The aim of this study was to assess clinical findings, radiological data, pulmonary functions and physical capacity change over time and to investigate factors associated with radiological abnormalities after coronavirus disease 2019 (COVID-19) in non-comorbid patients. This prospective cohort study was conducted between April 2020 and June 2020. A total of 62 symptomatic in non-comorbid patients with COVID-19 pneumonia were included in the study. At baseline and the 2nd, 5th and 12th months, patients were scheduled for follow-up. Males represented 51.6% of the participants and overall mean age was 51.60 ± 12.45 years. The percentage of patients with radiological abnormalities at 2 months was significantly higher than at 5 months (P < .001). At 12 months, dyspnea frequency (P = .008), 6-minute walk test (6MWT) distance (P = .045), BORG-dyspnea (P < .001) and BORG-fatigue (P < .001) scores was significantly lower, while median SpO2 after 6MWT (P < .001) was significantly higher compared to results at 2 months. The presence of radiological abnormalities at 2 months was associated with the following values measured at 5 months: advanced age (P = .006), lung involvement at baseline (P = .046), low forced expiratory volume in 1 second (P = .018) and low forced vital capacity (P = .006). Even in COVID-19 patients without comorbidities, control computed tomography at 2 months and pulmonary rehabilitation may be beneficial, especially in COVID-19 patients with advanced age and greater baseline lung involvement.

Aim: The evolution of coagulation factors in pregnant patients infected with SARS-CoV-2 during the pandemic is still debated. However, few studies have been carried out to evaluate the silent alterations of blood values in mild forms of the disease. Methods:A total of 153 pregnant patients with an asymptomatic form of COVID-19 and 306 healthy pregnant patients, who were admitted for delivery in our hospital between April 1, 2020 and March 1, 2022, were studied. The blood values harvested closest to the time of delivery were considered. Results:There was a significant variability in values of fibrinogen, prothrombin time, though these were still within normal limits. Conclusions:Pregnant patients with mild forms of COVID-19 displayed some blood alterations, even if they were asymptomatic for COVID-19.

[This retracts the article DOI: 10.1155/2022/9009406.].

During the early phase of the COVID-19 pandemic, reverse transcriptase-polymerase chain reaction (RT-PCR) testing faced limitations, prompting the exploration of machine learning (ML) alternatives for diagnosis and prognosis. Providing a comprehensive appraisal of such decision support systems and their use in COVID-19 management can aid the medical community in making informed decisions during the risk assessment of their patients, especially in low-resource settings. Therefore, the objective of this study was to systematically review the studies that predicted the diagnosis of COVID-19 or the severity of the disease using ML. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), we conducted a literature search of MEDLINE (OVID), Scopus, EMBASE, and IEEE Xplore from January 1 to June 31, 2020. The outcomes were COVID-19 diagnosis or prognostic measures such as death, need for mechanical ventilation, admission, and acute respiratory distress syndrome. We included peer-reviewed observational studies, clinical trials, research letters, case series, and reports. We extracted data about the study's country, setting, sample size, data source, dataset, diagnostic or prognostic outcomes, prediction measures, type of ML model, and measures of diagnostic accuracy. Bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO), with the number CRD42020197109. The final records included for data extraction were 66. Forty-three (64%) studies used secondary data. The majority of studies were from Chinese authors (30%). Most of the literature (79%) relied on chest imaging for prediction, while the remainder used various laboratory indicators, including hematological, biochemical, and immunological markers. Thirteen studies explored predicting COVID-19 severity, while the rest predicted diagnosis. Seventy percent of the articles used deep learning models, while 30% used traditional ML algorithms. Most studies reported high sensitivity, specificity, and accuracy for the ML models (exceeding 90%). The overall concern about the risk of bias was "unclear" in 56% of the studies. This was mainly due to concerns about selection bias. ML may help identify COVID-19 patients in the early phase of the pandemic, particularly in the context of chest imaging. Although these studies reflect that these ML models exhibit high accuracy, the novelty of these models and the biases in dataset selection make using them as a replacement for the clinicians' cognitive decision-making questionable. Continued research is needed to enhance the robustness and reliability of ML systems in COVID-19 diagnosis and prognosis.

A 29-year-old woman was admitted with a diagnosis of ischemic enteritis. She had a coronavirus disease 2019 (COVID-19) infection four weeks before this visit and continued to experience a cough. Four months before, she received the third COVID-19 vaccine. Chest computer tomography revealed scattered ground-glass opacities in both upper lobes. Based on abnormalities in chest imaging, eosinophilia, and a high level of fractional exhaled nitric oxide, she was diagnosed with eosinophilic lower airway inflammation due to COVID-19. Since the visit, the patient had an intermittent fever and no radiological improvement, so systemic corticosteroid treatment was initiated, and the symptoms and clinical findings improved. Clinicians should know the potential association between COVID-19 and eosinophilic lower airway inflammation, which may still occur despite multiple vaccinations.

The case describes how musculoskeletal disease can manifest in coronavirus disease. The most reported symptoms of covid infection are cough, fever and myalgia. Myalgia and myositis are similar conditions in that they both describe muscular pain and fatigue. However, they are distinguishable in that myalgia is usually benign and self-limiting whilst untreated myositis can lead to serious complications often requiring hospital admission. This case report aims to familiarise physicians with atypical presentations of coronavirus disease to prevent delays in diagnosis and treatment. Timely treatment of covid-induced myositis can decrease in-hospital mortality rates and improve patient outcomes.

During the corona virus disease 2019 (COVID-19) pandemic period, rapid screening of covid-19 patients has been of great interest by developing a fluorescent sensor for complexation with nonanal, which is a marker for Covid-19 detection in sweat. Solid phase micro-extraction gas chromatography-mass spectrometry (SPME GC-MS) was initially used to quantify nonanal in armpit sweat samples based on an external calibration curve. A sample containing a nonanal content above the threshold of 1.04 μL is expected to be COVID-19 positive with a sensitivity and specificity of 87% and 89%, respectively, validated by comparison with RT-PCR results. For more practical applications, helicene dye-encapsulated ethyl cellulose, namely EC@dyeNH, was applied to screen 140 sweat samples collected from the foreheads of volunteers. The mixed sensor and sweat solution droplets were then visualized and imaged under blacklight. The COVID-19 positive droplets exhibited yellow fluorescence emission, the brightness of which could be measured by using ImageJ in the grey scale. With the optimum color intensity of >73 for positive results, the screening performance was observed with a sensitivity and specificity of 96% and 93%, respectively. The overall test time of this method is approximately less than 15 min. This alternative method offers a promising practical screening approach for the diagnosis of COVID-19 in sweat.

After the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, a novel mRNA vaccine (BNT162b2) was developed at an unprecedented speed. Although most countries have achieved widespread immunity from vaccines and infections, yet people, even who have recovered from SARS-CoV-2 infection, are recommended to receive vaccination due to their effectiveness in lowering the risk of recurrent infection. However, the BNT162b2 vaccine has been reported to increase the risk of myocarditis. To our knowledge, for the first time in this study, we tracked changes in the chromatin dynamics of peripheral blood mononuclear cells (PBMCs) in the patient who underwent myocarditis after BNT162b2 vaccination. A longitudinal study of chromatin accessibility using concurrent analysis of single-cell assays for transposase-accessible chromatin with sequencing and single-cell RNA sequencing showed downregulation of interferon signaling and upregulated RUNX2/3 activity in PBMCs. Considering BNT162b2 vaccination increases the level of interferon-α/γ in serum, our data highlight the immune responses different from the conventional responses to the vaccination, which is possibly the key to understanding the side effects of BNT162b2 vaccination.

Flow cytometry is a versatile tool with excellent capabilities to detect and measure multiple characteristics of a population of cells or particles. Notable advancements in in vivo photoacoustic flow cytometry, coherent Raman flow cytometry, microfluidic flow cytometry, etc. have been achieved in the last two decades, which endows flow cytometry with new functions and expands its applications in basic research and clinical practice. The advanced flow cytometry broadens the tools available to researchers to conduct research involving cancer detection, microbiology (COVID-19, HIV, bacteria, etc.), and nucleic acid analysis. This review presents an overall picture of advanced flow cytometers and provides not only a clear understanding of their mechanisms but also new insights into their practical applications. We identify the latest trends in this area and aim to raise awareness of advanced techniques of flow cytometry. We hope this review expands the applications of flow cytometry and accelerates its clinical translation. This article is protected by copyright. All rights reserved.

We evaluated the new 2.0 version of the Roche Diagnostics SARS-CoV-2 Rapid Antigen Test (RAT 2.0) for the detection of SARS-CoV-2. Our evaluation material comprised of nasopharyngeal samples of 140 persons positive for SARS-CoV-2 nucleic acid amplification test (NAAT) and of 100 persons negative for SARS-CoV-2 NAAT. The sensitivity limit of the RAT 2.0 was further estimated with the additional selected samples of 27 persons with high NAAT cycle threshold (Ct) value representing low viral load. For the detection of possible cross-reactions in the RAT 2.0, routine respiratory samples positive for influenza A (N=5), respiratory syncytial virus (RSV) (N=4), or combined RSV and human coronavirus OC43 (N=1) were included in the study material. The overall sensitivity of the RAT 2.0 was 92.1% and specificity 100%. When evaluating the samples with NAAT Ct value ≤30, the sensitivity was 97.0%. All samples for cross-reactivity testing containing other viruses instead of SARS-CoV-2 remained negative in RAT 2.0. According to our findings, this RAT 2.0 offers a reliable tool for the diagnostics of acute COVID-19 in this pandemic environment.

COVID-19 resulted in extensive morbidity and mortality worldwide. SARS-CoV-2 evolved rapidly, with increasing transmission due to Variants of Concern (VOC). Identifying VOC became important but genome submissions from low-middle income countries (LMIC) remained low leading to gaps in genomic epidemiology. We demonstrate the use of a specific mutation RT-PCR based approach to identify VOC in SARS-CoV-2 positive samples through the pandemic in Pakistan. We selected 2150 SARS-CoV-2 PCR positive respiratory specimens tested between April 2021 and February 2022, at the Aga Khan University Hospital Clinical Laboratories, Karachi, Pakistan. Commercially available RT-PCR assays were used as required for mutations in Spike protein (N501Y, A570D, E484K, K417N, L452R, P681R and deletion69_70) to identify Alpha, Beta, Gamma, Delta, and Omicron variants respectively. Three pandemic waves associated with Alpha, Delta and Omicron occurred during the study period. Of the samples screened, VOC were identified in 81.7% of cases comprising mainly; Delta (37.2%), Alpha (29.8%) and Omicron (17.1%) variants. During 2021, Alpha variants were predominant in April and May; Beta and Gamma variants emerged in May and peaked in June; the Delta variant peaked in July and remained predominant until November. Omicron (BA.1) emerged in December 2021 and remained predominant until February 2022. The CT values of Alpha, Beta, Gamma and Delta were all significantly higher than that of Omicron variants (p<0.0001). We observed VOC through the pandemic waves using spike mutation specific RT-PCR assays. We show the spike mutation specific RT-PCR assay is a rapid, low-cost and adaptable for the identification of VOC as an adjunct approach to NGS to effectively inform the public health response. Further, by associating the VOC with CT values of its diagnostic PCR we gain information regarding the viral load of samples and therefore the level of transmission and disease severity in the population.

The World Health Organization (WHO) declared a pandemic in response to the coronavirus COVID-19 in 2020, which resulted in numerous deaths worldwide. Although the disease appears to have lost its impact, millions of people have been affected by this virus, and new infections still occur. Identifying COVID-19 requires a reverse transcription-polymerase chain reaction test (RT-PCR) or analysis of medical data. Due to the high cost and time required to scan and analyze medical data, researchers are focusing on using automated computer-aided methods. This review examines the applications of deep learning (DL) and machine learning (ML) in detecting COVID-19 using medical data such as CT scans, X-rays, cough sounds, MRIs, ultrasound, and clinical markers. First, the data preprocessing, the features used, and the current COVID-19 detection methods are divided into two subsections, and the studies are discussed. Second, the reported publicly available datasets, their characteristics, and the potential comparison materials mentioned in the literature are presented. Third, a comprehensive comparison is made by contrasting the similar and different aspects of the studies. Finally, the results, gaps, and limitations are summarized to stimulate the improvement of COVID-19 detection methods, and the study concludes by listing some future research directions for COVID-19 classification.

In this report, we present the case of a 72-year-old female diagnosed with an aortic dissection variant and bilateral pulmonary emboli (PE) in the setting of Coronavirus Disease of 2019 (COVID-19) infection. The patient was transported from home to the emergency department (ED) via emergency medical services (EMS) with acute chest pain and dyspnea. After arriving at the ED, she was hypoxic on her baseline supplemental O2 requirement and tachycardic and tachypneic. Computed tomography (CT) angiogram of the chest showed evidence of possible thoracic aortic dissection and bilateral PE. The patient was ultimately transported to a tertiary center for operative aortic repair and bilateral embolectomy and, fortunately, survived the procedures. Interestingly, during operative repair of the aorta, no obvious dissection flap was noted, but rather evidence of a limited tear in the intimal layer of the aorta. This is an interesting case as acute aortic injuries in the setting of COVID-19 infection have not been as widely documented as PE in the setting of COVID and highlight the need for further research on the possible association between them.

This study aimed to explore how metaphors were used to interpret the pandemic and to address its challenges in primary and secondary schools in Reggio Emilia, Italy. A questionnaire was administered to educators and teachers to understand how languages, images, and metaphors were used by themselves and their students to talk about the pandemic and their experiences of living with it. The goal of the questionnaire was to guide critical reflection and encourage more informed language choices. While the existing literature points out the alleged overuse of war metaphors and military frames in public discourse, our findings show that war metaphors are relatively frequent, with other metaphorical frames widely used by teachers and educators to foster resilient attitudes in students. Moreover, in their professional contexts, teachers and educators mostly use metaphorical frames involving resilient attitudes. Our interpretation of the results supports the hypothesis that the purposeful use and deliberate production of metaphors support the choice of metaphors with positive, constructive implications. Finally, some implications of these findings on the theory of metaphor and the methodology of the research are discussed.

Administration of the ChAdOx1 nCoV-19 (AstraZeneca) vaccination has recently been associated with rare, unusual cases of thrombotic events. We report a case of a 55-year-old woman who presented to hospital with headaches, petechial rashes and bruising-7 days after receiving her first vaccine dose. Blood tests showed low platelets, a markedly high d-dimer and positive anti-platelet factor 4 antibodies. Computed tomography (CT) of head and venogram showed features consistent with venous sinus thrombosis. She was immediately started on IV pooled immunoglobulin therapy, high-dose prednisolone and full anticoagulation. Subsequent magnetic resonance imaging of head and venogram supported the initial CT findings, with features suggestive of a small-volume venous sinus thrombosis. Additionally, CT pulmonary angiogram revealed a right-sided segmental pulmonary embolism. Our case highlights the importance of increased awareness of this complication after covid vaccination and how searching for distal thrombotic events and liaison with tertiary centres influence clinical outcomes.