Human serum from SARS-CoV-2 vaccinated and COVID-19 patients shows reduced binding to the RBD of SARS-CoV-2 Omicron variant The COVID-19 pandemic is caused by the betacoronavirus SARS-CoV-2. In November 2021, the Omicron variant was discovered and classified as a variant of concern (VOC). Omicron shows substantially more mutations in the spike protein than any previous variant, mostly in the receptor binding domain (RBD). We analyzed the binding of the Omicron RBD to the human ACE2 receptor (hACE2) and the ability of human sera from COVID-19 patients or vaccinees in comparison to Wuhan, Beta or Delta RBDs variants.

All RBDs were produced in insect cells. RBD binding to hACE2 was analyzed by ELISA and microscale thermophoresis (MST). Similarly, sera from 27 COVID-19 patients, 58 fully vaccinated individuals and 16 booster recipients were titrated by ELISA on the fixed RBDs from the original Wuhan strain, Beta, Delta and Omicron VOC.

Surprisingly, the Omicron RBD showed a weaker binding to ACE2 compared to Beta and Delta, arguing that improved ACE2 binding is not a likely driver of Omicron evolution. Serum antibody titers were significantly lower against Omicron RBD compared to the original Wuhan strain. However, a difference of 2.5 times was observed in RBD binding while in other studies the neutralization of Omicron SARS-CoV-2 was reduced by a magnitude of 10x and more. These results indicate an immune escape focused on neutralizing antibodies.

The reduced binding of sera to Omicron RBD adds evidence that current vaccination protocols may be less efficient against the Omicron variant.
Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the respiratory microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 respiratory microbiome studies by analyzing the upper (n=58) and lower (n=35) respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support, both of which are associated to additional treatments such as antibiotic usage, explained the most variation within the upper respiratory tract microbiome, while SARS-CoV-2 viral load had a reduced impact. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19. Single-cell transcriptomic analysis of the lower respiratory tract of mechanically ventilated COVID-19 patients identified specific oral bacteria, different to those observed in controls. These oral taxa were found physically associated with proinflammatory immune cells, which showed higher levels of inflammatory markers. Overall, our findings suggest confounders are driving contradictory results in current COVID-19 microbiome studies and careful attention needs to be paid to ICU stay and type of oxygen support, as bacteria favored in these conditions may contribute to the inflammatory phenotypes observed in severe COVID-19 patients.
Hepatic resection versus transarterial chemoembolization for the intermediate stage hepatocellular carcinoma：A cohort study BackgroundThe selection criterion for hepatic resection(HR) in intermediate-stage(IM) hepatocellular carcinoma(HCC) is still controversial. We used real-world data to evaluate the overall survival (OS) treated with HR or TACE.

MethodsIn all, 942 patients with IM-HCC were categorized in HR and TACE groups. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score- matched (PSM) analyses. The smooth curve was performed through the generalized additive model. The interaction test was performed to evaluate the HR impact on OS concerning risk factors. Also, we used multiple imputation to deal with the missing data.

ResultsTotally, 23.0% (n=225) of patients received HR. At a median overall survival of 23.7 months, HR was associated with the improved OS on multivariate analysis (hazard ratio, 0.45; 95%CI: 0.35, 0.58; after PSM: 0.56; 95%CI: 0.41, 0.77). Landmark analyses limited to long-term survivors of [&ge;] 6 months, [&ge;] 1, and [&ge;] 2 years demonstrated better OS with HR in all subsets (all P<0.05). After PSM analysis, however, HR increased 20% risk of death (HR, 1.20; 95%CI: 0.67, 2.15) in the subgroup of LDH [&le;]192 U/L (P for interaction = 0.037). Furthermore, the significant interaction was robust between the LDH and the HR with respect to 1-, 3-, and 5-year observed survival rate (all P<0.05).

ConclusionHepatic resection was superior to TACE for intermediate-stage HCC in the range of LDH level > 192 U/L. Moreover, TACE might be suitable for patients with LDH level [&le;] 192 U/L.

SynopsisO_LIHepatectomy was superior to TACE for BCLC-B HCC.
C_LIO_LIHepatectomy increased 20% risk of death for LDH < 192 U/L after matching.
C_LIO_LIA significant interaction was robust between LDH and with respect to hepatectomy the 1-, 3-, and 5-year observed survival rate.
C_LI Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. 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. Chemosensory dysfunctions induced by COVID-19 can persist up to 7 months: A study of over 700 healthcare workers Several studies have revealed either self-reported chemosensory alterations in large groups or objective quantified chemosensory impairments in smaller populations of patients diagnosed with COVID-19. However, due to the great variability in published results regarding COVID-19-induced chemosensory impairments and their follow-up, prognosis for chemosensory functions in patients with such complaints remains unclear. Our objective is to describe the various chemosensory alterations associated with COVID-19 and their prevalence and evolution after infection. A cross-sectional study of 704 healthcare workers with a RT-PCR confirmed SARS-CoV-2 infection between 28/2/2020 and 14/6/2020 was conducted 3 to 7 months after onset of symptoms. Data were collected with an online questionnaire. Outcomes included differences in reported chemosensory self-assessment of olfactory, gustatory, and trigeminal functions across time points and Chemosensory Perception Test scores from an easy-to-use at-home self-administered chemosensory test. Among the 704 participants, 593 (84.2%) were women, the mean (SD) age was 42 (12) years, and the questionnaire was answered on average 4.8 (0.8) months after COVID-19. During COVID-19, a decrease in olfactory, gustatory, and trigeminal sensitivities were reported by 81.3%, 81.5% and 48.0% respectively. Three to seven months later, reduced sensitivity was still reported by 52.0%, 41.9% and 23.3% respectively. Chemosensory Perception Test scores indicate that 19.5% of participants had objective olfactory impairment. These data suggest a significant proportion of COVID-19 cases have persistent chemosensory impairments at 3 to 7 months after their infection but the majority of those who had completely lost their olfactory, gustatory, and trigeminal sensitivity have improved. How Informative Were Early SARS-CoV-2 Treatment and Prevention Trials? A longitudinal cohort analysis of trials registered on clinicaltrials.gov BackgroundEarly in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

MethodsWe created a cohort of SARS-CoV-2 treatment and prevention efficacy trials that were initiated from 2020-01-01 to 2020-06-30 using ClinicalTrials.gov registration records. We evaluated trials on 3 criteria of informativeness: potential redundancy, design quality and feasibility of patient-participant recruitment. The study protocol was prospectively registered with the Open Science Framework (https://osf.io/fp726/).

ResultsWe included 500 trials in our cohort, 58% of which were Phase 2 and 84.8% were directed towards the treatment of SARS-CoV-2. Close to one third of trials met all three criteria and were deemed informative (29.0% (95% Confidence Interval 23.7 - 36.9)). The proportion of potentially redundant trials in our cohort was 4.1%. Over half of the trials in our cohort (56.2%) did not meet our criteria for high quality trial design. The proportion of trials with infeasible patient-participant recruitment was 22.6%.

ConclusionsLess than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic. Distinct patterns of cognitive outcome in young children with autism spectrum disorder receiving the Early Start Denver Model Evidence-based, early intervention significantly improves developmental outcome in young children with autism. Nonetheless, there is high interindividual heterogeneity in developmental trajectories during the therapy. It is currently not possible to predict a childs developmental outcome after receiving an early intervention based on his skills and symptoms at baseline. In this study, we analyze developmental trajectories of preschoolers with autism who received 2 years of intervention using the Early Start Denver Model (ESDM) approach in Geneva, Switzerland (n = 47). Our aim was to identify early predictors of response to treatment. We applied a cluster analysis to distinguish between 3 subgroups based on their cognitive level at intake, and rates of cognitive change over the course of treatment. The first subgroup of children only had a mild cognitive delay at intake, and nearly no cognitive delay by the end of treatment (Higher Cognitive at baseline: HC). The children in the two other subgroups all presented with severe cognitive delay at baseline, however, they had two very different patterns of response to treatment. The majority significantly improved developmental scores within their first year of intervention (Optimal Responders: OptR). Whereas a minority of children showed little to no improvement over the course of treatment (Minimal Responders: MinR). Our findings suggest that children who end up having an optimal two-year treatment outcome show rapid developmental improvement. Inversely, less significant progress by the sixth month of intervention may predict a less optimal response to treatment. Effectiveness of the Covid-19 vaccines in preventing infection in dental practitioners: results of a cross-sectional questionnaire based survey India started its vaccination program at the beginning of 2021, the main beneficiaries being health workers and frontline workers including police, paramilitary forces, sanitation workers, and disaster management volunteers in the first phase. By the time, the second wave of Covid-19 impacted India, approximately 14 million healthcare and frontline workers, including dentists had been vaccinated.

AimTo study the effectiveness of vaccination on a subset of high-risk healthcare workers i.e. dentists in preventing Covid-19 during the second wave of the pandemic.

Study designA questionnaire based pan-India online survey was carried out to record the Covid-related experiences of dentists prior to and after vaccination.

ResultThe sample size for this survey was 4493 respondents from across India. During the second wave, 9.18% (n=364) respondents became positive in spite of the vaccine, while 14.69%(n=78) became positive in the unvaccinated group. A chi-square test of independence was performed to examine the relation between vaccination and the Covid positivity rate in all age groups. The relation between these variables was highly significant, [X2 (1, N = 4493) = 15.9809, p=.000064].

ConclusionOur pan-India online survey inferred that vaccination has a definitive role to play in reducing the positivity rate amongst dentists during the second wave of the pandemic across all age groups. Treatment interruption is a risk factor for sickness presenteeism: a large-scale cross-sectional study during the COVID-19 pandemic ObjectivesThis study examined the relationship between interruption to routine medical care during the coronavirus disease 2019 pandemic and sickness presenteeism among workers in Japan.

MethodsA cross-sectional study using data obtained from an internet monitor questionnaire was conducted. Interruption to medical care was defined based on the response "I have not been able to go to the hospital or receive treatment as scheduled." The fraction of sickness presenteeism days in the past 30 days was employed as the primary outcome. A fractional logit model was used for analysis to treat bounded data.

ResultsOf the 27,036 participants, 17,526 (65%) were workers who did not require routine medical care, 8,451 (31%) were using medical care as scheduled, and 1,059 (4%) experienced interrupted medical care. The adjusted odds ratio (aOR) of sickness presenteeism was significantly higher among workers who experienced interrupted medical care (3.44; 95% confidence interval [CI]: 3.04-3.89) than those who did not require routine medical care. In terms of symptoms, the highest aOR was observed among workers with mental health symptoms (aOR: 5.59, 95%CI: 5.04-6.20).

ConclusionsThis study suggests the importance of continuing necessary treatment during a pandemic to prevent presenteeism. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. High concordance of 70-gene recurrence risk signature and 80-gene molecular subtyping signature between core needle biopsy and surgical resection specimens in early-stage breast cancer IntroductionWith an increase in neoadjuvant therapy recommendations for most early-stage breast cancer patients due to the COVID-19 pandemic, it has become increasingly imperative to ensure that molecular diagnostic assays provide reliable results from preoperative core needle biopsies. Therefore, the objective of this study was to determine the concordance of MammaPrint results (70-gene signature) and BluePrint results (80-gene signature) between core needle biopsies (CNB) and surgical resection (SR) specimens using prospectively collected matched tissues from patients enrolled in the FLEX trial (NCT03053193).

MethodsWe analyzed 113 matched CNB and SR tumor specimens from women with early-stage breast cancer enrolled in the FLEX trial. Each patient enrolled in the trial receives a MammaPrint recurrence risk classification test with or without BluePrint molecular subtyping. Concordance of MammaPrint is reported using overall percentage agreement, positive predictive value (PPV, High Risk), negative predictive value (NPV, Low Risk), and Cohens kappa coefficient. Additionally, correlations between sample types are reported using Pearson correlation coefficient.

ResultsWe found good concordance for MammaPrint results between CNB and SR tumor samples (90.3%, {kappa} = 0.803), with a 95.1% NPV and 84.6% PPV. There was also a strong correlation of MammaPrint indices between CNB and SR specimens (r = 0.94). In addition to our primary objective, we determined the concordance of BluePrint subtyping in the matched tumor samples, and found excellent concordance (98.2%) and strong correlation of BluePrint scores within each subtype.

ConclusionCNB samples demonstrated overall high concordance with paired SR samples for MammaPrint risk classification, ensuring that physicians are provided with accurate prognostic information for therapy decisions based on testing of core biopsy tissue. Further, BluePrint molecular subtyping also had good concordance between the sample types, outperforming concordance rates based on traditional IHC based classification. Overall, with an increase in neoadjuvant therapy, physicans and patients can be assured that MammaPrint and BluePrint provide reliable results that guide timely and appropriate therapies using preoperative CNB specimens. The kidney releases a non-polymerizing form of Uromodulin in the urine and circulation that retains the external hydrophobic patch domain Uromodulin (Tamm-Horsfall protein, THP) is a glycoprotein uniquely produced in the kidney. It is released by cells of the thick ascending limbs (TAL) apically in the urine, and basolaterally in the renal interstitium and systemic circulation. Processing of mature urinary THP, which polymerizes into supra-molecular filaments, requires cleavage of an external hydrophobic patch (EHP) at the C terminus. However, THP in the circulation is not polymerized, and it remains unclear if non-aggregated forms of THP exist natively in the urine. We propose that an alternative processing path, which retains the EHP domain, can lead to a non-polymerizing form of THP. We generated an antibody that specifically recognizes THP with retained EHP (THP+EHP) and established its presence in the urine in a non-polymerized native state. Proteomic characterization of urinary THP+EHP revealed its C-terminus to end at F617. In the human kidney, THP+EHP was not only detected in TAL cells, but also diffusely in the renal parenchyma. Using immunoprecipitation followed by proteomic sequencing and immunoblotting, we then demonstrated that serum THP has also retained EHP. In a small cohort of patients at risk for acute kidney injury (AKI), admission urinary THP+EHP was significantly lower in patients who subsequently developed AKI during hospitalization. Our findings uncover novel insights into uromodulin biology by establishing the presence of an alternative path for cellular processing, which could explain the release of non-polymerizing THP in the circulation. Larger studies are needed to establish the utility of urinary THP+EHP as a sensitive biomarker of kidney health and susceptibility to injury. Heterologous immunization with inactivated vaccine followed by mRNA booster elicits strong humoral and cellular immune responses against the SARS-CoV-2 Omicron variant BackgroundThere has been an unprecedented global effort to produce safe and effective vaccines against SARS-CoV-2. However, production challenges, supply shortages and unequal global reach, together with an increased number of breakthrough infections due to waning of immunity and the emergence of new variants of concern (VOC), have prolonged the pandemic. To boost the immune response, several heterologous vaccination regimes have been tested and have shown increased antibody responses compared to homologous vaccination. Here we evaluated the effect of mRNA vaccine booster on immunogenicity in individuals who had been vaccinated with two doses of inactivated vaccines.

MethodsThe levels of specific antibodies against the receptor-binding domain (RBD) of the spike protein from wild-type virus and the Beta, Delta and Omicron variants were measured in healthy individuals who had received two doses of homologous inactivated (BBIBP-CorV or CoronoVac) or mRNA (BNT162b2 or mRNA-1273) vaccines, and in donors who were given an mRNA vaccine boost after two doses of either vaccine. Pre-vaccinated healthy donors, or individuals who had been infected and subsequently received the mRNA vaccine were also included as controls. In addition, specific memory B and T cell responses were measured in a subset of samples.

ResultsA booster dose of an mRNA vaccine significantly increased the level of specific antibodies that bind to the RBD domain of the wild-type (6-fold) and VOCs including Delta (8-fold) and Omicron (14-fold), in individuals who had previously received two doses of inactivated vaccines. The level of specific antibodies in the heterologous vaccination group was furthermore similar to that in individuals receiving a third dose of homologous mRNA vaccines or boosted with mRNA vaccine after natural infection. Moreover, this heterologous vaccination regime significantly enhanced the specific memory B and T cell responses.

ConclusionsHeterologous prime-boost immunization with inactivated vaccine followed by an mRNA vaccine boost markedly increased the levels of specific antibodies and B and T cell responses and may thus increase protection against emerging SARS-CoV-2 variants including Omicron. Impact of HIV Infection on COVID-19 Outcomes Among Hospitalized Adults in the U.S. BackgroundWhether HIV infection is associated with differences in clinical outcomes among people hospitalized with COVID-19 is uncertain.

ObjectiveTo evaluate the impact of HIV infection on COVID-19 outcomes among hospitalized patients.

MethodsUsing the American Heart Associations COVID-19 Cardiovascular Disease registry, we used hierarchical mixed effects models to assess the association of HIV with in-hospital mortality accounting for patient demographics and comorbidities and clustering by hospital. Secondary outcomes included major adverse cardiac events (MACE), severity of illness, and length of stay (LOS).

ResultsThe registry included 21,528 hospitalization records of people with confirmed COVID-19 from 107 hospitals in 2020, including 220 people living with HIV (PLWH). PLWH were younger (56.0+/-13.0 versus 61.3+/-17.9 years old) and more likely to be male (72.3% vs 52.7%), Non-Hispanic Black (51.4% vs 25.4%), on Medicaid (44.5% vs 24.5), and active tobacco users (12.7% versus 6.5%).

Of the study population, 36 PLWH (16.4%) had in-hospital mortality compared with 3,290 (15.4%) without HIV (Risk ratio 1.06, 95%CI 0.79-1.43; risk difference 0.9%, 95%CI -4.2 to 6.1%; p=0.71). After adjustment for age, sex, race, and insurance, HIV was not associated with in-hospital mortality (aOR 1.13; 95%CI 0.77-1.6; p 0.54) even after adding body mass index and comorbidities (aOR 1.15; 95%CI 0.78-1.70; p=0.48). HIV was not associated with MACE (aOR 0.99, 95%CI 0.69-1.44, p=0.91), severity of illness (aOR 0.96, 95%CI 0.62-1.50, p=0.86), or LOS (aOR 1.03; 95% CI 0.76-1.66, p=0.21).

ConclusionHIV was not associated with adverse outcomes of COVID-19 including in-hospital mortality, MACE, or severity of illness.

Condensed AbstractWe studied 21,528 patients hospitalized with COVID-19 at 107 hospitals in AHAs COVID-19 registry to examine the association between HIV and COVID-19 outcomes. More patients with HIV were younger, male, non-Hispanic Black, on Medicaid and current smokers. HIV was not associated with worse COVID-19 in-hospital mortality (Risk ratio 1.06, 95%CI 0.79-1.43; p=0.71) even after adjustment (aOR 1.15; 95%CI 0.78-1.70; p=0.48). HIV was also not associated with MACE (aOR 0.99, 95%CI 0.69-1.44, p=0.91) or severity of illness (aOR 0.96, 95%CI 0.62-1.50, p=0.86. Our findings do not support that HIV is a major risk factor for adverse COVID-19 outcomes. The incidence of delirium in an acute geriatric community hospital: an observational cohort feasibility study. ObjectivesDelirium in hospitalised older adults is associated with negative health outcomes. Admission to an alternative care setting may lower the incidence of delirium. The Acute Geriatric Community Hospital (AGCH) was recently opened in the Netherlands and uses a multi-component non-pharmacological intervention strategy to prevent delirium. The objective of this study was to describe the incidence of delirium at the AGCH and compare this incidence to existing rates from literature. If a possible effect on delirium is seen in this comparison this would support conducting a larger prospectively controlled study on delirium in this new care setting.

DesignProspective cohort feasibility study; exploratory meta-analysis of proportions.

Setting and ParticipantsThe AGCH is an acute geriatric unit in a skilled nursing facility for patients aged >65 years with acute medical conditions.

MethodsDelirium assessment using the Confusion Assessment Method (CAM) upon admission and on day one, two and three or until delirium had resolved. Patients charts were reviewed if CAM was missing. In an linear mixed-effects model, the delirium incidence rate in AGCH was compared to pooled delirium incidence rates from six studies found in a high-quality review.

Results214 patients from the AGCH (mean age 81.9 years, 47% male, 12% with a history of dementia) were included in the analysis. Delirium developed in 8% (18/214) (95% confidence interval [CI] 5-13%) of patients during AGCH admission compared to 16% (95% CI 12-21%) in hospitals. Admission to the AGCH was associated with a decreased delirium incidence rate compared to the hospital control group (OR[odds ratio]= 0.49, 95% CI 0.24-0.98, p-value=0.044).

Conclusions and implicationsThe delirium incidence in the AGCH was low compared to those incidences found in general hospitals in literature. Based on these findings a controlled observational or randomized study measuring delirium in this care setting is recommended. COVID Outcome Prediction in the Emergency Department (COPE): Development and validation of a model for predicting death and need for intensive care in COVID-19 patients Background and aimCOVID-19 is putting extraordinary pressure on emergency departments (EDs). To support decision making in the ED, we aimed to develop a simple and valid model for predicting mortality and need for intensive care unit (ICU) admission in suspected COVID-19 patients.

MethodsFor model development, we retrospectively collected data of patients who were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020 (first wave of the pandemic). Based on prior literature we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of the need for ICU admission, both within 28 days after hospital admission. We assessed model performance (Area Under the ROC curve (AUC); calibration plots) with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing values.

ResultsThe development data included 5,831 patients, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. ICU admission was fully recorded for 2,633 first wave patients in 2 hospitals, with 214 (8%) ICU admissions within 28 days. A simple model - COVID Outcome Prediction in the Emergency Department (COPE) - with age, respiratory rate, C-reactive protein, lactic dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well-calibrated and showed good discrimination in 3,252 second wave patients (AUC in 4 hospitals: 0.82 [0.78; 0.86]; 0.82 [0.74; 0.90]; 0.79 [0.70; 0.88]; 0.83 [0.79; 0.86]). COPE was also able to identify patients at high risk of needing IC in 706 second wave patients with complete information on ICU admission (AUC: 0.84 [0.78; 0.90]; 0.81 [0.66; 0.95]). The models are implemented in web-based and mobile applications.

ConclusionCOPE is a simple tool that is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

CONTRIBUTION TO THE LITERATUREO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIPrediction models have the potential to support decision making about hospital admission of patients presenting to the emergency department with suspected COVID-19
C_LIO_LIMost currently available models that were independently assessed contain a high risk of bias
C_LIO_LIPromising models were developed in different patient selections and included predictors that are not quickly and objective obtainable in emergency departments
C_LI

What this study addsO_LIA simple and objective tool ("COPE") is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19
C_LIO_LICOPE may support ED physicians to identify high-risk patients - i.e. those at high risk of deterioration and/or death - requiring treatment in the ICU, intermediate-risk patients requiring admission to the clinical ward, and low-risk patients who can potentially be sent home
C_LI Spatial Allocation of Scarce COVID-19 Vaccines The COVID-19 Vaccines Global Access (COVAX) is an initiative led by the World Health Organization (WHO) and other partners that aims for an equitable access of COVID-19 vaccines. Despite a potential heterogeneous disease burden across space, countries receiving allotments of vaccines via COVAX may want to follow WHOs allocation rule and distribute vaccines to their jurisdictions based on the jurisdictions relative population size. Utilizing economic-epidemiological modeling, we benchmark the performance of this ad hoc allocation rule by comparing it to the rule that minimizes the economic damages and expenditures over time, including a penalty cost representing the social costs of deviating from the ad hoc allocation. Under different levels of vaccine scarcity and different demographic characteristics, we consider scenarios where length of immunity and compliance to travel restrictions vary, and consider the robustness of the rules when assumptions regarding these factors are incorrect. The benefits from deviating are especially high when immunity is permanent, when there is compliance to travel restrictions, when the supply of vaccine is low, and when there is heterogeneity in demographic characteristics. Interestingly, a lack of compliance to travel restrictions pushes the optimal allocations of vaccine towards the ad hoc and improves the relative robustness of the ad hoc rule, as the mixing of the populations reduces the spatial heterogeneity in disease burden.

JEL ClassificationC61, H12, H84, I18, Q54 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. Prospectively validated disease-agnostic predictive medicine with augmented intelligence Despite numerous superhuman achievements in complex challenges1,2, standalone AI does not free life science from the long-term bottleneck of linearly extracting new knowledge from exponentially growing new data3, severely limiting the success rate of drug discovery4. Inspired by the state-of-the-art AI training methods, we trained a human-centric hybrid augmented intelligence5 (HAI) to learn a foundation model6 that extracts all-encompassing knowledge of human physiology and diseases. To evaluate the quality of HAIs extracted knowledge, we designed the public, prospective prediction of pivotal ongoing clinical trial outcomes at large scale (PROTOCOLS) challenge to benchmark HAIs real-world performance of predicting drug clinical efficacy without access to human data. HAI achieved a 10.5-fold improvement from the baseline with 99% confidence7 in the PROTOCOLS validation, readily increasing the average clinical success rate of investigational new drugs from 7.9%8 to 90% for almost any human diseases9,10. The validated HAI confirms that exponentially extracted knowledge alone is sufficient for accurately predicting drug clinical efficacy, effecting a total reversal of Erooms law4. HAI is also the worlds first clinically validated model of human aging that could substantially speed up the discovery of preventive medicine for all age-related diseases11. Our results demonstrate that disruptive breakthroughs necessitate the smallest team size to attain the largest HAI for optimal knowledge extraction from high-dimensional low-quality data space, thus establishing the first prospective proof of the previous discovery that small teams disrupt12. The global adoption of training HAI provides a well-beaten economic path to mass-produce scientific and technological breakthroughs via exponential knowledge extraction and better designs of data labels for training better-performing AI13. Resting EEG spectral slopes are associated with age-related differences in information processing speed BackgroundPrevious research has shown the slope of the EEG power spectrum differentiates between older and younger adults in various experimental cognitive tasks. Here, we extend that work, assessing the relation between the EEG power spectrum and performance on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), a widely-used neuropsychological instrument that assesses a broad range of cognitive domains.

MethodsForty-four participants (21 younger adults, 23 older adults) completed the RBANS with EEG data collected at-rest. Using spectral parameterization, we tested the mediating effect of the spectral slope on age-related differences in subsequent cognitive task performance.

ResultsOlder adults performed reliably worse on the RBANS overall, and on the Attention and Delayed Memory domains. However, evidence of mediation was only found for the Coding subtest, a measure of information processing speed.

ConclusionsWe found some evidence that the slope of the resting EEG power spectrum mediated age-related differences in cognition. These effects were evident only in tasks requiring speeded processing, whereas this effect was not statistically significant for delayed memory, even though age-related differences were present. Sub-diagnostic effects of genetic variants associated with autism While over a hundred genes are significantly associated with autism, little is known about the prevalence of variants affecting them in the general population. Nor do we fully appreciate the phenotypic diversity beyond the formal autism diagnosis. Using data from more than 13,000 autistic individuals and 210,000 undiagnosed individuals, we provide a gene-level map of the odds ratio for autism associated to rare loss-of-function (LoF) variants in 185 genes robustly associated with autism, alongside 2,492 genes displaying intolerance to LoF variants. In contrast to autism-centric approaches, we investigated the phenotype of undiagnosed individuals heterozygous for such variants and show that they exhibit a decrease in fluid intelligence, qualification level and income, and an increase in material deprivation. These effects were larger for LoFs in autism-associated genes than in other LoF-intolerant genes and appeared largely independent of sex and polygenic scores for autism. Using brain imaging data from 21,049 UK-Biobank individuals, we provide evidence for smaller cortical surface area and volume among carriers of LoFs in genes with high odds ratios for autism. Our gene-level map is a key resource to distinguish genes with high and low odds ratio for autism, and highlights the importance of including quantitative data on both diagnosed and undiagnosed individuals to better delineate the effect of genetic variants beyond the categorical diagnosis. Data are available at https://genetrek.pasteur.fr/. 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. Serum proteome analysis of systemic JIA and related pulmonary alveolar proteinosis identifies distinct inflammatory programs and biomarkers ObjectivesRecent observations in systemic Juvenile Idiopathic Arthritis (sJIA) suggest an increasing incidence of high-mortality interstitial lung disease, characterized by a variant of pulmonary alveolar proteinosis (PAP). Co-occurrence of macrophage activation syndrome (MAS) and PAP in sJIA suggested a shared pathology, but sJIA-PAP patients also commonly experience features of drug reaction such as atypical rashes and eosinophilia. We sought to investigate immunopathology and identify biomarkers in sJIA, MAS, and sJIA-PAP.

MethodsWe used SOMAscan to measure >1300 analytes in sera from healthy controls and patients with sJIA, MAS, sJIA-PAP and other related diseases. We verified selected findings by ELISA and lung immunostaining. Because the proteome of a sample may reflect multiple states (sJIA, MAS, sJIA-PAP), we used regression modeling to identify subsets of altered proteins associated with each state. We tested key findings in a validation cohort.

ResultsProteome alterations in active sJIA and MAS overlapped substantially, including known sJIA biomarkers like SAA and S100A9, and novel elevations of heat shock proteins and glycolytic enzymes. IL-18 was elevated in all sJIA groups, particularly MAS and sJIA-PAP. We also identified an MAS-independent sJIA-PAP signature notable for elevated ICAM5, MMP7, and allergic/eosinophilic chemokines, which were all previously associated with lung damage. Immunohistochemistry localized ICAM5 and MMP7 in sJIA-PAP lung. ICAM5s ability to distinguish sJIA-PAP from sJIA/MAS was independently validated.

ConclusionsSerum proteins support an sJIA-to-MAS continuum, help distinguish sJIA, sJIA/MAS, and sJIA-PAP, and suggest etiologic hypotheses. Select biomarkers, such as ICAM5, could aid in early detection and management of sJIA-PAP.