Can individuals with low antibody responses to conventional antiviral vaccines acquire adequate antibody by the SARS-CoV-2 mRNA vaccine? ObjectiveIn Japan, healthcare workers (HCWs) are vaccinated against contagious viruses (measles, rubella, chickenpox, mumps, and hepatitis B) to prevent nosocomial infection; however, some do not produce sufficient antibodies (suboptimal responders). Whether suboptimal responders to live attenuated viruses or inactivated viruses vaccines can produce adequate antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines remains to be elucidated.

MethodsIn this prospective cohort study, SARS-CoV-2 anti-spike antibodies were measured 11 times, from before the first BNT162b2 vaccination to 5 months after the second vaccination. Antibody titers of suboptimal and normal responders were compared. SARS-CoV-2 neutralizing antibody activity was measured twice in suboptimal responders, 1 week to 1 month, and 5 months after the second vaccination.

PatientsThis study included 50 HCWs who received two doses of mRNA BNT162b2 vaccine 3 weeks apart.

ResultsAfter vaccination, the SARS-CoV-2 anti-spike antibody was detectable in the samples from suboptimal and normal responders at each timepoint. The median SARS-CoV-2 anti-spike antibody titer was higher in suboptimal responders than in normal responders 1 week after receiving the second dose of BNT162b2 vaccine (3721.0 vs. 2251.5, P=0.029). Suboptimal responders had SARS-CoV-2 neutralizing antibody activity 1 week to 1 month, and 5 months after the second vaccination, which exceeded the positive threshold 5 months after the second vaccination.

ConclusionAfter BNT162b2 vaccination, suboptimal responders acquired adequate SARS-CoV-2 anti-spike and SARS-CoV-2 neutralizing antibodies to prevent SARS-CoV-2. These results suggest that vaccination with mRNA vaccine against SARS-CoV-2 should also be recommended for suboptimal responders to conventional vaccines.
A scalable serology solution for profiling humoral immune responses to SARS-CoV-2 infection and vaccination OBJECTIVESAntibody testing against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been instrumental in detecting previous exposures and analyzing vaccine-elicited immune responses. Here, we describe a scalable solution to detect and quantify SARS-CoV-2 antibodies, discriminate between natural infection- and vaccination-induced responses, and assess antibody-mediated inhibition of the spike-angiotensin converting enzyme 2 (ACE2) interaction.

METHODSWe developed methods and reagents to detect SARS-CoV-2 antibodies by enzyme-linked immunosorbent assay (ELISA). The main assays focus on the parallel detection of immunoglobulin (Ig)Gs against the spike trimer, its receptor binding domain (RBD), and nucleocapsid (N). We automated a surrogate neutralization (sn)ELISA that measures inhibition of ACE2-spike or -RBD interactions by antibodies. The assays were calibrated to a World Health Organization reference standard.

RESULTSOur single-point IgG-based ELISAs accurately distinguished non-infected and infected individuals. For seroprevalence assessment (in a non-vaccinated cohort), classifying a sample as positive if antibodies were detected for [&ge;] 2 of the 3 antigens provided the highest specificity. In vaccinated cohorts, increases in anti-spike and -RBD (but not -N) antibodies are observed. We present detailed protocols for serum/plasma or dried blood spots analysis performed manually and on automated platforms. The snELISA can be performed automatically at single points, increasing its scalability.

CONCLUSIONSMeasuring antibodies to three viral antigens and identify neutralizing antibodies capable of disrupting spike-ACE2 interactions in high-throughput enables large-scale analyses of humoral immune responses to SARS-CoV-2 infection and vaccination. The reagents are available to enable scaling up of standardized serological assays, permitting inter-laboratory data comparison and aggregation.
Effectiveness of the Covid-19 vaccines in preventing infection in dental practitioners: results of a cross-sectional questionnaire based survey India started its vaccination program at the beginning of 2021, the main beneficiaries being health workers and frontline workers including police, paramilitary forces, sanitation workers, and disaster management volunteers in the first phase. By the time, the second wave of Covid-19 impacted India, approximately 14 million healthcare and frontline workers, including dentists had been vaccinated.

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

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

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

ConclusionOur pan-India online survey inferred that vaccination has a definitive role to play in reducing the positivity rate amongst dentists during the second wave of the pandemic across all age groups. Effectiveness of a short term induction regimen of a biosimilar Adalimumab in the long term management of symptomatic Ankylosing Spondylitis Symptomatic Ankylosing Spondylitis: A Community Based Proof of Concept Observational Study IntroductionCost and drug toxicity often deter prolonged therapeutic use of anti-TNF agents in ankylosing spondylitis (AS). A planned study was completed to endorse our clinic based observation of long term relief following short-term administration of anti-TNF agent.

Methods50 consenting patients with symptomatic active chronic AS under rheumatology care in a community clinic were enrolled. They had no past history of anti-TNF use. 40 mg standard biosimilar adalimumab (BS-ADA, Exemptia trade name)was injected subcutaneously every fortnight for six injections (10 weeks). Patients were monitored at several time points. Improvement was assessed at regular interval as per protocol which included standard indices (Bath and Assessment Spondyloarthritis International Society /ASAS). An intention to treat analysis with significant p<0.05 was carried out.

ResultsPatients showed early and substantial significant improvement in pain, NSAID requirement, function and in several indices (ASAS 20 & 40, ASAS partial remission, BASDAI, BASFI, ASDAS) which persisted after stopping injections. 84% and 52 % of patients respectively showed ASAS 20 improvement at week 12 and 48: corresponding ASAS partial remission 34% and 24%. Over 50% patients maintained prolonged improvement and provided proof of concept (defined a-priori). Serum Interleukin-6 assay showed a sharp reduction at 24 weeks. None developed TB or serious drug toxicity. 11 patients withdrew (mostly inadequate response). Absence of control was a limitation.

ConclusionA ten-week administration of biosimilar adalimumab in difficult to treat AS showed early substantial improvement which often persisted for 24 weeks. This unconventional strategy was socioeconomically appealing. It merits further validation and acceptance especially in resource strained settings. 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 Circulating LIGHT (TNFSF14) and Interleukin-18 Levels in Sepsis-Induced Multi-Organ Injuries The novel therapeutic target cytokine LIGHT (TNFSF14) was recently shown to play a major role in COVID19-induced acute respiratory distress syndrome (ARDS). This study aims to investigate the associations of plasma LIGHT and another potentially targetable cytokine, Interleukin-18 (IL-18), with ARDS, acute hypoxic respiratory failure (AHRF) or acute kidney injury (AKI), caused by non-COVID19 viral or bacterial sepsis. A cohort of 280 subjects diagnosed with sepsis, including 91 cases with sepsis triggered by viral infections, were investigated in this cohort study. Day 0 plasma LIGHT and IL-18, as well as 59 other biomarkers (cytokines, chemokines and acute-phase reactants) were measured by sensitive bead immunoassay and associated with symptom severity. We observed significantly increased LIGHT level in both bacterial sepsis patients (P=1.80E-05) and patients with sepsis from viral infections (P=1.78E-03). In bacterial sepsis, increased LIGHT level was associated with ARDS, AKI and higher Apache III scores, findings also supported by correlations of LIGHT with other biomarkers of organ failures. IL-18 levels were highly variable across individuals, and consistently correlated with Apache III scores, mortality, and AKI, in both bacterial and viral sepsis. There was no correlation between LIGHT and IL-18. For the first time, we demonstrate independent effects of LIGHT and IL-18 in septic organ failures. The association of plasma LIGHT with AHRF suggests that targeting the pathway warrants exploration, and ongoing trials may soon elucidate whether this is beneficial. Given the large variance of plasma IL-18 among septic subjects, targeting this pathway requires a precision application. 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. Adolescent vaccination with BNT162b2 (Comirnaty, Pfizer-BioNTech) vaccine and effectiveness against COVID-19: national test-negative case-control study, England Adolescents in the UK were recommended to have their first dose of mRNA vaccine during a period of high community transmission due to the highly transmissible Delta variant, followed by a second dose at an extended interval of 8-12 weeks. We used national SARS-CoV-2 testing, vaccination and hospitalisation data to estimate vaccine effectiveness (VE) using a test-negative case-control design, against PCR-confirmed symptomatic COVID-19 in England. BNT162b2 vaccination in 12-15-year-olds and 16-17-year-olds was associated with lower VE against symptomatic COVID-19 caused by Omicron compared to Delta. Data shows a rapid increase in VE against symptomatic COVID-19 after the second dose for both Delta and Omicron, although this declines to 23% against Omicron after 70+ days. Very high protection was achieved for Delta against hospitalisation after one dose. Our data highlight the importance of the second vaccine dose for protection against symptomatic COVID-19 and raise important questions about the objectives of an adolescent immunisation programme. If prevention of infection is the primary aim, then regular COVID-19 vaccine boosters will be required. 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. MELD Project: Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome.

The Multi-centre Epilepsy Lesion Detection (MELD) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centres worldwide. MRI-based maps of individual FCDs with accompanying demographic, clinical and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom.

FCDs were non-uniformly distributed, concentrating in the superior frontal sulcus, frontal pole and temporal pole. Epilepsy onset was typically before age 10. Earlier epilepsy onset was associated with lesions in primary sensory areas while later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%.

FCD location is an important determinant of its size, the age of epilepsy onset and the likelihood of seizure freedom post-surgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counselling in neurology. 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. Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

MethodsThis prospective cross-sectional study recruited ocular-treatment-naive patients with type 2 diabetes mellitus (DM) registered in the community of Guangzhou, China. OCTA was used to obtain the measurements of FD and BVT in the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). Univariate and multivariate linear regression was used to analyse the correlation of FD and BVT in different layers with DR severity.

ResultsA total of 1282 patients with DM (1282 eyes), with a mean age of 64.2{+/-}7.8 years, were included. FD in the DCP decreased and BVT in the DCP increased in DR patients compared to non-DR patients, even after adjusting for confounding factors (P< 0.05). Trend analysis showed a significant decrease in the FD values as the DR progressed, while the BVT progressively increased with worsening DR severity (P< 0.01). The FD in DCP had a statistically significant positive correlation with FD in SCP and a negative correlation with BVT in SCP and BVT in DCP in all of the participants, including the non-DR group, moderate DR group and severe DR group (P< 0.01).

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. Characterization of small fiber neuropathy in hypermobile Ehlers Danlos Syndrome Ehlers Danlos syndromes (EDS) are heritable connective tissue disorders. The hypermobile form (hEDS) is the most frequent, yet the only one without an identified genetic mutation. Patients suffering from symptomatic joint hypermobility, yet not fulfilling the hEDS criteria, enter the Hypermobility Spectrum Disorder (HSD) category. In addition to musculoskeletal pain affecting joints, hEDS/HSD patients often describe painful sensations, hypoesthesia, and autonomic symptoms suggesting a neuropathic component. Small fiber neuropathy (SFN) refers to the dysfunction or damage of A-{delta} and C-fibers, which relay thermal and nociceptive information as well as mediating autonomic function. SFN has been suggested by prior studies in hEDS but these early findings (case series N[&le;]20) with sole reliance on intraepidermal nerve fiber density (IENFD) called for a larger sample combined with functional testing.

In this retrospective chart extraction from 79 hEDS/HSD patients referred to a pain center due to neuropathic pain or dysautonomia, both functional (Quantitative Sensory Testing (QST), N=79) and structural (IENFD, N=69) evaluations of small nerve fibers were analyzed in combination with clinical data and standardized questionnaires.

All the patients reported moderate to severe pain interfering with daily life. A decreased thermal detection (QST) was shown in 55/79 patients (70%) and a decreased IENFD in 54/69 patients (78%). Hence a small fiber neuropathy (both abnormal IENFD and QST) was definite in 40/69 patients (58%), possible in 23/69 patients (33%) and excluded in only 6/69 patients (9%).

These results add strong evidence for a peripheral neuropathic contribution to pain symptoms in hEDS/HSD, in addition to the known nociceptive and central sensitization components. Such neuropathic contribution could raise the hypothesis of a neurological cause of hEDS, the only EDS syndrome still without a known genetic cause. Hence, our data is leading the way to a better stratification of this very heterogeneous population, which could improve symptommanagement and expand pathophysiological research. 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. Reflex single-gene non-invasive prenatal testing significantly increases the cost-effectiveness of carrier screening ObjectiveTo evaluate the clinical and cost savings benefits of adoption of a carrier screen with reflex single-gene non-invasive prenatal test (sgNIPT) in prenatal care.

MethodA decision-analytic model was developed to compare carrier screen with reflex sgNIPT (maternal carrier status and fetal risk reported together) as first-line carrier screening to the traditional carrier screening workflow (positive maternal carrier screen followed by paternal screening to evaluate fetal risk). The model compared the clinical outcomes and cost effectiveness between the two screening methods. These results were used to simulate appropriate pricing for reflex sgNIPT.

ResultsReflex sgNIPT carrier screening detected 108 of 110 affected pregnancies per 100,000 births (98.5% sensitivity), whereas traditional carrier screening detected 46 of 110 affected pregnancies (41.5% sensitivity). The cost to identify one affected pregnancy was reduced by 62% in the reflex sgNIPT scenario compared to the traditional scenario. Adding together the testing cost savings and the savings from earlier clinical intervention made possible by reflex sgNIPT, the total cost savings was $37.6 million per 100,000 pregnancies. Based on these cost savings, we simulated appropriate reflex sgNIPT pricing range: if the cost to identify one affected pregnancy is the unit cost, carrier screening with reflex sgNIPT can be priced up to $1,859 per test (or $7,233 if sgNIPT is billed separately); if the cost per 100,000 pregnancies is the unit cost, carrier screening with sgNIPT can be priced up to $1,070 per test (or $2,336 if sgNIPT is billed separately).

ConclusionUsing the carrier screen with reflex sgNIPT as first-line screening improves the detection of affected fetuses by 2.4-fold and can save costs for the healthcare system. A real-life experience will be needed to assess the clinical utility and exact cost savings of carrier screen with reflex sgNIPT. Effects of Glucagon-like Peptide-1 Receptor Agonists on Cardiovascular and Renal Outcomes: A Meta-analysis and Meta-regression Analysis AimsCardiovascular and renal effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been inconsistent in cardiovascular outcome trials, and factors associated with the efficacy of GLP-1RAs remain to be clarified. Here, we evaluate the cardiovascular and renal outcomes with GLP-1RAs and associations between these outcomes and HbA1c or weight reduction.

Materials and MethodsWe searched PubMed/MEDLINE, EMBASE, and CENTRAL for randomized, placebo-controlled trials of GLP1-RAs reporting major adverse cardiovascular events (MACE; a composite of cardiovascular mortality, stroke, and myocardial infarction) as the primary outcome. We conducted a meta-regression analysis of primary and secondary outcomes with HbA1c or weight reduction following a meta-analysis with a random-effects model for these outcomes.

ResultsWe extracted data of 60,800 individuals from eight eligible studies (ELIXA, LEADER, SUSTAIN-6, EXSCEL, HARMONY, PIONEER 6, REWIND, and AMPLITUDE-O). GLP-1RAs reduced MACE (hazard ratio [HR] 0.86; 95% CI: 0.80-0.93; P < 0.001) and secondary outcomes including the composite renal outcome (0.80; 0.73-0.87; P < 0.001). In meta-regression analysis, every 1% reduction in HbA1c was associated with 26% and 35% decreases in the logarithm of HR of MACE (P = 0.044; R2 = 0.65) and the composite renal outcome (P = 0.040; R2 = 0.85), respectively. On the contrary, weight reduction was not associated with any outcome, including MACE (P = 0.390).

ConclusionsThe reduction in HbA1c, but not body weight, is associated with cardiovascular and renal outcomes. The magnitude of HbA1c reduction can be a surrogate for cardiovascular and renal benefits of treatment with GLP-1RAs. A collaborative maternity and newborn dashboard (CoMaND) for the COVID-19 pandemic: a protocol for timely, adaptive monitoring of perinatal outcomes in Melbourne, Australia BackgroundThe COVID-19 pandemic has resulted in a range of unprecedented disruptions to the delivery of maternity care globally and has been associated with regional changes in perinatal outcomes such as stillbirth and preterm birth. Metropolitan Melbourne endured one of the longest and most stringent lockdowns in 2020. This paper presents the protocol for a collaborative maternity dashboard project to monitor perinatal outcomes in Melbourne, Australia, during the COVID-19 pandemic.

MethodsDe-identified maternal and newborn outcomes will be collected monthly from all public maternity services in Melbourne, allowing rapid analysis of a multitude of perinatal indicators. Weekly outcomes will be displayed as run charts according to established methods for detecting non-random  signals in health care. A pre-pandemic median for all indicators will be calculated for the period of January 2018 to March 2020. A significant shift is defined as [&le;] six consecutive weeks, all above or below the pre-pandemic median. Additional statistical analyses such as regression, time-series, and survival analyses will be performed for an in-depth examination of maternal and perinatal outcomes of interests.

Ethics and DisseminationThis study has been registered as an observational study with the Australian and New Zealand Clinical Trials Registry (ACTRN12620000878976).

Strengths and weaknesses of this study This project is the first clinician-led, multi-centre perinatal data collection system for metropolitan Melbourne.
 It complements the state government data collection, with the significant benefits of more timely and flexible reporting of outcomes, and granular detail on emerging areas of concern.
 The study relies on primary source coding of exposure and outcomes from each hospital that have not been internally validated during the study period.
 Data from private maternity hospitals, containing 25% of Melbourne births, are not available.
 This resource will support data-informed hospital pandemic responses through to the end of 2022. 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. Statistical modeling for quality risk assessment of clinical trials: follow-up at the era of remote auditing BackgroundAs investigator site audits have largely been conducted remotely during the COVID-19 pandemic, remote quality monitoring has gained some momentum. To further facilitate the conduct of remote Quality Assurance (QA) activities for clinical trials, we developed new quality indicators, building on a previously published statistical modeling methodology.

MethodsWe modeled the risk of having an audit or inspection finding using historical audits and inspections data from 2011 - 2019. We used logistic regression to model finding risk for 4 clinical impact factor (CIF) categories: Safety Reporting, Data Integrity, Consent and Protecting Endpoints.

ResultsWe could identify 15 interpretable factors influencing audit finding risk of 4 out of 5 CIF categories. They can be used to realistically predict differences in risk between 25 and 43% for different sites which suffice to rank sites by audit and inspection finding risk.

ConclusionContinuous surveillance of the identified risk factors and resulting risk estimates could be used to complement remote QA strategies for clinical trials and help to manage audit targets and audit focus also in post-pandemic times. Distinct patterns of cognitive outcome in young children with autism spectrum disorder receiving the Early Start Denver Model Evidence-based, early intervention significantly improves developmental outcome in young children with autism. Nonetheless, there is high interindividual heterogeneity in developmental trajectories during the therapy. It is currently not possible to predict a childs developmental outcome after receiving an early intervention based on his skills and symptoms at baseline. In this study, we analyze developmental trajectories of preschoolers with autism who received 2 years of intervention using the Early Start Denver Model (ESDM) approach in Geneva, Switzerland (n = 47). Our aim was to identify early predictors of response to treatment. We applied a cluster analysis to distinguish between 3 subgroups based on their cognitive level at intake, and rates of cognitive change over the course of treatment. The first subgroup of children only had a mild cognitive delay at intake, and nearly no cognitive delay by the end of treatment (Higher Cognitive at baseline: HC). The children in the two other subgroups all presented with severe cognitive delay at baseline, however, they had two very different patterns of response to treatment. The majority significantly improved developmental scores within their first year of intervention (Optimal Responders: OptR). Whereas a minority of children showed little to no improvement over the course of treatment (Minimal Responders: MinR). Our findings suggest that children who end up having an optimal two-year treatment outcome show rapid developmental improvement. Inversely, less significant progress by the sixth month of intervention may predict a less optimal response to treatment. Current state of COVID-19 knowledge, attitude, practices, and associated factors among Bangladeshi food handlers from various food industries. While people around the world are terrified of the global pandemic coronavirus disease 2019 (COVID-19) and are dying for a permanent solution, undertaking preventive safety measures are said to be the most effective way to stay away from it. Peoples adherences to these measures are broadly dependent on their knowledge, attitude, and practices (KAP). People working in the food industries must be extra cautious during this time because they are in close proximity to consumable items. The present study was designed to evaluate food handlers knowledge, attitude, and practices regarding COVID-19 in different food industries in Bangladesh. A number of 400 food handlers from 15 food industries took part in this online-based study. The information was collected from the participants through a questionnaire prepared in Google form. With a correct response rate of about 90% on average (knowledge 89.7%, attitude 93%, practices 88.2%), the participants showed an acceptable of KAP regarding COVID-19. Education and working experiences had a significant association with the total KAP scores (p < 0.05). The findings may assist public health professionals and practitioners in developing targeted strategies for implementing such studies in other industrial sectors and taking appropriate measures based on the KAP studies. USING PHYLOGENETICS TO INFER HIV-1 TRANSMISSION DIRECTION BETWEEN KNOWN TRANSMISSION PAIRS Inferring the transmission direction between linked individuals living with HIV provides unparalleled power to understand the epidemiology that determines transmission. Phylogenetic ancestral state reconstruction approaches infer the transmission direction by identifying the individual in whom the most recent common ancestor of the virus populations originated. However, these methods vary in their accuracy but it is unclear why. To evaluate the performance of phylogenetic ancestral state reconstruction, we inferred the transmission direction for 112 HIV transmission pairs where transmission direction was known and detailed additional information was available. We then fit a statistical model to evaluate the extent to which epidemiological, sampling, genetic and phylogenetic factors influenced the outcome of the inference. We repeated the analysis under real-life conditions with only routinely-collected data. We found that the inference of transmission direction depends principally on the topology class and branch length characteristics of the phylogeny. Under real-life conditions, the probability of identifying the correct transmission direction increases from 52%--when a monophyletic-monophyletic or paraphyletic-polyphyletic tree topology is observed, when the sample size in both partners is small and when the tip closest to the root does not agree with the state at the root--to 93% when a paraphyletic-monophyletic topology is observed, when the sample size is large and when the tip closest to the root agrees with root state. Our results suggest that discordance between previous studies in inferring the transmission direction can be explained by differences in key phylogenetic properties that arise due to different evolutionary, epidemiological and sampling processes.

Significance StatementIdentifying the direction of infectious disease transmission between individuals provides unparalleled power to understand infectious disease epidemiology. With epidemiological and clinical information typically unable to distinguish the direction, phylogenetic analysis of pathogen sequence data is an alternative approach. However, when these phylogenetic methods have been implemented, their accuracy is highly variable, and the reasons for this discordance is unknown. Here we analyse sequence data from over 100 pairs of individuals for whom both the direction of transmission of HIV is known and detailed epidemiological and sampling information is available. We find that easily quantifiable phylogenetic characteristics discriminate whether a phylogenetically-inferred transmission direction is correct. Our analysis highlights that phylogenetic approaches are unsuitable for individual-level analysis such as forensic investigations. An Accurate Model for SARS-CoV-2 Pooled RT-PCR Test Errors PCR testing is an important tool to mitigate outbreaks of infectious diseases. One way of increasing testing throughput is by simultaneously testing multiple samples for the presence of a pathogen, a technique known as pooling. During the current COVID-19 pandemic, rapidly testing individuals for the presence of SARS-CoV-2 is conducted in large amounts. Since testing is often a bottleneck in mitigating the spread of SARS-CoV-2, pooling is increasing in popularity. Most analyses of the error rates of pooling schemes assume that including more than a single infected sample in a pooled test does not increase the probability of a positive outcome. We challenge this assumption with experimental data and suggest a novel probabilistic model for the outcomes of pooled tests. As an application, we analyze the false-negative rates of one common pooling scheme known as Dorfman pooling. We show that the false-negative rates of Dorfman pooling increase when the prevalence of infection decreases. However, low infection prevalence is exactly the condition under which Dorfman pooling achieves highest throughput. We therefore implore the cautious use of pooling and development of pooling schemes that consider correctly accounting for tests error rates. The Addiction Risk Factor: A Unitary Genetic Vulnerability Characterizes Substance Use Disorders and Their Associations with Common Correlates Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modelling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance specific Ns range: 82,707-435,563), while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology. Preterm outcomes following COVID-19 lockdowns, Melbourne, Australia BackgroundCommunity lockdowns during the COVID-19 pandemic may influence preterm birth rates, but mechanisms are unclear.

MethodsWe compared neonatal outcomes of preterm infants born to mothers exposed to community lockdowns in 2020 (exposed group) to those born in 2019 (control group). Main outcome studied was composite of significant neonatal morbidity or death.

ResultsMedian gestational age was 35+4 weeks (295 infants, exposed group) vs. 35+0 weeks (347 infants, control group) (p = 0.108). The main outcome occurred in 36/295 (12.2%) infants in exposed group vs. 46/347 (13.3%) in control group (p = 0.69). Continuous positive airway pressure (CPAP) use, jaundice requiring phototherapy, hypoglycaemia requiring treatment, early neonatal white cell and neutrophil counts were significantly reduced in the exposed group.

ConclusionsCOVID-19 community lockdowns did not alter composite neonatal outcomes in preterm infants, but reduced rates of some common outcomes, and early white cell and neutrophil counts. The effect of D-cycloserine on brain processing of breathlessness over pulmonary rehabilitation - an experimental medicine study BackgroundPulmonary rehabilitation is the best treatment for chronic breathlessness in COPD but there remains an unmet need to improve efficacy. Pulmonary rehabilitation has strong parallels with exposure-based cognitive behavioural therapies (CBT), both clinically and in terms of brain activity patterns. The partial NMDA-receptor agonist, D-cycloserine has shown promising results in enhancing efficacy of CBT, thus we hypothesised that it would similarly augment the effects of pulmonary rehabilitation in the brain. Positive findings would support further development in phase 3 clinical trials.

Methods72 participants with mild-to-moderate COPD were recruited to a double-blind pre-registered (ID: NCT01985750) experimental medicine study running parallel to a pulmonary rehabilitation course. Participants were randomised to 250mg D-cycloserine or placebo, administered immediately prior to the first four sessions of pulmonary rehabilitation. Primary outcome measures were differences between D-cycloserine and placebo in brain activity in the anterior insula, posterior insula, anterior cingulate cortices, amygdala and hippocampus following completion of pulmonary rehabilitation. Secondary outcomes included the same measures at an intermediate time point and voxel-wise difference across wider brain regions.

ResultsNo difference between D-cycloserine and placebo groups was observed across the primary or secondary outcome measures. Questionnaire and measures of respiratory function showed no group difference.

ConclusionsThis is the first study testing brain-active drugs in pulmonary rehabilitation. Rigorous trial methodology and validated surrogate end-points maximised statistical power. Although increasing evidence supports therapeutic modulation of NMDA pathways to treat symptoms, we conclude that a phase 3 clinical trial of D-cycloserine would not be worthwhile.

Key MessagesO_ST_ABSWhat is the key question?C_ST_ABSDoes the partial NMDA-receptor agonist, D-cycloserine, augment the effects of pulmonary rehabilitation on breathlessness related brain activity?

What is the bottom line?Rigorous trial methodology and validated surrogate end-points revealed no effect of D-cycloserine on breathlessness related brain activity across pulmonary rehabilitation.

Why read on?This study highlights both the value of functional magnetic resonance imaging in "de-risking" expensive clinical trials and provides detailed investigation of brain-targeted points for pharmacological treatments of breathlessness.