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).
Decreased Diastolic Hydraulic Forces Incrementally Associate With Survival Beyond Conventional Measures of Diastolic Dysfunction AIMSDecreased hydraulic forces during diastole contribute to reduced left ventricular (LV) filling and heart failure with preserved ejection fraction. However, their association with diastolic function and patient outcomes are unknown. The aim of this study was to determine the association between diastolic hydraulic forces, estimated by echocardiography as the atrioventricular area difference (AVAD), and both diastolic function and survival.

METHODS AND RESULTSPatients (n=11,734, median [interquartile range] 3.9 [2.4-5.0] years follow-up, 1,213 events) were selected from the National Echo Database Australia based on the presence of relevant transthoracic echocardiographic measures, LV ejection fraction (LVEF) [&ge;]50%, heart rate 50-100 beats/minute, the absence of moderate or severe valvular disease, and no prior cardiac surgery. AVAD was calculated as the cross-sectional area difference between the LV and left atrium. LV diastolic dysfunction was graded according to 2016 guidelines. AVAD was weakly associated with E/e, left atrial volume index, and LVEF (multivariable global R2=0.15, p<0.001), and not associated with e and peak tricuspid regurgitation velocity. Decreased AVAD was independently associated with poorer survival, and demonstrated improved model discrimination after adjustment for diastolic function grading (C-statistic [95% confidence interval] 0.645 [0.629-0.662] vs 0.607 [0.592-0.623], p<0.001) and E/e (0.639 [0.623-0.655] vs 0.621 [0.604-0.637], p<0.001), respectively.

CONCLUSIONDecreased hydraulic forces, estimated by AVAD, are weakly associated with diastolic dysfunction and demonstrate an incremental prognostic association with survival beyond conventional measures used to grade diastolic dysfunction.
Estimating the impact of Angelman syndrome on parental productivity in Australia using productivity-adjusted life years Angelman syndrome (AS) is a severe neurodevelopmental condition associated with a significant socioeconomic impact. This is the first study to estimate the impact of AS on parental productivity in Australia using cost-of-illness modelling with simulated follow-up over a 10-year period using 2019 as the baseline year. Key data were obtained from a prospective cohort of AS families, peer-reviewed literature, and publicly-available sources. The base-case productivity burden borne by the estimated 330 living parents of the 428 prevalent-persons with AS totalled AUD$1.25 million, corresponding to a loss of 38.42% of PALYs per-parent. This shows that caring for a child with AS has a significant impact on the productivity of affected parents, with a large associated impact on the broader Australian economy. COVID-19 Acceleration and Vaccine Status in France - Summer 2021 ObjectivesThis note provides an assessment of COVID-19 acceleration among groups with different vaccine status in France.

MethodsWe assess viral acceleration using a novel indicator introduced in Baunez et al. (2021). The acceleration index relates the percentage change of tests that have been performed on a given day to the percentage change in the associated positive cases that same day. We compare viral acceleration among vaccinated and unvaccinated individuals in France over the period May 31st - August 29, 2021.

ResultsOnce the state of the epidemic within each groups is accounted for, it turns out that viral acceleration has since mid-July converged to similar levels among vaccinated and unvaccinated individuals in France, even though viral speed is larger for the latter group compared to the former.

ConclusionOur results call for an increasing testing effort for both vaccinated and unvaccinated individuals, in view of the fact that viral circulation is currently accelerating at similar levels for both groups in France. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

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

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

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. 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. 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 Using controlled interrupted time series to estimate the population-level effects of Ontario's recently implemented overdose prevention sites and consumption and treatment services BackgroundOntario recently implemented overdose prevention sites and consumption and treatment services (OPS/CTS) to stem the harms of the opioid epidemic. We tested whether operating any site improved local opioid-related health service use and mortality rates.

MethodsWe used monthly counts of all opioid-related emergency department (ED) visits, hospitalizations, and deaths between January 2014 and December 2020 for our outcomes. For each public health unit (PHU) that implemented any OPS/CTS, we created a synthetic control as a weighted combination of unexposed PHU. We estimated the population-level effects of operating any site using controlled interrupted time series with segmented regression and adjusted for time varying confounders (i.e. OPS/CTS capacity, naloxone kits distributed, and persons receiving opioid agonist treatment per 100,000 population). We repeated the analysis using a multiple baseline approach to estimate province-wide effects.

ResultsBetween 2017 and 2020, nine out of 34 PHU implemented at least one OPS/CTS. ED visit (RR=0.96, 95%CI: 0.92 - 0.99) and hospitalization (RR=0.95, 95%CI: 0.92 - 0.98) trends declined faster among treated units. Improvements in local ED visit rate trends were observed for the majority of treated units. Hospitalization rates declined faster for London (RR=0.97, 95%CI: 0.95 - 0.99) and Niagara (RR=0.95, 95%CI: 0.92 - 0.98); while mortality rates declined faster for Hamilton (RR=0.93, 95%CI: 0.90 - 0.96), Niagara (RR=0.97, 95%CI: 0.94 - 0.99) and Guelph (RR=0.94, 95%CI: 0.88 - 1.00).

ConclusionAlthough OPS/CTS are not sufficient to stem the harms of the opioid overdose epidemic on their own, they play a critical role in local harm reduction strategies. SARS-CoV-2 Acquisition and Immune Pathogenesis Among School-Aged Learners in Four Diverse Schools BackgroundUnderstanding SARS-CoV-2 infection in children is necessary to reopen schools safely.

MethodsWe measured SARS-CoV-2 infection in 320 learners [10.5 {+/-} 2.1(sd); 7-17 y.o.] at four diverse schools with either remote or on-site learning. Schools A and B served low-income Hispanic learners; school C served many special-needs learners; and all provided predominantly remote instruction. School D served middle- and upper-income learners, with predominantly on-site instruction. Testing occurred in the fall (2020), and 6-8 weeks later during the fall-winter surge (notable for a tenfold increase in COVID-19 cases). Immune responses and mitigation fidelity were also measured.

ResultsWe found SARS-CoV-2 infections in 17 learners only during the surge. School A (97% remote learners) had the highest infection (10/70, 14.3%, p<0.01) and IgG positivity rates (13/66, 19.7%). School D (93% on-site learners) had the lowest infection and IgG positivity rates (1/63, 1.6%). Mitigation compliance [physical distancing (mean 87.4%) and face covering (91.3%)] was remarkably high at all schools. Documented SARS-CoV-2-infected learners had neutralizing antibodies (94.7%), robust IFN-{gamma}+ T cell responses, and reduced monocytes.

ConclusionSchools can implement successful mitigation strategies across a wide range of student diversity. Despite asymptomatic to mild SARS-CoV-2 infection, children generate robust humoral and cellular immune responses.

Key PointsO_LISuccessful COVID-19 mitigation was implemented across a diverse range of schools.
C_LIO_LISchool-associated SARS-CoV-2 infections reflect regional rates rather than remote or on-site learning.
C_LIO_LISeropositive school-aged children with asymptomatic to mild SARS-CoV-2 infections generate robust humoral and cellular immunity.
C_LI The effect of stimulus duration on preferences for gain adjustments when listening to speech ObjectivesIn the personalisation of hearing aid fittings, gain is often adjusted to suit patient preferences using live speech. When using brief sentences as stimuli, the minimum gain adjustments necessary to elicit consistent preferences ( preference thresholds) were previously found to be much greater than typical adjustments in current practice. The current study examined the role of duration on preference thresholds.

DesignParticipants heard 2, 4 and 6-s segments of a continuous monologue presented successively in pairs. The first segment of each pair was presented at each individuals real-ear or prescribed gain. The second segment was presented with a {+/-}0-12 dB gain adjustment in one of three frequency bands. Participants judged whether the second was "better", "worse" or "no different" from the first.

Study SampleTwenty-nine adults, all with hearing-aid experience.

ResultsThe minimum gain adjustments needed to elicit "better" or "worse" judgments decreased with increasing duration for most adjustments. Inter-participant agreement and intra-participant reliability increased with increasing duration up to 4 s, then remained stable.

ConclusionsProviding longer stimuli improves the likelihood of patients providing reliable judgments of hearing-aid gain adjustments, but the effect is limited, and alternative fitting methods may be more viable for effective hearing-aid personalisation. A Randomised Trial of a Wearable UV dosimeter for Skin Cancer Prevention BackgroundNon-melanoma skin cancer (NMSC) is the most prevalent cancer in the United States, affecting 5 million people and costing $8.1 billion per year. Despite well-defined guidelines on ultraviolet radiation (UVR) avoidance, it remains difficult for people to assess their individual exposure, as UVR is invisible and the onset of symptoms due to UVR damage are delayed.

MethodsIn a prospective, randomized-controlled trial, 97 patients with a history of actinic keratoses were enrolled from March 2018 to July 2018 and followed over 6 months. 50 patients were given a wearable device that measured UV exposure and a smartphone application that provided both real-time and cumulative UV exposure information, and 47 patients were provided with UV protection counseling by a dermatologist.

ResultsWe observed a significant decrease in the incidence rate of NMSC in the intervention group compared to the control group over 3 months (p = 0.02). We did not observe a significant decrease in the incidence rate of actinic keratoses (AK) in the intervention group compared to the control group. The observed clinical benefit was not accompanied by psychological side effects such as anxiety and depression.

ConclusionsThis study suggests that providing real-time UV exposure data using a wearable UV dosimeter is a safe and effective behavioral change strategy to prevent NMSC. (Funded by the National Cancer Institute, contract HHSN261201700005C; ClinicalTrials.gov number NCT03315286.) 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. "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

MethodsA realist-informed qualitative study was conducted with unattached patients in Nova Scotia, Canada. Semi-structured interviews with nine participants were conducted and transcribed for analysis. The framework method was used to carry out analysis, which was guided by Donabedians model of assessing healthcare access and quality.

ResultsFive key findings were noted in this study: 1) Participants experienced a range of consequences from not having a regular PHC provider. Participants used creative strategies to 2) attempt to gain attachment to a regular PHC provider, and, to 3) address their health needs in the absence of a regular PHC provider. 4) Participants experienced negative feelings about themselves and the healthcare system, and 5) stress related to the consequences and added work of being unattached and lost care.

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need. Reports of myocarditis and pericarditis following mRNA COVID-19 vaccines: A systematic review of spontaneously reported data from the UK, Europe, and the US and of the literature ObjectivesTo bring together spontaneously reported data from around the world to estimate the reporting rate in different countries and better understand the risk factors for myocarditis and pericarditis following exposure to COVID-19 mRNA vaccines.

DesignSystematic review of the literature and systematic review of spontaneously reported data from the United Kingdom (UK), United States (US), and European Union/European Economic Area (EU/EEA).

Data sourcesSpontaneously reported data for COVID-19 Vaccine Pfizer/BioNTech (Comirnaty) and COVID-19 Vaccine Moderna (Spikevax) were obtained using outputs from the UKs Yellow Card scheme (covering the period 09/12/2020 - 20/10/2021), the Vaccine Adverse Event Reporting System (VAERS; US; covering the period 23/08/2021 - 21/10/2021), and EudraVigilance (EU/EEA; covering the period 21/12/2020 - 21/10/2021). Systematic searches of PubMed and Embase literature databases were performed with a datalock point of 11 October 2021.

Eligibility criteriaAll publicly available spontaneous reporting data from the three regions of interest were included. Data on events labelled "Myocarditis" and "Pericarditis" were included. No restrictions on age or gender were applied. For the systematic literature review, all pharmacoepidemiological studies of observational design investigating myocarditis and pericarditis following mRNA COVID-19 vaccines identified by our search were included. No restrictions on language or date were applied. Pre-print manuscripts were included if no peer-reviewed version was available. Studies of non-observational design, case reports, and case series were excluded. Study quality was assessed using relevant Critical Appraisal Skills Programme (CASP) tools. All studies were considered of sufficient quality for inclusion.

Data extraction and synthesisOne researcher extracted data from spontaneous reporting systems and published pharmacoepidemiological studies. Spontaneously reported events of myocarditis and pericarditis were presented for each individual data source, and stratified by vaccine, age, sex, and dose where this information was available. Vaccination data were obtained to the same date, and reporting rates were calculated for the events of myocarditis and pericarditis for each population of interest. For published pharmacoepidemiological studies, the study design, participant characteristics, and study results were tabulated.

ResultsOverall, there were 435 reports of myocarditis and 327 reports of pericarditis reported to the UKs Yellow Card scheme up to 20 October 2021. To 21 October 2021, in the US, 1936 reports of myocarditis and 1271 reports of pericarditis had been submitted to VAERS; there had been 2924 reports of myocarditis and 1855 reports of pericarditis submitted to EudraVigilance to the same date. Most reports (73.3%) had been submitted following Comirnaty (Pfizer/BioNTech). Males represented 74.9% of reports of myocarditis and 56.9% of pericarditis overall (for US and EU/EEA populations only), and the majority of reports concerned vaccinees ages under 40 years. Reports were more frequent following the second dose of mRNA COVID-19 vaccine. Reporting rates of myocarditis and pericarditis were consistent between the data sources. Seven pharmacoepidemiological studies were included; results of these studies were largely consistent with results of our spontaneous report analyses.

ConclusionsThis study provides evidence that younger vaccinees more frequently report myocarditis and pericarditis following mRNA COVID-19 vaccines compared with older vaccinees. These events had mild clinical course followed by full recovery in most cases. Results from published literature supported the results of our analyses.

Strengths and Limitations of the StudyO_LIThis is the first study to bring together spontaneously reported data from the United Kingdom, United States, and Europe on myocarditis and pericarditis following mRNA COVID-19 vaccines.
C_LIO_LIResults from this study provide evidence on the frequency of reported events of myocarditis and pericarditis following mRNA vaccines in different age groups, and by sex and vaccine dose. Analyses of spontaneous reports were consolidated with results of published literature, identified by systematic review.
C_LIO_LIResults may have been influenced by biases including different vaccination policies in each region examined, and publicity on events of myocarditis and pericarditis following mRNA vaccines.
C_LIO_LIThe study relied on outputs from spontaneous reporting systems in which the level of detail differed between the systems examined; furthermore, it is not possible to estimate incidence rates using spontaneous reports due to the lack of data on the exposed population, and there is no unvaccinated comparison group.
C_LIO_LIThere is an urgent need for further pharmacoepidemiological studies to be conducted to provide more accurate estimates of the frequency, clinical course, long term outcome, effects of treatment and impact on quality of life, to address many of the limitations of spontaneous reporting.
C_LI SARS-CoV-2 testing strategies to contain school-associated transmission: model-based analysis of impact and cost of diagnostic testing, screening, and surveillance BackgroundIn March 2021, the Biden administration allocated $10 billion for COVID-19 testing in schools. We evaluate the costs and benefits of testing strategies to reduce the infection risks of full-time in-person K-8 education at different levels of community incidence.

MethodsWe used an agent-based network model to simulate transmission in elementary and middle school communities, parameterized to a US school structure and assuming dominance of the delta COVID-19 variant. We assess the value of different strategies for testing students and faculty/staff, including expanded diagnostic testing ("test to stay" policies that take the place of isolation for symptomatic students or quarantine for exposed classrooms); screening (routinely testing asymptomatic individuals to identify infections and contain transmission); and surveillance (testing a random sample of students to signaling undetected transmission and trigger additional investigation or interventions).

Main outcome measuresWe project 30-day cumulative incidence of SARS-CoV-2 infection; proportion of cases detected; proportion of planned and unplanned days out of school; and the cost of testing programs and of childcare costs associated with different strategies. For screening policies, we further estimate cost per SARS-CoV-2 infection averted in students and staff, and for surveillance, probability of correctly or falsely triggering an outbreak response at different incidence and attack rates.

ResultsAccounting for programmatic and childcare costs, "test to stay" policies achieve similar model-projected transmission to quarantine policies, with reduced overall costs. Weekly universal screening prevents approximately 50% of in-school transmission, with a lower projected societal cost than hybrid or remote schooling. The cost per infection averted in students and staff by weekly screening is lower for older students and schools with higher mitigation and declines as community transmission rises. In settings where local student incidence is unknown or rapidly changing, surveillance may trigger detection of moderate-to-large in-school outbreaks with fewer resources compared to screening.

Conclusions"Test to stay" policies and/or screening tests can facilitate consistent in-person school attendance with low transmission risk across a range of community incidence. Surveillance may be a useful reduced-cost option for detecting outbreaks and identifying school environments that may benefit from increased mitigation. I wanna live and not think about the future; What place for advance care planning for people living with severe multiple sclerosis and their families? A qualitative study BackgroundLittle is known about how people with multiple sclerosis and their families comprehend advance care planning (ACP) and its relevance in their lives.

AimTo explore under what situations, with whom, how, and why do people with MS and their families engage in ACP

MethodsWe conducted a qualitative study comprising interviews with people living with MS and their families followed by an ethical discussion group with five health professionals representing specialties working with people affected by MS and their families. Twenty-seven people with MS and 17 family members were interviewed between June 2019 and March 2020. Interviews and the ethical discussion group were audio-recorded and transcribed verbatim. Data were analysed using the framework approach.

ResultsParticipants narratives focused on three major themes :(i) planning for an uncertain future; (ii) perceived obstacles to engaging in ACP that included uncertainty concerning MS disease progression, negative previous experiences of ACP discussions and prioritising symptom management over future planning; (iii) Preferences for engagement in ACP included a trusting relationship with a health professional and that information then be shared across services. Health professionals accounts from the ethical discussion group departed from viewing ACP as a formal document to that of an ongoing process of seeking preferences and values. They voiced similar concerns to people with MS about uncertainty and when to initiate discussions. Some shared concerns of a lack of confidence when having ACP discussions.

ConclusionThese findings support the need for a whole systems strategic approach where information about the potential benefits of ACP in all its forms can be shared with people with MS. Moreover, they highlight the need for health professionals to be skilled and trained in engaging in ACP discussions and where information is contemporaneously and seamlessly shared across services. Mutation burden-orthogonal tumor genomic subtypes delineate responses to immune checkpoint therapy Higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types. Systematic mutational signature analysis on all solid tumors in The Cancer Genome Atlas yielded eight distinct tumor genomic subtypes, which were characterized by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were construed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. Under this hypothesis, we developed a software to classify new tumors submitted to whole-exome sequencing. A pan-cancer dataset containing 973 cases treated with ICIs and clinical response was used for validation, where the classified tumor subtypes were significantly associated with ICI response, independent of cancer type and tumor mutational burden high or low status. The new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

Structured abstractO_ST_ABSBackgroundC_ST_ABSIn cancer therapy, higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types.

MethodsBased on mutational signature analysis, we developed a stratification for all solid tumors in The Cancer Genome Atlas (TCGA). Subsequently, we developed a new software (GS-PRACTICE) to classify new tumors submitted to whole-exome sequencing. Using existing data from 973 pan-cancer ICI-treated cases with outcomes, we evaluated the subtype-response predictive performance.

ResultsSystematic analysis on TCGA samples identified eight tumor genomic subtypes, which were characterized by features represented by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were presumed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. In the validation cohort, the samples assigned by GS-PRACTICE to the immune-reactive subtypes were significantly associated with ICI response independent of cancer type and TMB high or low status.

ConclusionsThe new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

One Sentence SummaryA novel tumor genome subtyping method based on mutation signature analysis can predict response to immune checkpoint therapy orthogonally to tumor mutational burden. A Hybrid Machine Learning Framework for Enhancing the Prediction Power in Large Scale Population Studies: The ATHLOS Project The ATHLOS cohort is composed of several harmonized datasets of international cohorts related to health and aging. The healthy aging scale has been constructed based on a selection of particular variables from 16 individual studies. In this paper, we consider a selection of additional variables found in ATHLOS and investigate their utilization for predicting the healthy aging. For this purpose motivated by the datasets volume and diversity we focus our attention upon the clustering for prediction scheme, where unsupervised learning is utilized to enhance prediction power, showing the predictive utility of exploiting structure in the data by clustering. We show that imposed computation bottlenecks can be surpassed when using appropriate hierarchical clustering within a clustering for ensemble classification scheme while retaining prediction benefits. We propose a complete methodology which is evaluated against baseline methods and the original concept. The results are very encouraging suggesting further developments in this direction along with applications in tasks with similar characteristics. A strait-forward open source implementation is provided for the R project. The Preventive Treatment of Migraine with Low-Dose Naltrexone/Acetaminophen Combination: Findings of a Small, Randomized, Double-Blind, and Placebo-Controlled Clinical Trial with an Open-Label Extension for None-Responders We tested a low-dose naltrexone and acetaminophen combination for episodic migraine prevention. We randomly assigned patients to naltrexone and acetaminophen combination (n=6) or placebo (n=6) for a 12-week double-blind treatment. Non-responders continued into open-label treatment with naltrexone and acetaminophen combination (n=5) for additional 12 weeks. Patients were adults who experienced 5 to 17 (average 9.7) migraine days at baseline. The primary endpoint was the mean change in the monthly migraine days during the last 4 weeks of the double-blind treatment period. The key secondary endpoint was the mean change in the monthly migraine days from the 4-week double-blind follow-up (2nd baseline) to the last 4 weeks of the open-label treatment period.

The magnitude of the treatment effect for the naltrexone and acetaminophen combination observed in the double-blind period was 2.2 fewer monthly migraine days than placebo (p=0.43). Four out of 6 (66.7%) naltrexone and acetaminophen-treated patients experienced 75% reduction in migraine days compared to 1 out of 6 (16.7%) placebo-treated patients (p=0.09).

In the open-label phase, treatment with the naltrexone and acetaminophen combination (n=5) led to 8.2 fewer mean monthly migraine days (from 11.8 to 3.6), representing 69.5% improvement (p=0.03), and 100% of the patients experienced a 50% reduction in monthly migraine days. Adverse events were mild to moderate and transient, included dry mouth, fatigue, sedation, nausea, and feeling jittery.

We postulate that naltrexones toll-like receptor (TLR4) antagonism properties prevent pro-inflammatory cytokines production in the trigeminal ganglion averting "overactive nerves" (laymans term) and migraine. Although this trial used low-dose naltrexone (defined as 1 - 5 mg/day), in future phase 3 studies we will test a range of naltrexone and acetaminophen combination doses. Trajectory of Growth of SARS-CoV-2 Variants in Houston, Texas, January through May 2021 Based on 12,476 Genome Sequences Genetic variants of the SARS-CoV-2 virus are of substantial concern because they can detrimentally alter the pandemic course and disease features in individual patients. Here we report SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist healthcare system diagnosed from January 1, 2021 through May 31, 2021. The SARS-CoV-2 variant designated U.K. B.1.1.7 increased rapidly and caused 63%-90% of all new cases in the Houston area in the latter half of May. Eleven of the 3,276 B.1.1.7 genomes had an E484K change in spike protein. Compared with non-B.1.1.7 patients, individuals with B.1.1.7 had a significantly lower cycle threshold value (a proxy for higher virus load) and significantly higher rate of hospitalization. Other variants (e.g., B.1.429, B.1.427, P.1, P.2, and R.1) also increased rapidly, although the magnitude was less than for B.1.1.7. We identified 22 patients infected with B.1.617 "India" variants; these patients had a high rate of hospitalization. Vaccine breakthrough cases (n=207) were caused by a heterogeneous array of virus genotypes, including many that are not variants of interest or concern. In the aggregate, our study delineates the trajectory of concerning SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, and heralds the arrival and spread of B.1.617 variants in the metroplex. Dental biofilm microbiota dysbiosis is associated with the risk of acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation Acute graft-versus-host disease (aGVHD) is one of the major causes of death after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Recently, aGVHD onset was linked to intestinal microbiota (IM) dysbiosis. However, other bacterial-rich gastrointestinal sites, such as the mouth, which hosts several distinctive microbiotas, may also impact the risk of GVHD. The dental biofilm microbiota (DBM) is highly diverse and, like the IM, interacts with host cells and modulates immune homeostasis. We characterized changes in the DBM of patients during allo-HSCT and evaluated whether the DBM could be associated with the risk of aGVHD. DBM dysbiosis during allo-HSCT was marked by a gradual loss of bacterial diversity and changes in DBM genera composition, with commensal genera reductions and potentially pathogenic bacteria overgrowths. High Streptococcus and high Corynebacterium relative abundance at preconditioning were associated with a higher risk of aGVHD (67% vs. 33%; HR = 2.89, P = 0.04 and 73% vs. 37%; HR = 2.74, P = 0.04, respectively), while high Veillonella relative abundance was associated with a lower risk of aGVHD (27% vs. 73%; HR = 0.24, P < 0.01). Enterococcus faecalis bloom during allo-HSCT was observed in 20% of allo-HSCT recipients and was associated with a higher risk of aGVHD (100% vs. 40%; HR = 4.07, P < 0.001) and severe aGVHD (60% vs. 12%; HR = 6.82, P = 0.01). To the best of our knowledge, this is the first study demonstrating that DBM dysbiosis is associated with the aGVHD risk after allo-HSCT. Prevalence of vitamin D is not associated with the COVID-19 epidemic in Europe. A critical update of the existing evidence. BackgroundCOVID-19 has emerged as a global pandemic, affecting nearly 104 million people worldwide as of February 4th 2021. In previous published studies, the association between the mean Vit D status of each country and COVID-19 infection rate, and mortality among the adult population in European countries was examined. The aim of this study was to re-examine the relationship between the Vit D status of each country and COVID-19 infection, recovery, and mortality using updated data and a different methodological approach.

MethodsInformation only form the last decade on Vit D concentration/deficiency for each country was retrieved through literature search on PubMed(R) database. As of February, 4th 2021, COVID-19 infections and mortalities per one million population as well as total recoveries were extracted from the Worldometer website. The association between vitamin D deficiency and COVID-19 infection, recovery, and mortality were explored using correlation coefficients and scatterplots.

FindingsThe prevalence of vitamin D deficiency among European countries ranged from 6.0 (Finland) to 75.5% (Turkey), with several countries facing more than 50% of vitamin D deficiency among their population. Non-significant correlations were observed between the number of COVID-19 infections (r=0.190; p=0.374), recoveries (rs=0.317, p=0.131), and mortalities (r=0.129; p=0.549) per one million population, with the prevalence of vitamin D deficiency.

InterpretationPrevalence of vitamin D deficiency was not significantly associated with either number of infections, recoveries or mortality rate of COVID-19 among European countries. Thus, it is an important parameter to be considered when implementing preventive measures to face COVID-19.

FundingNone Early prediction of preeclampsia in pregnancy with circulating cell-free RNA Liquid biopsies that measure circulating cell-free RNA (cfRNA) offer an unprecedented opportunity to noninvasively study the development of pregnancy-related complications and to bridge gaps in clinical care. Here, we used 404 blood samples from 199 pregnant mothers to identify and validate cfRNA transcriptomic changes that are associated with preeclampsia (PE), a multi-organ syndrome which is the second largest cause of maternal death globally. We find that changes in cfRNA gene expression between normotensive (NT) and preeclamptic mothers are striking and stable early in gestation, well before the onset of symptoms. These changes are enriched for genes specific to neuromuscular, endothelial, and immune cell types and tissues that reflect important aspects of PE physiology and suggest new hypotheses for disease progression. This enabled identification and independent validation of a panel of 18 genes whose measurement between 5-16 weeks of gestation can form the basis of a liquid biopsy test that would identify mothers at risk of PE well before the clinical symptoms manifest themselves. Finally, we demonstrate that cfRNA changes reflect the multifactorial nature of PE and provide a means to non-invasively monitor maternal organ health. Tests based on these observations could help predict and manage who is at risk for PE, an important and until now unachieved objective for obstetric care. Genetic factors affecting immune phenotypes in type 1 diabetes Large inter-individual variability in immunological cell composition and function determines immune responses in general and susceptibility to immune-mediated diseases in particular. While much has been learned about the genetic variants relevant for type 1 diabetes, the pathophysiological mechanisms through which these variations exert their effects are unknown. In this study, we characterize the genetic factors influencing immune responses in patients with type 1 diabetes. Genetic variants that determine susceptibility to T1D significantly affect T cell composition. Specifically, the CCR5+ regulatory T cells associate with T1D through the CCR region, suggesting a shared genetic regulation. Genome-wide quantitative trait loci (QTL) mapping analysis of immune traits revealed 15 genetic loci that influence immune responses in T1D. Among them, 12 have never been reported in healthy population studies, implying a disease-specific genetic regulation. Altogether this study provides new insights into the genetic factors that affect immunological responses in T1D.