Phenol red as electrochemical indicator for highly sensitive quantification of SARS-CoV-2 by loop-mediated isothermal amplification detection.

The current COVID-19 pandemic has made patent the need for rapid and cost-effective diagnostic tests, crucial for future infectious outbreaks. Loop-mediated isothermal amplification (LAMP) is a promising and decentralized alternative to qPCR. In this work we have developed a sensitive, fast, and simple innovative methodology for quantification of SARS-CoV-2 RNA copies, combining reverse-transcription LAMP with electrochemical detection. This is based on the oxidation of phenol red (PR), a visual and electroactive LAMP indicator, which oxidation peak potential (Ep) changes with the progress of the LAMP reaction. Using that Ep shift as analytical signal, a calibration curve was obtained for fragment N1 copies of SARS-CoV2 (which provided better results than N or S fragments), with a potential shift of 16.2 mV per order of magnitude, and a practical limit of detection of 21 copies·µL-1. Moreover, the precision of Ep is excellent (RSD < 2%): 557 ± 5 mV for negative and 602 ± 7 mV for positive (2148 N fragment RNA copies·µL-1·-1) LAMP controls. This methodology has been applied to the analysis of nasopharyngeal swab samples, resulting in total concordance with clinical RT-qPCR results. Advances towards fully decentralization have been achieved by designing and fabricating a small portable heater for isothermal procedures, obtaining comparable results to those from a commercial benchtop thermal cycler.

Relationship between anal swab PCR for SARS-CoV-2 with gastrointestinal clinical manifestations and severity of COVID-19 infection in Indonesia.

Introduction: Coronavirus disease 2019 (COVID-19) cases caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indonesia remain high. The virus can bind with ACE2 receptor which is not only found in the lungs, but also in the digestive tract. Thus, it allows SARS-CoV-2 infection in the gastrointestinal tract, gastrointestinal manifestations, and detection of viral RNA on anal swab using polymerase chain reaction (PCR). There hasn't been similar study about the role of anal swab in Indonesia yet. Therefore, this study aims to determine the relationship between SARS-COV-2 anal swab PCR with gastrointestinal clinical manifestations, and the severity of COVID-19 in Indonesia. Methods: This is an analytical study with cross-sectional design. Samples were obtained from hospitalized COVID-19 patients from July 2020 to January 2021. Demographic data, clinical manifestations, severity, and SARS-CoV-2 anal swabs PCR were collected using case report form. Results: A total of136 patients were analyzed. 52 patients (38.2%) had positive SARS-CoV-2 anal swabs PCR and 84 patients (61.8%) had negative results. The most common gastrointestinal clinical manifestations were nausea and vomiting in 69 patients (50.7%), anorexia in 62 patients (45.6%), and abdominal pain in 31 patients (22.8%). There were 114 patients (83,8%) classified as mild-moderate symptoms and 22 patients (16,2%) classified as severe-critical symptoms. There was a statistically significant relationship between the gastrointestinal tract SARS-CoV-2 infection and gastrointestinal clinical manifestations (P=0.031). There was no statistically significant relationship between the gastrointestinal SARS-CoV-2 infection and the severity of COVID-19 infection (P = 0.844). Conclusions: This study showed there is a significant relationship between SARS-CoV-2 anal swab PCR with gastrointestinal clinical manifestations. There is no significant relationship between anal swab PCR with the severity of COVID-19 infection.

Comparison of semen parameters in the same patients before and after diagnosis of COVID-19.

Clinical and histopathological evidence suggest that the male reproductive system may be negatively impacted in patients with coronavirus disease (COVID-19). The objective of this study is to investigate the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on semen parameters by comparing semen analyses before and after COVID-19 diagnosis in the same patient. We retrospectively analyzed 342 semen analyses by reviewing medical records. The study included two groups of patients: (i) those who underwent two consecutive semen analyses within 6 months, one before (n = 114) and one after (n = 114) COVID-19 diagnosis, and (ii) a control group (n = 114) that was age-matched and did not receive a diagnosis of COVID-19. The study results indicated a significant decrease in semen volume, total sperm count per ejaculate, progressive motile sperm count, total motile sperm count, and normal sperm morphology after SARS-CoV-2 infection in comparison to their respective values before the infection. Subgroup analyses showed that the duration of COVID-19 diagnosis (short-term vs. long-term) did not impact the changes in semen parameters. However, fever during the COVID-19 process had a negative effect on semen parameters, particularly sperm concentration, unlike in patients without fever. In conclusion, our findings suggest that SARS-CoV-2 infection is associated with a decline in semen quality, which may potentially impact male fertility. Furthermore, it's important to note that the negative effects on semen parameters may persist in the long-term. Our results also indicate that fever during active infection could be a significant risk factor that negatively affects spermatogenesis.

An interpretable machine learning framework for diagnosis and prognosis of COVID-19.

Coronaviruses have affected the lives of people around the world. Increasingly, studies have indicated that the virus is mutating and becoming more contagious. Hence, the pressing priority is to swiftly and accurately predict patient outcomes. In addition, physicians and patients increasingly need interpretability when building machine models in healthcare. We propose an interpretable machine framework(KISM) that can diagnose and prognose patients based on blood test datasets. First, we use k-nearest neighbors, isolated forests, and SMOTE to pre-process the original blood test datasets. Seven machine learning tools Support Vector Machine, Extra Tree, Random Forest, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, Logistic Regression, and ensemble learning were then used to diagnose and predict COVID-19. In addition, we used SHAP and scikit-learn post-hoc interpretability to report feature importance, allowing healthcare professionals and artificial intelligence models to interact to suggest biomarkers that some doctors may have missed. The 10-fold cross-validation of two public datasets shows that the performance of KISM is better than that of the current state-of-the-art methods. In the diagnostic COVID-19 task, an AUC value of 0.9869 and an accuracy of 0.9787 were obtained, and ultimately Leukocytes, platelets, and Proteina C reativa mg/dL were found to be the most indicative biomarkers for the diagnosis of COVID-19. An AUC value of 0.9949 and an accuracy of 0.9677 were obtained in the prognostic COVID-19 task and Age, LYMPH, and WBC were found to be the most indicative biomarkers for identifying the severity of the patient.

Diagnostic evaluation of Panbio™ antigen rapid diagnostic test for SARS-CoV-2: A systematic review and meta-analysis.

INTRODUCTION: The reverse transcriptase polymerase chain reaction (RT-PCR) is the reference diagnostic method for the confirmation of SARS-CoV-2 infected cases. However, various antigen rapid diagnostic tests (Ag-RDTs) have been developed. The purpose of this meta-analysis study was to assess the diagnostic performance of Panbio™ Ag-RDT (Abbott Point of Care) in identifying the SARS-CoV-2 virus. METHODS: We systematically searched eight databases from March 2020 until March 2023 to look for potentially eligible articles. Diagnostic meta-analysis of Panbio™ Ag-RDT used diverse evaluation indicators, including sensitivity, specificity, Diagnostic Odds Ratio (DOR), and the area under the curve (AUC) value. RESULTS: Of the 794 articles identified, 49 studies met the inclusion criteria. The pooled estimates of Panbio™ Ag-RDT for the diagnosis of SARS-CoV-2 were 0,65 (95% CI: 0,64-0,66), 0,99 (95% CI: 0,99-1,00), 578,03 (95% CI: 333,37-1002,26) for sensitivity, specificity, and DOR, respectively. Moreover, the summary receiver operating characteristic (SROC) curve revealed an AUC value of 0,942 (95% CI: 0,941-0,943), suggesting an outstanding diagnostic accuracy. Subgroup and meta-regression analyses showed that continent, study period, age, study population and cycle threshold (Ct) values constituted a source of heterogeneity. Furthermore, we demonstrated proof of publication bias for DOR values analyzed using Deek's test (p = 0,001) and funnel plot. CONCLUSION: Panbio™ Ag-RDT presented an outstanding diagnostic accuracy in the detection of the SARS-CoV-2 virus in both adults and children with or without symptoms.

Diagnostic Efficacy of Chest Computed Tomography with a Dual-Reviewer Approach in Patients Diagnosed with Pneumonia Secondary to Severe Acute Respiratory Syndrome Coronavirus 2.

To compare the diagnostic effectiveness of chest computed tomography (CT) utilizing a single- versus a dual-reviewer approach in patients with pneumonia secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we conducted a retrospective observational study of data from a cross-section of 4809 patients with probable SARS-CoV-2 from March to November 2020. All patients had a CT radiological report and reverse-transcription polymerase chain reaction (PCR) results. A dual-reviewer approach was applied to two groups while conducting a comparative examination of the data. Reviewer 1 reported 108 patients negative and 374 patients positive for coronavirus disease 2019 (COVID-19) in group A, and 266 negative and 142 positive in group B. Reviewer 2 reported 150 patients negative and 332 patients positive for COVID-19 in group A, and 277 negative and 131 positive in group B. The consensus result reported 87 patients negative and 395 positive for COVID-19 in group A and 274 negative and 134 positive in group B. These findings suggest that a dual-reviewer approach improves chest CT diagnosis compared to a conventional single-reviewer approach.

COVID-19: Association of risk classification with the Modified Early Warning Score and hospital outcomes. / COVID-19: Asociación entre la clasificación de riesgo y el Modified Early Warning Score y los resultados hospitalarios.

OBJECTIVE: to evaluate the association of the risk classification categories with the Modified Early Warning Score and the outcomes of COVID-19 patients in the emergency service. METHOD: a crosssectional study carried out with 372 patients hospitalized with a COVID-19 diagnosis and treated at the Risk Classification Welcoming area from the Emergency Room. In this study, the patients' Modified Early Warning Score was categorized into without and with clinical deterioration, from 0 to 4 and from 5 to 9, respectively. Clinical deterioration was considered to be acute respiratory failure, shock and cardiopulmonary arrest. RESULTS: the mean Modified Early Warning Score was 3.34. In relation to the patients' clinical deterioration, it was observed that, in 43%, the time for deterioration was less than 24 hours and that 65.9% occurred in the Emergency Room. The most frequent deterioration was acute respiratory failure (69.9%) and the outcome was hospital discharge (70.3%). CONCLUSION: COVID-19 patients who had a Modified Early Warning Scores > 4 were associated with the urgent, very urgent and emergency risk classification categories, had more clinical deterioration, such as respiratory failure and shock, and evolved more to death, which shows that the Risk Classification Protocol correctly prioritized patients at risk of life.

Prevalence and risk factors of COVID-19 infection, mortality, and post-infection lung fibrosis in patients with type 2 diabetes: a cross-sectional study.

OBJECTIVES: The clinical course of coronavirus disease 2019 (COVID-19) infection is often aggressive, with unfavorable outcomes for those with comorbidities such as type 2 diabetes mellitus (T2DM). We aimed to assess the prevalence and risk factors of COVID-19 infection, mortality, and post-infection lung fibrosis in patients with COVID-19 infection who had T2DM. METHODS: In this cross-sectional study, we included adult patients with T2DM who attended an endocrinology clinic and underwent testing for COVID-19 infection. RESULTS: Among 1039 included patients, the mean age was 59.5 ± 11.0 years and 429 (41.3%) were men. Overall, 87.1% of patients had received COVID-19 vaccination and 32.3% had confirmed COVID-19 infection. The COVID-19-related mortality was 3.0% and rate of post-COVID-19 lung fibrosis was 19.1%. Vaccination was associated with lower COVID-19-related mortality (odds ratio [OR]: 0.03, 95% confidence interval [CI]: 0.0-0.3) and post-COVID-19 lung fibrosis risk (OR: 0.3, 95% CI: 0.1-0.9). CONCLUSION: Patients with T2DM exhibited a high prevalence of COVID-19 infection and associated mortality. However, COVID-19 vaccines were beneficial in reducing the risks of COVID-19-related mortality and post-infection lung fibrosis in these patients. COVID-19 vaccines and boosters are recommended for patients with T2DM. Further studies involving larger study populations are necessary to validate these findings.

Can variants, reinfection, symptoms and test types affect COVID-19 diagnostic performance? A large-scale retrospective study of AG-RDTs during circulation of Delta and Omicron variants, Czechia, December 2021 to February 2022.

BackgroundThe sensitivity and specificity of selected antigen detection rapid diagnostic tests (AG-RDTs) for SARS-CoV-2 were determined in the unvaccinated population when the Delta variant was circulating. Viral loads, dynamics, symptoms and tissue tropism differ between Omicron and Delta.AimWe aimed to compare AG-RDT sensitivity and specificity in selected subgroups during Omicron vs Delta circulation.MethodsWe retrospectively paired AG-RDT results with PCRs registered in Czechia's Information System for Infectious Diseases from 1 to 25 December 2021 (Delta, n = 20,121) and 20 January to 24 February 2022 (Omicron, n = 47,104).ResultsWhen confirmatory PCR was conducted on the same day as AG-RDT as a proxy for antigen testing close to peak viral load, the average sensitivity for Delta was 80.4% and for Omicron 81.4% (p < 0.05). Sensitivity in vaccinated individuals was lower for Omicron (OR = 0.94; 95% confidence interval (CI): 0.87-1.03), particularly in reinfections (OR = 0.83; 95% CI: 0.75-0.92). Saliva AG-RDT sensitivity was below average for both Delta (74.4%) and Omicron (78.4%). Tests on the European Union Category A list had higher sensitivity than tests in Category B. The highest sensitivity for Omicron (88.5%) was recorded for patients with loss of smell or taste, however, these symptoms were almost 10-fold less common than for Delta. The sensitivity of AG-RDTs performed on initially asymptomatic individuals done 1, 2 or 3 days before a positive PCR test was consistently lower for Omicron compared with Delta.ConclusionSensitivity for Omicron was lower in subgroups that may become more common if SARS-CoV-2 becomes an endemic virus.

Nirmatrelvir or Molnupiravir Use and Severe Outcomes From Omicron Infections.

Importance: Ritonavir-boosted nirmatrelvir and molnupiravir are currently used in the US and in other countries to treat nonhospitalized patients who have mild-to-moderate COVID-19 and who are at high risk for progression to severe disease. The associations of these 2 oral antiviral drugs with hospitalization and death resulting from infection with new SARS-CoV-2 Omicron subvariants, particularly BQ.1.1 and XBB.1.5, are unknown. Objective: To assess the association of nirmatrelvir or molnupiravir use with the risks of hospitalization and death among patients infected with new Omicron subvariants. Design, Setting, and Participants: This was a cohort study of patients who received a diagnosis of COVID-19 at Cleveland Clinic from April 1, 2022, to February 20, 2023 (during which the Omicron variant evolved from BA.2 to BA.4/BA.5, then to BQ.1/BQ.1.1, and finally to XBB/XBB.1.5) and who were at high risk of progressing to severe disease, with follow-up through 90 days after diagnosis. The final date for follow-up data collection was February 27, 2023. Exposures: Treatment with ritonavir-boosted nirmatrelvir or molnupiravir. Main Outcomes and Measures: The primary outcome was time to death. The secondary outcome was time to either hospitalization or death. The association of either nirmatrelvir or molnupiravir use with each outcome was measured by the hazard ratio (HR) adjusted for demographic factors, socioeconomic status, date of COVID-19 diagnosis, coexisting medical conditions, COVID-19 vaccination status, and previous SARS-CoV-2 infection. Results: There were 68 867 patients (29 386 [42.7%] aged ≥65 years; 26 755 [38.9%] male patients; 51 452 [74.7%] non-Hispanic White patients). Thirty of 22 594 patients treated with nirmatrelvir, 27 of 5311 patients treated with molnupiravir, and 588 of 40 962 patients who received no treatment died within 90 days of Omicron infection. The adjusted HRs of death were 0.16 (95% CI, 0.11-0.23) for nirmatrelvir and 0.23 (95% CI, 0.16-0.34) for molnupiravir. The adjusted HRs of hospitalization or death were 0.63 (95% CI, 0.59-0.68) for nirmatrelvir and 0.59 (95% CI, 0.53-0.66) for molnupiravir. The associations of both drugs with both outcomes were observed across subgroups defined by age, race and ethnicity, date of COVID-19 diagnosis, vaccination status, previous infection status, and coexisting conditions. Conclusions and Relevance: These findings suggest that the use of either nirmatrelvir or molnupiravir is associated with reductions in mortality and hospitalization in patients infected with Omicron, regardless of age, race and ethnicity, virus strain, vaccination status, previous infection status, or coexisting conditions. Both drugs can, therefore, be used to treat nonhospitalized patients who are at high risk of progressing to severe COVID-19.

Boletim epidemiológico de vírus respiratórios (RS): semana epidemiológica (SE) 34 de 2023 / Epidemiological bulletin of respiratory viruses (RS): epidemiological week (SE) 34 of 2023

Com a declaração do fim das emergências de saúde pública de importância Nacional (abril/2022) e Internacional (maio/2023) e o ressurgimentos dos outros vírus respiratórios, o Boletim de COVID-19 foi expandido e passa avaliar de forma integrada os agentes virais de importância à saúde pública. Utilizado o modelo de Vigilância Sentinela para monitoramento da circulação de vírus respiratórios de interesse à saúde pública nas Síndromes Gripais(SG). O objetivo desta estratégia é detectar novos agentes virais e/ou novas linhagens para oportunamente desencadear medidas de controle necessárias e reduzir a carga da doença na sociedade. (AU)

Diagnosis, Progress, and Treatment Update of Kawasaki Disease.

Kawasaki disease (KD) is an acute inflammatory disorder that primarily affects children and can lead to coronary artery lesions (CAL) if not diagnosed and treated promptly. The original clinical criteria for diagnosing KD were reported by Dr. Tomisaku Kawasaki in 1967 and have been used for decades. However, research since then has highlighted the limitations of relying solely on these criteria, as they might lead to underdiagnosis or delayed diagnosis, potentially increasing the risk of coronary artery complications. This review appears to discuss several important aspects related to KD diagnosis and management. The current diagnostic methods for KD might need updates, especially considering cases that do not fit the typical clinical criteria. Recognizing diagnostic pitfalls and distinguishing KD from other conditions that might have similar clinical presentations is essential. The differences and similarities between KD and Multisystem Inflammatory Syndrome in Children (MIS-C), another inflammatory condition that has been associated with COVID-19, were also reviewed. The review explores the potential role of eosinophil count, new biomarkers, microRNA panels, and scoring systems in aiding the diagnosis of KD. Overall, the review article provides a comprehensive overview of the evolving landscape of KD diagnosis and management, incorporating new diagnostic methods, biomarkers, and treatment approaches to improve patient outcomes and reduce the risk of complications.

The Diagnostic, Prognostic, and Therapeutic Potential of Cell-Free DNA with a Special Focus on COVID-19 and Other Viral Infections.

Cell-free DNA (cfDNA) in human blood serum, urine, and other body fluids recently became a commonly used diagnostic marker associated with various pathologies. This is because cfDNA enables a much higher sensitivity than standard biochemical parameters. The presence of and/or increased level of cfDNA has been reported for various diseases, including viral infections, including COVID-19. Here, we review cfDNA in general, how it has been identified, where it can derive from, its molecular features, and mechanisms of release and clearance. General suitability of cfDNA for diagnostic questions, possible shortcomings and future directions are discussed, with a special focus on coronavirus infection.

Flexible and Innovative Connectivity Solution to Support National Decentralized Infectious Diseases Point-of-Care Testing Programs in Primary Health Services: Descriptive Evaluation Study.

BACKGROUND: Molecular point-of-care (POC) testing for Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Trichomonas vaginalis (TV) has been available in regional and remote primary health services in Australia as part of a decentralized POC testing program since 2016 and for SARS-CoV-2 from 2020. As there was no suitable existing connectivity infrastructure to capture and deliver POC test results to a range of end users, a new system needed to be established. OBJECTIVE: The aim of the study is to design, implement, and optimize a connectivity system to meet clinical management, analytical quality management, and public health surveillance needs. METHODS: We used commercially available e-messaging technology coupled with adapted proprietary software to integrate a decentralized molecular POC testing platform (GeneXpert) in primary health services and interface with end-user databases. This connectivity infrastructure was designed to overcome key barriers to the implementation, integration, and monitoring of these large multijurisdictional infectious disease POC testing networks. Test result messages were tailored to meet end-user needs. Using centrally captured deidentified data, we evaluated the time to receipt of test results and completeness of accompanying demographic data. RESULTS: From January 2016 to April 2020, we operationalized the system at 31 health services across 4 jurisdictions and integrated with 5 different patient management systems to support the real-time delivery of 29,356 CT/NG and TV test results to designated recipients (patient management system and local clinical and central program databases). In 2019, 12,105 CT/NG and TV results were delivered, and the median time to receipt of results was 3.2 (IQR 2.2-4.6) hours, inclusive of test runtime. From May 2020 to August 2022, we optimized the system to support rapid scale-up of SARS-CoV-2 testing (105 services; 6 jurisdictions; 71,823 tests) and additional sexually transmissible infection testing (16,232 tests), including the electronic disease-specific notifications to jurisdictional health departments and alerts for connectivity disruption and positive results. In 2022, 19,355 results were delivered with an overall median transmission time of 2.3 (IQR 1.4-3.1) hours, 2.2 (IQR 1.2-2.3) hours for SARS-CoV-2 (n=16,066), 3.0 (IQR 2.0-4.0) hours for CT/NG (n=1843), and 2.6 (IQR 1.5-3.8) hours for TV (n=1446). Demographic data (age, sex, and ethnicity) were completed for 99.5% of test results in 2022. CONCLUSIONS: This innovative connectivity system designed to meet end-user needs has proven to be sustainable, flexible, and scalable. It represents the first such system in Australia established independent of traditional pathology providers to support POC testing in geographically dispersed remote primary health services. The system has been optimized to deliver real-time test results and has proven critical for clinical, public health, and quality management. The system has significantly supported equitable access to rapid diagnostics for infectious diseases across Australia, and its design is suitable for onboarding other POC tests and testing platforms in the future.

Challenges and improvements associated with transitions between hospitals and care homes during the COVID-19 pandemic: a qualitative study with care home and healthcare staff in England.

BACKGROUND: Care home residents transitioning from hospital are at risk of receiving poor-quality care with their safety being challenged by the SARS-CoV-2 virus (COVID-19) pandemic. Little is known about how care home staff worked with hospital staff and other healthcare professionals to address these challenges and make improvements to increase patient safety. OBJECTIVE: To gain insight into how the COVID-19 pandemic influenced the safety of transitions between hospital and care home. METHOD: Semi-structured interviews were conducted with care home staff and healthcare professionals involved in hospital to care home transitions including doctors, nurses, paramedics, pharmacists, social workers, and occupational therapists. Commonalities and patterns in the data were identified using thematic analysis. RESULTS: Seventy participants were interviewed. Three themes were developed, first, 'new challenges', described care homes were pressurised to receive hospital patients amidst issues with COVID-19 testing, changes to working practices and contentious media attention, which all impacted staff negatively. Second, 'dehumanisation' described how care home residents were treated, being isolated from others amounted to feelings of being imprisoned, caused fear and engendered negative reactions from families. Third, 'better ways of working' described how health and social care workers developed relationships that improved integration and confidence and benefited care provision. CONCLUSION: The COVID-19 pandemic contributed to and compounded high-risk hospital-to-care home discharges. Government policy failed to support care homes. Rapid discharge objectives exposed a myriad of infection control issues causing inhumane conditions for care home residents. However, staff involved in transitions continued to provide and improve upon care provision.

Rapid, tunable, and multiplexed detection of RNA using convective array PCR.

Detection of RNA targets is typically achieved through RT-qPCR or RNAseq. RT-qPCR is rapid but limited in number and complexity of targets detected, while RNAseq is high-throughput but takes multiple days. We demonstrate simultaneous amplification and detection of 28 distinct RNA targets from a single unsplit purified RNA sample in under 40 minutes using our convective array PCR (caPCR) technology. We integrate tunable strand displacement probes into caPCR to allow detection of RNA species with programmable sequence selectivity for either a single, perfectly matched target sequence or for targets with up to 2 single-nucleotide variants within the probe-binding regions. Tunable probes allow for robust detection of desired RNA species against high homology background sequences and robust detection of RNA species with significant sequence diversity due to community-acquired mutations. As a proof-of-concept, we experimentally demonstrated detection of 7 human coronaviruses and 7 key variants of concern of SARS-CoV-2 in a single assay.

Active cancer as the main predictor of mortality for COVID-19 in oncology patients in a specialized center.

Introduction: The role of the type, stage and status of cancer in the outcome of COVID-19 remains unclear. Moreover, the characteristic pathological changes of severe COVID-19 reveled by laboratory and radiological findings are similar to those due to the development of cancer itself and antineoplastic therapies. Objective: To identify potential predictors of mortality of COVID-19 in cancer patients. Materials and methods: A retrospective and cross-sectional study was carried out in patients with clinical suspicion of COVID-19 who were confirmed for COVID-19 diagnosis by RT-PCR testing at the National Institute of Neoplastic Diseases between April and December 2020. Demographic, clinical, laboratory and radiological data were analyzed. Statistical analyses included area under the curve and univariate and multivariate logistic regression analyses. Results: A total of 226 patients had clinical suspicion of COVID-19, the diagnosis was confirmed in 177 (78.3%), and 70/177 (39.5%) died. Age, active cancer, leukocyte count ≥12.8 × 109/L, urea ≥7.4 mmol/L, ferritin ≥1,640, lactate ≥2.0 mmol/L, and lung involvement ≥35% were found to be independent predictors of COVID-19 mortality. Conclusion: Active cancer represents the main prognosis factor of death, while the role of cancer stage and type is unclear. Chest CT is a useful tool in the prognosis of death from COVID-19 in cancer patients. It is a challenge to establish the prognostic utility of laboratory markers as their altered values it could have either oncological or pandemic origins.

Dual-stream EfficientNet with adversarial sample augmentation for COVID-19 computer aided diagnosis.

Though a series of computer aided measures have been taken for the rapid and definite diagnosis of 2019 coronavirus disease (COVID-19), they generally fail to achieve high enough accuracy, including the recently popular deep learning-based methods. The main reasons are that: (a) they generally focus on improving the model structures while ignoring important information contained in the medical image itself; (b) the existing small-scale datasets have difficulty in meeting the training requirements of deep learning. In this paper, a dual-stream network based on the EfficientNet is proposed for the COVID-19 diagnosis based on CT scans. The dual-stream network takes into account the important information in both spatial and frequency domains of CT scans. Besides, Adversarial Propagation (AdvProp) technology is used to address the insufficient training data usually faced by the deep learning-based computer aided diagnosis and also the overfitting issue. Feature Pyramid Network (FPN) is utilized to fuse the dual-stream features. Experimental results on the public dataset COVIDx CT-2A demonstrate that the proposed method outperforms the existing 12 deep learning-based methods for COVID-19 diagnosis, achieving an accuracy of 0.9870 for multi-class classification, and 0.9958 for binary classification. The source code is available at https://github.com/imagecbj/covid-efficientnet.

Deep Learning Assisted Surface-Enhanced Raman Spectroscopy (SERS) for Rapid and Direct Nucleic Acid Amplification and Detection: Toward Enhanced Molecular Diagnostics.

Surface-enhanced Raman scattering (SERS) has evolved into a robust analytical technique capable of detecting a variety of biomolecules despite challenges in securing a reliable Raman signal. Conventional SERS-based nucleic acid detection relies on hybridization assays, but reproducibility and signal strength issues have hindered research on directly amplifying nucleic acids on SERS surfaces. This study introduces a deep learning assisted ZnO-Au-SERS-based direct amplification (ZADA) system for rapid, sensitive molecular diagnostics. The system employs a SERS substrate fabricated by depositing gold on uniformly grown ZnO nanorods. These nanorods create hot spots for the amplification of the target nucleic acids directly on the SERS surface, eliminating the need for postamplification hybridization and Raman reporters. The limit of detection of the ZADA system was superior to those of the conventional amplification methods. Clinical validation of the ZADA system with coronavirus disease 2019 (COVID-19) samples from human patients yielded a sensitivity and specificity of 92.31% and 81.25%, respectively. The integration of a deep learning program further enhanced sensitivity and specificity to 100% and reduced SERS analysis time, showcasing the potential of the ZADA system for rapid, label-free disease diagnosis via direct nucleic acid amplification and detection within 20 min.

Streamlined Specimen Purification for Rapid COVID-19 Diagnosis Using Positively Charged Polymer Thin Film-Coated Surfaces and Chamber Digital PCR.

The ongoing coronavirus disease 2019 (COVID-19) pandemic demands rapid and straightforward diagnostic tools to prevent early-stage viral transmission. Although nasopharyngeal swabs are a widely used patient sample collection method for diagnosing COVID-19, using these samples for diagnosis without RNA extraction increases the risk of obtaining false-positive and -negative results. Thus, multiple purification steps are necessary, which are time-consuming, generate significant waste, and result in substantial sample loss. To address these issues, we developed surface-modified polymerase chain reaction (PCR) tubes using the tertiary aminated polymer poly(2-dimethylaminomethylstyrene) (pDMAMS) via initiated chemical vapor deposition. Introducing the clinical samples into the pDMAMS-coated tubes resulted in approximately 100% RNA capture efficiency within 25 min, which occurred through electrostatic interactions between the positively charged pDMAMS surface and the negatively charged RNA. The captured RNA is then detected via chamber digital PCR, enabling a sensitive, accurate, and rapid diagnosis. Our platform provides a simple and efficient RNA extraction and detection strategy that allows detection from 22 nasopharyngeal swabs and 21 saliva specimens with 0% false negatives. The proposed method can facilitate the diagnosis of COVID-19 and contribute to the prevention of early-stage transmission.