discover.HSLS - "COVID-19" (2024)

Early physical rehabilitation dosage in the Intensive Care Unit predicts hospital outcomes after critical COVID-19new window

Abstract Objective : to examine the relationship between physical rehabilitation parameters including a novel approach to quantifying dosage with hospital outcomes for patients with critical COVID-19. Design: Retrospective practice analysis from March 5, 2020, to April 15, 2021. Setting: Intensive care units (ICU) at four medical institutions Patients: n = 3,780 adults with ICU admission and diagnosis of COVID-19 Interventions: We measured the physical rehabilitation treatment delivered in ICU and patient outcomes: 1) mortality; 2) discharge disposition; and 3) physical function at hospital discharge measured by the Activity Measure-Post Acute Care (AM-PAC) “6-Clicks” (6-24, 24=greater functional independence). Physical rehabilitation dosage was defined as the average mobility level scores in the first three sessions (a surrogate measure of intensity) multiplied by the rehabilitation frequency (PT + OT frequency in hospital). Measurements and Main Results: The cohort was a mean 64 ± 16 years old, 41% female, mean BMI of 32 ± 9 kg/m 2 and 46% (n=1739) required mechanical ventilation. For 2191 patients with complete data, rehabilitation dosage and AM-PAC at discharge were moderately, positively associated (Spearman’s rho [r] = 0.484, p < 0.001). Multivariate linear regression (model adjusted R 2 = 0.68, p <0.001) demonstrates mechanical ventilation (β = -0.86, p = 0.001), average mobility score in first three sessions (β = 2.6, p <0.001) and physical rehabilitation dosage (β = 0.22, p = 0.001) were predictive of AM-PAC scores at discharge when controlling for age, sex, BMI, and ICU LOS. Conclusions: Greater physical rehabilitation exposure early in the ICU is associated with physical function at hospital discharge.

Assessing the quality of life of university students during COVID-19 lockdown: A structural equation modelling approachnew window

Abstract Purpose In the face of the upsurge of the COVID-19 pandemic global students including those of Bangladesh are forced to go into distance learning mode due to the lockdown or social isolation that is being imposed. The present study was intended to evaluate the impact of distance education on the quality of life (QOL) among Bangladeshi university students that are exerted due to the COVID-19 lockdown. Methods We used the World Health Organization Quality of Life (WHOQOL)-Bref questionnaire which was distributed among students from four universities in Bangladesh using electronic platforms such as WhatsApp, Facebook, and Email. The scores of the WHOQOL-Bref were converted into a linear scale from 0 to 100 and recorded (0–70) as low/moderate quality of life whereas (≥ 70) were coded as high quality of life. Results The study obtained an excellent internal consistency of WHOQOL-Bref (α = 0.878). The mean QOL (0-100) among the participants was 78.29 ± 11.59 with a median of (73.35, IQR: 42.53–88.30). All domains showed a strong to moderate correlation with the overall quality of life score. The domain most affected by isolation was the psychological domain, and the social relationship domain showed the weakest correlation with the overall quality of life scores. In the regression analysis, factors such as increased Internet use, watching more TV, participating in classes with zooms, and residing with a family of more than three members were found to be associated with having a good quality of life. Conclusions The study pointed out that, while there are no alternatives to keep the educational system functioning thus distance learning during this overwhelming COVID-19 situation, more interactive platforms such as Zoom, the promotion of more internet and television use can be of value to retain the good quality of life among the students in this overwhelming condition.

Longevity of hybrid immunity against SARS-CoV-2 in adults vaccinated with an adenovirus- based COVID-19 vaccinenew window

Abstract Background. Hybrid immunity provides better protection against COVID-19 than vaccination or prior natural infection alone. It induces high magnitude and broadly cross-reactive neutralising anti-Spike IgG antibodies. However, it is not clear how long these potent antibodies last, especially in the context of adenovirus-based COVID-19 vaccines. Methods. We conducted a longitudinal cohort study and enrolled 20 adults who had received an adenovirus-based COVID-19 vaccine before a laboratory-confirmed SARS-CoV-2 infection. We followed up the study participants for 390 days post the initial breakthrough infection. We assessed the longevity and cross-reactive breadth of serum antibodies against SARS-CoV-2 variants of concern (VOCs), including Omicron. Results. The binding anti-Spike IgG antibodies remained within the reported putative levels for at least 360 days and were cross-neutralising against Beta, Gamma, Delta, and Omicron. During the follow up period, a median of one SARS-CoV-2 re-infection event was observed across the cohort, but none resulted in severe COVID-19. Moreover, the re-exposure events were associated with augmented anti-Spike and anti-RBD IgG antibody titres. Conclusions. This study confirms that hybrid immunity provides durable broadly cross-reactive antibody immunity against SARS-CoV-2 variants of concern for at least a year (360 days), and that it is further augment by SARS-CoV-2 re-exposure.

Inferring Enterovirus D68 Transmission Dynamics from the Genomic Data of Two 2022 North American outbreaksnew window

Abstract Enterovirus D68 (EV-D68) has emerged as a significant cause of acute respiratory illness in children globally, notably following its extensive outbreak in North America in 2014. A recent outbreak of EV-D68 was observed in Ontario, Canada, from August to October 2022. Our phylogenetic analysis revealed a notable genetic similarity between the Ontario outbreak and a concurrent outbreak in Maryland, USA. Utilizing Bayesian phylodynamic modeling on whole genome sequences (WGS) from both outbreaks, we determined the median peak time-varying reproduction number (R t ) to be 2.70 (95% HPD 1.76, 4.08) in Ontario and 2.10 (95% HPD 1.41, 3.17) in Maryland. The R t trends in Ontario closely matched those derived via EpiEstim using reported case numbers. Our study also provides new insights into the median infection duration of EV-D68, estimated at 7.94 days (95% HPD 4.55, 12.8) in Ontario and 10.8 days (95% HPD 5.85, 18.6) in Maryland, addressing the gap in the existing literature surrounding EV-D68’s infection period. We observed that the estimated Time since the Most Recent Common Ancestor (TMRCA) and the epidemic's origin coincided with the easing of COVID-19 related social contact restrictions in both areas. This suggests that the relaxation of non-pharmaceutical interventions, initially implemented to control COVID-19, may have inadvertently facilitated the spread of EV-D68. These findings underscore the effectiveness of phylodynamic methods in public health, demonstrating their broad application from local to global scales and underscoring the critical role of pathogen genomic data in enhancing public health surveillance and outbreak characterization.

A Modeling Investigation of the Disease Severity Driven by COVID-19-Induced Diabetic Patientsnew window

Abstract In this study, we propose a new SEICHR compartmental model to investigate the transmission dynamics of COVID-19 in diabetic and non-diabetic patients. We emphasize the role of COVID-19-induced diabetic patients in disease dynamics. The well-posedness of the model and the stability of the equilibrium points are confirmed through rigorous mathematical analysis. Mathematical results are validated using numerical simulations. Sensitivity and bifurcation analyses are conducted to determine the most sensitive parameters in the proposed model. The sensitivity of the model parameters is examined using the partial rank correlation coefficients (PRCC) analysis. The results show that the disease progression rate is higher among COVID-19 infected diabetic patients than non-diabetic patients. The role of COVID-19-induced diabetic patients in driving disease severity was then analyzed through a constant and progressive delay in isolating them in hospitals. It can be observed numerically that a forward bifurcation region increases gradually with increases of the value of exposed individuals. In addition, the progressive waiting time was found to have a way greater effect on the transmission dynamics compared to the constant waiting time. Furthermore, the model outcomes could not verified in the light of real field data due to unavailability of data.

Survival, Mortality and Epidemic Risk Status of COVID-19: A Population- Based Study in Golestan Province, Irannew window

Abstract Background Appreciating the various dimensions of the coronavirus disease 2019 (COVID-19) pandemic can improve health systems and prepare them to deal better with future pandemics and public health events. This study was conducted to investigate the association between the survival of hospitalized patients with COVID-19 and the epidemic risk stratification of the disease in Golestan province, Iran. Methods In this study, all patients with COVID-19 who were hospitalized in the hospitals of Golestan province of Iran from February 20, 2020, to December 19, 2022, and were registered in the Medical Care Monitoring Center (MCMC) system (85,885 individuals) were examined.The community's epidemic risk status (ERS) was determined based on the daily incidence statistics of COVID-19. The survival distribution and compare Survival in different subgroups was investigated using Kaplan-Meier and log-rank test and association between the survival and ERS by multiple Cox regression modeling Results Out of 68,983 individuals whose data were correctly recorded, the mean age was 49 (SD = 23.98) years, and 52.8% were women. In total, 11.1% eventually died. The length of hospital stay was varying significantly with age, gender, ERS, underlying diseases, and COVID-19 severity (P < 0.001 for all). The adjusted hazard ratio of death for the ERS at medium, high, and very high-risk status compared to the low-risk status increased by 19%, 26%, and 56%, respectively (P < 0.001 for all). Conclusions Enhancing preparedness, facilitating rapid rises in hospital capacities, and developing backup healthcare capacities can prevent excessive hospital referrals during health crises and further deaths.

Doctors of Tomorrow: Evaluating the effectiveness and impact of a virtual medical pipeline program during the COVID-19 p...new window

Background: Doctors of Tomorrow (DoT) is a medical student-run pipeline program between the University of Michigan Medical School and high schools in Detroit, MI. During the COVID-19 pandemic, this program was offered virtually for the first time during the 2020–2021 academic year. There are limited studies on the outcomes of virtual pipeline programs. This study aims to identify the successes and limitations of the virtual DoT program by examining the participants’ self-reported perspectives and knowledge acquisition from their session participation. Methods Multiple methods were executed in this study. Matched pre- and post- surveys completed by the 2020–2021 participant cohort were analyzed using paired t-tests. In addition, participants’ responses to free-response questions were analyzed by coding with NVivo and subsequent content analysis. Results Program participants experienced a significant increase in their self-rated knowledge of delivered content after each session. Additionally, a significant increase in familiarity was detected with the path to becoming a physician and with a variety of medical fields. In the qualitative analysis, five overarching categories emerged: 1) path to medical school, 2) mentorship and role models, 3) scientific inquiry, 4) sense of belonging, and 5) fields of medicine. Conclusions The DoT virtual pipeline program provides convincing evidence that distance learning can still be an effective way to help URiM students explore careers in medicine, gain awareness about the path to medical school, and connect with mentors. This may serve as a low-cost option for universities to engage with and extend their service to communities, especially in an increasingly digital world.

A Forecasting Model Approach: Investigating Calendar Anomalies and Volatility Patterns in the Cryptocurrency Marketnew window

This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.

Navigating the Pandemic: Shifts in Breast Reconstruction Trends and Surgical Decision-Making in the United Statesnew window

Background: This study aimed to investigate the impact of the COVID-19 pandemic on breast reconstruction trends in the United States, focusing on implant-based and autologous techniques, as well as the timing of reconstruction (immediate vs. delayed). Methods: A retrospective analysis of data from the American Society of Plastic Surgeons' National Plastic Surgery Statistics from 2015 to 2022 was conducted. Annual trends in breast reconstruction procedures were analyzed, comparing the pre-pandemic (2015-2019) and pandemic (2020-2022) periods. Results: The total number of breast reconstructions increased from 106,338 in 2015 to 151,641 in 2022. The proportion of implant-based reconstructions decreased from 81.41% pre-pandemic to 76.51% during the pandemic (p < 0.001), with a notable rise in direct-to-implant procedures from 10.37% to 19.12% (p < 0.001). Autologous reconstructions increased from 18.59% to 23.49% (p < 0.001). Among autologous techniques, DIEP flaps remained the most popular. Immediate reconstruction rates increased from 72.61% pre-pandemic to 75.57% during the pandemic, while delayed recon-struction rates decreased from 27.39% to 24.43% (p < 0.001). Conclusions: The COVID-19 pandemic has significantly influenced breast reconstruction trends in the United States, with a shift towards autologous techniques, particularly DIEP flaps, and an in-crease in immediate reconstructions. These changes may reflect adaptations in surgical practice and decision-making processes in response to the unique challenges posed by the pandemic. Further research is needed to assess the long-term outcomes and patient satisfaction associated with these trends.

DeClEx-Processing Pipeline for Critical Healthcare Applicationnew window

Over the last decade, the prevalence of health issues has increased by approximately 29.1%, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly, however many present approaches are unsuitable for real-world implementation due to high memory footprints and lack of interpretability. We introduce DeClEx, a pipeline designed to address these issues. DeClEx ensures that data mirrors real-world settings by incorporating gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state of the art pre-trained models while achieving threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification and explainability in a single pipeline called DeClEx.

Effectiveness of a Single Fixed Dose 3 mg Rasburicase for Prevention and Management of Hyperuricemia of Tumor Lysis Synd...new window

Abstract: Effectiveness of a Single Fixed Dose 3 mg Rasburicase for Prevention and Management of Hyperuricemia of Tumor Lysis Syndrome in adult Cancer Patients Background: Tumor lysis syndrome (TLS) is a potentially life-threatening complication associated with certain types of cancer. Rasburicase is an essential medicine required to prevent and treat the hyperuricemia associated with TLS. Due to a shortage of rasburicase during the COVID-19 pandemic, a fixed dose strategy of 3 mg rasburicase had been used in many adult cancer patients in our center. Objective: The objective of this study was to assess the effectiveness of a 3 mg fixed dose of rasburicase in preventing and managing hyperuricemia associated with TLS in adult cancer patients. Methods: We conducted a retrospective, observational cohort study between March 2020 and November 2022. The study included adult patients who received a fixed dose of 3 mg rasburicase. The primary outcome measure was the reduction in serum UA levels of

Prediction of COVID-19 Hospitalization and Mortality Using Artificial Intelligencenew window

COVID-19 has substantially influenced healthcare systems, requiring early prognosis for innovative therapies and optimal results, especially in individuals with comorbidities. Healthcare practitioners have used AI systems for investigating, anticipating, and predicting diseases, through means including medication development, clinical trial analysis, and pandemic forecasting. This study proposes the use of AI to predict disease severity in terms of hospital mortality among COVID-19 patients. Methodology: A cross-sectional study was conducted the approval from the Research Ethics Committee of King Abdulaziz University (KAU), Saudi Arabia. The study used sequential sampling approaches to include 50 Real-Time Polymerase Chain Reaction (RT-PCR) positive COVID-19 patients from KAU's coronavirus isolation wards. A pre-designed form was used to collect each patient's demographic information, including age and gender, signs and symptoms, illness severity (mild, moderate, severe), and laboratory findings. Furthermore, the length of the hospital stay and the result, whether the patient recovered or died, were reported. Results: The study involved 50 patients with varying degrees of disease severity, most of whom suffered from fever, fatigue, cough, sore throat, and diarrhoea. Laboratory analysis of COVID-19 patients showed increased white blood cell and platelet counts, with C-reactive protein levels above normal. Elevated LDH levels indicated possible tissue damage, while ferritin levels were elevated. Other enzymes were in the normal range, but bilirubin levels were slightly elevated. Overall, the patient's lab results indicated inflammation and possible blood clot formation. The study evaluated the predictive accuracy for outcomes and mortality of COVID-19 patients based on factors such as CRP, LDH, Ferritin, ALP, Bilirubin, D-dimers, and hospital stay (p-value ≤0.05). The predictive accuracy mortality of patients with COVID-19 using AI showed Hospital stay, D-Dimers ALP, Bilirubin, LDH, CRP, and Ferritin significantly affected hospital mortality. (p ≤ 0.0001). Conclusion: Artificial Intelligence is crucial for identifying early coronavirus infections and monitoring patient conditions. It improves treatment consistency and decision-making via the development of algorithms. AI can track the crisis at various scales, facilitate research, and aid in developing treatment regimens, prevention strategies, and drugs and vaccines. It also aids in monitoring health and facilitating research on the virus.

Exploring respiratory viral pathogens and bacteriome from symptomatic SARS-CoV-2-negative and positive individualsnew window

In the COVID pandemic era, increased mortality was seen despite some unknown etiologies other than SARS-CoV2 viral infection. Vaccination targeted to SARS-CoV2 was successful due to infection caused by pathogens of viral origin based on symptomatology. Hence, it is essential to detect other viral and bacterial infections throughout the initial wave of the COVID-19 disease outbreak, particularly in those suffering from a symptomatic respiratory infection with SARS-CoV-2-negative status. This study was planned to explore the presence of bacterial and other respiratory viruses in symptomatic patients with SARS-CoV2-positive or negative status. The study selected128 patient’s samples out of 200 patients’ samples (100 at each time point) collected for routine SARS-CoV-2 detection schedule in December 2020 and June 2021. Considering the seasonal changes responsible for the occurrence of respiratory pathogens, we finalized 64 SARS-CoV-2 tested patients with 32 SARS-CoV-2-negatives and 32 SARS-CoV-2-positives from each collection time to examine them further using real-time PCR for the presence of other viral species and bacterial infection analyzing 16S rRNA metagenome supporting to cause respiratory infections. Along with various symptoms, we observed the co-infection of adenovirus and influenza B(Victoria) virus to two SARS-CoV-2-positive samples. The SARS-CoV-2-negative but symptomatic patient showed Rhinovirus (7/64 i.e. 10.9%) and Influenza (A/H3N2) infection in 4 patients out of 64 patients (6.25%). Additionally, one SARS-CoV-2-negative patient enrolled in June 2021 showed PIV-3 infection. Influenza A/H3N2 and Adenovirus were the cause of symptoms in SARS-CoV-2-negative samples significantly. Thus, the overall viral infections are considerably higher among SARS-CoV-2-negative patients (37.5% Vs 6.25%) compared to SARS-CoV-2-positive patients representing respiratory illness probably due to the abundance of the viral entity as well as competition benefit of SARS-CoV-2 in altering the imperviousness of the host. Simultaneously, 16S rRNA ribosomal RNA metagenomenext-generation sequencing (NGS) data from the same set of samples indicated a higher frequency of Firmicutes, Proteobacteria, Bacteroidota, Actinobacteriota, fusobacteriota, Patescibacteria, and Campilobacterotaphyla out of 15 phyla, 240 species from positive and 16 phyla, 274 species from negative samples. Exploring co-infecting respiratory viruses and bacterial populations becomes significant in understanding the mechanisms associated with multiple infecting pathogens from symptomatic COVID-positive and negative individuals for initiating proper antimicrobial therapy. Author Summary Frequent transfer of SARS-CoV-2 events has resulted in the emergence of other viral infections along with several evolutionarily separate viral lineages in the global SARS-CoV-2 population, presenting significant viral variants in various regions worldwide. This variation also raises the possibility of reassortment and the creation of novel variants of SARS-CoV-2, as demonstrated by the COVID pandemic in all the waves, which may still be able to cause illness and spread among people. Still unclear, though, are the molecular processes that led to the adaption of other viral and bacterial pathogens in humans when a human SARS-CoV-2 virus was introduced. In this study, we identified the presence of various other viral infections and bacterial content in symptomatic COVID-19-positive and negative patients, as evidenced by the data obtained using next-generation sequencing of 16S rRNA metagenome and real-time PCR detection technologies. Symptoms might have been induced by bacterial content and various viral entities other than the SARS-CoV-2 viral infection in the COVID-negative population, indicating its importance in detecting and initiating appropriate therapy to recover from all other infections.

Adjuvanted subunit intranasal vaccine prevents SARS-CoV-2 onward transmission in hamstersnew window

Most COVID-19 vaccine trials have focused on recipient protection, not protection of their contacts, a critical need. As a subunit intranasal COVID-19 vaccine reduced nasopharyngeal virus more than did an intramuscular (IM) vaccine, we hypothesized that this vaccine might reduce onward transmission to others. We vaccinated hamsters with either the IM-administrated Moderna mRNA vaccine twice or one dose of mRNA IM followed by adjuvanted subunit intranasal vaccine. 24 hours after SARS-CoV-2 challenge, these animals were housed with naïve recipients in a contactless chamber that allows airborne transmission. Onward airborne transmission was profoundly blocked: the donor and recipients of the intranasal vaccine-boosted group had lower oral and lung viral loads (VL), which correlated with mucosal ACE2 inhibition activity. These data strongly support the use of the intranasal vaccine as a boost to protect not only the vaccinated person, but also people exposed to the vaccinated person, a key public health goal. Author summary Natural transmission of SARS-CoV-2 is primarily airborne, through the respiratory mucosal route. However, current licensed COVID-19 vaccines are all intramuscular and induce more systemic than mucosal immunity. Here, we did a head-to-head comparison of COVID-19 booster vaccines on SARS-CoV-2 onward transmission. We found that compared to boosting with a Moderna mRNA systemic vaccine, a nanoparticle intranasal COVID-19 vaccine much more effectively prevents onward airborne transmission to naïve recipient hamsters. The protection was correlated with local mucosal antibody. Thus, a mucosal nanoparticle vaccine should be considered for preventing onward airborne transmission, a key public health necessity that has not been adequately studied.

Unique RNA replication characteristics and nucleocapsid protein expression may explain differences in the replication ca...new window

Summary COVID-19 pandemic in Brazil was characterized by the sequential circulation of the SARS-CoV-2 lineages B.1.1.33, and variants Zeta (P.2), Gamma (P.1/P.1.*), Delta (B.1.617.2/AY.*), and Omicron (BA.*). Our research aimed to compare the biological traits of these lineages and variants by analyzing aspects of viral replication including binding, entry, RNA replication, and viral protein production. We demonstrated that the replication capacity of these variants varies depending on the cell type, with Omicron BA.1 exhibiting the lowest replication in the human pulmonary cells. Additionally, the nucleocapsid proteoforms generated during infection exhibit distinct patterns across variants. Our findings suggest that factors beyond the initial stages of virus entry influence the efficiency of viral replication among different SARS-CoV-2 variants. Thus, our study underscores the significance of RNA replication and the role of nucleocapsid proteins in shaping the replicative characteristics of SARS-CoV-2 variants. Author summary The COVID-19 pandemic was characterized by the emergence of different viral variants that presents specific properties such as response to antibodies, pathogenicity and detection by diagnostic tests. The circulation of these variants presented a particular pattern depending on the global geographic regions. Despite the cessation of the pandemic, as officially declared by the World Health Organization in 2023, new viral variants continue to emerge while aspects of the virus-cell interaction that contribute to the replication of these variants have not yet been completely understood. In our study, we compared the biological characteristics of SARS-CoV-2 variants that circulated in Brazil during the pandemic, verifying aspects of entry, viral replication and production of viral RNA and proteins. Our results indicate that Omicron BA.1 variant has reduced replication and protein production in human lung cells. We also observed that the viral nucleocapsid protein presents proteoforms that vary according to the variant. These differences could help to explain the differences observed in viral replication in human pulmonary cells.

Coming out of the ashes we rise: Culturally and linguistically diverse international nursing students during the COVID-1...new window

Background and aim Research on international students conducted during the COVID-19 pandemic has persistently highlighted the vulnerabilities and challenges that they experienced when staying in the host country to continue with their studies. The findings from such research can inevitably create a negative image of international students and their ability to respond to challenges during unprecedented times. Therefore, this paper took a different stance and reported on a qualitative study that explored culturally and linguistically diverse (CaLD) international nursing students who overcame the challenges brought about by the pandemic to continue with their studies in Australia. Method A descriptive qualitative research design guided by the processes of constructivist grounded theory was selected to ascertain insights from participants’ experiences of studying abroad in Australia during the COVID-19 pandemic. Results Three themes emerged from the collected data that described the participants’ lived experiences, and they were: 1) Viewing international education as the pursuit of a better life , 2) Focusing on personal growth , and 3) Coming out of the ashes we rise . Discussion The findings highlight the importance of recognising the investments and sacrifices that CaLD international students and their families make in pursuit of international tertiary education. The findings also underscore the importance of acknowledging the qualities that CaLD international students have to achieve self-growth and ultimately self-efficacy as they stay in the host country during a pandemic. Conclusion Future research should focus on identifying strategies that are useful for CaLD international nursing students to experience personal growth and ultimately self-efficacy and continue with their studies in the host country during times of uncertainty such as a pandemic.

SAFETY AND IMMUNOGENICITY OF A PHH-1V BOOSTER DOSE AFTER DIFFERENT PRIME VACCINATION SCHEMES AGAINST COVID-19: PHASE III...new window

In this phase III, open label, single arm, multicenter clinical study, we report safety, tolerability and immunogenicity of PHH-1V as a booster dose in subjects primary vaccinated against COVID-19 with the BNT162b2, mRNA-1273, ChAdOx1-S, or Ad26.COV2.S vaccines, with or without previous COVID-19 infection. A total of 2661 subjects were included in this study and vaccinated with the PHH-1V vaccine. Most treatment-emergent adverse events (TEAE) were solicited local and systemic reactions with grade 1 (58.70%) or grade 2 (27.58%) intensity, being the most frequently reported injection site pain (82.83%), fatigue (31.72%) and headache (31.23%). Additionally, immunogenicity was assessed at Baseline and Days 14, 91, 182 and 365 in a subset of 235 subjects primary vaccinated. On Day 14, geometric mean triter (GMT) in neutralizing antibody against SARS-CoV-2 Wuhan and Beta, Delta and Omicron BA.1 variants increased in all primary vaccination with a geometric mean fold raise (GMFR) of 6.90 (95% CI 4.96-9.58), 12.27 (95% CI 8.52-17.67), 7.24 (95% CI 5.06-10.37) and 17.51 (95% CI 12.28-24.97), respectively. Despite GMT decay after day 14, it remains in all cases significatively higher from baseline up to 1 year after PHH-1V booster administration and GMFR against Beta and Omicron BA.1 variants over 3 at 1 year after booster compared to baseline. PHH-1V booster vaccination elicited also a significant RBD/Spike-specific IFN-γ + T-cell responses on Day 14. Overall, PHH-1V vaccine was immunogenic and well-tolerated regardless of the previous primary vaccination scheme received with no reported cases of severe COVID-19 infection throughout the entire study.

Potential drug-drug interactions with nirmatrelvir/ritonavir in critically ill patients with COVID-19 – a retrospective ...new window

Background: Nirmatrelvir/ritonavir is recommended for high-risk patients with COVID-19 to reduce disease progression and mortality. Ritonavir significantly increases the bioavailability of nirmatrelvir and is the most potent irreversible cytochrome P 450 3A4 inhibitor in clinical use, resulting in a substantial risk for drug-drug interactions (DDI). We aimed to analyze the incidence of potential DDI (pDDI) in critically ill patients with SARS-CoV-2 infection. 7.2 Methods This is a retrospective single-center study in a quaternary care center in Northern Germany. We reviewed electronic health records for demographic characteristics, comorbid conditions, and medication history. The pre-existing comedication was screened for pDDI with nirmatrelvir/ritonavir using publicly available databases. Binary logistic regression was used to identify patient characteristics associated with pDDI. 7.3 Results Of 500 critically ill patients with SARS-CoV-2 infection, 362 (72.4%) received pre-existing comedication. A total of 241/500 patients (48.2%) had a medication history prone to pDDI. Antidiabetics, lipid-lowering drugs, and anticoagulants were among the most frequently used agents with a pDDI. Higher age (OR 1.043; 1.028-1.058; p<0.01) and the number of comorbidities (OR 1.229; 1.119-1.350; p<0.01) were significantly associated with pDDI. 7.4 Conclusion The very patient population that may benefit most from treatment with nirmatrelvir/ritonavir also has the greatest risk of pDDI. Polypharmacy is frequently present in these patients and a conscientious check of the comedication is mandatory before a treatment with nirmatrelvir/ritonavir can be initiated.

Machine Learning for COVID-19 Patient Management: Predictive Analytics and Decision Supportnew window

Abstract Background . The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has profoundly affected economies and healthcare systems around the world, including Lebanon. While numerous meta-analyses have explored the systemic manifestations of COVID-19, few have linked them to patient history. Our study aims to fill this gap by using cluster analysis to identify distinct clinical patterns among patients, which could aid prognosis and guide tailored treatments. Methods. We conducted a retrospective cohort study at Beirut's largest teaching hospital on 556 patients with SARS-CoV-2. We performed cluster analyses using K-prototypes, KAMILA and LCM algorithms based on 26 variables, including laboratory results, demographics and imaging findings. Silhouette scores, concordance index and signature variables helped determine the optimal number of clusters. Subsequent comparisons and regression analyses assessed survival rates and treatment efficacy according to clusters. Results. Our analysis revealed three distinct clusters: "resilient recoverees" with varying disease severity and low mortality rates, "vulnerable veterans" with severe disease and high mortality rates, and "paradoxical patients" with a late severe presentation but eventual recovery. Conclusions. These clusters offer insights for prognosis and treatment selection. Future studies should include vaccination data and various COVID-19 strains for a comprehensive understanding of the disease's dynamics.

Rare host variants in ciliary expressed genes contribute to COVID-19 severity in Bulgarian patientsnew window

Abstract Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a pneumonia with extremely heterogeneous clinical presentation, ranging from asymptomatic to severely ill patients. Previous studies have reported links between the presence of host genetic variants and the outcome of the COVID-19 infection. In our study, we used whole exome sequencing in a cohort of 444 SARS-CoV-2 patients, admitted to hospital in the period October-2020-April-2022, to search for associations between rare pathogenic/potentially pathogenic variants and COVID-19 progression. We used gene prioritization-based analysis in genes that have been reported by host genetic studies. Although we did not identify correlation between the presence of rare pathogenic variants and COVID-19 outcome, in critically ill patients we detected known mutations in a number of genes associated with severe disease related to cardiovascular disease, primary ciliary dyskinesia, cystic fibrosis, DNA damage repair response, coagulation, primary immune disorder, hemoglobin subunit β, and others. Additionally, we report 93 novel pathogenic variants found in severely infected patients who required intubation or died. A network analysis showed main component, consisting of 13 highly interconnected genes related to epithelial cilium. In conclusion, we have detected rare pathogenic host variants that may have influenced the COVID-19 outcome in Bulgarian patients.

Laparoscopic repair of parastomal hernia following radical cystectomy and ileal conduit: A Single-Center Experiencenew window

Abstract Purpose: Parastomal hernia (PH) is a frequent complication following radical cystectomy and ileal conduit (IC). The purpose of this study was to summarize the clinical experience and technical characteristics of laparoscopic repair of PH following IC. Methods : We retrospectively evaluated all patients who underwent laparoscopic treatment of PH following IC at Huashan Hospital, Fudan University from May 2013 to December 2022. Results :Thirty-five patients were included in the study. Median follow up was 32 months. Three patients presented with a recurrence (8.6%), with a median time to recurrence of 14 months. Out of the 35 patients, Thirty-two underwent totally laparoscopic repair using the Sugarbaker technique, Three patients required open surgery to repair the intestinal injury after laparoscopic exploration. One patient died 9 months post-surgery due to COVID-19. During the follow-up period, two patients developed a peristomal abscess, and one patient experienced partial intestinal obstruction 10 days after surgery. Conclusion : Surgical management of PH following IC is challenging. The laparoscopic Sugarbaker technique for repairing PHfollowing IC has low complication and recurrence rate.

Scedosporium boydii disseminated infection complicating severe SARS-CoV2 infection in an immunocompetent patient: a case...new window

Abstract Background: Disseminated disease by species in the Scedosporium genus are rare in immunocompetent patients, and have not been reported in the context of severe SARS Cov-2 infection. Case presentation: A retired, 41-year-old police officer with a history of obesity and arterial hypertension presented to emergency department with acute respiratory hypoxemic failure due to severe SARS-Cov2 pneumonia. He used to practice home aquarium care, biking, river swimming, and fishing. He reported no recent travel to the sea, lakes, or caves. He required prolonged mechanical ventilation, and had several documented episodes of ventilator-associated pneumonia due to Pseudomonas aeruginosa and Klebsiella pneumoniae, which later evolved to necrotizing pneumonia, multiple lung abscesses, bronchopleural fistula, empyema and subpleural abscess. Despite sedation withdrawal he remained unconscious; a brain MRI revealed multiple brain abscesses. Scedosporium boydii was isolated from both lung and brain abscess cultures. In addition to percutaneous drainage of lung abscesses, he was treated with combined therapy with voriconazole and liposomal amphotericin B, considering a possible synergic effect. Drainage of the multiple brain abscesses was not feasible; thus, radiological progression was documented, leading to the patient´s demise despite five weeks of treatment. Conclusion: Invasive fungal infections (IFIs) by molds are an emerging condition in patients with COVID-19. Cases of aspergillosis, candidiasis and mucormycosis were increasingly reported during the COVID-19 pandemic. This is the first report of a fatal disseminated infection due to Scedosporium boydii preceded by a severe SARS Cov-2 infection.

HIGH THROUGHPUT QUANTITATION OF HUMAN NEUTROPHIL RECRUITMENT AND FUNCTIONAL RESPONSES IN AN AIR-BLOOD BARRIER ARRAYnew window

Dysregulated neutrophil recruitment drives many pulmonary diseases, but most preclinical screening methods are unsuited to evaluate pulmonary neutrophilia, limiting progress towards therapeutics. Namely, high throughput therapeutic screening systems typically exclude critical neutrophilic pathophysiology, including blood-to-lung recruitment, dysfunctional activation, and resulting impacts on the air-blood barrier. To meet the conflicting demands of physiological complexity and high throughput, we developed an assay of 96-well Leukocyte recruitment in an Air-Blood Barrier Array (L-ABBA-96) that enables in vivo -like neutrophil recruitment compatible with downstream phenotyping by automated flow cytometry. We modeled acute respiratory distress syndrome (ARDS) with neutrophil recruitment to 20 ng/mL epithelial-side interleukin 8 (IL-8) and found a dose dependent reduction in recruitment with physiologic doses of baricitinib, a JAK1/2 inhibitor recently FDA-approved for severe COVID-19 ARDS. Additionally, neutrophil recruitment to patient-derived cystic fibrosis sputum supernatant induced disease-mimetic recruitment and activation of healthy donor neutrophils and upregulated endothelial e-selectin. Compared to 24-well assays, the L-ABBA-96 reduces required patient sample volumes by 25 times per well and quadruples throughput per plate. Compared to microfluidic assays, the L-ABBA-96 recruits two orders of magnitude more neutrophils per well, enabling downstream flow cytometry and other standard biochemical assays. This novel pairing of high-throughput in vitro modeling of organ-level lung function with parallel high-throughput leukocyte phenotyping substantially advances opportunities for pathophysiological studies, personalized medicine, and drug testing applications.

SARS-CoV-2 Humoral and Cellular Immune Responses in HIV-Positive Patientsnew window

Immunosuppressed individuals, such as people living with HIV (PLWH), remain vulnerable to severe COVID-19. We analyzed the persistence of specific SARS-CoV-2 humoral and cellular immune responses in a retrospective, cross-sectional study in PLWH on antiretroviral therapy. Among 104 participants, 70.2% had anti-S IgG antibodies and 55.8% had significant neutralizing activity against the Omicron variant in a surrogate virus neutralization test. Only 38.5% were vaccinated (8.76 ± 4.1 months prior), all displaying anti-S IgG, 75% with neutralizing antibodies and anti-S IgA. 29.8% had no SARS-CoV-2 serologic markers and displayed significantly lower CD4 counts and HIV viral load. Severe immunosuppression (present in 12.5% of participants) was linked to lower levels of detectable anti-S IgG (0.0003), anti-S IgA (p &lt; 0.0001) and lack of neutralizing activity against Omicron variant (p &lt; 0.0001). T-cell responses were present in 86.7% of tested participants, even in those lacking serological markers. In PLWH without severe immunosuppression, neutralizing antibodies and T-cell responses persisted for up to 9 months post-infection or vaccination. Advanced immunosuppression led to diminished humoral immunity, but retained cellular immune.

Single-Facility Analysis of COVID-19 Status of Healthcare Employee During the Eighth and Ninth Pandemic Waves in Japan A...new window

Background: Community infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased rapidly since the emergence of the Omicron strain. During the eighth and ninth pandemic waves—when movement restrictions in the community were eased—the all-case registration system was changed, and the actual status of infection became uncertain. Methods We conducted regular rapid antigen tests (R-RAT) once or twice a week to examine the actual state of coronavirus disease (COVID-19) diagnosis among healthcare employees. Results Overall, 320 (1.42/day) and 299 (1.76/day) employees were infected in the eighth and ninth pandemic waves. During both periods, 59/263 doctors (22.4%), 335/806 nurses (41.6%), 92/194 administrative employees (47.4%), and 129/218 clinical laboratory technicians (59.2%) were infected. In the eighth wave, 56 of 195 employees were infected through close contact; in the ninth wave, 26 of 62 employees were infected. No significant difference was observed in the number of vaccinations between infected and non-infected employees. The positivity rate of R-RAT was 0.41% and 0.45% in the eighth and ninth waves. R-RAT detected infection in 212 and 229 employees during the eighth and ninth waves, respectively; the ratio of R-RAT-detected positive employees to those who reported infection was significantly higher during the ninth wave (odds ratio: 1.67, 95% confidence interval: 1.17–2.37, p