A systematic review of enteric pathogens and antibiotic resistance genes in outdoor urban aerosols Aerosol transport of enteric microbiota including fecal pathogens and antimicrobial resistance genes (ARGs) has been documented in a range of settings but remains poorly understood outside indoor environments. We conducted a systematic review of the peer-reviewed literature to summarize evidence on specific enteric microbiota including enteric pathogens and ARGs that have been measured in aerosol samples in urban settings where the risks of outdoor exposure and antibiotic resistance (AR) spread may be highest. Following PRISMA guidelines, we conducted a key word search for articles published within the years 1990-2020 using relevant data sources. Two authors independently conducted the keyword searches of databases and conducted primary and secondary screenings before merging results. To be included, studies contained extractable data on enteric microbes and AR in outdoor aerosols regardless of source confirmation and reported on qualitative, quantitative, or viability data on enteric microbes or AR. Qualitative analyses and metric summaries revealed that enteric microbes and AR have been consistently reported in outdoor aerosols, generally via relative abundance measures, though gaps remain preventing full understanding of the role of the aeromicrobiological pathway in the fate and transport of enteric associated outdoor aerosols. We identified remaining gaps in the evidence base including a need for broad characterization of enteric pathogens in bioaerosols beyond bacterial genera, a need for greater sampling in locations of high enteric disease risk, and a need for quantitative estimation of microbial and nucleic acid densities that may be applied to fate and transport models and in quantitative microbial risk assessment.

FUNDINGThis study was funded by the National Science Foundation under grant number 1653226. This funding source had no role in the design of this study and had no role during its execution, analyses, interpretation of the data, or decision to submit results.
Cohort profile: Actionable Register of Geneva Out- and inpatients with SARS-CoV-2 (ARGOS) PurposeThe Actionable Register of Geneva Out- and inpatients with SARS-CoV-2 (ARGOS) is an ongoing prospective cohort created by the Geneva Directorate of Health (GDH). It consists of an operational database compiling all SARS-CoV-2 test results conducted in the Geneva area since late February 2020. This article aims at presenting this comprehensive cohort, in light of some of the varying public health measures in Geneva, Switzerland, since March 2020.

ParticipantsAs of June 1st, 2021, the database included 356868 patients, among which 65475 had at least one positive test result for SARS-CoV-2. Among all positive patients, 37.6% were contacted only once, 10.6 % had one follow-up call, 8.5% had two, and 27.7% had 3 or more follow-up calls. Participation rate among positive patients is 94%. Data collection is ongoing.

Findings to dateARGOS data illustrates the magnitude of COVID-19 pandemic in Geneva, Switzerland, and details a variety of population factors and outcomes. The content of the cohort includes demographic data, comorbidities and risk factors for poor clinical outcome, self-reported COVID-19 symptoms, environmental and socio-economic factors, prospective and retrospective contact tracing data, travel quarantine data, and deaths. The registry has already been used in several publications focusing on symptoms and long COVID, infection fatality rate, and re-infection.

Future plansThe data of this large real-world registry provides a valuable resource for various types of research, such as clinical research, epidemiological research or policy assessment as it illustrates the impact of public health policies and overall disease burden of COVID-19.

STRENGTHS AND LIMITATIONS OF THIS STUDYO_LIARGOS main strength consists of its large number of cases, representative of all diagnosed cases on a regional level with the primary aim of assessing all cases.
C_LIO_LIARGOS involves every individual who performed a SARS-CoV-2 test (PCR or antigenic) and is not limited to hospitalized patients, thus providing a valuable resource to assess the overall disease burden of COVID-19 in a geographically defined population.
C_LIO_LITo mitigate confounding effects and improve data analysis and interpretation, we present the data according to four policy periods.
C_LIO_LIThis cohort is multicentric as it includes all tests performed in Genevas hospitals (both public and private), private practices and medical centers.
C_LIO_LIDue to operational needs, symptoms and comorbidities are self-reported, which may lead to measurement error or misclassification.
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 The lost microbes of COVID-19: Bifidobacteria depletion and decreased microbiome diversity are a predictability marker of severe COVID 19, a cross sectional study ObjectiveThe study objective was to compare gut microbiome diversity and composition in SARS-CoV-2 polymerase chain reaction (PCR)-positive patients whose symptoms ranged from asymptomatic to severe, versus PCR-negative exposed controls.

DesignUsing a cross-sectional design, we performed shotgun next-generation sequencing (NGS) on stool samples to evaluate gut microbiome composition and diversity in both patients with SARS-CoV-2 PCR- confirmed infections, that had presented to Ventura Clinical Trials for care from March 2020 through October 2021, and SARS-CoV-2 PCR-negative exposed controls. Patients were classified as being asymptomatic or having mild, moderate, or severe symptoms based on NIH criteria. Exposed controls were individuals with prolonged or repeated close contact with patients with SARS-CoV-2 infection or their samples, e.g. household members of patients or frontline healthcare workers. Microbiome diversity and composition were compared between patients and exposed controls at all taxonomic levels.

ResultsCompared with controls (n=20), severely symptomatic SARS-CoV-2 infected patients (n=28) had significantly less bacterial diversity (Shannon Index, P=0.0499; Simpson Index, P=0.0581), and positive patients overall had lower relative abundances of Bifidobacterium (P<0.0001), Faecalibacterium (P=0.0077), and Roseburium (P=0.0327), while having increased Bacteroides (P=0.0075). Interestingly, there was an inverse association between disease severity and abundance of the same bacteria.

ConclusionWe hypothesize that low bacterial diversity and depletion of Bifidobacterium genera either before or after infection led to reduced pro-immune function, thereby allowing SARS-CoV-2 infection to become symptomatic. This particular dysbiosis pattern may be a susceptibility marker for symptomatic severity from SARS-CoV-2 infection and may be amenable to pre-, intra-, or post infection intervention.Keywords: SARS-CoV-2, COVID, Microbiome, Bifidobacterium, Faecalibacterium, Bacteriodes, Shannon Index, Simpson Index, Severity, Microbiota

Registrationclinicaltrials.gov NCT04031469 (PCR -) and 04359836 (PCR+)



O_TBL View this table:
org.highwire.dtl.DTLVardef@173dbe8org.highwire.dtl.DTLVardef@16a75b5org.highwire.dtl.DTLVardef@55d55eorg.highwire.dtl.DTLVardef@12b2302org.highwire.dtl.DTLVardef@107663d_HPS_FORMAT_FIGEXP  M_TBL C_TBL Best practices for multi-ancestry, meta-analytic transcriptome-wide association studies: lessons from the Global Biobank Meta-analysis Initiative SUMMARYThe Global Biobank Meta-analysis Initiative (GBMI), through its genetic and demographic diversity, provides a valuable opportunity to study population-wide and ancestry-specific genetic associations. However, with multiple ascertainment strategies and multi-ethnic study populations across biobanks, the GBMI provides a distinct set of challenges in implementing statistical genetics methods. Transcriptome-wide association studies (TWAS) are a popular tool to boost detection power for and provide biological context to genetic associations by integrating single nucleotide polymorphism to trait (SNP-trait) associations from genome-wide association studies (GWAS) with SNP-based predictive models of gene expression. TWAS presents unique challenges beyond GWAS, especially in a multi-biobank and meta-analytic setting like the GBMI. In this work, we present the GBMI TWAS pipeline, outlining practical considerations for ancestry and tissue specificity and meta-analytic strategies, as well as open challenges at every step of the framework. Our work provides a strong foundation for adding tissue-specific gene expression context to biobank-linked genetic association studies, allowing for ancestry-aware discovery to accelerate genomic medicine. CD19+IgD+CD27- naive B Cells as predictors of humoral response to COVID 19 mRNA vaccination in immunocompromised patients Immunocompromised patients are considered high-risk and prioritized for vaccination against COVID-19. We aimed to analyze B-cell subsets in these patients to identify potential predictors of humoral vaccination response. Patients (n=120) suffering from hematologic malignancies or other causes of immunodeficiency and healthy controls (n=79) received a full vaccination series with an mRNA vaccine. B-cell subsets were analyzed prior to vaccination. Two independent anti-SARS-CoV-2 immunoassays targeting the receptor-binding domain (RBD) or trimeric S protein (TSP) were performed three to four weeks after the second vaccination. Seroconversion occurred in 100% of healthy controls, in contrast to 67% (RBD) and 82% (TSP) of immunocompromised patients, while only 32% (RBD) and 22% (TSP) achieved antibody levels comparable to those of healthy controls. The number of circulating CD19+IgD+CD27- naive B cells was strongly associated with antibody levels ({rho}=0.761, P<0.001) and the only independent predictor for achieving antibody levels comparable to healthy controls (OR 1.07 per 10-{micro}l increase, 95%CI 1.02-1.12, P=0.009). Receiver operating characteristic analysis identified a cut-off at [&ge;]61 naive B cells per {micro}l to discriminate between patients with and without an optimal antibody response. Consequently, measuring naive B cells in immunocompromised hematologic patients could be useful in predicting their humoral vaccination response. Clinical impact of the rapid molecular detection of RSV and influenza A and B viruses in the emergency department IntroductionUsing respiratory viruses rapid diagnostic tests in the emergency room (ER) could allow a better and faster clinical management. Point-of-care PCR instruments provide now results in less than 30 minutes. The objective of this study was to assess the impact of the use of the cobas(R) Influenza A/B & RSV Assay for use on Roches cobas(R) Liat(R) instrument on the clinical management of ER patients.

MethodsPatients (adults and children) requiring admission or suffering from an underlying condition at risk of respiratory complication were prospectively recruited in the ER of four hospitals in the Brussels region. Physicians intentions regarding admission, isolation, antibiotic and antiviral use were collected before and after performing a cobas(R) Influenza A/B & RSV molecular test. Additionally, a comparison of the analytical performance of this test against antigen rapid tests and viral culture was performed as well as a time-to-result evaluation.

ResultsPCR yielded twice more positive results than antigen rapid diagnostic tests. It allowed a decrease in the overall need for isolation and treatment by limiting the isolation of negative patients and the antibiotic use for positive patients. Meanwhile, antiviral treatments better targeted patients with a positive influenza PCR.

ConclusionThe use of a rapid influenza and RSV molecular test improves the clinical management of patients admitted to the ER by providing a fast and reliable result. Their additional cost compared to antigen tests should be balanced with the benefit of their analytical performance, leading to efficient reductions in the need of isolation and antibiotic use. 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. Pathogenesis of Alzheimer's disease: Involvement of the Choroid Plexus Aging and Alzheimers disease (AD), a major age-related disorder, are both characterized by inflammatory changes in the cerebrospinal fluid (CSF). The origin and the mechanisms underlying these inflammatory changes, however, remain poorly understood. Here, we report that aging elicits inflammatory changes in the CSF that become accentuated uniquely in AD compared to other inflammatory and neurodegenerative disorders. We show that the choroid plexus (ChP), which produces CSF, gains a pro-inflammatory profile, exhibits perturbed metabolism and contributes to the CSF changes observed in AD. We then use MRI imaging to establish a correlation between cognitive decline and increased volume of significantly remodelled ChP in patients with AD, and provide clinical relevance to the identified ChP pathology. These findings collectively suggest that ChP, unable to resolve inflammatory insults efficiently over the lifetime, participates in the inflammation and the pathogenesis of AD. Classifying Radiology Abstracts with Deep Learning BackgroundThe Radiological Society of North America (RSNA) receives more than 8000 abstracts yearly for scientific presentations, scientific posters, and scientific papers. Each abstract is assigned manually one of 16 top-level categories (e.g. "Breast Imaging") for workflow purposes. Additionally, each abstract receives a grade from 1-10 based on a variety of subjective factors such as style and perceived writing quality. Using machine learning to automate, at least partially, the categorization of abstract submissions can result in saving many hours of manual labor.

MethodsA total of 45527 RSNA abstract submissions from 2014 through 2019 were ingested, tokenized, and pre-processed with a standard natural language programming protocol. A bag-of-words (BOW) model was used as a baseline to evaluate two more sophisticated models, convolutional neural networks and recurrent neural networks, and also evaluate an ensemble model featuring all three neural networks.

Resultsensemble model was able to achieve 73% testing accuracy for classifying the 16 top-level categories, outperforming all other models. The top model for classifying abstract grade was also an ensemble model, achieving a mean average error (MAE) of 1.01.

ConclusionWhile the baseline BOW model was the highest performing individual classifier, ensemble models that included state-of-the-art neural networks were able to outperform it. Our research shows that machine learning techniques can, to a reasonable degree of accuracy, predict both objective factors such as abstract category as well as subjective factors such as abstract grade. This work builds upon previous research involving using natural language processing on scientific abstracts to make useful inferences that address a meaningful problem. Alternative Covid-19 mitigation measures in school classrooms: analysis using an agent-based model of SARS-CoV-2 transmission 1.The SARS-CoV-2 epidemic continues to have major impacts on childrens education, with schools required to implement infection control measures that have led to long periods of absence and classroom closures. We have developed an agent-based epidemiological model of SARS-CoV-2 transmission that allows us to quantify projected infection patterns within primary school classrooms, and related uncertainties; the basis of our approach is a contact model constructed using random networks, informed by structured expert judgement. The effectiveness of mitigation strategies are considered in terms of effectiveness at supressing infection outbreaks and limiting pupil absence. Covid-19 infections in schools in the UK in Autumn 2020 are re-examined and the model used for forecasting infection levels in autumn 2021, as the more infectious Delta-variant was emerging and school transmission thought likely to play a major role in an incipient new wave of the epidemic. Our results were in good agreement with available data. These findings indicate that testing-based surveillance of infections in the classroom population with isolation of positive cases is a more effective mitigation measure than bubble quarantine, both for reducing transmission in primary schools and for avoiding pupil absence, even accounting for insensitivity of self-administered tests. Bubble quarantine entails large numbers of pupils being absent from school, with only modest impact on classroom infection levels. However, maintaining reduced contact rates within the classroom can have a major beneficial impact for managing Covid-19 in school settings. 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. Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods BackgroundPreventing in-hospital mortality in Patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.

ObjectivesThe objective of our research was to to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods.

MethodsWe divide non-randomly the American population with acute STEMI into a training set, a test set,and a validation set. We converted the unbalanced data into balanc ed data. We used artificial intelligence methods to develop and externally validate the dia gnostic model of in-hospital mortality in acute STEMI patients. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluat e the pros and cons of the above models.

ResultsThe strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation(AF), ventricular fibrillation(VF),third degree atrioventricular block,in-hospital bleeding, underwent percutaneous coronary intervention(PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history.The F2 score of logistic regression in the training set, the test set, and the validation data set were 0.81, 0.6, and 0.59 respectively.The AUC of logistic regression in the training set, the test set, and the validation data set were 0.77, 0.78, and 0.8 respectively. The diagnostic model built by logistic regression was the best.

ConclusionWe had used artificial intelligence methods developed and externally validated the diagnostic model of in-hospital mortality in acute STEMI patients.

We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). Survival and outcomes of tocilizumab use in severe and critically ill COVID-19 patients not responding to steroids BackgroundMortality and morbidity are highest in severe and critically ill patients with COVID -19 pneumonia. Recently corticosteroids have shown a definite mortality benefit in these patients. In this study we used interleukin -6 inhibitor, tocilizumab in patients who failed to show any clinical improvement after initial treatment with steroids.

Patients and methodsThis is a retrospective observational study conducted at a tertiary care referral hospital in India. Severe and critical COVID 19 patients, who got admitted to intensive care unit and subsequently received tocilizumab were included. Patients who worsened clinically or had no change in oxygen requirement even after 24hrs of receiving Intravenous methylprednisolone at a dose of 1-2mg/kg/day received a maximum total dose of 800mg of intravenous tocilizumab. The day 28 all cause mortality and progression to mechanical ventilation were the primary outcome measures. Clinical improvement and oxygen requirements after tocilizumab administration along with trends in inflammatory markers were secondary outcome. Secondary infections rates and other drug related side effects were also noted.

ResultsA total of 51 patients who did not show clinical improvement even after 24 hours of intravenous steroids and received tocilizumab were included. In these patients, there was a significant decrease in oxygen requirement by day 3 and clinical improvement by day 7 of tocilizumab administration. Among the inflammatory markers, we observed elevated median baseline values of CRP (114.2 mg/L), IL-6 (55.4 pg/ml) and Neutrophil to Lymphocyte Ratio (12.4). Out of these only CRP showed a significant decrease after the drug administration. 13 (26.5%) of the 49 patients who were on non-invasive or conventional oxygen support progressed to mechanical ventilation. The day 28 all-cause mortality rate was 10/51(19.6%). 10(19.6%) of the 51 patients had life threatening infections, 5/51 had thrombocytopenia, 3/51 had pneumo-mediastenum/pneumothorax, 1 patient had colonic perforation and 1 patient had transaminitis following tocilizumab administration.

ConclusionEarly and timely administration of tocilizumab only in selected severe and critical covid patients not responding to initial steroids appears to increase the survival. Further randomized controlled trials are required to confirm this finding. 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. Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes BackgroundIndividuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

MethodsUsing data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

FindingsThe model predicts the progression to diabetic kidney disease with accuracy: 0.96{+/-}0.25 and 0.96{+/-}0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75{+/-}0.14 and 0.79{+/-}0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

InterpretationWith further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

FundingThis study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Research in context

Evidence before this studyMicrovascular diabetes complications (DCs), such as diabetic kidney disease (DKD) and diabetic retinopathy (DR), lead to increased mortality, blindness, kidney failure and overall decreased quality of life in individuals with diabetes.

Added value of this studyWe have developed four algorithms based on traditional risk factors alone and risk factors with metabolomic and lipidomic data. Two accurately predicted the future progression in individuals with type 1 diabetes. The top predictors chosen by the algorithm were hemoglobin A1c, albuminuria and retinopathy status at baseline for diabetic retinopathy. The most promising models predicted future diabetic kidney disease in which albuminuria, eGFR, retinopathy status at baseline were complemented with a number of ketones and sugar derivatives.

Implications of all the available evidenceWith further validation in several cohorts, the prediction models presented here have the potential for early diagnosis of CKD in persons with diabetes, thus enabling appropriate decisions on the available therapies. It is envisaged that these algorithms will be trialed and support clinicians with precision diagnosis and treatments. Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study) 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. Why one size fits all is not enough when designing covid-19 immunity certificates for domestic use: a UK wide cross-sectional online survey ObjectivesThe present study explored publics willingness to use COVID-19 immunity certificates across six different domestic scenarios.

DesignCross-sectional online survey.

SettingUK representative survey conducted on the 3rd of August 2021.

Participants534 UK residents over 18 years old.

InterventionsParticipants replied to the same set of questions.

Primary and secondary outcome measuresThe primary outcome measure was willingness to use immunity certificates across three different domestic settings (1. Visiting the GP for a non-urgent health issue, 2. Dining in a restaurant, and 3. Attending a performance in a theatre). For each setting two options, one prioritising convenience (option A) and the other privacy (option B), were offered. Our secondary outcome measures were computed indices from items adapted from the Health Belief Model; Attitudes towards sharing immunity status with service providers; Prior to COVID-19 lifestyle. In addition, we recorded data about respondents socio-demographic characteristics.

ResultsRespondents were more willing to use immunity certificates that prioritised convenience, rather than privacy, when visiting their GP (92%). However, privacy was more favorable (84%) in the other two settings (dining in a restaurant and going to a theatre) compared to convenience (39%). Personal beliefs about COVID-19 and immunity certificates were associated with variations in willingness to use these across all scenarios. No variations were observed across socio-demographics and lifestyle.

ConclusionsThe findings of this survey suggest that there is not one size fits all solution for designing immunity certificates. Immunity certificates are complex socio-technical systems, any attempt to implement these for domestic use should be tailored to different settings and user needs. The design of certification services requires a more evidence-based approach and further research is needed to understand how different settings, design elements (like convenience or privacy) and personal beliefs about the pandemic should inform their design.

Strengths and limitations of this studyO_LIThis study presents unique knowledge about the publics willingness to use immunity certificates for domestic purposes where there is very little published research at the moment.
C_LIO_LIThe study reports knowledge about the interaction between individual characteristics, domestic settings, and types of immunity certificate design on willingness to use these certificates.
C_LIO_LIUK nationally representative sample for age, gender, and ethnic background, but limited to people who have the means and capacity to use digital technologies (survey administered using Prolific.co).
C_LIO_LIWe present evidence-based recommendations for Public Health services and policy makers about the use of immunity certificates in different domestic settings.
C_LIO_LISince, as to the writing of this paper, COVID-19 certification has not been mandated in the UK, the scenarios used in the survey were hypothetical.
C_LI 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/. The role of classroom volume, occupancy, voice reduction and ffp2 masks in transmission risk of SARS-CoV2 in schools 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. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Safety and efficacy of Pulmonary physiotherapy in hospitalized patients with severe COVID-19 pneumonia (PPTCOVID Study): A prospective, randomised, single-blind, controlled trial BackgroundPulmonary physiotherapy (PPT) is an important treatment in the management of patients with different types of pulmonary disorders. We aimed to evaluate safety and efficacy of PPT in hospitalized patients with severe COVID-19 pneumonia.

MethodsIn this randomised, single-blind, controlled trial, we enrolled hospitalized, non-intubated patients (18 to 75 years with oxygen saturation (Spo2) in free-air breathing [&le;]90%) with COVID-19 pneumonia at a referral hospital. Participants were randomly assigned (1:1) to receive PPT (six sessions PPT with breathing exercises and airway clearance techniques) or basic care. The primary outcomes were venous blood O2 (pO2) and CO2 (pCO2) pressures, Spo2, and three-minute walking test (3MWT) that were assessed before and end of sixth session. Secondary outcomes included level of dyspnea, venous blood PH, one-month mortality, three-month mortality and short form-36 (SF-36) after one and three months. The assessor was blinded to the assignment. This trial is registered with ClinicalTrials.gov (NCT04357340).

FindingsIn April-May 2020, 40 participants were randomly assigned to PPT or basic care groups. While at the end of intervention, pO2 (adjusted mean difference to baseline measure (AMD) 6.43 mmHg [95%CI 2.8, 10.07], P<0.01), Spo2 (AMD 4.43% [95%CI 2.04, 6.83], P=0.0011), and 3MTW (AMD 91.44 m [95%CI 68.88, 113.99], P<0.01) were higher in PPT group and basic care group, pCO2 was not improved (AMD -2.1 mmHg [95%CI-6.36, 2.21], P=0.33). Mortality rate was 20% (OR adjusted to baseline Spo2 .19 [95%CI .03, 1.30], P=.09) and 25% (OR adjusted to baseline Spo2 .16 [95%CI .26, 1.05], P=.056) lower in the PPT group at three-month at one-month and three-month, respectively. There were no significant differences in most SF-36 domains scores after one and three months. No serious adverse event was observed during PPT sessions.

ConclusionEarly PPT can be considered a safe and effective therapeutic choice for patients with severe COVID-19. Short Practical Regimen of Acupuncture for Melasma: A Prospective Cohort Study in a Tertiary Hospital in Thailand BackgroundMelasma is a common skin pigmentation disorder. Acupuncture shows benefits for patients with melasma, although no standardized method or optimal number of sessions have been determined.

ObjectiveTo comparatively assess clinical outcomes of melasma between five vs ten standard acupuncture sessions.

MethodsWe performed a prospective observational cohort study in all melasma patients at the Acupuncture Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. All patients were treated with standard acupuncture procedure twice a week and were evaluated after the fifth and the tenth sessions of acupuncture, with a follow-up one week after the last session. Participants were divided into two treatment groups: Groups A and B received five and ten acupuncture sessions respectively. Melasma outcomes were assessed by using the Melanin Index (MI), Melasma Area and Severity Index (MASI), patient-reported improvement scores and acupuncture-related adverse events.

ResultsOf 113 participants, 67 received five sessions of acupuncture treatment while 39 received ten sessions. 7 participants did not finish treatment. After five sessions of acupuncture in Group A, the mean MI decreased by 28.7 (95%CI -38.5 to -18.8), whereas the median MASI decreased by 3.4 (-6.9, -1.2) points. After ten sessions of acupuncture in Group B, the mean MI decreased by 31.3 (95%CI -45.0 to -17.6), whereas the median MASI decreased by 5.4 (-9.9, - 3.0) points. The first five sessions of acupuncture had a higher effect on the change in magnitude than the last five sessions, although there was no statistically significant difference. However, ten-session of acupuncture, had not reached the peak benefit on melasma yet. Further studies should be done with a higher number of sessions to determine the optimal rounds of treatment. Twenty-nine participants reported minor side effects, mostly consisting of persistent pain and small hematoma. Group B had RR of having adverse events 1.8 times (95% CI 1.0-3.4) compared to group A.

ConclusionAcupuncture has a potential dose-response effect on clinical and patient-reported melasma outcomes with minor side effects. mRNA COVID-19 vaccine booster fosters B and T cell responses in immunocompromised patients SARS-CoV-2 vaccination has proven effective in inducing an immune response in healthy individuals and is progressively allowing to overcome the pandemic. Recent evidence has shown that response to vaccination in some vulnerable patients may be diminished, and it has been proposed a booster dose. We tested the kinetic of development of serum antibodies to the SARS-CoV-2 Spike protein, their neutralizing capacity, the CD4 and CD8 IFN-{gamma} T cell response in 328 subjects, including 131 immunocompromised individuals (cancer, rheumatologic, and hemodialysis patients), 160 healthcare workers (HCW) and 37 subjects older than 75 yo, after vaccination with two or three doses of mRNA vaccines. We stratified the patients according to the type of treatment. We found that immunocompromised patients, depending on the type of treatment, poorly respond to SARS-CoV-2 mRNA vaccines. However, an additional booster dose of vaccine induced a good immune response in almost all of the patients except those receiving anti-CD20 antibody. Similarly to HCW, previously infected and vaccinated immunocompromised individuals demonstrate a stronger SARS-CoV-2 specific immune response than those who are vaccinated without prior infection.

Summary blurbImmunocompromised patients poorly respond to two doses of SARS-CoV-2 mRNA vaccines. However, an additional booster dose elicits a strong humoral and cellular immune response in these subjects.