentation regions was proposed to solve the problem of fuzzy boundary of the lesion area. This model was evaluated by the public dataset (COVID-19 Lung CT Lesion Segmentation Challenge-2020) and compared its performance with those of classical models. Our method gains an advantage over other models in multiple metrics. Such as the Dice coefficient, specificity (Spe), and intersection over union (IoU), our CAPA-ResUNet obtained 0.775 points, 0.972 points, and 0.646 points, respectively. The Dice coefficient of our model was 2.51% higher than Content-aware residual UNet (CARes-UNet). The code is available at https://github.com/malu108/LungInfectionSeg.

How accurate are radiography and computed tomography in the diagnosis of COVID-19?-A Bayesian approach

Background

The role of radiology in patients with clinical suspicion of COVID-19 is evolving with scientific evidence, but there are differences in opinion on when and how the technique should be used for clinical diagnosis.

Purpose

To estimate the pre-test and post-test probability that a patient has COVID-19 in the event of a positive and/or negative result from chest X-ray and chest computed tomography (CT) radiological studies, comparing with those of real time polymerase chain reaction (RT-PCR) tests.

Methods

The literature on the sensitivity and specificity of the chest X-ray, chest CT, and RT-PCR was reviewed. Based on these reported data, the likelihood ratios (LR) were estimated and the pre-test probabilities were related to the post-test probabilities after positive or negative results.

Results

The chest X-ray has only a confirmatory value in cases of high suspicion. Chest CT analyses showed that when it is used as a general study, it has almost confirmatory value under high clinical suspicion. A chest CT classified with CO-RADS ≥ 4 has almost a diagnostic certainty of COVID-19 even with moderate or low clinical presumptions, and the CO-RADS 5 classification is almost pathognomonic before any clinical presumption. To rule out COVID-19 completely is only possible in very low clinical assumptions with negative RT-PCR and/or CT.

Conclusions

Chest X-ray and especially CT are fast studies that have the capacity to report high probability of COVID-19, being a real contribution to the concept of "probable case" and allowing support to be installed in an early and timely manner.

The Role of Community-Level Factors on Disparities in COVID-19 Infection Among American Indian/Alaska Native Veterans

OBJECTIVES

American Indian and Alaska Native (AI/AN) communities have been disproportionately affected by the coronavirus disease 2019 (COVID-19) pandemic. This study examines whether neighborhood characteristics mediate AI/AN versus White-non-Hispanic Veteran COVID-19 infection disparities, and whether mediation differs based on proximity to reservations.

METHODS

Using Veteran Health Administration's (VHA) national database of VHA users evaluated for COVID-19 infection (3/1/2020-8/25/2020), we examined whether census tract neighborhood characteristics (percent households overcrowded, without complete plumbing, without kitchen plumbing, and neighborhood socioeconomic status [n-SES]) mediated racial disparities in COVID-19 infection, using inverse odds-weighted logistic models controlling for individual-level characteristics. Using moderated mediation analyses, we assessed whether neighborhood mediating effects on disparities differed for those residing in counties containing/near federally recognized tribal lands (i.e., Contract Health Service Delivery Area [CHSDA] counties) versus not.

RESULTS

The percent of households without complete plumbing, percent without kitchen plumbing, and n-SES partially mediated AI/AN-White-non-Hispanic COVID-19 infection disparities (accounting for 17-35% of disparity) to a similar extent in CHSDA and non-CHSDA counties. The percent of households without kitchen plumbing had stronger mediating effects for CHSDA than non-CHSDA residents.

CONCLUSIONS

Neighborhood-level social determinants of health may contribute to the disproportionate COVID-19 infection burden on AI/ANs; differences are exacerbated among AI/ANs living near reservations.

The diagnostic performance of lung ultrasound for detecting COVID-19 in emergency departments: A systematic review and meta-analysis

PURPOSE

To perform a systematic review and meta-analysis of published literature investigating the use of lung ultrasound (LUS) on COVID-19 patients, in emergency point of care settings, and to determine its diagnostic value compared with lung computed tomography (LCT) diagnostic performance. Whilst using the real-time polymerase chain reaction test as the 'gold standard'.

METHODS

Literature searches were performed on MEDLINE, Embase, Web of Science, and PubMed databases for eligible studies. The LUS and LCT pooled diagnostic performance were measured using DerSimonian-Laird random effect method.

RESULT

Out of a total of 158 studies, 16 met the eligibility criteria and were included in this review. The pooled sensitivity, specificity, positive and negative likelihood ratios were 86.9%, 62.4%, 2.4 and 0.19, respectively for LUS and 93.5%, 72.6%, 3.3 and 0.05, respectively for LCT.

CONCLUSION

The lung ultrasound (LUS) demonstrated acceptable sensitivity but poor specificity when used independently to diagnose COVID-19 pneumonia patients in emergency departments, while the lung computed tomography showed higher performance. Thus, LUS can be used to supplement existing diagnostic tools and possibly for the triage of patients.

Clinical features associated with Severe Acute Respiratory Syndrome (SARS-COV2)

The present study was conducted to isolation and identification of Aspergillus fumigatus. Isolated from immunocompromised patients with (Diabetes, Cancer) by different identification methods including direct examination, laboratory culture and electron microscopy. During the period from (July to September 2016), a total of 50 swab were collected from immunocompromised patients with attending to the in AL- Sadder Medical City (the Center for Diabetes and Endocrinology) and (Euphrates middle Center for cancer diseases). In AL-Najaf Governorate, the samples were collected as following: 30 swab from the eyes of cancer patients who were suffering from prostate, leukemia, stomach and intestines cancer, also 20 swabs from the ears of diabetic patients. The percentage of female to male was as following, 29 females (58%) males and 21 (42%). In this study, the results show that the incidence of aspergillosis in women was higher than the male. The results of the present study reveal that the prevalence of aspergillosis from patient with cancer was more than diabetes patients which was 18 (66.66%) and 9 (33.33%), respectively.

The Role of Ionizing Radiation for Diagnosis and Treatment against COVID-19: Evidence and Considerations

The Coronavirus disease 2019 (COVID-19) pandemic continues to spread worldwide with over 260 million people infected and more than 5 million deaths, numbers that are escalating on a daily basis. Frontline health workers and scientists diligently fight to alleviate life-threatening symptoms and control the spread of the disease. There is an urgent need for better triage of patients, especially in third world countries, in order to decrease the pressure induced on healthcare facilities. In the struggle to treat life-threatening COVID-19 pneumonia, scientists have debated the clinical use of ionizing radiation (IR). The historical literature dating back to the 1940s contains many reports of successful treatment of pneumonia with IR. In this work, we critically review the literature for the use of IR for both diagnostic and treatment purposes. We identify details including the computed tomography (CT) scanning considerations, the radiobiological basis of IR anti-inflammatory effects, the supportive evidence for low dose radiation therapy (LDRT), and the risks of radiation-induced cancer and cardiac disease associated with LDRT. In this paper, we address concerns regarding the effective management of COVID-19 patients and potential avenues that could provide empirical evidence for the fight against the disease.

Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry

BACKGROUND

The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date.

METHOD

23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity.

FINDINGS

Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81-0.96) and specificity 0.88 (interquartile range 0.82-0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application.

CONCLUSIONS

This systematic review and meta-analysis demonstrates the potential for mass spectrometry and 'omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.