Diagnosis Of COVID-19 Research Articles

Factors Associated with Post-COVID Syndrome Three Months After COVID-19

Objective: Post-COVID Syndrome has been defined as a syndrome with chronic fatigue and psychiatric problems continue after COVID-19. In this study, it was aimed to evaluate patients' health-related quality of life standards 3 months after COVID-19 diagnosis. Method: In this study, the psychosocial status and quality of life standards of patients, who were older than 18 years old and followed up due to COVID-19 in the outpatient clinic, ward, or intensive care unit of a university hospital, were assesed by the short form-36 scoring system. Results: Of 67 patients, 57 were followed up and treated at home, nine were admitted to the ward, and one was admitted to the the intensive care unit. Short form-36 test scores of women patients, patients aged over 65, had at least one comorbid disease, and inpatient treatments during acute infection were found to be statistically significantly lower. Conclusion: Gender, advanced age, presence of comorbidity, and history of hospitalization were determined as risk factors for Post-COVID Syndrome.

Evaluation of Coagulation Disorders in Intubated and Non-Intubated Patients with Covid-19 Diagnosis in The Intensive Care unit

Objective: It is known that the need for invasive mechanical ventilation due to severe respiratory failure develops in COVID-19 patients followed in the intensive care unit. It has been reported in the literature that coagulopathy seen during COVID-19 disease is an important cause of mortality and morbidity. Our aim in our study was to evaluate coagulation disorders developing between intubated and non-intubated patients. Method: The data of 812 patients diagnosed with COVID-19 in the Intensive Care Unit, between March 2020 and September 2021 were retrospectively analyzed. The patients were divided into two groups according to the need for invasive mechanical ventilation. Demographic characteristics, laboratory values at the time of diagnosis, coagulopathy development status and survival of the patients were investigated. Results: Of the 812 patients included in the study, 459 (56.5%) were male. The mean age was 66,4 ± 15,2. 257 (31.7%) of the patients received invasive mechanical ventilation support. Coagulopathy was detected in 146 (56.8%) of these patients. Distribution of coagulopathy in intubated patients; 26% Disseminated Intravascular Coagulation, 17.9% Acute Coronary Syndrome, 10.5% Hemorrhage (inside or outside the body), 5.4% Pulmonary Embolism, 5% Heparin-Induced Thrombocytopenia, 3.5% Ischemic Stroke, 1.9% Hemorrhagic Stroke and 0.8% found as Deep Vein Thrombosis. We found that 32% of the patients who were not intubated developed coagulopathy, and this difference was statistically significant (p

An Investigation on Inception V3 Network Models for Disease Severity Identification

Due to the high incubation period of COVID-19 and the use of restricted data, it is difficult to anticipate the number of casualties and the rate at which the virus would spread in the COVID-19 scenario. Monitoring those who are impacted and those who have interacted with them is perhaps the most difficult procedure. Since COVID-19 does require 14 days to incubate, it is doubtful that patients have been detected earlier. Patients have the ability to influence everyone they interact with while they are in the designated incubation period. Typically, the various machine learning algorithms are given the COVID-19 deep properties in order to classify the illness severity levels. Consequently, this may help in the early diagnosis of COVID-19. The created a deep feature extraction and classification model that successfully classified the COVID-19 severity levels using a variety of deep and machine learning algorithms. It has the ability to classify COVID-19 severity levels for early, accurate diagnosis. Ultimately, the results showed that the Inception V3 classifier outperformed all other models in both feature extraction and classificational, successfully extracting deep features from CT images and classifying the severity levels of COVID-19 infection. The testing results also showed that the classification of deep characteristics achieves promising use in COVID-19 severity prediction and diagnosis.

Mitigating COVID-19 in meat processing plants: what have we learned from cluster investigations?

Several COVID-19 outbreaks have been reported in meat processing plants in different countries. The aim of this study was to assess the environmental and socio-economic risk factors favouring the transmission of SARS-CoV-2 in meat processing plants and to describe the prevention measures implemented. Data from epidemiological investigations of COVID-19 clusters in France, the scientific literature, structured interviews and site visits were collected and summarised to investigate the main risk factors for SARS-CoV-2 infection in meat processing plants, including determinants within and outside the workplace. An increased risk of infection was identified among workers with unfavourable socio-economic status (temporary/non-permanent workers, migrants, ethnic minorities, etc.), possibly related to community activities (house-sharing, car-sharing, social activities). Working conditions (proximity between workers) and environmental factors (low temperatures and inadequate ventilation) also appear to be important risk factors. These environmental conditions are particularly prevalent in cutting and boning plants, where the majority of reported cases are concentrated. Preventive measures applied included screening for COVID-19 symptoms, testing, wearing masks, increased hygiene and sanitation, physical and temporal distancing, control of ventilation. Certain food safety hygiene measures were compatible with protecting workers from SARS-CoV-2. The hygiene culture of agri-food workers made it easier to implement preventive measures after adaptation. This study made it possible to identify the environmental and socio-economic factors conducive to the transmission of SARS-CoV-2 in meat processing plants. The knowledge gained from this work was used in simulations to understand the transmission of the virus in the plants.

Detection of COVID-19 incidence among attendees of the 2022 Hajj season

ObjectivesThis study investigated the presence of COVID-19 cases among pilgrims, health care workers (HCWs), and non-HCWs of Hajj 2022. MethodsNasopharyngeal samples were collected from 491 attendees of Hajj 2022. All participants received three doses of COVID-19 vaccines. Paired (n = 138; 69 participants) and unpaired (n = 422; 422 participants) nasopharyngeal swabs were subjected to reverse transcription–polymerase chain reaction targeting E gene of β-coronaviruses and RNA-dependent RNA polymerase of SARS-CoV-2. The results were linked to the participants’ profiles, including role during Hajj, presence of respiratory symptoms or comorbidities, contact with symptomatic individuals, smoking status, and COVID-19 recovery. ResultsA total of 20 (20 of 560; 3.6%) samples tested positive for COVID-19. Most cases (18 of 20; 90%) were pilgrims and non-HCWs. Six (30%) samples belonged to participants with previous positive reverse transcription–polymerase chain reaction. A total of 12 (60%) samples belonged to participants with respiratory symptoms. Three (15%) cases were linked to participants who had contact with individuals with respiratory symptoms. All cases belonged to individuals with no comorbidities, apart from a single case who has a chronic sinusitis. Five (25%) cases were smokers. No significant association was found between positive COVID-19 test and participants’ profiles. ConclusionsFew COVID-19 cases were detected in this study. Sustainable surveillance of COVID-19 and other respiratory viruses during Hajj seasons remains necessary.

Patients with type 1 diabetes are at elevated risk of developing new hypertension, chronic kidney disease and diabetic ketoacidosis after COVID-19: Up to 40 months' follow-up.

The aim was to investigate whether COVID-19 increases new incidence of hypertension (HTN), chronic kidney disease (CKD) and diabetic ketoacidosis (DKA) in patients with type 1 diabetes (T1D) up to 40 months post-infection. Three groups of patients from the Montefiore Health System in the Bronx (1 March 2020 to 1 July 2023) were studied: T1D patients hospitalized for COVID-19 (H-COVID-19, n = 511), T1D patients with COVID-19 but not hospitalized for COVID-19 (NH-COVID-19, n = 306) and T1D patients without a positive COVID-19 test on record (non-COVID-19, n = 1547). COVID-19 patients were those with a positive polymerase-chain-reaction test on record, and non-COVID-19 patients were either tested negative or not tested on record. Cumulative incidences and adjusted hazard ratios (aHR) with 95% confidence intervals (CI) were computed with adjustment for competing risks. Compared to non-COVID-19 patients, both H-COVID-19 (unadjusted 19.72% vs. 3.14%, p < 0.001; aHR = 7.55 [3.33, 17.06], p < 0.001) and NH-COVID-19 (10.26% vs. 3.14%, p = 0.004; aHR = 5.08 [2.19, 11.78], p < 0.001) patients were more likely to develop new HTN. Compared to non-COVID-19 patients, both H-COVID-19 (11.41% vs. 1.14%, p < 0.001; aHR = 9.76 [4.248, 22.25], p < 0.001) and NH-COVID-19 (7.69% vs. 1.14%, p < 0.001; aHR = 6.54 [2.91, 14.67], p < 0.001) patients were more likely to develop new CKD. Compared to non-COVID-19 patients, both H-COVID-19 (4.09% vs. 1.06%, p < 0.001; aHR = 12.24 [4.09, 36.59], p < 0.001) and NH-COVID-19 (3.06% vs. 1.06%, p = 0.035; aHR = 12.94 [4.09, 40.89], p < 0.001) patients were more likely to develop new DKA at follow-up. T1D patients with COVID-19 are at higher risk of developing new HTN, CKD and DKA compared to T1D patients without COVID-19.

COVID-19 Computed tomography patterns in renal replacement therapy patients.

Lung diseases are common in patients with end stage kidney disease (ESKD), making differential diagnosis with COVID-19 a challenge. This study describes pulmonary chest tomography (CT) findings in hospitalized ESKD patients on renal replacement therapy (RRT) with clinical suspicion of COVID-19. ESKD individuals referred to emergency department older than 18 years with clinical suspicion of COVID-19 were recruited. Epidemiological baseline clinical information was extracted from electronic health records. Pulmonary CT was classified as typical, indeterminate, atypical or negative. We then compared the CT findings of positive and negative COVID-19 patients. We recruited 109 patients (62.3% COVID-19-positive) between March and December 2020, mean age 60 ± 12.5 years, 43% female. The most common etiology of ESKD was diabetes. Median time on dialysis was 36 months, interquartile range = 12-84. The most common pulmonary lesion on CT was ground glass opacities. Typical CT pattern was more common in COVID-19 patients (40 (61%) vs 0 (0%) in non-COVID-19 patients, p < 0.001). Sensitivity was 60.61% (40/66) and specificity was 100% (40/40). Positive predictive value and negative predictive value were 100% and 62.3%, respectively. Atypical CT pattern was more frequent in COVID-19-negative patients (9 (14%) vs 24 (56%) in COVID-19-positive, p < 0.001), while the indeterminate pattern was similar in both groups (13 (20%) vs 6 (14%), p = 0.606), and negative pattern was more common in COVID-19-negative patients (4 (6%) vs 12 (28%), p = 0.002). In hospitalized ESKD patients on RRT, atypical chest CT pattern cannot adequately rule out the diagnosis of COVID-19.

The Risks and Safety Practices of Waste Pickers at Selected Dumping Sites in Pretoria, South Africa, During the COVID-19 Pandemic

Amid the COVID-19 outbreak, the accumulation of household waste continued to rise as the number of COVID-19 patients increased. COVID-19 can survive and be transmitted from contaminated surfaces, making waste pickers more vulnerable and at risk of contracting and spreading the virus through contact with infected household waste. The study assessed safety practices and risks related to waste picking during the COVID-19 pandemic at two selected dumping sites in the north of Pretoria. Structured questionnaires were used to collect data from 81 waste pickers at these landfill sites. Results showed that 100.0% of waste pickers at Site A and 86.7% at Site B collected plastics; 96.7% at Site A and 90.5% at Site B collected bottles; and 100% at Site B and 95.5% at Site A collected metals. The majority, 92.0% at Site A and 90.0% at Site B, were aware of the dangers and risks associated with waste handling if protective gear was not worn. From sites A and B, 97.0% and 90% of the waste pickers respectively had heard of COVID-19, although 51.9% from both sites believed they could not contract COVID-19 while handling waste. Only 18.0% of waste pickers from Site A and 82.0% from Site B faced challenges with purchasing their own PPE. All waste pickers at Site A wore facial masks, whereas 86.0% at Site B did so. Regarding testing for COVID-19, 22.0% from Site A and 19.0% from Site B were tested, with 2.0% from Site A and none (0.0%) from Site B testing positive. It is recommended that all waste pickers be educated about COVID-19 transmission and provided with PPE during the pandemic.

Maximal respiratory pressure after COVID-19 compared with reference material in healthy adults: A prospective cohort study (The SECURe study).

After COVID-19 long term respiratory symptoms and reduced lung function including maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) have been reported. However, no studies have looked at MIP and MEP in all disease groups and the reference materials collection methods differ substantially. We aimed to determine MIP and MEP in individuals after COVID-19 infection with different disease severity using reference material of healthy control group obtained using the same standardized method. Patients with COVID-19 were included March 2020-March 2021 at Rigshospitalet, Denmark. MIP and MEP were measured using microRPM. Predicted MIP and MEP were calculated using reference material obtained from 298 healthy adults aged 18-97 years using the same method. In SECURe, 145 participants were measured median 5 months after COVID-19 diagnosis and of these 16% had reduced MIP and/or MEP. There was reduced spirometry and total lung capacity, but not reduced diffusion capacity in those with abnormal MIP and/or MEP compared with normal MIP and MEP. Of those with reduced MIP and/or MEP at 5 months, 80% still had reduced MIP and/or MEP at 12 months follow-up. In conclusion, few have reduced MIP and/or MEP 5 months after COVID-19 and little improvement was seen over time.

Impact of COVID-19 on Antibiotic Stewardship, Antimicrobial Resistance, and Prescribing Habits at Two General Hospitals in Abu Dhabi: A Retrospective Analysis.

Introduction The COVID-19 pandemic has overwhelmingly affected healthcare systems, particularly in the area of antibiotic management. The surge in antimicrobial use to address secondary bacterial infections in COVID-19 patients has heightened concerns about overuse and antimicrobial resistance (AMR). This study examined the pandemic's effect on the antibiotic stewardship program (ASP) at two general hospitals in Abu Dhabi, focusing on changes in prescribing practices, adherence to stewardship guidelines, resistance trends, and overall health system impact. The present retrospective study evaluated shifts in antibiotic consumption, compliance with stewardship practices, and broader healthcare implications. The aim is to assess the pandemic's impact, identify improvement areas, and provide insights to enhance the ASP in addressing the global AMR crisis. Methods This retrospective review assessed electronic medical records from two general hospitals in Abu Dhabi over a 24-month period, from January 2019 to December 2020. It included pre-COVID-19 data from 2019 and data from 2020 during the COVID-19 surge. The study focused on patients aged 25 to 40 years with respiratory tract infections, urinary tract infections, ventilator-associated pneumonia, and nosocomial infections, identified using predefined ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes. Patients with COVID-19 diagnoses and those undergoing surgical procedures were excluded. Key metrics compared data from 2019 and 2020 to assess changes in clinicians' prescribing practices, antibiotic usage, ASP interventions, and their impact on the healthcare system. Results The COVID-19 pandemic influenced antibiotic use and resistance trends, leading to longer hospital stays (3.86 days in 2019 vs. 4.29 days in 2020) and increased use of duplicate anaerobic therapy (4.58% in 2019 vs. 5.71%in 2020). From 2019 to 2020, the average duration of antibiotic therapy decreased from 6.23 days to 5.24 days, but empirical therapy without sufficient evidence rose. The average length of treatment increased (2.87 days in 2019 vs. 3.28 days in 2020), and there was a rise in the use of antibiotics for viral and fungal infections, with cases growing from 17.08%in 2019 to 22.38%in 2020. Despite modest improvements in stewardship practices in 2020, AMR challenges persisted. These results underscore the need for enhanced stewardship programs and continued research to address the ongoing impacton antibiotic prescribing and resistance. Conclusion The COVID-19 pandemic increased antibiotic use and altered resistance patterns. Although stewardship practices improved, AMR challenges remained. Enhanced stewardship programs and ongoing research are essential to mitigate these effects and improve antibiotic management. Recommendation To address changes in antibiotic use and resistance during the COVID-19 pandemic, it is recommended to strengthen ASPs to adapt to new prescribing trends, ensure adherence to evidence-based practices, provide ongoing education for clinicians, invest in research on long-term resistance impacts, and enhance data tracking and monitoring systems.

634. SURGICAL OUTCOMES OF ESOPHAGEAL CANCER PATIENTS BASED ON PRIOR COVID DIAGNOSIS

Abstract Background Since the Covid pandemic, many studies have been performed to determine the impact of Covid on surgical outcomes. Many researchers have found that prior Covid diagnosis puts surgical patients at higher risk of complication and mortality. The aim of this study is to determine if esophageal cancer patients undergoing esophagectomy are at higher risk based on previous Covid status. Methods The National Cancer Database (NCDB) was queried for all patients who underwent esophagectomy for cancer in 2020. This study was limited to the 2020 database as this was the year that Covid status was added to the NCDB registry. Patients with a Covid history and without a Covid history were compared. Only patients with complete Covid information were included in this study. Peri-operative outcomes including hospital length of stay and 30-day readmission were compared between groups. Wilcoxon rank-sum tests were performed to compare continuous variables between groups and Chi-square/Fisher’s exact tests were performed to compare categorical variables between groups. Results A total of 2387 patients met inclusion criteria, of which 114 (5%) had prior diagnosis of Covid and 2273 (95%) did not have prior Covid. There were no significant differences regarding basic demographics, including age, gender, neoadjuvant therapy, or pathologic staging. Both groups had similar rates of minimally invasive techniques and conversions to open surgery. There was no difference regarding 30-day readmission, however, the Covid group had a statistically longer hospital length of stay, 9 days (IQR 6-15) vs 8 days (IQR 1-11), p=0.007. On logistic regression, Covid was an independent predictor of increased overall length of stay (p=0.045). Conclusion Despite previous evidence that Covid patients may experience more surgical complications than their non-Covid counterparts, this NCDB study of esophageal patients undergoing esophagectomy demonstrated similar baseline demographics and outcomes with the only significant difference being longer hospital length of stay. Further research is necessary to determine risk of previous Covid diagnosis in surgical outcomes.

Lessons Learned from Community Partnership During the COVID-19 Pandemic

Abstract: Underserved communities have been disproportionately affected by the COVID-19 pandemic. The Project Promoting Engagement and COVID-19 Testing for Health (PEACH) study was designed to understand the attitudes, beliefs, and infrastructure associated with COVID-19 risk, testing, and prevention behaviors in people living with, caring for, or at risk for type 2 diabetes. The purpose of this joint community–academic partnered manuscript is to share lessons learned for maintaining community partnerships through the challenging times of a pandemic. New and existing community partners were invited to share their perceptions about the facilitators and barriers of partnering with academia during the COVID-19 public health crisis. Key facilitators included those partners felt heard and their input valued. And the changing nature and demands in response to the pandemic on the partners’ responsibilities were among the key challenges. Successful maintenance of the partnerships required flexibility, creativity, and a willingness to adapt engagement as community partners responded to the needs of their communities.

Impact of Cardiorespiratory Fitness on COVID-19–Related Outcomes: The Exercise Testing and Health Outcomes Study (ETHOS)

ObjectiveTo assess the association between cardiorespiratory fitness (CRF) and COVID-19–related health outcomes including mortality, hospitalization, and mechanical ventilation. Patients and MethodsIn a retrospective analysis of 750,302 patients included in the Exercise Testing and Health Outcomes Study, we identified 23,140 who had a positive result on COVID-19 testing between March 2020 and September 2021 and underwent a maximal exercise test in the Veterans Affairs Health Care System between October 1, 1999 to September 3, 2020. The association between CRF and risk for severe COVID-19 outcomes, including mortality, hospitalization due to COVID-19, and need for intubation was assessed after adjustment for 15 covariates. Patients were stratified into 5 age-specific CRF categories (Least-Fit, Low-Fit, Moderate-Fit, Fit, and High-Fit), based on peak metabolic equivalents achieved. ResultsDuring a median of follow-up of 100 days, 1643 of the 23,140 patients (7.1%) died, 4995 (21.6%) were hospitalized, and 927 (4.0%) required intubation for COVID-19–related reasons. When compared with the Least-Fit patients (referent), the Low-Fit, Moderate-Fit, Fit, and High-Fit patients had hazard ratios for mortality of 0.82 (95% CI, 0.72 to 0.93), 0.73 (95% CI, 0.63 to 0.86), 0.61 (95% CI, 0.53 to 0.72), and 0.54 (95% CI, 0.45 to 0.65), respectively. Patients who were more fit also had substantially lower need for hospital admissions and intubation. Similar patterns were observed for elderly patients and subgroups with comorbidities including hypertension, diabetes, cardiovascular disease, and chronic kidney disease; for each of these conditions, those in the High-Fit category had mortality rates that were roughly half those in the Low-Fit category. ConclusionAmong patients positive for COVID-19, higher CRF had a favorable impact on survival, need for hospitalization, and need for intubation regardless of age, body mass index, or the presence of comorbidities.

Retrospective Study Of The Clinical Characteristics Of Cases With Covid-19

background: COVID-19 pandemic placed immense pressure on health systems. The disease is transmitted by inhalation or contact with infected droplets. The symptoms are usually fever, cough, sore throat, breathlessness, fatigue and malaise. The aim of this study was to determine the clinical characteristics of cases with covid-19. Design: Observational retrospective study was followed in this study. Study setting: This study was conducted at Tanta main university hospital and Itay El-baroud general hospital. Subjects: A purposeful sample of 100 adult isolated patients from the previosly mentioned settings was included in the study. Collection tools: one tool was used to collect data in this study "Covid-19 clinical characteristics assessment sheet" this tool consists of 2 parts: Part (1): Demograhic data of the studied cases with covid-19 Part (2): clinical characteristics of studied cases with covid-19. The results were as follow: the results indicated that around one third of the participants were dead and there was highly significant relationship between hypertension, diabetes mellitus, serum Ferritin level and blood group A and death (p&lt;0.001). ICU admission rate was 71% and 35% of covid-19 cases needed invasive mechanical ventilation. Conclusion: it was concluded that the majority of confirmed covid-19 patients were old males. The highly reported signs and symptoms were fatigue, weakness, anorexia, tachypnea and fever. Hypertension and diabetes mellitus were the most reported comorbid diseases of confirmed covid-19 patients. Recommendations: Generalize the awareness of the most reported clinical characteristics of covid-19 to help health care providers to make the correct initial suspected diagnosis of COVID-19

Detecting COVID-19 from chest X-ray images using machine learning and deep convolutional neural networks

&lt;p&gt;The world was affected by a novel coronavirus in December 2019 that changed human life. Several types of research have been done, substantial scientific advances have been made, and millions of dollars have been spent on bringing scholars and scientists to one platform to end this critical pandemic. Ascertaining COVID-19 diagnoses in the initial stage of the pandemic was critical, specifically for patients with no manifestations. In this case, artificial intelligence-based systems were proposed to identify the virus at an earlier phase. Thus, the present study suggests a machine vision scheme to identify COVID-19 from chest X-ray images. Three machine learning approaches, such as logistic regression (LR), decision tree (DT), and random forest (RF), were implemented with more than 95% accuracy. The deep convolutional neural network (CNN) architecture was also proposed and implemented with a 99.99% detection rate. Therefore, the present work can effectively detect COVID-19 cases in the early stages.&lt;/p&gt;

A Single-center Experience With >200 Lung Transplant Recipients With COVID-19 Infection.

Although COVID-19 is no longer a declared global health emergency, data remain limited on the impact of COVID-19 in lung transplant recipients. We identified lung transplant recipients who were diagnosed with COVID-19 from March 2020 through August 2022 in our institutional database and investigated clinical outcomes. We then analyzed outcomes based on date of COVID-19 diagnosis (first wave March 2020-October 2020; second wave November 2020-2021; third wave December 2021-September 2022) and compared these results. Of the 210 lung transplant recipients (median age 67; 67% men) enrolled, 140 (67%) required hospital admission. Among admitted recipients, 35 (25%) were intubated and 7 (5%) were placed on extracorporeal membrane oxygenation. Overall survival was 67.1% at 1 y and 59.0% at 2 y post-COVID-19 diagnosis. COVID-19 led to mortality in all 5 patients diagnosed during their index admission for lung transplantation. Although overall survival was significantly better in recipients with COVID-19 during the third wave, in-hospital mortality remained high (first wave 28%, second wave 38%, and 28% third wave). Vaccination (partially vaccinated versus none and fully vaccinated versus none) was the only significant protective factor for hospital admission, and age 70 y and older and partially vaccinated (versus none or fully vaccinated) were independent risk factors for in-hospital mortality. Overall survival after COVID-19 infection in lung transplant recipients continues to improve; however, in-hospital mortality remains remarkably high. Vaccination appears to have been impactful in preventing hospital admission, but its impact on in-hospital mortality is still unclear. Further research is needed to better identify lung transplant recipients at high risk for mortality from COVID-19.

Improving Fairness of Automated Chest Radiograph Diagnosis by Contrastive Learning.

Purpose To develop an artificial intelligence model that uses supervised contrastive learning (SCL) to minimize bias in chest radiograph diagnosis. Materials and Methods In this retrospective study, the proposed method was evaluated on two datasets: the Medical Imaging and Data Resource Center (MIDRC) dataset with 77 887 chest radiographs in 27 796 patients collected as of April 20, 2023, for COVID-19 diagnosis and the National Institutes of Health ChestX-ray14 dataset with 112 120 chest radiographs in 30 805 patients collected between 1992 and 2015. In the ChestX-ray14 dataset, thoracic abnormalities included atelectasis, cardiomegaly, effusion, infiltration, mass, nodule, pneumonia, pneumothorax, consolidation, edema, emphysema, fibrosis, pleural thickening, and hernia. The proposed method used SCL with carefully selected positive and negative samples to generate fair image embeddings, which were fine-tuned for subsequent tasks to reduce bias in chest radiograph diagnosis. The method was evaluated using the marginal area under the receiver operating characteristic curve difference (∆mAUC). Results The proposed model showed a significant decrease in bias across all subgroups compared with the baseline models, as evidenced by a paired t test (P < .001). The ∆mAUCs obtained by the proposed method were 0.01 (95% CI: 0.01, 0.01), 0.21 (95% CI: 0.21, 0.21), and 0.10 (95% CI: 0.10, 0.10) for sex, race, and age subgroups, respectively, on the MIDRC dataset and 0.01 (95% CI: 0.01, 0.01) and 0.05 (95% CI: 0.05, 0.05) for sex and age subgroups, respectively, on the ChestX-ray14 dataset. Conclusion Employing SCL can mitigate bias in chest radiograph diagnosis, addressing concerns of fairness and reliability in deep learning-based diagnostic methods. Keywords: Thorax, Diagnosis, Supervised Learning, Convolutional Neural Network (CNN), Computer-aided Diagnosis (CAD) Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Johnson in this issue.

Innovation and Patenting Activities During COVID-19 and Advancement of Biochemical and Molecular Diagnosis in the Post- COVID-19 Era.

The COVID-19 pandemic is to escalate globally and acquire new mutations quickly, so accurate diagnostic technologies play a vital role in controlling and understanding the epidemiology of the disease. A plethora of technologies acquires diagnosis of individuals and informs clinical management of COVID. Some important biochemical parameters for COVID diagnosis are the elevation of liver enzymes, creatinine, and nonspecific inflammatory markers such as C-reactive protein (CRP) and Interleukin 6 (IL-6). The main progression predictors are lymphopenia, elevated D-dimer, and hyperferritinemia, although it is also necessary to consider LDH, CPK, and troponin in the marker panel of diagnosis. Owing to the greater sensitivity and accuracy, molecular technologies such as conventional polymerase chain reaction (PCR), reverse transcription (RT)-PCR, nested PCR, loop-mediated isothermal amplification (LAMP), and xMAP technology have been extensively used for COVID diagnosis for some time now. To make so many diagnostics accessible to general people, many techniques may be exploited, including point of care (POC), also called bedside testing, which is developing as a portable promising tool in pathogen identification. Some other lateral flow assay (LFA)-centered techniques like SHERLOCK, CRISPR-Cas12a (AIOD-CRISPR), and FNCAS9 editor limited uniform detection assay (FELUDA), etc. have shown auspicious results in the rapid detection of pathogens. More recently, low-cost sequencing and advancements in big data management have resulted in a slow but steady rise of next-generation sequencing (NGS)-based approaches for diagnosis that have potential relevance for clinical purposes and may pave the way toward a better future. Due to the COVID-19 pandemic, various institutions provided free, specialized websites and tools to promote research and access to critically needed advanced solutions by alleviating research and analysis of data within a substantial body of scientific and patent literature regarding biochemical and molecular diagnosis published since January 2020. This circumstance is unquestionably unique and difficult for anyone using patent information to find pertinent disclosures at a specific date in a trustworthy manner.

Autoimmune Sequelae After Delta or Omicron Variant SARS-CoV-2 Infection in a Highly Vaccinated Cohort

Studies have reported increased risk of autoimmune sequelae after SARS-CoV-2 infection. However, risk may potentially be attenuated by milder Omicron (B.1.1.529) variant infection and availability of booster vaccination. To estimate the 300-day risk of new-incident autoimmune sequelae after SARS-CoV-2 Delta or Omicron BA.1 or BA.2 variant infection in adults who received COVID-19 vaccines and boosters, compared with a contemporary control group without infection. This cohort study in Singapore enrolled adults from September 1, 2021, to March 7, 2022, and followed up for 300 days. Participants were adults aged 18 years or older with SARS-CoV-2 infection during the predominance of the Delta and Omicron BA.1 or BA.2 variants and were still alive at 30 days after COVID-19 diagnosis. The national SARS-CoV-2 testing registry was used to construct cohorts of adults with SARS-CoV-2 Delta or Omicron BA.1 or BA.2 variant infection (hereafter, cases) and a contemporaneous group with negative polymerase chain reaction or rapid antigen test results (hereafter, controls). New-incident autoimmune diagnoses after SARS-CoV-2 infection. This information was recorded in the MediClaims national health care claims database and identified 31 to 300 days after index date of infection. Risks and excess burdens were estimated using Cox proportional hazards regression model with overlap weights applied. In total, 1 766 036 adults (915 096 females [51.9%]; mean [SD] age, 49 [18] years) were included in the study population, with 480 082 (27.2%) categorized as cases and 1 285 954 (72.8%) as controls. Of these adults, 73.1% had Chinese, 13.7% Malay, and 9.9% Indian ethnicity. There were 104 179 cases and 666 575 controls included during the Delta variant-predominance transmission, while 375 903 cases and 619 379 controls were included during the Omicron variant-predominance transmission. During the Delta variant period, 81.1% of cases had completed primary vaccination; during the Omicron variant period, 74.6% of cases received boosters. No significantly elevated risk of 12 prespecified autoimmune sequelae was recorded across the Omicron and Delta variant cohorts. Elevated risks of inflammatory bowel disease (adjusted hazard ratio [AHR], 2.23; 95% CI, 1.45-3.46; P < .001) and bullous skin disorders (AHR, 4.88; 95% CI, 2.47-9.66; P < .001) were observed only in the subset of COVID-19 cases requiring hospitalization during the predominance of the Omicron variant. While elevated risk of vasculitis (AHR, 5.74; 95% CI, 1.48-22.23; P = .01) was observed in vaccine-breakthrough Omicron variant infections, no increased risk of vasculitis was observed in the corresponding subgroup who received boosters. This cohort study observed no significantly elevated long-term risk of autoimmune sequelae after SARS-CoV-2 Delta and Omicron BA.1 or BA.2 variant infection, except for a modestly increased risk of inflammatory bowel disease and bullous skin disorders in the hospitalized subgroup during the predominance of the Omicron variant. Booster vaccination appeared to mitigate the risk of long-term autoimmune sequelae.

“I felt like it was the right thing to do”: How college students’ decisions to disclose COVID-19 diagnoses reflect privacy preferences, perceptions of stigma, and cultural norms

Background: COVID-19 diagnoses can be difficult to share, as COVID-19 faces ongoing stigmatization. Aim: Framed by communication privacy management theory, this study examines how college students make decisions to disclose their COVID-19-positive statuses (or why they may not), and how those decisions are affected by perceptions of stigma and cultural norms. Methods: This study utilizes a qualitative, interview-based methodology with twenty undergraduate student participants. Results: Responses are analyzed for themes relating to communication privacy management, noting information control and co-ownership, boundary coordination, and forced/required disclosures. Responses demonstrate that a stigmatized view of COVID-19 has largely subsided, but still affects disclosure preferences and decisions. In addition, several cultural factors also shape beliefs about disclosure practices. Discussion: These findings illuminate how perceptions of COVID-19’s stigma and cultural norms shape college students’ notions of privacy, information control, co-ownership, and ultimately disclosure practices. Highlighting implications for how best to respond to future pandemics, the data presented herein provides an exploration of the relationship between privacy strategies, stigmatization beliefs, and cultural norms. Conclusion: This information will be useful in generating institutional, education, and public health responses to future pandemics, as findings suggest an under-theorized relationship between the areas of privacy management, stigmatization, and cultural norms.