Excess Mortality by Suicide associated with COVID-19 in Japan through August, 2021 BackgroundCountermeasures against COVID-19 outbreak such as lockdown and voluntary restrictions against going out adversely affect human stress and economic activity. Particularly, this stress might lead to suicide.

ObjectWe examined excess mortality attributable to suicide caused by COVID-19. Method: We applied the NIID model to suicide deaths from October 2009 through September, 2021 for the whole of Japan by gender. Effects of the great earthquake that struck in eastern Japan on March 11, 2011 were incorporated into the estimation model. Results: Significant excess mortality in suicide was found between July, 2020 and July, 2021 for both genders. However, in August and September, 2021, excess mortality in suicide was detected only in female. It was greater among females than among males. In total, 2950 excess cases of mortality were identified.

Discussion and ConclusionExcess mortality during the four months was more than two times greater than the number of COVID-19 deaths confirmed by PCR testing. Countermeasures against COVID-19 should be chosen carefully in light of suicide effects.
Detection and genome sequencing of SARS-CoV-2 belonging to the B.1.1.7 lineage in the Philippines We report the sequencing and detection of 39 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples containing lineage-defining mutations specific to viruses belonging to the B.1.1.7 lineage (UK variant) in the Philippines.
Hyperreflective foci, OCT progression indicators in age-related macular degeneration, include transdifferentiated retinal pigment epithelium PurposeBy optical coherence tomography (OCT) imaging, hyperreflective foci (HRF) indicate progression risk for advanced age-related macular degeneration (AMD) and are in part attributable to ectopic retinal pigment epithelium (RPE). We hypothesized that ectopic RPE are molecularly distinct from in-layer cells and that their cross-retinal course follows Muller glia.

MethodIn clinical OCT (61 eyes, 44 AMD patients, 79.4 {+/-} 7.7 years; 29 female; follow-up = 4.7 {+/-} 0.9 years) one HRF type, RPE plume, was reviewed. Twenty eyes of 20 donors characterized by ex vivo OCT were analyzed by histology (normal, 4; early/intermediate AMD, 7; geographic atrophy (GA), 6; 3 neovascular AMD (nvAMD). Cryosections were stained with antibodies to retinoid (RPE65, CRALPB) and immune (CD68, CD163) markers. In published RPE cellular phenotypes, red immunoreactivity was assessed semi-quantitatively by one observer (none, some cells, all cells).

ResultsTrajectories of RPE plume and cellular debris paralleled Muller glia, whether ordered or subsident, near atrophy borders. RPE corresponding to HRF lost immunoreactivity for retinoid markers and gained immunoreactivity for immune markers. Aberrant immunoreactivity appeared in individual in-layer RPE cells and extended to all abnormal phenotypes. Muller glia remained CRALBP-positive. Plume cells approached and contacted retinal capillaries.

ConclusionGain- and loss-of-function starts with individual in-layer RPE cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may impair rod vision while Muller glia sustain cone vision. Evidence for RPE transdifferentiation, possibly due to ischemia, supports a proposed process of epithelial-mesenchyme transition. Data can propel new biomarkers and therapeutic strategies for AMD.

PrecisHyperreflective foci (HRF) are OCT progression risk indicators in age-related macular degeneration. Abnormal RPE cells including some that correspond to HRF lose immunoreactivity for retinoid markers and gain immunoreactivity for immune markers, indicating molecular transdifferentiation. Pausing methotrexate improves immunogenicity of COVID-19 vaccination in elderly patients with rheumatic diseases ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).

MethodsNeutralising SARS-CoV-2 antibodies were measured after second vaccination in 64 rheumatic patients on methotrexate therapy, 31 of whom temporarily paused medication without a fixed regimen. The control group consisted of 21 AIRD patients without immunosuppressive medication.

ResultsMTX patients showed a significantly lower median antibody response compared to AIRD patients without immunosuppressive therapy (p< 0.001). Young age (<60 years) and MTX-hold after vaccination were found to be the main factors influencing antibody response after vaccination, while BMI or MTX dose demonstrated no effect. For patients taking MTX, age correlated negatively with immune response (r=-0.49; p<0.001) and all patients with antibody levels (14 %) below the cut-off were older than 60 years. Patients who held MTX during at least one vaccination showed significantly higher median neutralising antibody levels after second vaccination, compared to patients who continued MTX therapy during both vaccinations (68.82 %, 92.73 %, p=<0.001). This effect was particularly pronounced in patients older than 60 years (p=0.0016). The impact of the time period after vaccination was greater than of the time before vaccination with the critical cut-off being 10 days.

ConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age. Covid-19 Associated Hepatitis in children (CAH-C) during the second wave of SARS-CoV-2 infections in Central India: Is it a complication or transient phenomenon. Objective: While pediatric population has largely remained free of severe COVID-19, in some cases SARS-CoV-2 infection has been associated with complications like Multiple Inflammatory Syndrome in children (MIS-C). We mention another unique presentation subsequent to asymptomatic infection of SARS-CoV-2, a unique form of hepatitis designated by us as COVID-19 Associated Hepatitis in Children (CAH-C). The contrasting clinical presentations, temporal association and viral parameters of CAH-C cases, to the MIS-C cases are presented here. Methods: As a retrospective and follow-up observational study we reviewed all children testing positive for SARS-CoV-2 during study period. Children presenting with sudden onset of hepatitis, elevated transaminases, non-obstructive jaundice, lacking marked inflammatory responses and without evidence of (a) other known causes of acute hepatitis or previous underlying liver disease (b) multi-system involvement were classified as CAH-C, are described here. Results: Among 475 children who tested positive, 47 patients presented with hepatitis, 37 patients who had features of CAH-C, having symptoms of hepatitis only, with un-elevated inflammatory markers and uneventful recovery following supportive treatment. Whereas remaining 10 MIS-C hepatitis had protracted illness, multiple system involvement, required admission to critical care, and had mortality of 30%. Conclusion: With the emergence of newer variants of concern (VOC) including the Delta variant which predominated the second wave of infections in India and has now spread to more than 142 countries with changing presentations, CAH-C might be one of them. Cases of such new entities need to be identified early and differentiated from other emerging syndromes in children during the ongoing pandemic for preventing adversities by timely intervention. Human lipoproteins comprise at least 12 different classes that are lognormally distributed. Lipoproteins in medical samples have been measured by enzymatic methods that coincide with conventional ultracentrifugation. However, the high gravity and time required for ultracentrifugation can cause sample degradation. This study presents the results of HPLC, a gentler and rapid separation method, for 55 human serum samples. The elution patterns were analysed parametrically, and the attribute of each class was confirmed biochemically. Human samples contained 12 classes of lipoproteins, each of which may consist primarily of proteins. There are three classes of VLDLs. The level of each class was distributed lognormally, and the standard amount and the 95% range were estimated. Enzymatic methods measure the levels of several mixed classes. This lognormal character suggests that the levels are controlled by the synergy of multiple factors. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. A transnational and transregional study of the impact and effectiveness of social distancing for COVID-19 mitigation We present an analysis of the relationship between SARS-CoV-2 infection rates and a social distancing metric from data for all the states and most populous cities in the United States and Brazil, all the 22 European Economic Community countries and the United Kingdom. We discuss why the infection rate, instead of the effective reproduction number or growth rate of cases, is a proper choice to perform this analysis when considering a wide span of time. We obtain a strong Spearmans rank order correlation between the social distancing metric and the infection rate in each locality. We show that mask mandates increase the values of Spearmans correlation in the United States, where a mandate was adopted. We also obtain an explicit numerical relation between the infection rate and the social distancing metric defined in the present work. Comparison of respiratory protection during exercising tasks between different wearing methods of replaceable particulate respirators and powered air-purifying respirators BackgroundThis study evaluated the differences in respiratory protection between replaceable particulate respirators (RPRs) and powered air-purifying respirators (PAPRs), with different wearing methods, during exercising tasks.

MethodsTen participants wore either RPR or PAPR according to the recommended method, with a knit cover placed between the facepiece cushion and the face, or with the headband on a helmet. We measured the number of particles inside and outside the respiratory protective equipment (RPE) during exercising tasks for each wearing variation. The exercise state was set to exercise with an ergometer set at 80W load. While exercising tasks, the participants performed five actions adopted from JIS T8150 in 2018 (1. Normal breathing, 2. Deep breathing, 3. Turning head side to side, 4. Moving head up and down, 5. Talking). Each action was performed for 1 min. For measurements of exercise state, after 10 minutes of exercise tasks, we measured while the exercise was continued. The fit factor was calculated by dividing the concentration within the RPE by the concentration outside of it. Data were analyzed after they were log-transformed with a linear mixed model, with fit factor as the dependent variable.

ResultsWe compared the results with experimental data of resting state reported in our previous studies. Fit factor of RPRs in the exercise state was significantly lower (p<0.001) than that in the resting state, indicating inadequate respiratory protection. In contrast, the fit factor of PAPRs during exercising tasks was significantly lower (p<0.001) than that at rest; however, respiratory protection was maintained. PAPR did not show a significant decrease (p=1.000) in fit factor owing to the wearing variations during exercising tasks.

ConclusionsPAPRs were found to be superior to RPRs in terms of respiratory protection. PAPRs are better than RPRs for workers who have to wear RPE inappropriately due to health problems. Arrhythmic Outcomes in Catecholaminergic Polymorphic Ventricular Tachycardia IntroductionCatecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare cardiac ion channelopathy. The aim of this study is to examine the genetic basis and identify pre-dictive factors for arrhythmic outcomes in CPVT patients from Hong Kong.

MethodsThis was a territory-wide retrospective cohort study of consecutive patients diagnosed with CPVT at public hospitals or clinics in Hong Kong. The primary outcome was spontaneous ventricular tachycardia/ventricular fibrillation (VT/VF).

ResultsA total of 16 (mean presentation age=11{+/-}4 years old) patients were included. All patients presented at or before 19 years of age. Fifteen patients (93.8%) were initially symptomatic. Ten patients had both premature ventricular complexes (PVCs) and VT/VF, whereas one patient had PVCs without VT/VF. Genetic tests were performed in 14 patients (87.5%). Eight (57.1%) tested positive for the RyR2 gene. Seven variants have been described else-where (c.14848G>A, c.12475C>A, c.7420A>G, c.11836G>A, c.14159T>C, c.10046C>T and c.7202G>A). c.14861C>G is a novel RyR2 variant that has not been reported outside this cohort. All patients were treated with beta-blockers, three patients received amiodarone and two received verapamil. Sympathectomy (n=8), ablation (n=1) and implantable-cardioverter defibrillator implantation (n=3) were performed. Over a median follow-up of 127 (IQR: 97-143) months, six patients suffered from incident VT/VF. No significant predictors were identified on Cox regression. Nevertheless, a random survival forest model identified initial VT/VF/sudden cardiac death, palpitations, QTc, initially symptomatic and heart rate as important variables for estimating the probability of developing incident VT/VF.

ConclusionAll CPVT patients who are from Hong Kong presented at or before 19 years of age. Clinical and electrocardiographic findings can be used to predict arrhythmic outcomes. A nonparametric machine learning survival analysis achieved high accuracy for predicting the probability of incident VT/VF. The energy balance theory: an unsatisfactory model of body composition fluctuations Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. COMPARISON OF sPLA2-IIA PERFORMANCE WITH HIGH-SENSITIVE CRP, NEUTROPHIL PERCENTAGE, PCT AND LACTATE TO IDENTIFY BACTERIAL INFECTION: A PROSPECTIVE STUDY Early bacterial infection (BI) identification in resource-limiting Emergency Departments (ED) is challenging especially in low- and middle-income counties (LMIC). Misdiagnosis predisposes to antibiotic overuse and propagates antimicrobial resistance. This study evaluates new emerging biomarkers, secretory phospholipase A2 group IIA (sPLA2-IIA), and compares with other biomarkers on their performance characteristic of BI detection in Malaysia, an LMIC. A prospective cohort study was conducted involving 151 consecutive patients admitted to the ED. A single measurement was taken upon patient arrival in ED and was analysed for serum levels of sPLA2-IIA, high-sensitive C-reactive protein (CRP), procalcitonin (PCT), neutrophil percentage (N%), and lactate. All biomarkers performance was compared for the outcomes using area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The performance of sPLA2-IIA (AUROC 0.93 [95% CI: 0.89-0.97]; Sn 80% [95% CI: 72-87] Sp 94% [95% CI: 81-89]) was the highest among all. It was comparable with high-sensitive CRP (AUROC 0.93 [95% CI: 0.88-0.97]; Sn 75% [95% CI: 66-83]; Sp 91 [95% CI: 77-98]) but had a higher Sn and Sp. The sPLA2-IIA was also found superior to N%, PCT, and lactate. This finding suggested sPLA2-IIA was recommended biomarkers for BI detection in LMIC. Vaccination or restriction?: COVID-19 vaccine hesitancy and vaccine passports ObjectivesWhile the development of vaccines against the novel coronavirus (COVID-19) brought the hope of establishing herd immunity, which might help end the global pandemic, vaccine hesitancy can hinder the progress towards herd immunity. In this study, we assess the determinants of vaccine hesitancy, reasons for hesitation, and effectiveness of vaccine passports in relaxing public health restrictions.

MethodsThrough an online survey that includes a conjoint experiment of a demographically representative sample of 5,000 Japanese adults aged 20-74, we assess the determinants of vaccine hesitancy, reasons for hesitation, and effectiveness of hypothetical vaccine passports.

ResultsWe found that about 30% of respondents did not intend to vaccinate or have not yet decided, with major reasons for vaccine hesitancy being related to concerns about the safety and side effects of the vaccine. In line with previous findings, younger age, lower socioeconomic status, and psychological factors such as weaker COVID-19 fear were associated with vaccine hesitancy. The easing of public health restrictions such as travel, wearing face masks, and dining out at night was associated with an increase in vaccine acceptance by 4-10%.

ConclusionVaccine hesitancy can be reduced by mitigating the concerns about vaccine safety and side effects, as well as by relaxing public health restrictions. However, the feasibility of vaccine passports needs to be sufficiently assessed, taking the ethical issues of passports and the public health impacts of the relaxation of restrictions into careful consideration.

Strengths and limitations of this study{square} This study includes timely data on COVID-19 vaccine hesitancy, obtained from a demographically representative sample of 5,000 Japanese adults.
{square}A conjoint experiment allows assessing the effectiveness of easing public health restrictions on vaccine acceptance.
{square}Actual behaviour may diverge from the survey responses or fluctuate due to the pandemic situation and the timing of the survey.
{square}Results may not be applicable in other countries, since the pandemic situation, government responses to the pandemic, and reasons for vaccine hesitancy can vary across countries. High failure rate of ChAdOx1-nCoV19 immunization against asymptomatic infection in healthcare workers during a Delta variant surge: a case for continued use of masks post-vaccination Immunization is expected to confer protection against infection and severe disease for vaccinees, while reducing risks to unimmunized populations by inhibiting transmission. Here, based on serial serological studies, we show that during a severe SARS-CoV2 Delta-variant outbreak in Delhi, 25.3% (95% CI 16.9 - 35.2) of previously uninfected, ChAdOx1-nCoV19 double vaccinated, healthcare-workers (HCW) were infected within a period of less than two months, based on serology. Induction of anti-spike response was similar between groups with breakthrough infection (541 U/ml, IQR 374) or not (342 U/ml, IQR 497), as was induction of neutralization activity to wildtype. Most infections were unrecognized. The Delta-variant thus causes frequent unrecognized breakthrough infections in adequately immunized subjects, reducing any herd-effect of immunity, and requiring reinstatement of preventive measures such as masking. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

ObjectiveTo develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging.

DesignDerivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules.

SettingPrimary and Express care clinics in a Pennsylvania health system.

ParticipantsPatients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19.

Main outcomes and measuresClassification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC).

ResultsOverall, 7.4% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21) and 5.5% in the late validation cohort (3806 patients presenting 3/1/21 or later) were ultimately hospitalized. We developed and temporally validated three risk scores that all included age, dyspnea, and the presence of comorbidities, adding respiratory rate for the second score and oxygen saturation for the third. All had very good overall accuracy (AUC 0.77 to 0.78) and classified over half of patients in the validation cohort as very low risk with a 1.7% or lower likelihood of hospitalization. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization (2.8%).

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/. Cohort profile: The Australian Parkinson's Genetics Study (APGS) - pilot (N=1,532) PurposeParkinsons disease (PD) is a neurodegenerative disorder associated with progressive disability. While the precise aetiology is unknown, there is evidence of significant genetic and environmental influences on individual risk. The Australian Parkinsons Genetics Study (APGS) seeks to study genetic and patient-reported data from a large cohort of individuals with PD in Australia to understand the sociodemographic, genetic, and environmental basis of PD susceptibility, symptoms and progression.

ParticipantsIn the pilot phase reported here, 1,819 participants were recruited through assisted mailouts facilitated by Services Australia based on having three or more prescriptions for anti-PD medications in their Pharmaceutical Benefits Scheme (PBS) records. The average age at the time of the questionnaire was 64 {+/-} 6 years. We collected patient-reported PD information and socio-demographic variables via an online (93% of the cohort) or paper-based (7%) questionnaire. One thousand five hundred thirty-two participants (84.2%) met all inclusion criteria, and 1,499 provided a DNA sample via traditional post.

Findings to date65% of participants were male, and 92% identified as being of European descent. A previous traumatic brain injury was reported by 16% of participants and was correlated with a younger age of symptom onset. At the time of the questionnaire, constipation (36% of participants), depression (34%), anxiety (17%), melanoma (16%) and diabetes (10%) were the most reported comorbid conditions.

Future plansWe plan to recruit sex- and age-matched unaffected controls, genotype all participants, and collect non-motor symptoms and cognitive function data. Future work will explore the role of genetic and environmental factors in the aetiology of PD susceptibility, onset, symptoms, and progression, including as part of international PD research consortia.

Article summaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIWe used a time- and cost-effective recruitment method that enabled us to reach out to a random sample of individuals who have been prescribed medications for Parkinsons disease across all over Australia to invite them to participate in this study.
C_LIO_LIThe identities of letter recipients remained private and confidential and were not shared with the researchers. However, those recipients who were interested and willing to participate were directed to a website where they could sign up and provide informed consent.
C_LIO_LIThe source database only captures individuals who have been prescribed medications to treat Parkinsons disease in Australia and who are eligible for Medicare. Those without an official diagnosis, not receiving treatment, or not eligible for government subsidies are not included.
C_LIO_LIWe collected a wide range of patient-reported variables relevant to disease onset, diagnosis, symptoms, medical comorbidities, lifestyle, and family history in a large cohort of participants. However, some variables might not be as accurate as when measured by a specialist clinician.
C_LIO_LIGiven the 9% response rate to our single-letter invitation, there is a substantial risk of self-selection bias. Thus, patient characteristics for this cohort might differ from those of the typical population of individuals with Parkinsons disease in Australia.
C_LI Virtual reality intervention alleviates dyspnea in patients recovering from COVID pneumonia BackgroundImmersive virtual reality (iVR)-based digital therapeutics (DTx) are gaining clinical attention in the field of pain management. Based on known analogies between pain and dyspnea, we investigated the effects of visual-respiratory feedback, on persistent dyspnea in patients recovering from COVID-19 pneumonia.

MethodsWe performed a controlled, randomized, single-blind, cross-over clinical study to evaluate an iVR-based intervention to alleviate dyspnea in patients recovering from COVID-19 pneumonia. Included patients reported persistent dyspnea ([&ge;]5 on a 10-point scale) and preserved cognitive function (MoCA>24). Assignment was random and concealed. Patients received synchronous (intervention) or asynchronous (control) feedback of their breathing, embodied via a gender-matched virtual body. Outcomes were assessed using questionnaires and breathing recordings. COVVR is registered with ClinicalTrials.gov (NCT04844567).

FindingsStudy enrollment was open between November 2020 and April 2021. Twenty-six patients were enrolled (27% women; age: median=55, interquartile range (IQR)=18). Data were available for 24 of 26 patients. The median (IQR) rating on a 7-point Likert-scale of breathing comfort improved from 1(2) at baseline, to 2(1) for synchronous feedback, but remained unchanged at 1(1.5) for asynchronous feedback (p<0.05) between iVR conditions). Moreover, 91.2% of all patients were satisfied with the intervention (p<0.0001) and 66.7% perceived it as beneficial for their breathing (p<0.05). No adverse events were reported.

InterpretationBased on these findings, our iVR-based DTx presents a feasible and safe respiratory rehabilitation tool that improves breathing comfort in patients recovering from COVID-19 infection presenting with persistent dyspnea. Future research should investigate the DTxs generalizability to persistent dyspnea with other etiologies and its potential for preventing chronification.

FundingMarie Sklodowska-Curie Individual Fellowship (H2020-MSCA-IF-2019 894111/ RESPVR), Bertarelli Foundation Signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas Genetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the COVID-19 pandemic. The recently described variant of concern designated Omicron (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of COVID-19 cases in many countries. Because Omicron was recognized very recently, many knowledge gaps exist about its epidemiology and clinical severity and disease course. A comprehensive genome sequencing study of SARS-CoV-2 in the Houston Methodist healthcare system identified 862 symptomatic patients with infections caused by Omicron from late November 2021 through December 18, 2021. Omicron very rapidly increased in only three weeks to cause 90% of all new COVID-19 cases. Compared to patients infected with either Alpha or Delta variants in our healthcare system, Omicron patients were significantly younger, had significantly increased vaccine breakthrough rates, and were significantly less likely to be hospitalized. Omicron patients required less intense respiratory support and had a shorter length of hospital stay, consistent with decreased disease severity. Although the number of Omicron patients we studied is relatively small, in the aggregate the data document the unusually rapid spread and increased occurrence of COVID-19 caused by the Omicron variant in metropolitan Houston, and provide information about disease character. Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank ObjectivesTo evaluate the benefit of combining polygenic risk scores (PRS) with the QCancer-10 (colorectal cancer) non-genetic risk prediction model to identify those at highest risk of colorectal cancer (CRC).

DesignPopulation based cohort study. Six different PRS for CRC were developed (using LDpred2 PRS software, clumping and thresholding approaches, and genome-wide significant models). The top-performing genome-wide and GWAS-significant PRS were then combined with QCancer-10 and performance compared to QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women.

Setting and participantsUK Biobank Study. A total of 434587 individuals with complete genetic and QCancer-10 predictor data were included in the QCancer-10+PRS modelling cohorts.

Main outcome measuresPrediction of colorectal cancer diagnosis by genetic, non-genetic and combined risk models.

FindingsPRS derived using the LDpred2 program performed best, with an odds-ratio per standard deviation of 1.58, and top age- and sex-adjusted C-statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10+PRS models out-performed QCancer-10 alone. In men, the integrated LDpred2 (QCancer-10+LDP) model produced a C-statistic of 0.730 (0.720 to 0.741) and explained variation of 28.1% (26.3% to 30.0%), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9% to 23.1%) for QCancer-10 alone. Performance improvements in women were similar. In the top 20% of individuals at highest absolute risk, the sensitivity of QCancer-10+LDP models for predicting CRC diagnosis within 5 years was 47.6% in men and 42.5% in women, with respective 3.49-fold and 2.75-fold absolute increases in the top 5% of risk compared to average. Decision curve analysis showed that adding PRS to QCancer-10 improved net-benefit and interventions avoided, across most probability thresholds.

ConclusionsIntegrating PRS with QCancer-10 significantly improves risk prediction over QCancer-10 alone. Evaluation of risk stratified population screening using this approach is warranted.

Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIRisk stratification based on genetic or environmental risk factors could improve cancer screening outcomes
C_LIO_LINo previously published study has examined integrated models combining genome-wide PRS and non-genetic risk factors beyond age
C_LIO_LIQCancer-10 (colorectal cancer) is the top-performing non-genetic risk prediction model for CRC
C_LI

What this study addsO_LIAdding PRS to the QCancer-10 (colorectal cancer) risk prediction model improves performance and clinical benefit, with greatest gain from the LDpred2 genome-wide PRS, to a level that suggests utility in stratifying CRC screening and prevention
C_LI Mitigating Covid-19 aerosol infection risk in school buildings: the role of natural ventilation, classroom volume, occupancy and face masks Issues linked to aerosol physics within school buildings and related infection risk still lack a proper recognition in school safety regulations. In this theoretical work we try to shed more light on the critical role of air ventilation, classroom volume, occupancy, and face mask types (surgical vs ffp2) in controlling airborne transmission risk in educational settings. Limited spaces available in many schools require to precisely assess the occupancy/volume ratio in each classroom and to investigate the specific risk levels from aerosolization of viral loads from infective sources. Moreover, most schools are not provided with mechanical HVAC systems. Fundamental questions are therefore: how the specific classroom volume affects the long-range contagion risk in a given classroom? is linear social distancing the right way to assess a volumetric risk problem? How effective are other countermeasures like reduced speaking volume or equipping teachers with microphones? We present here the results of a numerical analysis based on the Gammaitoni-Nucci infection risk model and the consolidated Wells-Riley like approach, with SARS-CoV2 input data and geometric data from a typical high-school classroom in Italy. We investigated separately the case of infective asymptomatic student and infective asymptomatic teacher as source of viral quanta, taking into account thermal gradient effects on the air ventilation rates. First recommendations based on the volumetric nature of aerosol risk are suggested to extend the linear social distancing approach applied so far. Finally we discuss the concept of "cumulative infection risk" over multiple lesson+break cycles in Wells-Riley-like infection models. We believe that any attempt to proper model infection risk in closed environments with cycled changes of the source and the susceptible individuals, should carefully consider this point, particularly when modelling air ventilation breaks in classrooms. Development of machine learning models for the prediction of complications after colonic, colorectal and small intestine anastomosis in psychiatric and non-psychiatric patient collectives (PSTUDY) Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

MethodPatient data will be collected from several participating national and international surgical centers The machine learning models will be calculated and coded, but also published according to the TRIPOD guidelines (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis).

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

Material & MethodsUsing mass spectrometry and immunoblotting analyses, we profiled degradation patterns of cytoskeletal proteins in deceased (n=55) and living (n=10) donor kidneys.

ResultsWe found that in DBD kidneys, key podocyte cytoskeletal proteins had been proteolytically cleaved. Generated degradation profiles were not associated to donor related demographic and clinical factors but were associated to suboptimal post-transplant function. Strikingly, -actinin -4 and Talin-1 degradation profiles were not observed in circulatory-death or living-donor kidneys. As Talin-1 is a specific proteolytic target of Calpain-1, we investigated a potential trigger of Calpain activation and Talin-1 degradation using ex-vivo precision-cut human kidney slices and in-vitro immortalised human podocytes. Notably, we found that Transforming-Growth Factor-{beta} (TGF-{beta}) activated Calpain-1 and proteolytically cleaved Talin-1 to generate distinct peptide fragments. These peptide fragments were of similar size and matched the degradation patterns observed in DBD kidneys. Talin-1 degradation was prevented in vitro by Calpain-1 inhibition.

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Evaluating a first fully automated interview grounded in Multiple Mini Interview (MMI) methodology: results from a feasibility study ObjectivesGlobal, Covid-driven restrictions around face-to-face interviews for healthcare student selection have forced admissions staff to rapidly adopt adapted online systems before supporting evidence is available. We have developed, what we believe is, the first fully automated interview grounded in Multiple Mini-Interview (MMI) methodology. This study aimed to explore test re-test reliability, acceptability and usability of the system.

Design, setting and participantsmixed-methods feasibility study in Physician Associate (PA) programmes from two UK and one US university during 2019 - 2020.

Primary, secondary outcomesFeasibility measures (test retest reliability acceptability and usability) were assessed using intra-class correlation (ICC), descriptive statistics, thematic and content analysis.

MethodsVolunteers took (T1), then repeated (T2), the automated MMI, with a seven-day interval (+/- 2) then completed an evaluation questionnaire. Admissions staff participated in focus group discussions.

ResultsSixty-two students and seven admission staff participated; 34 students and four staff from UK and 28 students and three staff from US universities.

Good-excellent test-retest reliability was observed with T1 and T2 ICC between 0.62-0.81 (p<0.001) when assessed by individual total scores (range 80.6-119), station total scores 0.6-0.91, p<0.005, individual site (all ICC[&ge;] 0.76 p<0.001) and mean test retest across sites 0.82 p<0.001 (95% CI 0.7-0.9).

Admissions staff reported potential to reduce resource costs and bias through a more objective screening tool for pre-selection or to replace some MMI stations in a  hybrid model. Maintaining human interaction through  touch points was considered essential.

Users positively evaluated the system, stating it was intuitive with an accessible interface. Concepts chosen for dynamic probing needed to be appropriately tailored.

ConclusionThese preliminary findings suggest that the system is reliable, generating consistent scores for candidates and is acceptable to end-users provided human touchpoints are maintained. Thus, there is evidence for the potential of such an automated system to augment healthcare student selection processes. Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface Prosthetics and orthotics have been recognized for decades as a potential means to restore hand function and independence to individuals living with impairment due to stroke. However, 75% of stroke survivors, caregivers, and health care professionals (HCP) believe current practices are insufficient, specifically calling out the upper extremity as an area where innovation is needed to develop highly usable prosthetics/orthotics for the stroke population. A promising method for controlling upper limb technologies is to infer movement intent non-invasively from surface electromyography (EMG) activity. While this approach has garnered significant attention in the literature, existing technologies are often limited to research settings and struggle to meet stated user needs. To address these limitations, we have developed the NeuroLife(R) EMG System, which consists of a wearable forearm sleeve with 150 embedded electrodes and associated hardware and software to record and decode surface EMG. Here, we demonstrate accurate decoding of 12 functional hand, wrist, and forearm movements, including multiple types of grasps from participants with varying levels of chronic impairment from stroke, with an overall accuracy of 77.1{+/-}5.6%. Importantly, we demonstrate the ability to decode a subset of 3 fundamental movements in individuals with severe hand impairment at 85.4{+/-}6.4% accuracy, highlighting the potential as a control mechanism for assistive technologies. Feedback from stroke survivors who tested the system indicates that the sleeves design meets various user needs, including being comfortable, portable, and lightweight. The sleeve is in a form factor such that it can be used at home without an expert technician and can be worn for multiple hours without discomfort. Taken together, the NeuroLife EMG System represents a platform technology to record and decode high-definition EMG for the eventual real-time control of assistive devices in a form factor designed to meet user needs.