Kikuchi-Fujimoto Disease Following COVID-19 Vaccination: Experience at a Population-Based Referral Center

Objectives: Multiple case reports describe Kikuchi-Fujimoto disease (KFD) following COVID-19 vaccination, but the true nature of this phenomenon is unknown. The purpose of this study was to further assess the relationship between KFD and COVID-19 vaccination at the population level.Methods: Confirmed KFD cases from January 2018 to April 2022 were identified from provincial pathology archives and analyzed in the context of vaccination statistics from public health resources.Results: Our statistical models provide evidence of a temporal association between KFD and both antecedent COVID-19 vaccine administration as well as age-stratified vaccination rates. Eight new cases of plausible COVID-19 vaccine-associated KFD are presented, collectively exhibiting clinical and pathologic features that overlap substantially with those of idiopathic KFD.Conclusions: Our findings indicate that KFD is observed in association with COVID-19 vaccination and suggest that mechanistic studies are warranted.

Defensive Behaviors During COVID-19 and the 2020–2021 Firearm Purchasing Surge: A Latent Class Analysis

Objective: This study examined the extent to which political beliefs and public health behaviors cluster together and define distinct groups of individuals and whether those groups differ on firearm purchasing behaviors. Methods: 6,404 US residents (Minnesota, n = 1,789;Mississippi, n = 1,418;New Jersey, n = 3,197) were recruited via Qualtrics panels. Participants were matched to 2010 census data. Results: Fit statistics determined a four-class solution fit the data best. The Liberal-Many Health Behaviors class had high probabilities of voting for President Biden, reporting more liberal political beliefs than other classes, and engaging in multiple health behaviors (e.g., mask wearing, vaccination). The Moderate-Few Health Behaviors class had high probabilities of voting for President Biden, reporting moderate political beliefs, and engaging in few health behaviors. The Conservative-Few Health Behaviors class had high probabilities of voting for former President Trump, reporting conservative political beliefs, and engaging in few health behaviors. The Conservative-Many Health Behaviors class had high probabilities of voting for former President Trump, having conservative political beliefs, and engaging in many health behaviors. Of the participants in the study who reported owning firearms, those in the Few Health Behavior classes were more likely to have purchased firearms during the purchasing surge, whereas those in the Many Health Behavior classes were likely to have become first-time firearm owners in 2020-2021. Lastly, the Few Health Behavior classes exhibited significantly less trust in the intentions of scientists. Conclusion: Different subgroups of firearm owners may evaluate and respond to risk differently, resulting in a pattern of adopting or avoiding a range of public health recommendations. Those who avoided mask wearing and COVID-19 vaccinations and who purchased firearms during the firearm purchasing surge appear to have less trust in science, highlighting the need for trusted messengers to increase the reach of behavioral interventions. [ FROM AUTHOR] Copyright of Journal of Social & Clinical Psychology is the property of Guilford Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Remote research methods for Human-AI-Robot Teaming

This study focuses on methodological adaptations and considerations for remote research on Human-AI-Robot Teaming (HART) amidst the COVID-19 pandemic. Themes and effective remote research methods were explored. Central issues in remote research were identified, such as challenges in attending to participants' experiences, coordinating experimenter teams remotely, and protecting privacy and confidentiality. Instances of experimental design overcoming these challenges were identified in methods for recruitment and onboarding, training, team task scenarios, and measurement. Three case studies are presented in which interactive in-person testbeds for HART were rapidly redesigned to function remotely. Although COVID-19 may have temporarily constrained experimental design, future HART studies may adopt remote research methods to expand the research toolkit. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Elective Joint Arthroplasty Should be Delayed by One Month After COVID-19 Infection to Prevent Postoperative Complications.

BACKGROUND: It remains unclear whether a history of recent COVID-19 infection affects the outcomes and risks of complications of total joint arthroplasty (TJA). The purpose of this study was to compare the outcomes of TJA in patients who have and have not had a recent COVID-19 infection. METHODS: A large national database was queried for patients undergoing total hip and total knee arthroplasty. Patients who had a diagnosis of COVID-19 within 90-days preoperatively were matched to patients who did not have a history of COVID-19 based on age, sex, Charlson Comorbidity Index, and procedure. A total of 31,453 patients undergoing TJA were identified, of which 616 (2.0%) had a preoperative diagnosis of COVID-19. Of these, 281 COVID-19 positive patients were matched with 281 patients who did not have COVID-19. The 90-day complications were compared between patients who did and did not have a diagnosis of COVID-19 at 1, 2, and 3 months preoperatively. Multivariate analyses were used to further control for potential confounders. RESULTS: Multivariate analysis of the matched cohorts showed that COVID-19 infection within 1 month prior to TJA was associated with an increased rate of postoperative deep vein thrombosis (odds ratio [OR]: 6.50, 95% confidence interval: 1.48-28.45, P = .010) and venous thromboembolic events (odds ratio: 8.32, confidence interval: 2.12-34.84, P = .002). COVID-19 infection within 2 and 3 months prior to TJA did not significantly affect outcomes. CONCLUSION: COVID-19 infection within 1 month prior to TJA significantly increases the risk of postoperative thromboembolic events; however, complication rates returned to baseline after that time point. Surgeons should consider delaying elective total hip arthroplasty and total knee arthroplasty until 1 month after a COVID-19 infection.

Antiviral nanopharmaceuticals: Engineered surface interactions and virus-selective activity.

The COVID-19 pandemic has inspired large research investments from the global scientific community in the study of viral properties and antiviral technologies (e.g., self-cleaning surfaces, virucides, antiviral drugs, and vaccines). Emerging viruses are a constant threat due to the substantial variation in viral structures, limiting the potential for expanded broad-spectrum antiviral agent development, and the complexity of targeting multiple and diverse viral species with unique characteristics involving their virulence. Multiple, more infectious variants of SARS-CoV2 (e.g., Delta, Omicron) have already appeared, necessitating research into versatile, robust control strategies in response to the looming threat of future viruses. Nanotechnology and nanomaterials have played a vital role in addressing current viral threats, from mRNA-based vaccines to nanoparticle-based drugs and nanotechnology enhanced disinfection methods. Rapid progress in the field has prompted a review of the current literature primarily focused on nanotechnology-based virucides and antivirals. In this review, a brief description of antiviral drugs is provided first as background with most of the discussion focused on key design considerations for high-efficacy antiviral nanomaterials (e.g., nanopharmaceuticals) as determined from published studies as well as related modes of biological activity. Insights into potential future research directions are also provided with a section devoted specifically to the SARS-CoV2 virus. This article is categorized under: Toxicology and Regulatory Issues in Nanomediciney > Toxicology of Nanomaterials Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease Therapeutic Approaches and Drug Discovery > Nanomedicine for Respiratory Disease.

Correlates of psychological distress among undergraduate women engaged in remote learning through a New York City college during the COVID-19 pandemic.

OBJECTIVE: The study's objective is to explore psychological distress (PD) among remote learners during COVID-19. PARTICIPANTS: Female undergraduates matriculated at an NYC college in Winter 2020. METHODS: Using the Kessler-6 scale, we defined PD as no/low (LPD), mild/moderate (MPD), and severe (SPD) and assessed if residing in/near NYC modified associations. RESULTS: PD was common (MPD: 34.1%, SPD: 38.9%). Students identifying as Other/Multiracial had lower MPD odds (aOR = 0.39 [0.17-0.88]). SPD was associated with identifying as White (aOR = 2.02 [1.02-3.99]), unbalanced meals (aOR = 2.59 [1.06-6.30]), violence experience (aOR = 1.77 [1.06-2.94]), no social support (aOR = 3.24 [1.37-7.64]), and loneliness (aOR = 2.52 [1.29-4.95]). Among students in/near NYC, moderate/high drug use (aOR = 2.76 [1.15-6.61]), no social support (aOR = 3.62 [1.10-1.19]), and loneliness (aOR = 2.92 [1.11-7.63]) were SPD correlates. CONCLUSIONS: PD was high and associated with food insecurity, violence experience, no social support, and loneliness. Living in/near NYC modified drug use, loneliness, and social support associations. Mental health initiatives should address modifiable risk factors to ameliorate pandemic-associated PD.

Adaptive behaviour in children exposed to topiramate in the womb: An observational cohort study.

OBJECTIVE: Many women with epilepsy need to continue anti-seizure medications (ASMs) throughout pregnancy. The current study investigated adaptive behaviour outcomes in children exposed to topiramate in the womb. METHOD: An observational, cross-sectional study was designed, recruiting mother-child-pairs from the UK Epilepsy and Pregnancy Register (UKEPR). Health, developmental histories and Vineland Adaptive Behaviour Scale-Third Edition (VABS-III) assessments were administered via telephone by a blinded researcher, supplemented with prospectively collected pregnancy and medication information. Topiramate monotherapy exposed children were compared to VABS-III normative data as recruitment was disrupted by the COVID-19 pandemic. RESULTS: Thirty-four women with epilepsy from 135 (25%) initially agreed to participate in the study, of whom 26 women completed telephone interviews about their children (n = 28). Children ranged from 2.5 to 17 years of age at the time of assessment. Six topiramate-exposed children were born small for gestational age, and there were significant associations between birthweight, dose and VABS-III scores. Significantly lower scores were observed in topiramate-exposed children (n = 21) with a significant dose-response relationship established after adjustment for parental educational level. Daily mean dosage was 280.21 mg, with high dosages of topiramate associated with a 12-point reduction in VABS-III scores. Additionally, four topiramate-exposed children (19.05%) had diagnoses of Autism Spectrum Disorder, which was significantly higher than UK prevalence rates (1.1%). CONCLUSIONS: The findings of poorer adaptive behaviour, higher incidence of ASD and associations with birth weight are of concern and require further validation and replication using larger prospectively-recruited samples and comparator cohorts. Implications for research and clinical practice are discussed.

Digital device use, dry eye and quality of life in youth

Purpose: Excessive screen use is a pervasive global phenomenon, recently aggravated by COVID-19-related mobility restrictions. Wide-ranging implications for health and quality of life are linked to extended screen time, the early onset of which may place young people at risk. This study evaluated screen use habits, dry eye disease markers and the associated impacts on quality of life and vision in a young cohort of extended screen users. Method(s): A total of 456 attendees of a gaming convention in Auckland, New Zealand completed a self-directed iPad-based survey on personal screen use habits, ocular symptoms and quality of life. Habitual blinking was assessed covertly using the front-facing iPad camera and proxy tear film stability measurements were conducted. Result(s): Participants (aged 24+/-10, 38% female, 11% contact lens wearers) reported a weekly average screen time of 44+/-24 hours. When compared to non-lens wearers, contact lens wearers reported a higher impact severity on daily quality of life (38% vs 29%), on vision-related quality of life (40% vs 31%) and more severe and frequent dryness symptoms (42% vs 32%;all p<0.009). Overall, 27% of respondents qualified as symptomatic for dry eye disease based on a Dry Eye Questionnaire-5 (DEQ-5) score >= 6 and proxy tear film stability values of <10 seconds. Extended screen use was associated with ocular symptomology, blink frequency and proxy tear film stability (all p<0.05). Conclusion(s): Young participants commonly report extended habitual screen use that are associated with typical symptoms and signs of dry eye disease, as well as significant impacts on quality of life. This may place youth at risk of deteriorating ocular health and comfort, underlining a pressing need for evidence to guide policy development on safe screen use, and for screening and educational interventions around screen use in routine clinical practice. Copyright © 2022

Promoting the Success and Sustainability of Coordinated Specialty Care Teams in Ohio.

Recent COVID-19-related federal legislation has resulted in time-limited increases in Mental Health Block Grant (MHBG) set-aside dollars for coordinated specialty care (CSC) throughout the United States. The state of Ohio has opted to apply these funds to establish a learning health network of Ohio CSC teams, promote efforts to expand access to CSC, and quantify the operating costs and rates of reimbursement from private and public payers for these CSC teams. These efforts may provide other states with a model through which they can apply increased MHBG funds to support the success of their own CSC programs.

Heparin Inhibits SARS-CoV-2 Replication in Human Nasal Epithelial Cells.

SARS-CoV-2 is the causative agent of the COVID-19 pandemic. Vaccination, supported by social and public health measures, has proven efficacious for reducing disease severity and virus spread. However, the emergence of highly transmissible viral variants that escape prior immunity highlights the need for additional mitigation approaches. Heparin binds the SARS-CoV-2 spike protein and can inhibit virus entry and replication in susceptible human cell lines and bronchial epithelial cells. Primary infection predominantly occurs via the nasal epithelium, but the nasal cell biology of SARS-CoV-2 is not well studied. We hypothesized that prophylactic intranasal administration of heparin may provide strain-agnostic protection for household contacts or those in high-risk settings against SARS-CoV-2 infection. Therefore, we investigated the ability of heparin to inhibit SARS-CoV-2 infection and replication in differentiated human nasal epithelial cells and showed that prolonged exposure to heparin inhibits virus infection. Furthermore, we establish a method for PCR detection of SARS-CoV-2 viral genomes in heparin-treated samples that can be adapted for the detection of viruses in clinical studies.

Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales.

BACKGROUND: Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a prothrombotic state, but long-term effects of COVID-19 on incidence of vascular diseases are unclear. METHODS: We studied vascular diseases after COVID-19 diagnosis in population-wide anonymized linked English and Welsh electronic health records from January 1 to December 7, 2020. We estimated adjusted hazard ratios comparing the incidence of arterial thromboses and venous thromboembolic events (VTEs) after diagnosis of COVID-19 with the incidence in people without a COVID-19 diagnosis. We conducted subgroup analyses by COVID-19 severity, demographic characteristics, and previous history. RESULTS: Among 48 million adults, 125 985 were hospitalized and 1 319 789 were not hospitalized within 28 days of COVID-19 diagnosis. In England, there were 260 279 first arterial thromboses and 59 421 first VTEs during 41.6 million person-years of follow-up. Adjusted hazard ratios for first arterial thrombosis after COVID-19 diagnosis compared with no COVID-19 diagnosis declined from 21.7 (95% CI, 21.0-22.4) in week 1 after COVID-19 diagnosis to 1.34 (95% CI, 1.21-1.48) during weeks 27 to 49. Adjusted hazard ratios for first VTE after COVID-19 diagnosis declined from 33.2 (95% CI, 31.3-35.2) in week 1 to 1.80 (95% CI, 1.50-2.17) during weeks 27 to 49. Adjusted hazard ratios were higher, for longer after diagnosis, after hospitalized versus nonhospitalized COVID-19, among Black or Asian versus White people, and among people without versus with a previous event. The estimated whole-population increases in risk of arterial thromboses and VTEs 49 weeks after COVID-19 diagnosis were 0.5% and 0.25%, respectively, corresponding to 7200 and 3500 additional events, respectively, after 1.4 million COVID-19 diagnoses. CONCLUSIONS: High relative incidence of vascular events soon after COVID-19 diagnosis declines more rapidly for arterial thromboses than VTEs. However, incidence remains elevated up to 49 weeks after COVID-19 diagnosis. These results support policies to prevent severe COVID-19 by means of COVID-19 vaccines, early review after discharge, risk factor control, and use of secondary preventive agents in high-risk patients.

C-reactive protein, immunothrombosis and venous thromboembolism

C-reactive protein (CRP) is a member of the highly conserved pentraxin superfamily of proteins and is often used in clinical practice as a marker of infection and inflammation. There is now increasing evidence that CRP is not only a marker of inflammation, but also that destabilized isoforms of CRP possess pro-inflammatory and pro-thrombotic properties. CRP circulates as a functionally inert pentameric form (pCRP), which relaxes its conformation to pCRP* after binding to phosphocholine-enriched membranes and then dissociates to monomeric CRP (mCRP). with the latter two being destabilized isoforms possessing highly pro-inflammatory features. pCRP* and mCRP have significant biological effects in regulating many of the aspects central to pathogenesis of atherothrombosis and venous thromboembolism (VTE), by directly activating platelets and triggering the classical complement pathway. Importantly, it is now well appreciated that VTE is a consequence of thromboinflammation. Accordingly, acute VTE is known to be associated with classical inflammatory responses and elevations of CRP, and indeed VTE risk is elevated in conditions associated with inflammation, such as inflammatory bowel disease, COVID-19 and sepsis. Although the clinical data regarding the utility of CRP as a biomarker in predicting VTE remains modest, and in some cases conflicting, the clinical utility of CRP appears to be improved in subsets of the population such as in predicting VTE recurrence, in cancer-associated thrombosis and in those with COVID-19. Therefore, given the known biological function of CRP in amplifying inflammation and tissue damage, this raises the prospect that CRP may play a role in promoting VTE formation in the context of concurrent inflammation. However, further investigation is required to unravel whether CRP plays a direct role in the pathogenesis of VTE, the utility of which will be in developing novel prophylactic or therapeutic strategies to target thromboinflammation.

Change in college student health and well-being profiles as a function of the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic has potential for long-lasting effects on college students' well-being. We examine changes from just before to during the pandemic in indicators of health and well-being and comprehensive profiles of health and well-being, along with links between covariates and profiles during the pandemic. PARTICIPANTS: 1,004 students participated in a longitudinal study that began in November 2019. METHODS: Latent class analysis identified health and well-being profiles at both waves; covariates were included in relation to class membership. RESULTS: Mental health problems increased, whereas substance use, sexual behavior, physical inactivity, and food insecurity decreased. Six well-being classes were identified at each wave. Baseline class membership, sociodemographic characteristics, living situation, ethnicity, coping strategies, and belongingness were associated with profile membership at follow-up. CONCLUSIONS: COVID-19 has had significant and differential impacts on today's students; their health and well-being should be considered holistically when understanding and addressing long-term effects of this pandemic.

Potent Inactivation of Human Respiratory Viruses Including SARS-CoV-2 by a Photoactivated Self-Cleaning Regenerative Antiviral Coating.

The COVID-19 pandemic marks an inflection point in the perception and treatment of human health. Substantial resources have been reallocated to address the direct medical effects of COVID-19 and to curtail the spread of the virus. Thereby, shortcomings of traditional disinfectants, especially their requirement for regular reapplication and the related complications (e.g., dedicated personnel and short-term activity), have become issues at the forefront of public health concerns. This issue became especially pressing when infection-mitigating supplies dwindled early in the progression of the pandemic. In consideration of the constant threat posed by emerging novel viruses, we report a platform technology for persistent surface disinfection to combat virus transmission through nanomaterial-mediated, localized UV radiation emission. In this work, two formulations of Y2SiO5-based visible-to-UV upconversion nanomaterials were developed using a facile sol-gel-based synthesis. Our formulations have shown substantial antiviral activities (4 × 104 to 0 TCID50 units in 30 min) toward an enveloped, circulating human coronavirus strain (OC43) under simple white light exposure as an analogue to natural light or common indoor lighting. Additionally, we have shown that our two formulations greatly reduce OC43 RNA recovery from surfaces. Antiviral activities were further demonstrated toward a panel of structurally diverse viruses including enveloped viruses, SARS-CoV-2, vaccinia virus, vesicular stomatitis virus, parainfluenza virus, and Zika virus, as well as nonenveloped viruses, rhinovirus, and calicivirus, as evidence of the technology's broad antiviral activity. Remarkably, one formulation completely inactivated 105 infectious units of SARS-CoV-2 in only 45 min. The detailed technology has implications for the design of more potent, long-lived disinfectants and modified/surface-treated personal protective equipment targeting a wide range of viruses.

BindingSiteAugmentedDTA: Enabling A Next-Generation Pipeline for Interpretable Prediction Models in Drug-Repurposing (preprint)

While research into Drug-Target Interaction (DTI) prediction is fairly mature, generalizability and interpretability are not always addressed in the existing works in this field. In this paper, we propose a deep learning-based framework, called BindingSite-AugmentedDTA, which improves Drug-Target Affinity (DTA) predictions by reducing the search space of potential binding sites of the protein, thus making the binding affinity prediction more efficient and accurate. Our BindingSite-AugmentedDTA is highly generalizable as it can be integrated with any DL-based regression model, while it significantly improves their prediction performance. Also, unlike many existing models, our model is highly interpretable due to its architecture and self-attention mechanism, which can provide a deeper understanding of its underlying prediction mechanism by mapping attention weights back to protein binding sites. The computational results confirm that our framework can enhance the prediction performance of seven state-of-the-art DTA prediction algorithms in terms of 4 widely used evaluation metrics, including Concordance Index (CI), Mean Squared Error (MSE), modified squared correlation coefficient (rm2 ), and the Area Under the Precision Curve (AUPC). We also contribute to the two most commonly used DTA benchmark datasets, namely Kiba and Davis, by including additional information on 3D structure of all proteins contained in these two datasets. We manually extracted this information from Protein Data Bank (PDB) files of proteins available at https://www.uniprot.org/. Furthermore, we experimentally validate the practical potential of our proposed framework through in-lab experiments. We measure the binding interaction between several drug candidate compounds for the inhibition of binding between (SARS-CoV-2 S-protein RBD) Spike and ACE-2 (host cell binding target) proteins. We then compare the computationally-predicted results against the ones experimentally-observed in the laboratory. The relatively high agreement between computationally-predicted and experimentally-observed binding interactions supports the potential of our framework as the next-generation pipeline for prediction models in drug repurposing.

The Remarkable Selectivity of Nirmatrelvir.

The SARS-CoV-2 main protease is among the most attractive targets for the development of therapeutic interventions for COVID-19. Successful candidate agents will not only possess potent on-target activity versus SARS-CoV-2 Mpro but also minimal polypharmacology versus human cysteine proteases. This Viewpoint explores the activity profile of the first approved SARS-CoV-2 Mpro inhibitor (Nirmatrelvir) versus a panel of cysteine proteases and considers the therapeutic implications of the data.

People in intensive care with COVID-19: demographic and clinical features during the first, second, and third pandemic waves in Australia.

OBJECTIVE: To compare the demographic and clinical features, management, and outcomes for patients admitted with COVID-19 to intensive care units (ICUs) during the first, second, and third waves of the pandemic in Australia. DESIGN, SETTING, AND PARTICIPANTS: People aged 16 years or more admitted with polymerase chain reaction-confirmed COVID-19 to the 78 Australian ICUs participating in the Short Period Incidence Study of Severe Acute Respiratory Infection (SPRINT-SARI) Australia project during the first (27 February - 30 June 2020), second (1 July 2020 - 25 June 2021), and third COVID-19 waves (26 June - 1 November 2021). MAIN OUTCOME MEASURES: Primary outcome: in-hospital mortality. SECONDARY OUTCOMES: ICU mortality; ICU and hospital lengths of stay; supportive and disease-specific therapies. RESULTS: 2493 people (1535 men, 62%) were admitted to 59 ICUs: 214 during the first (9%), 296 during the second (12%), and 1983 during the third wave (80%). The median age was 64 (IQR, 54-72) years during the first wave, 58 (IQR, 49-68) years during the second, and 54 (IQR, 41-65) years during the third. The proportion without co-existing illnesses was largest during the third wave (41%; first wave, 32%; second wave, 29%). The proportion of ICU beds occupied by patients with COVID-19 was 2.8% (95% CI, 2.7-2.9%) during the first, 4.6% (95% CI, 4.3-5.1%) during the second, and 19.1% (95% CI, 17.9-20.2%) during the third wave. Non-invasive (42% v 15%) and prone ventilation strategies (63% v 15%) were used more frequently during the third wave than during the first two waves. Thirty patients (14%) died in hospital during the first wave, 35 (12%) during the second, and 281 (17%) during the third. After adjusting for age, illness severity, and other covariates, the risk of in-hospital mortality was similar for the first and second waves, but 9.60 (95% CI, 3.52-16.7) percentage points higher during the third than the first wave. CONCLUSION: The demographic characteristics of patients in intensive care with COVID-19 and the treatments they received during the third pandemic wave differed from those of the first two waves. Adjusted in-hospital mortality was highest during the third wave.

Diabetes mellitus, glycaemic control, and severe COVID-19 in the Australian critical care setting: A nested cohort study.

BACKGROUND: Internationally, diabetes mellitus is recognised as a risk factor for severe COVID-19. The relationship between diabetes mellitus and severe COVID-19 has not been reported in the Australian population. OBJECTIVE: The objective of this study was to determine the prevalence of and outcomes for patients with diabetes admitted to Australian intensive care units (ICUs) with COVID-19. METHODS: This is a nested cohort study of four ICUs in Melbourne participating in the Short Period Incidence Study of Severe Acute Respiratory Infection (SPRINT-SARI) Australia project. All adult patients admitted to the ICU with COVID-19 from 20 February 2020 to 27 February 2021 were included. Blood glucose and glycated haemoglobin (HbA1c) data were retrospectively collected. Diabetes was diagnosed from medical history or an HbA1c ≥6.5% (48 mmol/mol). Hospital mortality was assessed using logistic regression. RESULTS: There were 136 patients with median age 58 years [48-68] and median Acute Physiology and Chronic Health Evaluation II (APACHE II) score of 14 [11-19]. Fifty-eight patients had diabetes (43%), 46 patients had stress-induced hyperglycaemia (34%), and 32 patients had normoglycaemia (23%). Patients with diabetes were older, were with higher APACHE II scores, had greater glycaemic variability than patients with normoglycaemia, and had longer hospital length of stay. Overall hospital mortality was 16% (22/136), including nine patients with diabetes, nine patients with stress-induced hyperglycaemia, and two patients with normoglycaemia. CONCLUSION: Diabetes is prevalent in patients admitted to Australian ICUs with severe COVID-19, highlighting the need for prevention strategies in this vulnerable population.

UnbiasedDTI: Mitigating Real-World Bias of Drug-Target Interaction Prediction by Using Deep Ensemble-Balanced Learning.

Drug-target interaction (DTI) prediction through in vitro methods is expensive and time-consuming. On the other hand, computational methods can save time and money while enhancing drug discovery efficiency. Most of the computational methods frame DTI prediction as a binary classification task. One important challenge is that the number of negative interactions in all DTI-related datasets is far greater than the number of positive interactions, leading to the class imbalance problem. As a result, a classifier is trained biased towards the majority class (negative class), whereas the minority class (interacting pairs) is of interest. This class imbalance problem is not widely taken into account in DTI prediction studies, and the few previous studies considering balancing in DTI do not focus on the imbalance issue itself. Additionally, they do not benefit from deep learning models and experimental validation. In this study, we propose a computational framework along with experimental validations to predict drug-target interaction using an ensemble of deep learning models to address the class imbalance problem in the DTI domain. The objective of this paper is to mitigate the bias in the prediction of DTI by focusing on the impact of balancing and maintaining other involved parameters at a constant value. Our analysis shows that the proposed model outperforms unbalanced models with the same architecture trained on the BindingDB both computationally and experimentally. These findings demonstrate the significance of balancing, which reduces the bias towards the negative class and leads to better performance. It is important to note that leaning on computational results without experimentally validating them and by relying solely on AUROC and AUPRC metrics is not credible, particularly when the testing set remains unbalanced.