Diagnostic Concordance of Telemedicine as Compared With Face-to-Face Care in Primary Health Care Clinics in Rural India: Randomized Crossover Trial.

BACKGROUND: With the COVID-19 pandemic, there was an increase and scaling up of provider-to-provider telemedicine programs that connect frontline health providers such as nurses and community health workers at primary care clinics with remote doctors at tertiary facilities to facilitate consultations for rural patients. Considering this new trend of increasing use of telemedicine, this study was conducted to generate evidence for patients, health providers, and policymakers to compare if provider-to-provider telemedicine-based care is equivalent to in-person care and is safe and acceptable in terms of diagnostic and treatment standards. OBJECTIVE: This study aims to compare the diagnosis and treatment decisions from teleconsultations to those of in-person care in teleclinics in rural Gujarat. METHODS: We conducted a diagnostic concordance study using a randomized crossover study design with 104 patients at 10 telemedicine primary care clinics. Patients reporting to 10 telemedicine primary care clinics were randomly assigned to first receive an in-person doctor consultation (59/104, 56.7%) or to first receive a health worker-assisted telemedicine consultation (45/104, 43.3%). The 2 groups were then switched, with the first group undergoing a telemedicine consultation following the in-person consultation and the second group receiving an in-person consultation after the teleconsultation. The in-person doctor and remote doctor were blinded to the diagnosis and management plan of the other. The diagnosis and treatment plan of in-person doctors was considered the gold standard. RESULTS: We enrolled 104 patients reporting a range of primary health care issues into the study. We observed 74% (77/104) diagnostic concordance and 79.8% (83/104) concordance in the treatment plan between the in-person and remote doctors. No significant association was found between the diagnostic and treatment concordance and the order of the consultation (P=.65 and P=.81, respectively), the frontline health worker-doctor pair (both P=.93), the gender of the patient (both P>.99), or the mode of teleconsultation (synchronous vs asynchronous; P=.32 and P=.29, respectively), as evaluated using Fisher exact tests. A significant association was seen between the diagnostic and treatment concordance and the type of case (P=.004 and P=.03, respectively). The highest diagnostic concordance was seen in the management of hypertension (20/21, 95% concordance; Cohen kappa=0.93) and diabetes (14/15, 93% concordance; Cohen kappa=0.89). The lowest values were seen in cardiology (1/3, 33%) and patients presenting with nonspecific symptoms (3/10, 30%). The use of a digital assistant to facilitate the consultation resulted in increased adherence to evidence-based care protocols. CONCLUSIONS: The findings reflect that telemedicine can be a safe and acceptable alternative mode of care especially in remote rural settings when in-person care is not accessible. Telemedicine has advantages. for the potential gains for improved health care-seeking behavior for patients, reduced costs for the patient, and improved health system efficiency by reducing overcrowding at tertiary health facilities.

Evaluation of the Quality of Electronic Educational Courses for Higher Education Institutions

The transition to distance and blended forms of education in most higher education institutions during the period of the COVID-19 pandemic, and then the actions of martial law in Ukraine prompted teachers to create their own electronic educational resources and electronic training courses, with the help of which the content of the academic discipline is transmitted. The article describes approaches to the evaluation of the quality of electronic educational courses. The main structural components of an electronic educational course for higher education institutions are distinguished: technical and technological, normative and organizational, methodical, substantive, result and evaluative, which can be considered factors affecting its quality. It was determined that the technical and technological factor is characterized by the possibility and convenience of installing electronic educational course on PCs and mobile devices, compatibility of electronic educational course with various operating systems availability and quality of instructions for installing/starting electronic educational course, availability of a description of technical characteristics of electronic educational course and contacts of its developer(s). The criteria of the regulatory and organizational factor are normative acts related to the educational course, reviews of the electronic educational course, questionnaires for applicants of higher education and teachers regarding the determination of the quality of the electronic educational course. Features of the methodological block are instructions for the electronic educational course users, methodological materials for students of higher education on the performance of the main types of tasks, methodological recommendations for the electronic educational course teacher, feedback. The content factor is characterized by lecture texts, presentations for each topic, multimedia materials, a terminological dictionary, tasks (practical, interactive, for independent work, creative, research), project works, reference materials, a list of main and additional sources, additional educational materials, a glossary.A basic factor-criterion model for evaluating the quality of an electronic educational course for higher education institutions is proposed, which makes it possible to carry out an objective quantitative assessment of the quality of an electronic educational course and to identify possible shortcomings in order to eliminate them in time, which can be used during the development and evaluation of electronic educational courses for higher education institutions in various academic disciplines.

Efficacy, perception, and utilization of pediatric teledermatology: A systematic review.

Background: The use of teledermatology abruptly expanded with the arrival of COVID-19. Here, we review recent studies regarding the efficacy, perception, and utilization of telemedicine in the pediatric population. Objective: To evaluate the current state of pediatric teledermatology. Methods: A literature search was performed using the terms "pediatric," "teledermatology," "dermatology," "telemedicine" and "telehealth" in PubMed, Scopus, Embase, and Google Scholar. 44 articles published between 2008 and 2022 were included. Results: Diagnostic concordance between pediatric teledermatologist and in-person dermatologist ranged from 70.1% to 89%. Conditions treated with pediatric teledermatology were similar to those treated in-person. The rate of in-person follow-up after an initial telemedicine appointment pre and postpandemic was 12% to 51.9% and 13.5% to 28.1%, respectively. Patient satisfaction with teledermatology was between 70% to 98% and provider satisfaction was approximately 95%. The integration of teledermatology can reduce missed appointments and wait times among pediatric patients. However, considerable technological challenges exist, particularly in underserved communities. Globally, teledermatology may expand access to care though limited literature exists regarding its use in pediatric populations. Conclusion: Telemedicine is effective for the diagnosis and treatment of many dermatological conditions in children, with high patient and provider satisfaction. Implementation of teledermatology can potentially increase access to care both locally and globally, but obstacles to engagement remain.

Drug Repositioning for Coronavirus (COVID-19) using Different Deep Learning Architectures

In December 2019, the COVID-19 epidemic was found in Wuhan, China, and soon hundreds of millions were infected. Therefore, several efforts were made to identify commercially available drugs to repurpose them against COVID-19. Inferring potential drug indications through computational drug repositioning is an efficient method. The drug repositioning problem is a top-K recommendation function that presents the most likely drugs for specific diseases based on drug and disease-related data. The accurate prediction of drug-target interactions (DTI) is very important for drug repositioning. Deep learning (DL) models were recently exploited for promising DTI prediction performance. To build deep learning models for DTI prediction, encoder-decoder architectures can be utilized. In this paper, a deep learning-based drug repositioning approach is proposed, which is composed of two experimental phases. Firstly, training and evaluating different deep learning encoder-decoder architecture models using the benchmark DAVIS Dataset. The trained deep learning models have been evaluated using two evaluation metrics;mean square error and the concordance index. Secondly, predicting antiviral drugs for Covid-19 using the trained deep learning models created during the first phase. In this phase, these models have been experimented to predict different antiviral drug lists, which then have been compared with a recently published antiviral drug list for Covid-19 using the concordance index metric. The overall experimental results of both phases showed that the most accurate three deep learning compound-encoder/protein-encoder architectures are Morgan/AAC, CNN/AAC, and CNN/CNN with best values for the mean square error, the first phase concordance index, and the second phase concordance index. © 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

Adherence therapy for adults with type 2 diabetes: a feasibility study of a randomized controlled trial.

BACKGROUND: Adherence Therapy is a candidate intervention to promote consistent medication taking in people with type 2 diabetes. The aim of this study was to establish the feasibility of conducting a randomized controlled trial of adherence therapy in people with type 2 diabetes who were non-adherent with medication. METHODS: The design is an open-label, single-center, randomized controlled feasibility trial. Participants were randomly allocated to receive either eight sessions of telephone-delivered adherence therapy or treatment as usual. Recruitment occurred during the COVID-19 pandemic. Outcome measures-adherence, beliefs about medication, and average blood glucose (sugar) levels (HbA1c)-were administered at baseline and after 8 weeks (TAU group) or at the completion of the treatment (AT group). Feasibility outcomes included the number of people approached to participate in the trial and the numbers that consented, completed study measures, finished treatment with adherence therapy, and dropped out of the trial. Fieldwork for this trial was conducted in the National Guard Hospital, a tertiary care provider, in the Kingdom of Saudi Arabia. RESULTS: Seventy-eight people were screened, of which 47 met eligibility criteria and were invited to take part in the trial. Thirty-four people were excluded for various reasons. The remaining thirteen who consented to participate were enrolled in the trial and were randomized (AT, n = 7) (TAU, n = 6). Five (71%) of the seven participants in the adherence therapy arm completed treatment. Baseline measures were completed by all participants. Week 8 (post-treatment) measures were completed by eight (62%) participants. Dropout may have been linked to a poor understanding of what was involved in taking part in the trial. CONCLUSIONS: It may be feasible to conduct a full RCT of adherence therapy, but careful consideration should be given to developing effective recruitment strategies, consent procedures, rigorous field testing, and clear support materials. TRIAL REGISTRATION: The trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12619000827134, on the 7th of June 2019.

Thematic Analysis: A Corpus-Based Method for Understanding Themes/Topics of a Corpus through a Classification Process Using Long Short-Term Memory (LSTM)

Using advanced algorithms to conduct a thematic analysis reduces the time taken and increases the efficiency of the analysis. Long short-term memory (LSTM) is effective in the field of text classification and natural language processing (NLP). In this study, we adopt LSTM for text classification in order to perform a thematic analysis using concordance lines that are taken from a corpora of news articles. However, the statistical and quantitative analyses of corpus linguistics are not enough to fully identify the semantic shift of terms and concepts. Therefore, we suggest that a corpus should be classified from a linguistic theoretical perspective, as this would help to determine the level of the linguistic patterns that should be applied in the experiment of the classification process. We suggest investigating the concordance lines of the articles rather than only the relationship between collocates, as this has been a limitation for many studies. The findings of this research work highlight the effectiveness of the proposed methodology for the thematic analysis of media coverage, reaching 84% accuracy. This method provides a deeper thematic analysis than only applying the classification process through the collocational analysis.

Diagnostic accuracy and management concordance of otorhinolaryngological diseases through telehealth or remote visits: A systematic review & meta-analysis.

INTRODUCTION: COVID-19 has led to delays in providing healthcare in both emergency and non-emergency settings, especially in surgical subspecialties which rely heavily on referrals and in-person visits. Without an established telehealth infrastructure, many otorhinolaryngological departments experienced decreases in consultations. Telemedicine has attempted to bridge the gap between pre- and post-pandemic periods by creating a safe avenue of communication between otorhinolaryngologists and patients. This review hopes to address the accuracy of telemedicine in patient diagnosis and management. METHODS: Searches were conducted since study conception until June 30, 2022, on multiple databases including PubMed, SCOPUS, and CINAHL for this systematic review and meta-analysis. Diagnostic accuracy, management accuracy, kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were meta-analyzed by comparing virtual visits to in-person visits (gold standard). RESULTS: Nineteen studies were included in this review. A total of 1518 patients were included across all studies. When comparing virtual visits against in-person visits, accurate diagnosis was made in 86.2% [82.1,89.9, I2 = 73.5%, P < 0.0001] of patients and management accuracy was 91.5% [86.1,95.7, I2 = 81.8%, P < 0.0001] when treating patients. Kappa value determining interrater reliability was 0.8 [0.7,0.9, I2 = 81.8%, P < 0.0001]. CONCLUSION: Our data suggest that diagnostic and management concordance is above 80% when comparing diagnosis and management strategies in patients who underwent both telehealth and in-person visits with an otorhinolaryngologist. In uncomplicated patients, telehealth might be a reliable source for diagnosis and management however, in-person consultation is likely still required for pathologies in which physical exam, imaging or procedural elements represent a vital component of the work-up.

Urban tourist profiles during the pandemic in Taiwan: A multigroup analysis.

Participating in tourism activities in crowded areas such as cities during the COVID-19 pandemic represents a risk. This study examined the demographic and psychological features of Taiwanese domestic urban tourists during the pandemic in 2021. The theoretical framework was based on push-pull motivation, self-concordance, and push-pull-mooring theories. The 680 valid questionnaire responses indicated that the respondents were generally interested in domestic urban tourism despite the pandemic threat. Moreover, 187 respondents regarded themselves as urban tourism seekers. Their demographic features were consistent with the typical primary urban tourism market profile: they were young, highly educated, and employed in skilled occupations. In terms of psychological features, the push factors, representing the individuals' intrinsic urban tourism motivations, were more potent than the pull factors, representing a city's tourism opportunities, as motivational drivers for increasing seekers' urban tourism intention during the pandemic. The methodology and findings of this study strengthen the literature on urban tourism and pandemic recovery.

Stochastic ordering of systemic risk in commodity markets

The contribution of commodity risks to the systemic risk is assessed in this paper through a novel approach that relies on the stochastic property of concordance ordering of CoVaR. Considering the period that spans from 2005 to 2022 and the VIX as the proxy for the stability of the financial system, we build the stochastic ordering of systemic risk for 35 commodities belonging to four sectors: Agriculture, Energy, Industrial Metals, and Precious Metals. The estimates of the ΔCoVaR signal that contagion effects from commodity markets to the financial system have been stronger during the years 2017–2019. Backtests validate CoVaR as a more resilient risk measure than the VaR, especially during periods of market turmoils. The stochastic ordering of CoVaR shows that severe losses (downside risk) in commodity markets tend to exacerbate systemic financial distress more than gains (upside risk). Commodity risks arising from WTI and EUA are threatening triggers for systemic risk. In contrast, the financial system is less vulnerable to a broader range of scenarios arising from fluctuations in Gold prices. As top contributors to the systemic risk, among the sectors we find Energy and Precious Metals with respect to upside risk and downside risk. The Covid-19 crisis has deeply amplified the systemic influence arising from the downside risk of WTI, Gasoline, and Natural Gas UK and has confirmed the safe-haven role of Gold. © 2022 Elsevier B.V.

Multi-informant Assessment of Internalizing Concerns: Rater Concordance and Implications for Decision-Making.

Rising rates of mental health challenges among youths have become a significant concern following the COVID 19 pandemic. Although strong evidence supports the implementation of universal screening as a preventative approach to address unmet mental health concerns, the research is less clear surrounding the use of such data in decision-making processes when significant discrepancies between informants (e.g., students and teachers) exist. The purpose of the study was twofold. First, the study aimed to determine the degree of rater concordance between teachers and students on students' internalizing concerns. The second objective was to determine whether concordance on internalizing behaviors differs across ages/grades and if this differentially impacts distal (i.e., academic) outcomes. Results indicated that teachers and students demonstrated limited agreement on ratings of internalizing behaviors. However, when students and teachers agreed, higher and more positive emotional behaviors were linked to higher reading/math performance. Furthermore, patterns of informant dis/agreement and relationships between internalizing concerns and academic outcomes were similar across grade levels. Implications and areas for future research are discussed.

Child Maltreatment Reporting Practices by a Person Most Knowledgeable for Children and Youth: A Rapid Scoping Review.

Child maltreatment is a global public health and child rights crisis made worse by the ongoing COVID-19 pandemic. While understanding the breadth of the child maltreatment crisis is foundational to informing prevention and response efforts, determining accurate estimates of child maltreatment remains challenging. Alternative informants (parents, caregivers, a Person Most Knowledgeable-PMK) are often tasked with reporting on children's maltreatment experiences in surveys to mitigate concerns associated with reporting child maltreatment. The overall purpose of this study was to examine child maltreatment reporting practices in surveys by PMKs for children and youth. The research question is: "What is the nature of the evidence of child maltreatment reporting practices in general population surveys by PMKs for children and youth?" A rapid scoping review was conducted to achieve the study's purpose. A search strategy was conducted in nine databases (e.g., MEDLINE, EBSCO, Scopus, Global Health, ProQuest). The findings from this review indicate that most studies involved PMK informants (i.e., maternal caregivers), included representative samples from primarily Western contexts, and utilized validated measures to assess child maltreatment. Half of the studies assessed involved multi-informant reports, including the PMKs and child/youth. Overall, the congruence between PMK-reported and child/youth-reported child maltreatment experiences was low-to-fair/moderate, and children/youth reported more maltreatment than the PMKs.

Test concordance and diagnostic accuracy of three serological assays for detection of anti-SARS-CoV-2 antibody: result from a population-based sero-epidemiological study in Delhi.

BACKGROUND: Several methodological tests are available to detect SARS-CoV-2 antibody. Tests are mostly used in the aid of diagnosis or for serological assessment. No tests are fully confirmatory and have variable level of diagnostic ability. We aimed at assessing agreement with three serological tests: quantitative anti receptor binding domain ELISA (Q-RBD), qualitative ELISA (WANTAI SARS-CoV-2 Ab) and qualitative chemiluminescence assay (CLIA). METHODS: This study was a part of a large population based sero-epidemiological cohort study. Participants aged 1 year or older were included from 25 randomly selected clusters each in Delhi urban (urban resettlement colony of South Delhi district) and Delhi rural (villages in Faridabad district, Haryana). Three type of tests were applied to all the baseline blood samples. Result of the three tests were evaluated by estimating the total agreement and kappa value. RESULTS: Total 3491 blood samples collected from March to September, 2021, out of which 1700 (48.7%) from urban and 1791 (51.3%) from rural. Overall 44.1% of participants were male. The proportion of sero-positivity were 78.1%, 75.2% and 31.8% by Wantai, QRBD and CLIA tests respectively. The total agreement between Wantai and QRBD was 94.5%, 53.1% between Wantai and CLIA, and 56.8% between QRBD and CLIA. The kappa value between these three tests were 0.84 (95% CI 0.80-0.87), 0.22 (95% CI 0.19-0.24) and 0.26 (95% CI 0.23-0.28). CONCLUSIONS: There was strong concordance between Wantai and QRBD test. Agreement between CLIA with other two tests was low. Wantai and QRBD tests measuring the antibody to same S protein can be used with high agreement based on the relevant scenario.

A Delphi method on the positive impact of COVID-19 on higher education institutions: Perceptions of academics from Malaysia.

The COVID-19 pandemic has drastically altered the education sector. Rather than the impact of COVID-19, many higher education institutions (HEIs) are on the verge of insolvency due to a lack of digital transformation readiness and poor business models. The bleak financial future many HEIs will face while others may be forced to close their doors completely will erode HEIs' ability to fulfil their societal responsibilities. However, HEIs that have survived and maintained their operations anticipate the transition to online learning or the effects of any economic crisis, including university closures in the short, medium, or long term. The entire educational ecosystem was forced to transform its operations quickly and entirely to an online teaching-learning scenario in just a few weeks. Notably, HEIs that have long offered online courses worldwide can easily transition to digital teaching and learning when necessary. The second roundtable session's result of the International Higher Education Conference, organized by INTI International University on March 31 2022, was used to organize a Delphi method to identify further factors that positively impact HEIs by COVID-19. The importance of these factors was then determined using Kendall's coefficient of concordance. Recommendations on how HEIs should move towards institutional sustainability during the endemic phase are presented accordingly.

A multi-criteria-based analytical study of the impact of COVID-19 on ELSS fund performance

This paper examines the impact of COVID-19 on the performance of select equity linked savings scheme (ELSS) funds in India for two different time periods namely June 2019 (before COVID-19) and June 2021 (after COVID-19) using risk, return and market perception based criteria. We use a hybrid multi-criteria decision-making (MCDM) framework of level based weight assessment (LBWA) and measurement of alternatives and ranking according to compromise solution (MARCOS). We test the group harmony using Kendall's concordance coefficient. We find that the result is validated and shows stability in the sensitivity analysis. To the best of our knowledge, the present work is the first of its kind that assesses the impact of COVID-19 on asset management companies (AMC) of ELSS funds from multiple perspectives. We observe that AMCs are unable to maintain their performance and ranks which suggests a highly competitive and fragmented nature of India's growing ELSS funds.

Ascertainment of vaccination status by self-report versus source documentation: Impact on measuring COVID-19 vaccine effectiveness.

BACKGROUND: During the COVID-19 pandemic, self-reported COVID-19 vaccination might facilitate rapid evaluations of vaccine effectiveness (VE) when source documentation (e.g., immunization information systems [IIS]) is not readily available. We evaluated the concordance of COVID-19 vaccination status ascertained by self-report versus source documentation and its impact on VE estimates. METHODS: Hospitalized adults (≥18 years) admitted to 18 U.S. medical centers March-June 2021 were enrolled, including COVID-19 cases and SARS-CoV-2 negative controls. Patients were interviewed about COVID-19 vaccination. Abstractors simultaneously searched IIS, medical records, and other sources for vaccination information. To compare vaccination status by self-report and documentation, we estimated percent agreement and unweighted kappa with 95% confidence intervals (CIs). We then calculated VE in preventing COVID-19 hospitalization of full vaccination (2 doses of mRNA product ≥14 days prior to illness onset) independently using data from self-report or source documentation. RESULTS: Of 2520 patients, 594 (24%) did not have self-reported vaccination information to assign vaccination group; these patients tended to be more severely ill. Among 1924 patients with both self-report and source documentation information, 95.0% (95% CI: 93.9-95.9%) agreement was observed, with a kappa of 0.9127 (95% CI: 0.9109-0.9145). VE was 86% (95% CI: 81-90%) by self-report data only and 85% (95% CI: 81-89%) by source documentation data only. CONCLUSIONS: Approximately one-quarter of hospitalized patients could not provide self-report COVID-19 vaccination status. Among patients with self-report information, there was high concordance with source documented status. Self-report may be a reasonable source of COVID-19 vaccination information for timely VE assessment for public health action.

High concordance in SARSCoV-2 detection between automated (Abbott m2000) and manual (DaAn gene) RT-PCR systems: The EDCTP PERFECT-Study in Cameroon.

Molecular diagnosis of COVID-19 is critical to the control of the pandemic, which is a major threat to global health. Several molecular tests have been validated by WHO, but would require operational evaluation in the field to ensure their interoperability in diagnosis. In order to ensure field interoperability in molecular assays for detection of SARS-CoV-2 RNA, we evaluated the diagnostic concordance of SARS-CoV-2 between an automated (Abbott) and a manual (DaAn gene) realtime PCR (rRT-PCR), two commonly used assays in Africa. A comparative study was conducted on 287 nasopharyngeal specimens at the Chantal BIYA International Reference Centre (CIRCB) in Yaounde- Cameroon. Samples were tested in parallel with Abbott and DaAn gene rRT-PCR, and performance characteristics were evaluated by Cohen's coefficient and Spearman's correlation. A total of 273 participants [median age (IQR) 36 (26-46) years] and 14 EQA specimens were included in the study. Positivity was on 30.0% (86/287) Abbott and 37.6% (108/287) DaAn gene. Overall agreement was 82.6% (237/287), with k=0.82 (95%CI: 0.777-0.863), indicating an excellent diagnostic agreement. The positive and negative agreement was 66.67% (72/108) and 92.18 % (165/179) respectively. Regarding Viral Load (VL), positive agreement was 100% for samples with high VLs (CT<20). Among positive SARS-CoV- 2 cases, the mean difference in Cycle Threshold (CT) for the manual and Cycle Number (CN) for the automated was 6.75±0.3. The excellent agreement (>80%) between the Abbott and DaAn gene rRTPCR platforms supports interoperability between the two assays. Discordance occurs at low-VL, thus underscoring these tools as efficient weapons in limiting SARS-CoV-2 community transmission.

Harmonization of Multiple SARS-CoV-2 Reference Materials Using the WHO IS (NIBSC 20/136): Results and Implications.

Background: There is an urgent need for harmonization between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology platforms and assays prior to defining appropriate correlates of protection and as well inform the development of new rapid diagnostic tests that can be used for serosurveillance as new variants of concern (VOC) emerge. We compared multiple SARS-CoV-2 serology reference materials to the WHO International Standard (WHO IS) to determine their utility as secondary standards, using an international network of laboratories with high-throughput quantitative serology assays. This enabled the comparison of quantitative results between multiple serology platforms. Methods: Between April and December 2020, 13 well-characterized and validated SARS-CoV-2 serology reference materials were recruited from six different providers to qualify as secondary standards to the WHO IS. All the samples were tested in parallel with the National Institute for Biological Standards and Control (NIBSC) 20/136 and parallel-line assays were used to calculate the relevant potency and binding antibody units. Results: All the samples saw varying levels of concordance between diagnostic methods at specific antigen-antibody combinations. Seven of the 12 candidate materials had high concordance for the spike-immunoglobulin G (IgG) analyte [percent coefficient of variation (%CV) between 5 and 44%]. Conclusion: Despite some concordance between laboratories, qualification of secondary materials to the WHO IS using arbitrary international units or binding antibody units per milliliter (BAU/ml) does not provide any benefit to the reference materials overall, due to the lack of consistent agreeable international unit (IU) or BAU/ml conversions between laboratories. Secondary standards should be qualified to well-characterized reference materials, such as the WHO IS, using serology assays that are similar to the ones used for the original characterization of the WHO IS.

Unsupervised 3D prediction model for pulmonary disease progression in chest CT

We developed a 3D-image-based unsupervised prediction model, called vox2pred, for predicting the progression of pulmonary diseases based on a conditional generative adversarial network (cGAN). The architecture of the vox2pred model includes a time generator that consists of an encoding convolutional network and a fully connected prediction network, and a discriminator network. The time generator is trained to generate the progression time from the chest 3D CT image volumes of each patient. The discriminator is a patch-based 3D-convolutional network that is trained to differentiate between "predicted pairs"of a chest CT image volume and a predicted progression time from "true pairs"of the chest CT image volume and the corresponding observed progression time of the patient. For a pilot evaluation, we retrospectively collected high-resolution chest CT images of 141 patients with the coronavirus disease 2019 (COVID-19). The progression predictions of the vox2pred model on these patients were compared with those of existing clinical prognostic biomarkers by use of a two-sided t-test with bootstrapping. Concordance index (C-index) and relative absolute error (RAE) were used as measures of the prediction performance. The bootstrap evaluation yielded C-index and RAE values of 87.4% and 18.5% for the vox2pred model, whereas those for the visual assessment of the CT images in terms of a total severity score were 62.4% and 51.8%, and for the total severity score for crazy paving and consolidation (CPC), they were 64.7% and 51.3%, respectively. The increase in the accuracy of the progression prediction by the vox2pred model was statistically significant (p < 0.0001), indicating the high effectiveness of vox2pred as a prediction model for pulmonary disease progression in chest CT. © 2022 SPIE.

Handheld Fundus Camera for Diabetic Retinopathy Screening: A Comparison Study with Table-Top Fundus Camera in Real-Life Setting.

The aim of the study was to validate the performance of the Optomed Aurora® handheld fundus camera in diabetic retinopathy (DR) screening. Patients who were affected by diabetes mellitus and referred to the local DR screening service underwent fundus photography using a standard table-top fundus camera and the Optomed Aurora® handheld fundus camera. All photos were taken by a single, previously unexperienced operator. Among 423 enrolled eyes, we found a prevalence of 3.55% and 3.31% referable cases with the Aurora® and with the standard table-top fundus camera, respectively. The Aurora® obtained a sensitivity of 96.9% and a specificity of 94.8% in recognizing the presence of any degree of DR, a sensitivity of 100% and a specificity of 99.8% for any degree of diabetic maculopathy (DM) and a sensitivity of 100% and specificity of 99.8% for referable cases. The overall concordance coefficient k (95% CI) was 0.889 (0.828-0.949) and 0.831 (0.658-1.004) with linear weighting for DR and DM, respectively. The presence of hypertensive retinopathy (HR) was recognized by the Aurora® with a sensitivity and specificity of 100%. The Optomed Aurora® handheld fundus camera proved to be effective in recognizing referable cases in a real-life DR screening setting. It showed comparable results to a standard table-top fundus camera in DR, DM and HR detection and grading. The Aurora® can be integrated into telemedicine solutions and artificial intelligence services which, in addition to its portability and ease of use, make it particularly suitable for DR screening.

Slicing the Past to Predict Future

In this research, a heuristic approach is proposed and experimented with to detect warning signs based on historical data. The paper makes use of COVID-19 positive count reported by different states of the USA for illustration of the methods. These are data in the form of several single variable time series related to a concept. The basic idea is to divide the total time period into smaller segments and examine changes within and between series in the segments. Algorithms for clustering series and concordance are used as tools of the heuristic. The approach is to observe the behavior of members of clusters in the segments and predictions are formulated based on observed changes which is heuristic part. Hidden Markov Model is used for change detection and series clustering. Concordance is used for comparing similarity in behavior of series in segments.