SARS-CoV-2 B.1.1.7 escape from mRNA vaccine-elicited neutralizing antibodies Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) transmission is uncontrolled in many parts of the world, compounded in some areas by higher transmission potential of the B1.1.7 variant now seen in 50 countries. It is unclear whether responses to SARS-CoV-2 vaccines based on the prototypic strain will be impacted by mutations found in B.1.1.7. Here we assessed immune responses following vaccination with mRNA-based vaccine BNT162b2. We measured neutralising antibody responses following a single immunization using pseudoviruses expressing the wild-type Spike protein or the 8 amino acid mutations found in the B.1.1.7 spike protein. The vaccine sera exhibited a broad range of neutralising titres against the wild-type pseudoviruses that were modestly reduced against B.1.1.7 variant. This reduction was also evident in sera from some convalescent patients. Decreased B.1.1.7 neutralisation was also observed with monoclonal antibodies targeting the N-terminal domain (9 out of 10), the Receptor Binding Motif (RBM) (5 out of 31), but not in neutralising mAbs binding outside the RBM. Introduction of the E484K mutation in a B.1.1.7 background to reflect newly emerging viruses in the UK led to a more substantial loss of neutralising activity by vaccine-elicited antibodies and mAbs (19 out of 31) over that conferred by the B.1.1.7 mutations alone. E484K emergence on a B.1.1.7 background represents a threat to the vaccine BNT162b.
The lost microbes of COVID-19: Bifidobacteria depletion and decreased microbiome diversity are a predictability marker of severe COVID 19, a cross sectional study ObjectiveThe study objective was to compare gut microbiome diversity and composition in SARS-CoV-2 polymerase chain reaction (PCR)-positive patients whose symptoms ranged from asymptomatic to severe, versus PCR-negative exposed controls.

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

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

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

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



O_TBL View this table:
org.highwire.dtl.DTLVardef@173dbe8org.highwire.dtl.DTLVardef@16a75b5org.highwire.dtl.DTLVardef@55d55eorg.highwire.dtl.DTLVardef@12b2302org.highwire.dtl.DTLVardef@107663d_HPS_FORMAT_FIGEXP  M_TBL C_TBL
The effect of hypersensitivity pneumonitis guideline on pathologic diagnosis of interstitial pneumonia Hypersensitivity pneumonitis (HP) and interstitial pneumonia (IP) have several overlapping characteristics, and a high diagnostic concordance rate of HP is rarely obtained. New guideline, highly influenced by pathology, were devised for its diagnosis. We recently reported that the 2020 HP guideline may result in a possible overdiagnosis of fibrotic HP (fHP) through multidisciplinary discussion. Here, we attempted to investigate the impact of the 2020 HP guideline on the pathological diagnosis of cases previously diagnosed as IP. We classified 247 cases with fibrotic IP diagnoses sourced from 2014-2019 into three categories according to the 2020 HP guideline: typical, probable, and indeterminate HP. The original pathological diagnosis and categorization based on the 2020 HP guideline were compared. The clinical data including serum data and pulmonary function tests were compared among groups. The number of cases that changed to HP from an original diagnosis other than HP based on the guideline was 56 (23%). The clinical data of these cases bore a greater resemblance to cases diagnosed as indeterminate for HP than those diagnosed as typical or probable. The ratio of typical and probable HP to the total cases was significantly lower when using a transbronchial lung cryobiopsy (TBLC). Based on the new guideline, the pathological diagnosis of HP efficiently excluded HP cases but increased the rate of HP diagnosis for cases with fibrotic IP that may not suit an HP diagnosis. Thus, a TBLC may not be useful when imparting findings for fibrotic HP diagnosis using the new criteria.

Key messagesO_LIWhat is the key question? >
Does the 2020 HP Guideline improve pathological diagnosis?
C_LIO_LIWhat is the bottom line? >
By applying the new guideline, about 1/4 of the pathological diagnoses were changed from not chronic HP to probable or typical fHP, but most of the changed cases showed a clinical picture closer to not chronic HP.
C_LIO_LIWhy read on? >
To understand that simple application of the pathological criteria of the HP guideline may cause a misleading diagnosis.
C_LI Disparate Impacts on Online Information Access during the COVID-19 Pandemic The COVID-19 pandemic has stimulated a staggering increase in online information access (1, 2), but the extent to which different communities of internet users enlist digital resources to meet everyday needs varies (2-4). We analyze 55 billion everyday web search interactions across 25,150 US ZIP codes and demonstrate that there were disparate impacts of the pandemic on online information access across several information domains, including health and pandemic-relevant online resources (e.g., online learning, online food delivery). Among many findings, we show that ZIP codes associated with higher proportions of Black residents intensified their access to unemployment resources, and ZIP codes associated with lower income reduced their access to health information resources relative to their counterpart ZIP codes. Because these disparate impacts on the access to online information may result in downstream offline gaps in health, education, employment, and well-being (3), public health interventions should target potential barriers to accessing the necessary digital resources and provide adequate support to meet the intensified digital resource needs.

One Sentence SummaryLarge-scale web search logs reveal disparate impacts on online health, education, unemployment, and food information access. Prospectively validated disease-agnostic predictive medicine with augmented intelligence Despite numerous superhuman achievements in complex challenges1,2, standalone AI does not free life science from the long-term bottleneck of linearly extracting new knowledge from exponentially growing new data3, severely limiting the success rate of drug discovery4. Inspired by the state-of-the-art AI training methods, we trained a human-centric hybrid augmented intelligence5 (HAI) to learn a foundation model6 that extracts all-encompassing knowledge of human physiology and diseases. To evaluate the quality of HAIs extracted knowledge, we designed the public, prospective prediction of pivotal ongoing clinical trial outcomes at large scale (PROTOCOLS) challenge to benchmark HAIs real-world performance of predicting drug clinical efficacy without access to human data. HAI achieved a 10.5-fold improvement from the baseline with 99% confidence7 in the PROTOCOLS validation, readily increasing the average clinical success rate of investigational new drugs from 7.9%8 to 90% for almost any human diseases9,10. The validated HAI confirms that exponentially extracted knowledge alone is sufficient for accurately predicting drug clinical efficacy, effecting a total reversal of Erooms law4. HAI is also the worlds first clinically validated model of human aging that could substantially speed up the discovery of preventive medicine for all age-related diseases11. Our results demonstrate that disruptive breakthroughs necessitate the smallest team size to attain the largest HAI for optimal knowledge extraction from high-dimensional low-quality data space, thus establishing the first prospective proof of the previous discovery that small teams disrupt12. The global adoption of training HAI provides a well-beaten economic path to mass-produce scientific and technological breakthroughs via exponential knowledge extraction and better designs of data labels for training better-performing AI13. A genome-wide association study of chronic ALT-based non-alcoholic fatty liver disease in the Million Veteran Program with histological and radiological validation. Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic alanine aminotransferase elevation (cALT) without other liver diseases, we performed a trans-ancestry genome-wide association study in the Million Veteran Program including 90,408 cALT cases and 128,187 controls. In the Discovery stage, seventy-seven loci exceeded genome-wide significance - including 25 without prior NAFLD or ALT associations - with one additional locus identified in European-American-only and two in African-American-only analyses (P<5x10-8). External replication in cohorts with NAFLD defined by histology (7,397 cases, 56,785 controls) or liver fat extracted from radiologic imaging (n=44,289) validated 17 SNPs (P<6.5x10-4) of which 9 were novel (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH, and IFI30). Pleiotropy analysis showed that 61 of 77 trans-ancestry and all 17 validated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD. Remote exposure to secondhand tobacco smoke is associated with lower exercise capacity through effects on oxygen pulse, a proxy of cardiac stroke volume BackgroundPast exposure to secondhand tobacco smoke (SHS) is associated with exercise limitation. Pulmonary factors including air trapping contribute to this limitation but the contribution of cardiovascular factors is unclear.

ObjectiveTo determine contribution of cardiovascular mechanisms to SHS-associated exercise limitation.

MethodsWe examined the cardiovascular responses to maximum effort exercise in 245 never-smokers with remote, prolonged occupational exposure to SHS and no known history of cardiovascular disease. We estimated the contribution of oxygen-pulse (proxy for cardiac stroke volume) and changes in systolic (SBP) and diastolic blood pressures (DBP) and heart rate (HR) towards exercise capacity, and examined whether the association of SHS with exercise capacity was mediated through these variables.

ResultsAt peak exercise (highest workload completed [WattsPeak]=156{+/-}46 watts [135{+/-}33 %predicted]), oxygen consumption (VO2Peak) and oxygen-pulse (O2-PulsePeak) were 1,557{+/-}476 mL/min (100{+/-}24 %predicted) and 11.0{+/-}3.0 mL/beat (116{+/-}25 %predicted), respectively, with 29% and 3% participants not achieving their predicted normal range. Oxygen saturation at peak exercise was 98{+/-}1% and remained >93% in all participants. Sixty-six percent showed hypertensive response to exercise. In models adjusted for covariates, WattsPeak was associated directly with O2-PulsePeak, HRPeak, and SBPPeak and inversely with SHS, air trapping (RV/TLC), and rise of SBP over workload (all P<0.01). Moreover, SHS exposure association with WattsPeak was substantially (41%) mediated through its effect on O2-PulsePeak (P<0.038). Although not statistically significant, a considerable proportion (36%) of air trapping effect on WattsPeak seemed to be mediated through O2-PulsePeak (P=0.078). The likelihood of having baseline respiratory symptoms (modified Medical Research Council score [&ge;]1) was associated with steeper rise in SBP over workload (P<0.01).

ConclusionIn a never-smoker population with remote exposure to SHS, abnormal escalation of afterload and an SHS-associated reduction in cardiac output contributed to lower exercise capacity.

Key messagesO_ST_ABSWhat is the key question?C_ST_ABSWhat are the cardiovascular health effects of past exposure to secondhand tobacco smoke in never-smokers? How do pulmonary and cardiovascular systems interact in this setting?

What is the bottom line?Healthy never-smokers with history of remote past exposure to secondhand tobacco smoke have an abnormal cardiovascular response to exercise, which is characterized by a stroke volume and thus an exercise capacity that are reduced proportional to their years of exposure to secondhand tobacco smoke.

Why read on?The abnormal cardiovascular response to exercise in this population reveals the presence of an occult or subclinical pathology that impairs the cardiopulmonary functional reserve and reduces the efficiency of bodys oxygen delivery machinery, which could be disadvantageous during the times of increased cardiopulmonary output demands as in physiological distress or disease. Surgical interventions targeting the nucleus caudalis for craniofacial pain: a systematic and historical review. IntroductionChronic facial pain is a prevalent group of conditions and when refractory to common treatments poses a social and economic burden. The last decade has seen a multitude of advancements in the multimodal management of pain. Ablative or neuromodulatory interventions targeting the nucleus caudalis (NC) of the trigeminocervical complex is one such treatment that has remained underutilized.

MethodsHere we present a systematic review of the literature and historical perspective regarding interventions targeting the NC. We examine the various intervention techniques, clinical indications, and procedural efficacy. A novel outcome reporting scheme was devised to allow comparison between studies using differing outcome reporting methods.

ResultsA review of the literature revealed 49 retrospective studies published over the last 80 years, reporting on 858 patients. The most common technique was the open NC dorsal root entry zone nucleotomy/tractotomy (n=515, 60.0%); however, there has been an emergence of novel approaches such as endoscopic (n=6, 0.7%) and spinal cord stimulation (n=20, 2.3%) in the last 10 years. Regardless of intervention technique or preoperative diagnosis, 90.4% of patients demonstrated some improvement from treatment.

ConclusionThis systematic review highlights recent advancements in NC intervention technique and the wide range of facial pain syndromes for which these interventions show promising efficacy. New and less invasive techniques continue to emerge, however prospective studies remain absent in the literature. Future work should address efficacy comparisons between intervention type and preoperative diagnosis. 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. Chemosensory dysfunctions induced by COVID-19 can persist up to 7 months: A study of over 700 healthcare workers Several studies have revealed either self-reported chemosensory alterations in large groups or objective quantified chemosensory impairments in smaller populations of patients diagnosed with COVID-19. However, due to the great variability in published results regarding COVID-19-induced chemosensory impairments and their follow-up, prognosis for chemosensory functions in patients with such complaints remains unclear. Our objective is to describe the various chemosensory alterations associated with COVID-19 and their prevalence and evolution after infection. A cross-sectional study of 704 healthcare workers with a RT-PCR confirmed SARS-CoV-2 infection between 28/2/2020 and 14/6/2020 was conducted 3 to 7 months after onset of symptoms. Data were collected with an online questionnaire. Outcomes included differences in reported chemosensory self-assessment of olfactory, gustatory, and trigeminal functions across time points and Chemosensory Perception Test scores from an easy-to-use at-home self-administered chemosensory test. Among the 704 participants, 593 (84.2%) were women, the mean (SD) age was 42 (12) years, and the questionnaire was answered on average 4.8 (0.8) months after COVID-19. During COVID-19, a decrease in olfactory, gustatory, and trigeminal sensitivities were reported by 81.3%, 81.5% and 48.0% respectively. Three to seven months later, reduced sensitivity was still reported by 52.0%, 41.9% and 23.3% respectively. Chemosensory Perception Test scores indicate that 19.5% of participants had objective olfactory impairment. These data suggest a significant proportion of COVID-19 cases have persistent chemosensory impairments at 3 to 7 months after their infection but the majority of those who had completely lost their olfactory, gustatory, and trigeminal sensitivity have improved. 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.) Survey of Contaminated Percutaneous Injuries in Anesthesia Practitioners BackgroundAnesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.

MethodsAfter institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).

ResultsThe overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50-68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings years of anesthesia practice was 69% (95% CI, 44-94) for 5-10 years, 62.5% (95% CI, 29-96) for 10-15 years, and 79% (95% CI, 63- 95) for greater than 15 years of practice.

35% (95% CI, 26-44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65-85) reported the incident at the time of injury. 59% (95% CI, 48-70) of injuries were due to hollow bore needles. 50% (95% CI, 39-61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.

ConclusionMost anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting. 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. Development of machine learning models for the prediction of complications after colonic, colorectal and small intestine anastomosis in psychiatric and non-psychiatric patient collectives (PSTUDY) Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

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

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years. Variation in colorectal cancer treatment and outcomes in Scotland: real world evidence from national linked administrative data BackgroundColorectal cancer (CRC) is the third most common type of cancer in Scotland and the second leading cause of cancer death. Despite improvements in CRC survival over time, Scotland lags behind its UK and European counterparts. Linked administrative datasets can provide a real-world representation of current care as a basis for evaluation of new interventions or policies and to understand variation in care and outcomes. In this study, we aim to provide up to date, population level evidence on CRC treatment and survival in Scotland for patients treated with curative or palliative intent as a basis for the understanding of variation, and to provide data to underpin the evaluation of new treatments.

MethodsWe conducted a retrospective analysis of adults with an incident CRC registered on the Scottish Cancer Registry (ICD-10 codes C18-20) between January 2006 and December 2018. Data on patients with incident CRC was linked to hospital inpatient records allowing description of their demographic, diagnostic and treatment characteristics. For a curative cohort (n = 26,204) Cox-Proportional Hazards regression models were used to assess the factors affecting overall survival (OS) and CRC specific survival (CRCS).

ResultsOverall, 32,691 (73%) and 12,184 (27%) patients had a diagnosis of colon and rectal cancer respectively. On average, patients with colorectal cancer had two hospital inpatient stays in the five-years pre-diagnosis. Chemotherapy was used in 42% with colon cancer and 30% with colon cancer. Radiotherapy use was 2% and 39% respectively. Five year OS (CRCS) within the curative cohort was 71% (81%) and 75% (82%) for patients with colon and rectal cancer respectively. After accounting for patient and tumour characteristics, survival outcomes demonstrated significant geographical variation.

ConclusionsNational linked administrative datasets have the ability to provide real-world representation of the treatments and outcomes for patients with cancer. In a Scottish population of curative patients with CRC, there was significant variation in survival depending on sex and geography. 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 Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank ObjectivesTo evaluate the benefit of combining polygenic risk scores (PRS) with the QCancer-10 (colorectal cancer) non-genetic risk prediction model to identify those at highest risk of colorectal cancer (CRC).

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

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

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

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

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

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

What this study addsO_LIAdding PRS to the QCancer-10 (colorectal cancer) risk prediction model improves performance and clinical benefit, with greatest gain from the LDpred2 genome-wide PRS, to a level that suggests utility in stratifying CRC screening and prevention
C_LI 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. Evaluation of Clinical Threshold Policies for Cataract Surgery and the Regional Variation in Rates of Surgery Background/AimsTo characterise the national patterns in rates of cataract surgery across England, review clinical thresholds against NICE guidance, and determine how far variable access to cataract surgery is attributable to regional variation in policy stringency and social deprivation.

Methods127 Clinical Commissioning Groups ("CCGs") provided cataract surgery data and threshold policies in response to a Freedom of Information request. Local cataract surgery rates were grouped by threshold stringency and analysed on an age group-corrected basis. ANOVA testing was used to assess effect of policy stringency on regional rates of cataract surgery.

ResultsIn England, rates of cataract surgery vary threefold across CCGs, from 1,980 to 6,427 per 100,000 population over 60, with a standard deviation (784.76) of 22% of the mean value, 3,598. Threshold policies vary across CCGs: 33 had no policy, 45 utilised policies accessible on the basis of Quality of Life ("QoL") impact, and 39, against NICE guidance, required a Visual Acuity ("VA") threshold be exceeded. Rates of surgery by CCG were negatively correlated with restrictiveness of policy ({eta}2=0.18, p<0.01), and positively correlated with the Index of Multiple Deprivation (IMD), (r2{square}={square}0.11, p<0.01). Prior approval processes are not significantly associated with reduced rates of surgery.

ConclusionOver two-thirds of CCGs continue to use threshold-based policies for access to cataract surgery, with one-third doing so solely on the basis of VA requirements, despite NICE guidance to the contrary. For NHS operations, variation in policy restrictiveness accounts for more of the variation in surgery rates than socioeconomic deprivation. Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes BackgroundIndividuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

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

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

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

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

Research in context

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

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

Implications of all the available evidenceWith further validation in several cohorts, the prediction models presented here have the potential for early diagnosis of CKD in persons with diabetes, thus enabling appropriate decisions on the available therapies. It is envisaged that these algorithms will be trialed and support clinicians with precision diagnosis and treatments. Impact of tozinameran (BNT162b2) mRNA vaccine on kidney transplant and chronic dialysis patients: 3-5 months followup BackgroundDetermining the humoral immunogenicity of tozinameran (BNT162b2) vaccine in patients requiring chronic renal replacement therapy, and its impact on COVID-19 morbidity several months after vaccination, will guide risk assessment and subsequent changes in vaccination policy.

MethodsIn a prospective post-vaccination cohort study with up to 5 months follow-up we studied outpatient dialysis and kidney transplant patients and respective healthcare teams. Outcomes were anti S1/S2 antibody response to vaccine or infection and infection rate during followup.

Results175 dialysis patients (40% women, 65{+/-}15 years), 252 kidney transplant patients (33% women, 54{+/-}14 years) and 71 controls (65% women, 44{+/-}14 years) were followed. Three months or longer after vaccination we detected anti S1/S2 IgG antibodies in 80% of dialysis patients, 44% of transplant recipients and 100% of controls, whereas respective rates after infection were 94%, 75% and 100%. Predictors of non-response were older age, diabetes, history of cancer, lower lymphocyte count and lower vitamin-D levels. Factors associated with lower titers in dialysis patients were modality (hemodialysis vs peritoneal) and high serum ferritin levels. In transplant patients, hypertension and higher calcineurin or mTOR inhibitor drug levels were linked with diminished antibody response. Vaccination associated with fewer subsequent infections (HR=0.23, p<0.05). Moreover, higher antibody titers associated with fewer events, HR 0.41 for each unit increased in log10titer (p<0.05).

ConclusionsDialysis patients, and more so kidney transplant recipients, mounted reduced antibody response to COVID-19 mRNA vaccination, and lesser humoral response associated with more infections. Measures to identify and protect non-responsive patients are urgently required.

SignificanceReports on the humoral immunogenicity of SARS-CoV-2 mRNA vaccines in patients with end stage renal disease are scarce, and association with subsequent COVID-19 morbidity is unknown. In this cohort study that included 175 patients treated with dialysis, 252 kidney transplant recipients and 71 control volunteers, the proportion achieving an antibody response was time- and group-dependent, reaching 80%, 44% and 100% at 3 months post prime inoculation. Personal history of vaccination, positive antibody responses and antibody titers associated with significantly lower risk of COVID-19 infection. Thus, in patients with end stage renal disease, SARS-CoV-2 antibody testing may be warranted after vaccination, to identify non-responders at higher risk for disease. Neural Correlates of Eye Contact and Social Function in Autism Spectrum Disorder Reluctance to make eye contact during natural interactions is a central diagnostic criterion for autism spectrum disorder (ASD). However, the underlying neural correlates for natural eye contacts in ASD are unknown, and diagnostic biomarkers are active areas of investigation. Here, neuroimaging, eye-tracking, and pupillometry data were acquired simultaneously using two-person functional near-infrared spectroscopy (fNIRS) during live eye-to-eye contact and eye-gaze at a video face in typically developed (TD) and ASD participants to identify the neural correlates of live eye-to-eye contact in both groups. Direct comparisons between ASD and TD participants showed decreased right dorsal parietal activity and increased right ventral temporal-parietal activity for ASD relative to TD during live eye-to-eye contact (p[&le;]0.05, FDR-corrected) consistent with the hypothesis of alternative neural systems for live eye contact. The additional hypothesis that hypoactivity of the right dorsal-parietal regions during eye contact is associated with social performance in ASD was supported by the correlation of right dorsal parietal activity with individual measures of social function: ADOS-2, Autism Diagnostic Observation Schedule, 2nd Edition (r = -0.69); and SRS-2, Social Responsiveness Scale, Second Edition (r = -0.58). That is, as social ability decreased, the neural responses in the right dorsal parietal region to real eye-contact also decreased consistent with a neural correlate for social characteristics in ASD. 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.