PSTCNN: Explainable COVID-19 diagnosis using PSO-guided self-tuning CNN

Since 2019, the coronavirus disease-19 (COVID-19) has been spreading rapidly worldwide, posing an unignorable threat to the global economy and human health. It is a disease caused by severe acute respiratory syndrome coronavirus 2, a single-stranded RNA virus of the genus Betacoronavirus. This virus is highly infectious and relies on its angiotensin-converting enzyme 2-receptor to enter cells. With the increase in the number of confirmed COVID-19 diagnoses, the difficulty of diagnosis due to the lack of global healthcare resources becomes increasingly apparent. Deep learning-based computer-aided diagnosis models with high generalisability can effectively alleviate this pressure. Hyperparameter tuning is essential in training such models and significantly impacts their final performance and training speed. However, traditional hyperparameter tuning methods are usually time-consuming and unstable. To solve this issue, we introduce Particle Swarm Optimisation to build a PSO-guided Self-Tuning Convolution Neural Network (PSTCNN), allowing the model to tune hyperparameters automatically. Therefore, the proposed approach can reduce human involvement. Also, the optimisation algorithm can select the combination of hyperparameters in a targeted manner, thus stably achieving a solution closer to the global optimum. Experimentally, the PSTCNN can obtain quite excellent results, with a sensitivity of 93.65% ± 1.86%, a specificity of 94.32% ± 2.07%, a precision of 94.30% ± 2.04%, an accuracy of 93.99% ± 1.78%, an F1-score of 93.97% ± 1.78%, Matthews Correlation Coefficient of 87.99% ± 3.56%, and Fowlkes-Mallows Index of 93.97% ± 1.78%. Our experiments demonstrate that compared to traditional methods, hyperparameter tuning of the model using an optimisation algorithm is faster and more effective. © 2023 Centro Regional de Invest. Cientif. y Tecn.. All rights reserved.

Diagnostic test property of transcription-reverse transcription concerted reaction reagent TRCReady® SARS-CoV-2 i using nasopharyngeal swab samples

TRCReady® SARS-CoV-2 i is a reagent for transcription-reverse transcription concerted reaction (TRC) to detect SARS-CoV-2 N2 gene, used with the automated rapid isothermal nucleic acid amplification test (NAAT) analyzer TRCReady®-80. Sensitivity and specificity of TRCReady® SARS-CoV-2 i was assessed by comparison with the results of real-time reverse transcription-polymerase chain reaction (RT-PCR) using nasopharyngeal swab samples. From November 2020 to March 2021, a total of 441 nasopharyngeal swabs were obtained and analyzed both with TRCReady® SARS-CoV-2 i and RT-PCR. Sensitivity and specificity of TRCReady® SARS-CoV-2 i were 94.6% (53/56) and 99.2% (382/385), respectively. Reaction time to positivity of TRCReady® SARS-CoV-2 i ranged from 1.166 to 9.805 (median: 2.887) min, and minimum detection sensitivity of TRCReady® SARS-CoV-2 i was 9 copies per test, with reaction time as 5.014 min. Detection of SARS-CoV-2 gene from nasopharyngeal swab sample using TRCReady® SARS-CoV-2 i shows comparative diagnostic test accuracy with RT-PCR, and can be used as a useful test to diagnose SARS-CoV-2 infection. © 2022 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases

Potential usage of anterior nasal sampling in clinical practice with three rapid antigen tests for SARS-CoV-2

Introduction: Anterior nasal sampling (AN) might be more convenient for patients than NP sampling to diagnose coronavirus disease. This study investigated the feasibility of rapid antigen tests for AN sampling, and the factors affecting the test accuracy. Methods: This single-center prospective study evaluated one qualitative (ESP) and two quantitative (LUMI and LUMI-P) rapid antigen tests using AN and NP swabs. Symptomatic patients aged 20 years or older, who were considered eligible for reverse-transcription quantitative polymerase chain reaction using NP samples within 9 days of onset were recruited. Sensitivity, specificity, and positive and negative concordance rates between AN and NP samples were assessed for the rapid antigen tests. We investigated the characteristics that affected the concordance between AN and NP sampling results. Results: A total of 128 cases were recruited, including 28 positive samples and 96 negative samples. The sensitivity and specificity of AN samples using ESP were 0.81 and 1.00, while those of NP samples were 0.94 and 1.00. The sensitivity of AN and NP samples was 0.91 and 0.97, respectively, and specificity was 1.00, for both LUMI and LUMI-P. The positive concordance rates of AN to NP sampling were 0.87, 0.94, and 0.85 for ESP, LUMI, and LUMI-P, respectively. No factor had a significant effect on the concordance between the sampling methods. Conclusions: ESP, LUMI, and LUMI-P showed practical diagnostic accuracy for AN sampling compared to NP sampling. There was no significant factor affecting the concordance between AN and NP sampling for these rapid antigen tests. © 2022 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases

Lung disease detection using Self-Attention Generative Adversarial Capsule network optimized with sun flower Optimization Algorithm

Lung cancer is the uncontrolled growth of abnormal cells in one or both lungs. This is one of the dangerous diseases. A lot of feature extraction with classification methods were discussed previously regarding this disease, but none of the methods give sufficient results, not only that, those methods have high over fitting problem, as a result, the detection accuracy was minimizing. Therefore, to overcome these issues, a Lung Disease Detection using Self-Attention Generative Adversarial Capsule Network optimized with Sun flower Optimization Algorithm (SA-Caps GAN-SFOA-LDC) is proposed in this manuscript. Initially, NIH chest X-ray image dataset is gathered through Kaggle repository to diagnose the lung disease. Then, the chests X-ray images are pre-processed by using the contrast limited adaptive histogram equalization (CLAHE) filtering method to eliminate the noise and to enhance the image quality. These pre-processed outputs are fed to feature extraction process. In the feature extraction process, the empirical wavelet transform method is used. These extracted features are given into Self-Attention based Generative Adversarial Capsule classifier for detecting the lung disease. The hyper parameters of SA-Caps GAN classifier is optimized using Sun flower Optimization Algorithm. The simulation is implemented in MATLAB. The proposed SA-Caps GAN-SFOA-LDC method attains higher accuracy 21.05%, 33.28%, 30.27%, 29.68%, 32.57% and 44.28%, Higher Precision 30.24%, 35.68%, 32.08%, 41.27%, 28.57% and 34.20%, Higher F-Score 32.05%, 31.05%, 36.24%, 30.27%, 37.59% and 22.05% analyzed with the existing methods, SVM-SMO-LDC, CNN-MOSHO-LDC, XGboost-PSO-LDC respectively. © 2022 Elsevier Ltd

Nail ridging in rheumatoid arthritis patients and relation to disease activity: An integrated rheumatology-dermatology multi-centre study

Aim of the work: To evaluate the frequency of nail ridging (NR) in patients with rheumatoid arthritis (RA) and to study its relation to disease activity. Patients and methods: 230 RA patients and 97 matched controls from Helwan, Ain Shams and Mansoura university hospitals were studied. Disease activity score (DAS28) was assessed. NR has been searched for in all patients. The number of affected fingers was recorded. NR was determined by a magnifying lens, seen by naked eye or seen and felt. Dermoscopic photography of the NR using Dermalite DL4 3Gen dermatoscope has been recorded. Results: The median age of patients was 49 years (42–58 years);they were 221 females and 19 males (F:M 11.1:1) with a disease duration 9 years (5–11 years). Their DAS28 was 3.6 (2.9–4.6). NR was significantly increased in RA cases vs. control;73% vs 20%;p < 0.001. In patients, NR was detected by a magnifying lens in 32.6%, seen in 27% and seen and felt in 13.5%. Joint deformities were significantly higher in those with NR. DAS28 was a significant independent predictor of NR;for every one-point increase in DAS28, there was a 153 times higher odds to exhibit NR at a sensitivity of 93.5%, specificity 80.3% and at a diagnostic accuracy of 90%. Conclusion: NR is a frequent finding in RA. An integrated rheumatological- dermatological clinical evaluation may be helpful and further studies are required to prove the importance of this sign for follow up of RA patients.

Estimating the extent of asymptomatic covid-19 and its potential for community transmission: Systematic review and meta-analysis

Background: Knowing the prevalence of true asymptomatic coronavirus disease 2019 (COVID-19) cases is critical for designing mitigation measures against the pandemic. We aimed to synthesize all available research on asymptomatic cases and transmission rates. Methods: We searched PubMed, Embase, Cochrane COVID-19 trials, and Europe PMC for primary studies on asymptomatic prevalence in which (1) the sample frame includes at-risk populations, and;(2) follow-up was sufficient to identify pre-symptomatic cases. Meta-analysis used fixed-effects and random-effects models. We assessed risk of bias by combination of questions adapted from risk of bias tools for prevalence and diagnostic accuracy studies. Results: We screened 2,454 articles and included 13 low risk-of-bias studies from seven countries that tested 21,708 at-risk people, of which 663 were positive and 111 asymptomatic. Diagnosis in all studies was confirmed using a real-time reverse transcriptase–polymerase chain reaction test. The asymptomatic proportion ranged from 4% to 41%. Meta-analysis (fixed effects) found that the proportion of asymptomatic cases was 17% (95% CI 14% to 20%) overall and higher in aged care (20%;95% CI 14% to 27%) than in non-aged care (16%;95% CI 13% to 20%). The relative risk (RR) of asymptomatic transmission was 42% lower than that for symptomatic transmission (combined RR 0.58;95% CI 0.34 to 0.99, p = 0.047). Conclusions: Our one-in-six estimate of the prevalence of asymptomatic COVID-19 cases and asymptomatic transmission rates is lower than those of many highly publicized studies but still sufficient to warrant policy attention. Further robust epidemiological evidence is urgently needed, including in subpopulations such as children, to better understand how asymptomatic cases contribute to the pandemic.

Rapid differential diagnosis of SARS-CoV-2, influenza A/B and respiratory syncytial viruses: Validation of a novel RT-PCR assay.

BACKGROUND: Influenza and respiratory syncytial (RSV) viruses are expected to co-circulate with SARS-CoV-2 in the upcoming seasons and clinical differential diagnosis between them is difficult. Laboratory-based RT-PCR is a gold standard diagnostic method for influenza, RSV and SARS-CoV-2. The objective of this study was to estimate the diagnostic performance of a novel point-of-care RT-PCR assay STANDARD M10 Flu/RSV/SARS-CoV-2 (SD Biosensor) in a large number of clinical specimens with diversified (co)-infection patterns and viral loads. METHODS: This was a retrospective study, in which all samples were tested in both STANDARD M10 Flu/RSV/SARS-CoV-2 index and Allplex SARS-CoV-2/Respiratory Panel 1 (Seegene) reference kits. Samples with discordant results were further processed in a third resolver test (Resp-4-Plex, Abbott). RESULTS: A total of 1,019 naso-/oropharyngeal samples (50.3% positive for at least one virus) were processed in both STANDARD M10 Flu/RSV/SARS-CoV-2 and Allplex assays and the overall between-assay agreement was as high as 94.6%. Positive percent agreement of the STANDARD M10 Flu/RSV/SARS-CoV-2 was 100%, 96.6%, 97.3% and 99.4% for influenza A, B, RSV and SARS-CoV-2, respectively. The corresponding negative percent agreement was 99.7%. 100%, 100% and 98.4%, respectively. The expected positive and negative predictive values for all viruses were constantly above 96% in a reasonable range of disease prevalence. CONCLUSIONS: STANDARD M10 Flu/RSV/SARS-CoV-2 is a reliable RT-PCR assay able to detect influenza A, influenza B, RSV and SARS-CoV-2 in one hour or less, fostering a rapid differential diagnosis of common respiratory viruses.

An efficient lung disease classification from X-ray images using hybrid Mask-RCNN and BiDLSTM

Lung diseases mainly affect the inner lining of the lungs causing complications in breathing, airway obstruction, and exhalation. Identifying lung diseases such as COVID-19, pneumonia, fibrosis, and tuberculosis at the earlier stage is a great challenge due to the availability of insufficient laboratory kits and image modalities. The rapid progression of the lung disease can be easily identified via Chest X-rays and this serves as a major boon for the terminally ill patients admitted to Intensive Care Units (ICU). To enhance the decision-making capability of the clinicians, a novel lung disease prediction framework is proposed using a hybrid bidirectional Long-Short-Term-Memory (BiDLSTM)-Mask Region-Based Convolutional Neural Network (Mask-RCNN) model. The Crystal algorithm is used to optimize the scalability and convergence issues in the Mask-RCNN model by hyperparameter tuning. The long-range dependencies for lung disease prediction are done using the BiDLSTM architecture which is connected to the fully connected layer of the Mask RCNN model. The efficiency of the proposed methodology is evaluated using three publicly accessible lung disease datasets namely the COVID-19 radiography dataset, Tuberculosis (TB) Chest X-ray Database, and National Institute of Health Chest X-ray Dataset which consists of the images of infected lung disease patients. The efficiency of the proposed technique is evaluated using different performance metrics such as Accuracy, Precision, Recall, F-measure, Specificity, confusion matrix, and sensitivity. The high accuracy obtained when comparing the proposed methodology with conventional techniques shows its efficiency of it in improving lung disease diagnosis. Copyright © 2022 Elsevier Ltd

Sensitivity and specificity of lateral flow antigen test kits for covid-19 in asymptomatic population of quarantine centre of province 3

Background Nearly after 6 months of the spread of Corona Virus Disease 19, along with the world Nepal is still trying to control the spread and prevent general population from acquiring it. With limited resources in manpower, technology and evidence it has been a difficult battle. But with time and more understanding of the virus new technology to detect the virus are coming up. It is a major breakthrough in the diagnostic field as this helps us in not only detecting the virus but also helps us to mobilize our human resources. This comes in a time where the cases are increasing at an alarming rate. Although numbers of Polymerase Chain Reaction testing have increased but due to the time consuming and the cost wise, we need a faster and equally reliable alternative. Antigen test approved by different countries can be used for point of care, screening and surveillance depending upon the requirements after calculating its sensitivity, specificity and accuracy. Objective To find out sensitivity and specificity of the Antigen test kit for COVID-19. Method Antigen tests were compared with Reverse Transcription Polymerase Chain Reaction as a reference standard in calculated sample size of 113 subjects in a high risk population. Both Reverse Transcription Polymerase Chain Reaction and antigen test were performed in a same subject with in maximum of 2 days' interval. Convenience sampling technique was used to select the subjects. Ethical approval was taken from Nepal Health Research Council before data collection. Study was done from August to September 2020 from Quarantine center of Province 3. Result There were total of 113 test carried out, among those 47 were positive and 66 were negative in Reverse Transcription Polymerase Chain Reaction. After preparing two by two table, Sensitivity and specificity of the tested was calculated which came out to be 85% and 100% respectively, with accuracy of 93.80%. Conclusion Even though the sensitivity and specificity came to be higher, this test should be interpreted cautiously depending upon the prevalence of Corona Virus Disease 19 in that particular community and the clinical and epidemiological context of the person who has been tested. When in doubt by clinical correlation should be confirmed with Reverse Transcription Polymerase Chain Reaction. Copyright © 2020, Kathmandu University. All rights reserved.

Testing Frequency Matters | An Evaluation of the Diagnostic Performance of a SARS-CoV-2 Rapid Antigen Test in United States Correctional Facilities.

BACKGROUND: The CDC recommends serial rapid antigen assay collection within congregate facilities. Though modeling and observational studies from communities and long-term care facilities have shown serial collection provides adequate sensitivity and specificity, the accuracy within correctional facilities remains unknown. METHODS: Using Connecticut Department of Corrections (DOC) data from November 21st 2020 to June 15th 2021, we estimated the accuracy of a rapid assay, BinaxNOW, under three collection strategies, single test collection and serial collection of two and three tests separated by 1-4 days. The sensitivity and specificity of the first (including single), second, and third serially collected BinaxNOW tests were estimated relative to RT-PCRs collected within one day of the BinaxNOW test. The accuracy metrics of the testing strategies were then estimated as the sum (sensitivity) and product (specificity) of tests in each strategy. RESULTS: Of the 13,112 residents who contributed ≥1 BinaxNOW test during the study period, 3,825 contributed ≥1 RT-PCR paired BinaxNOW test. In relation to RT-PCR, the three-rapid antigen test strategy had a sensitivity of 95.9% (95% confidence intervals (CI): 93.6-97.5%) and specificity of 98.3% (CI: 96.7-99.1%). The sensitivity of the two- and one-rapid antigen test strategies were 88.8% and 66.8%, respectively, and the specificities were 98.5% and 99.4%, respectively. The sensitivity was higher among symptomatic residents and when RT-PCRs were collected before BinaxNOW tests. CONCLUSIONS: We found serial antigen test collection resulted in high diagnostic accuracy. These findings support serial collection for outbreak investigation, screening, and when rapid detection is required (such as intakes or transfers).

Diagnostic accuracy of autoverification and guidance system for COVID-19 RT-PCR results.

Background: To date, most countries worldwide have declared that the pandemic of COVID-19 is over, while the WHO has not officially ended the COVID-19 pandemic, and China still insists on the personalized dynamic COVID-free policy. Large-scale nucleic acid testing in Chinese communities and the manual interpretation for SARS-CoV-2 nucleic acid detection results pose a huge challenge for labour, quality and turnaround time (TAT) requirements. To solve this specific issue while increase the efficiency and accuracy of interpretation, we created an autoverification and guidance system (AGS) that can automatically interpret and report the COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR) results relaying on computer-based autoverification procedure and then validated its performance in real-world environments. This would be conductive to transmission risk prediction, COVID-19 prevention and control and timely medical treatment for positive patients in the context of the predictive, preventive and personalized medicine (PPPM). Methods: A diagnostic accuracy test was conducted with 380,693 participants from two COVID-19 test sites in China, the Hong Kong Hybribio Medical Laboratory (n = 266,035) and the mobile medical shelter at a Shanghai airport (n = 114,658). These participants underwent SARS-CoV-2 RT-PCR from March 28 to April 10, 2022. All RT-PCR results were interpreted by laboratorians and by using AGS simultaneously. Considering the manual interpretation as gold standard, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were applied to evaluate the diagnostic value of the AGS on the interpretation of RT-PCR results. Results: Among the 266,035 samples in Hong Kong, there were 16,356 (6.15%) positive, 231,073 (86.86%) negative, 18,606 (6.99%) indefinite, 231,073 (86.86%, negative) no retest required and 34,962 (13.14%, positive and indefinite) retest required; the 114,658 samples in Shanghai consisted of 76 (0.07%) positive, 109,956 (95.90%) negative, 4626 (4.03%) indefinite, 109,956 (95.90%, negative) no retest required and 4702 (4.10%, positive and indefinite) retest required. Compared to the fashioned manual interpretation, the AGS is a procedure of high accuracy [99.96% (95%CI, 99.95-99.97%) in Hong Kong and 100% (95%CI, 100-100%) in Shanghai] with perfect sensitivity [99.98% (95%CI, 99.97-99.98%) in Hong Kong and 100% (95%CI, 100-100%) in Shanghai], specificity [99.87% (95%CI, 99.82-99.90%) in Hong Kong and 100% (95%CI, 99.92-100%) in Shanghai], PPV [99.98% (95%CI, 99.97-99.99%) in Hong Kong and 100% (95%CI, 99.99-100%) in Shanghai] and NPV [99.85% (95%CI, 99.80-99.88%) in Hong Kong and 100% (95%CI, 99.90-100%) in Shanghai]. The need for manual interpretation of total samples was dramatically reduced from 100% to 13.1% and the interpretation time fell from 53 h to 26 min in Hong Kong; while the manual interpretation of total samples was decreased from 100% to 4.1% and the interpretation time dropped from 20 h to 16 min at Shanghai. Conclusions: The AGS is a procedure of high accuracy and significantly relieves both labour and time from the challenge of large-scale screening of SARS-CoV-2 using RT-PCR. It should be recommended as a powerful screening, diagnostic and predictive system for SARS-CoV-2 to contribute timely the ending of the COVID-19 pandemic following the concept of PPPM.

A Metasynthesis and Meta-analysis of the Impact and Diagnostic Safety of COVID-19 Symptom Agnostic Rapid Testing in Low- and Middle-Income Countries: Protocol for a Systematic Review.

BACKGROUND: Amid all public health measures to contain COVID-19, the most challenging has been how to break the transmission chain. This has been even more challenging in low- and middle-income countries (LMICs). A public health emergency warrants a public health perspective, which comes down to prevention. Rapid mass testing has been advocated throughout the pandemic as a way to promptly deal with asymptomatic infections, but its usefulness in LMICs is yet to be fully understood. OBJECTIVE: The study objectives of this paper are to (1) investigate the impact of the different rapid mass testing options for SARS-CoV-2 that have been delivered at point of care in LMICs and (2) evaluate the diagnostic safety (accuracy) of rapid mass testing for SARS-CoV-2 in LMICs. METHODS: This review will systematically search records in PubMed, EBSCOhost, Cochrane library, Global Index Medicus COVID-19 Register, and Scopus. Records will be managed using Mendeley reference manager and SWIFT-Review. Risk of bias for randomized controlled trials will be assessed using the RoB 2 assessment tool, while nonrandomized interventions will be assessed using the tool developed by the Evidence Project. A narrative approach will be used to synthesize data under the first objective, and either a meta-analysis or synthesis without meta-analysis for the second objective. Tables, figures, and textual descriptions will be used to present findings. The overall body of evidence for the first objective will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach, and for the second objective using GRADE. RESULTS: The screening of records has been finalized. We hope to finalize the synthesis by the end of February 2023 and to prepare the manuscript for publication by April 2023. The study will be reported in accordance with standard guidelines for the reporting of systematic reviews. Review results will be disseminated through conferences and their peer-reviewed publication in a relevant journal. CONCLUSIONS: This review highlights the role of a preventive approach in infection control using rapid mass testing. It also flags the overriding need to involve users and providers in the evaluation of such tests in the settings for which they are intended. This will be the first review to the best of our knowledge to generate both qualitative and quantitative evidence regarding rapid mass testing specific to LMICs. TRIAL REGISTRATION: PROSPERO CRD42022283776; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=283776. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/41132.