GWAS of Retinal Vessel Tortuosity Identifies 173 Novel Loci Revealing Genes and Pathways Associated with Vascular Pathomechanics and Diseases BackgroundFundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Blood vessel tortuosity is a morphological feature associated with many diseases including hypertension.

MethodsWe analyzed 116 639 fundus images of suitable quality from 63 662 participants from three cohorts, namely the UK Biobank (n = 62 751), SKIPOGH (n = 397), and OphtalmoLaus (n = 512). We used a fully automated image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, characterizing these subjects in terms of their median retinal vessel tortuosity specific to arteries and to veins. Tortuosity was measured by the distance factor (the length of a vessel segment over its chord length), as well as measures that integrate over vessel curvature. Using these measures as traits, we performed the largest genome-wide association study (GWAS) of vessel tortuosity to date. We assessed gene set enrichment using the novel high-precision statistical method PascalX.

ResultsHigher tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, meta-cohort. We estimated heritability at [~]25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 114 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, Mendelian randomization revealed causal effects between tortuosity, BMI and LDL.

ConclusionsSeveral alleles associated with retinal vessel tortuosity point to a common genetic architecture of this trait with cardiovascular diseases and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images.

Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIWe automatically estimated arterial and venous tortuosity in over 100k retinal fundus images using image analysis and deep learning.
C_LIO_LIGWAS revealed 173 novel loci.
C_LIO_LIMendelian randomization showed that increased venous tortuosity reduces BMI whereas elevated LDL levels reduce the tortuosity of both arteries and veins.
C_LIO_LIMeasuring tortuosity in terms of the distance factor, which is sensitive to total vessel elongation, had higher heritability and more associated loci than other tortuosity measures that are sensitive to local vessel bending.
C_LI

What are the clinical implications?O_LITortuosity genes were overexpressed in the aorta, tibial artery, coronary artery, and in two heart tissues.
C_LIO_LIHigher tortuosity was associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis and hypertension.
C_LIO_LIWe demonstrated a shared genetic architecture between retinal tortuosity and certain diseases related to the vasculature, and the associations included several cardiometabolic disease variants and risk factors. Further research is needed to investigate the potential of the retinal vessel tortuosity as a clinically relevant biomarker for cardiovascular disease and metabolic syndrome.
C_LIO_LIEnriched pathways include a well-known therapeutic target for ocular diseases (VEGFA-VEGFR2) affecting tissue remodeling. We highlight several transcription factors as interesting targets for further experimentation.
C_LI
Sub-diagnostic effects of genetic variants associated with autism While over a hundred genes are significantly associated with autism, little is known about the prevalence of variants affecting them in the general population. Nor do we fully appreciate the phenotypic diversity beyond the formal autism diagnosis. Using data from more than 13,000 autistic individuals and 210,000 undiagnosed individuals, we provide a gene-level map of the odds ratio for autism associated to rare loss-of-function (LoF) variants in 185 genes robustly associated with autism, alongside 2,492 genes displaying intolerance to LoF variants. In contrast to autism-centric approaches, we investigated the phenotype of undiagnosed individuals heterozygous for such variants and show that they exhibit a decrease in fluid intelligence, qualification level and income, and an increase in material deprivation. These effects were larger for LoFs in autism-associated genes than in other LoF-intolerant genes and appeared largely independent of sex and polygenic scores for autism. Using brain imaging data from 21,049 UK-Biobank individuals, we provide evidence for smaller cortical surface area and volume among carriers of LoFs in genes with high odds ratios for autism. Our gene-level map is a key resource to distinguish genes with high and low odds ratio for autism, and highlights the importance of including quantitative data on both diagnosed and undiagnosed individuals to better delineate the effect of genetic variants beyond the categorical diagnosis. Data are available at https://genetrek.pasteur.fr/.
Background rates of five thrombosis with thrombocytopenia syndromes of special interest for COVID-19 vaccine safety surveillance: incidence between 2017 and 2019 and patient profiles from 25.4 million people in six European countries BackgroundThrombosis with thrombocytopenia syndrome (TTS) has been reported among individuals vaccinated with adenovirus-vectored COVID-19 vaccines. In this study we describe the background incidence of TTS in 6 European countries.

MethodsElectronic medical records from France, Netherlands, Italy, Germany, Spain, and the United Kingdom informed the study. Incidence rates of cerebral venous sinus thrombosis (CVST), splanchnic vein thrombosis (SVT), deep vein thrombosis (DVT), pulmonary embolism (PE), and stroke, all with concurrent thrombocytopenia, were estimated among the general population between 2017 to 2019. A range of additional adverse events of special interest for COVID-19 vaccinations were also studied in a similar manner.

FindingsA total of 25,432,658 individuals were included. Background rates ranged from 1.0 (0.7 to 1.4) to 8.5 (7.4 to 9.9) per 100,000 person-years for DVT with thrombocytopenia, from 0.5 (0.3 to 0.6) to 20.8 (18.9 to 22.8) for PE with thrombocytopenia, from 0.1 (0.0 to 0.1) to 2.5 (2.2 to 2.7) for SVT with thrombocytopenia, and from 0.2 (0.0 to 0.4) to 30.9 (28.6 to 33.3) for stroke with thrombocytopenia. CVST with thrombocytopenia was only identified in one database, with incidence rate of 0.1 (0.1 to 0.2) per 100,000 person-years. The incidence of TTS increased with age, with those affected typically having more comorbidities and greater medication use than the general population. TTS was also more often seen in men than women. A sizeable proportion of those affected were seen to have been taking antithrombotic and anticoagulant therapies prior to their TTS event.

InterpretationAlthough rates vary across databases, TTS has consistently been seen to be a very rare event among the general population. While still very rare, rates of TTS are typically higher among older individuals, and those affected were also seen to generally be male and have more comorbidities and greater medication use than the general population.

FundingThis study was funded by the European Medicines Agency (EMA/2017/09/PE Lot 3). Using controlled interrupted time series to estimate the population-level effects of Ontario's recently implemented overdose prevention sites and consumption and treatment services BackgroundOntario recently implemented overdose prevention sites and consumption and treatment services (OPS/CTS) to stem the harms of the opioid epidemic. We tested whether operating any site improved local opioid-related health service use and mortality rates.

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

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

ConclusionAlthough OPS/CTS are not sufficient to stem the harms of the opioid overdose epidemic on their own, they play a critical role in local harm reduction strategies. What We Learned from COVID-19: From endotheliitis to treatment ObjectiveCOVID-19 may yield a variety of clinical pictures, differing from pneumonitis to Acute Respiratory Distress Syndrome (ARDS) along with vascular damage in the lung tissue, named as endotheliitis. To date, no specific treatment strategy was approved by any authority for the prevention or treatment of COVID-19 in terms of endotheliitis-related comorbidities. Here, we present our experience of COVID-19 by evaluating 11,190 COVID-19 patients with the manifestations of endotheliitis in skin, lung, and brain tissues according to the different phases of COVID-19.

MethodsAfter a retrospective examination, patients were divided into three groups according to their repercussions of vascular distress, which were represented by radiological, histopathological, and clinical findings. (Group A: no or mild pulmonary involvement, Group B: moderate pulmonary involvement with clinical risk of deterioration, Group C: severe pulmonary involvement and respiratory failure). We presented the characteristics and disease course of seven representative and complicated cases which represents the different phases of the disease, and discussed the treatment strategies in each group. The current pathophysiological mechanisms responsible from SARS-CoV-2 infection, COVID-19 related respiratory failure and current treatment strategies were reviewed and discussed in detail.

ResultsAmong 11.190 patients, 9294 patients met the criteria for Group A, and 1376 patients were presented to our clinics with Group B characteristics. Among these patients, 1896 individuals(Group B and Group C) were hospitalized. While 1220 inpatients were hospitalized within the first 10 days after the diagnosis, 676 of them were worsened and hospitalized 10 days after their diagnosis. Among hospitalized patients, 520 of them did not respond to group A and B treatments and developed hypoxemic respiratory failure (Group C) and 146 individuals needed ventilator support and were followed in the intensive care unit, and 43 (2.2%) patients died.

ConclusionDistinctive manifestations in each COVID-19 patient, including non-respiratory conditions in the acute phase and the emerging risk of long-lasting complications, suggest that COVID-19 has an endotheliitis-centred thrombo-inflammatory pathophysiology. Endotheliitis can also explain the mechanism behind the respiratory failure in COVID-19, and the difference of COVID-19 related ARDS from ARDS seen in other critical conditions. In addition, use of early corticosteroid in patients with early symptoms and early tocilizumab in ICU helps to reduce mortality and progression of the disease. Endotheliitis-based pathophysiological mechanisms are known to be momentarily changing and difficut to manage due to their risk of sudden aggrevation. Hence, daily evaluation of clinical, laboratory and radiological findings of patients and deciding appropriate pathophysiological treatment would help to reduce the mortality rate of COVID-19. Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study) Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

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

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years. 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. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

ObjectiveTo develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging.

DesignDerivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules.

SettingPrimary and Express care clinics in a Pennsylvania health system.

ParticipantsPatients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19.

Main outcomes and measuresClassification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC).

ResultsOverall, 7.4% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21) and 5.5% in the late validation cohort (3806 patients presenting 3/1/21 or later) were ultimately hospitalized. We developed and temporally validated three risk scores that all included age, dyspnea, and the presence of comorbidities, adding respiratory rate for the second score and oxygen saturation for the third. All had very good overall accuracy (AUC 0.77 to 0.78) and classified over half of patients in the validation cohort as very low risk with a 1.7% or lower likelihood of hospitalization. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization (2.8%).

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/. Thromboembolism risk among patients with diabetes/stress hyperglycemia and COVID-19 AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSPurposeC_ST_ABSIndividuals with diabetes/stress hyperglycemia carry an increased risk for adverse clinical outcome in case of SARS-CoV-2 infection. The purpose of this study was to evaluate whether this risk is, at least in part, modulated by an increase of thromboembolic complications.

MethodsWe prospectively followed 180 hospitalized patients with confirmed COVID-19 pneumonia admitted to the Internal Medicine Units of San Raffaele Hospital. Data from 11 out of 180 patients were considered incomplete and excluded from the analysis. We analysed inflammation, tissue damage biomarkers, hemostatic parameters, thrombotic events (TEs) and clinical outcome according to the presence of diabetes/stress hyperglycemia.

ResultsAmong 169 patients, 51 (30.2%) had diabetes/stress hyperglycemia. Diabetes/stress hyperglycemia and fasting blood glucose (FBG) were associated with increased inflammation and tissue damage circulating markers, higher D-dimer levels, increased prothrombin time and lower antithrombin III activity. Forty-eight venous and 10 arterial TEs were identified in 49 (29%) patients. Diabetes/stress hyperglycemia (HR 2.71, p=0.001), fasting blood glucose (HR 4.32, p<0.001) and glucose variability (HR 1.6, p < 0.009) were all associated with an increased risk of thromboembolic complication. TEs significantly increased the risk for an adverse clinical outcome only in the presence of diabetes/stress hyperglycemia (HR 3.05, p=0.01) or fasting blood glucose [&ge;] 7 mmol/l (HR 3.07, p=0.015).

ConclusionsThromboembolism risk is higher among patients with diabetes/stress hyperglycemia and COVID-19 pneumonia and is associated to poor clinical outcome. In case of SARS-Cov-2 infection patients with diabetes/stress hyperglycemia could be considered for a more intensive prophylactic anticoagulation regimen. Distinct temporal characteristics of circulating alveolar epithelial and endothelial injury markers in ARDS with COVID-19: a preliminary retrospective report The time course and specific contributions of alveolar epithelial and endothelial injury to the pathogenesis of acute respiratory distress syndrome (ARDS) with coronavirus disease (COVID-19) remain unclear. Here, we evaluated the characteristics of circulating markers of alveolar epithelial and endothelial injury in serum samples from eleven ARDS patients and ten non-ARDS patients, all with COVID-19. Our results indicates that the alveolar epithelial injury at the very early disease stage and the endothelial injury which continues to exacerbate during the later disease stage seem to be the hallmarks of ARDS with COVID-19. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. iBKH: The integrative Biomedical Knowledge Hub The rapidly increasing biomedical knowledge, derived from biological experiments or gained from clinical practice, has become the important treasure in the biomedical research. The emerging knowledge graphs (KGs) provide an efficient and effective way to organize and retrieval the huge and increasing volume of biomedical knowledge. A biomedical KG (BKG) typically stores and represents knowledge by constructing a semantic network describing entities and the relationships between them. Previous efforts have been conducted to construct and curate BKGs by comprehensively integrating various biomedical data resources. Though the resulting BKGs have made a significant progress in this filed in advancing biological and medical research, there remain a big gap to a perfect one that is comprehensive and fine-grained enough. To this end, in the present study, we collected and integrated data from diverse well-curated biomedical knowledge bases and BKGs to curate a more comprehensive one, named the integrative Biomedical Knowledge Hub (iBKH). To enhance the usage in accelerating biomedical research, we deployed iBKH using the famous graph database, Neo4j. This is a continuing effort and we are adding in more and more contents in iBKH to support the various complex needs in biomedical data analysis. Please contact us if you have better ideas and suggestions. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

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

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

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. 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. 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. How Informative Were Early SARS-CoV-2 Treatment and Prevention Trials? A longitudinal cohort analysis of trials registered on clinicaltrials.gov BackgroundEarly in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

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

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

ConclusionsLess than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic. Treatment interruption is a risk factor for sickness presenteeism: a large-scale cross-sectional study during the COVID-19 pandemic ObjectivesThis study examined the relationship between interruption to routine medical care during the coronavirus disease 2019 pandemic and sickness presenteeism among workers in Japan.

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

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

ConclusionsThis study suggests the importance of continuing necessary treatment during a pandemic to prevent presenteeism. Risk factors for early childhood growth faltering in rural Cambodia IntroductionInadequate nutrition in early life and exposure to sanitation-related enteric pathogens have been linked to poor growth outcomes in children. Despite rapid development in Cambodia, high prevalence of growth faltering and stunting continue to persist. This study aimed to assess nutrition and WASH variables and their association with nutritional status of children under 24 months in rural Cambodia.

MethodsWe conducted surveys in 491 villages across 55 rural communes in Cambodia in September 2016 to measure associations between child, household, and community-level risk factors for stunting and length-for-age z-score (LAZ). A primary survey measured child-level variables, including anthropometric measures and risk factors for growth faltering and stunting, for 4,036 children under 24 months of age from 3,877 households (approximately 8 households per village). For LAZ, we calculated bivariate and adjusted associations (as mean differences) with 95% confidence intervals using generalised estimating equations (GEEs) to fit linear regression models with robust standard errors. For stunting, we calculated unadjusted and adjusted prevalence ratios (PRs) with 95% confidence intervals using GEEs to fit Poisson regression models with robust standard errors. For all models assessing effects of household-level variables, we used GEEs to account for clustering at the village level.

ResultsAfter adjustment for potential confounding, presence of water and soap at a households handwashing station was found to be significantly associated (p<0.05) with increased LAZ (adjusted mean difference in LAZ +0.10, 95% CI: 0.03, 0.16), and household use of an improved drinking water source was associated with less stunting in children compared to households that did not use an improved source of drinking water (aPR 0.81, 95% CI: 0.66, 0.98); breastfeeding was associated with a lower LAZ score (-0.16, 95% CI: -0.27, -0.05). No other feeding practices (i.e., dietary diversity, meal frequency, minimum acceptable diet) or sanitation variables (i.e., households safe disposal of child stools, household-level sanitation, community-level sanitation) were associated with LAZ scores or stunting in children under 24 months of age. In an age-stratified analysis, children under 12 months of age were longer (LAZ +0.12, 95% CI: 0.02, 0.21) if there was presence of water and soap at the household handwashing station; at the community level, higher prevalence of shared sanitation (percentage of households in a village who report to use shared sanitation facilities) was negatively associated with child length (LAZ - 0.36, 95% CI: -0.66, -0.07). Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.

ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. 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. Stability of the stroke code during the COVID-19 pandemic in the region of Madrid: a retrospective cohort study Acute Stroke (AS) is the most common time-dependent disease attended in the Emergency Medicine Service (EMS) of Madrid (SUMMA 112). Community of Madrid has been one of the most affected regions in Spain by the coronavirus disease 2019 (COVID19) pandemic. A significant reduction in AS hospital admissions has been reported during the COVID-19 pandemic compared to the same period one year before. As international clinical practice guidelines support those patients with suspected acute stroke should be accessed via EMS, it is important to know whether the pandemic has jeopardized urgent pre-hospital stroke care, the first medical contact for most patients. We aimed to examine the impact of the COVID-19 in stroke codes (SC) in our EMS among three periods of time: the COVID-19 period, the same period the year before, and the 2019-2020 seasonal influenza period. Methods: We compared the SC frequency among the periods with high cumulative infection rate (above the median of the series) of the first wave of COVID-19, seasonal influenza, and also with the same period of the year before. Results: 1,130 SC were attended during the three periods. No significant reduction in SC was found during the COVID-19 pandemic. The reduction of hospital admissions might be attributable to patients attending the hospital by their means. The maximum SC workload seen during seasonal influenza has not been reached during the pandemic. We detected a non-significant deviation from the SC protocol, with a slight increase in hospitals transfers to hospitals without stroke units. Fundamental limits on inferring epidemic resurgence in real time using effective reproduction numbers We find that epidemic resurgence, defined as an upswing in the effective reproduction number (R) of the contagion from subcritical to supercritical values, is fundamentally difficult to detect in real time. Inherent latencies in pathogen transmission, coupled with smaller and intrinsically noisier case incidence across periods of subcritical spread, mean that resurgence cannot be reliably detected without significant delays of the order of the generation time of the disease, even when case reporting is perfect. In contrast, epidemic suppression (where R falls from supercritical to subcritical values) may be ascertained 5-10 times faster due to the naturally larger incidence at which control actions are generally applied. We prove that these innate limits on detecting resurgence only worsen when spatial or demographic heterogeneities are incorporated. Consequently, we argue that resurgence is more effectively handled proactively, potentially at the expense of false alarms. Timely responses to recrudescent infections or emerging variants of concern are more likely to be possible when policy is informed by a greater quality and diversity of surveillance data than by further optimisation of the statistical models used to process routine outbreak data.

Author summaryThe timely detection of epidemic resurgence (i.e., upcoming waves of infected cases) is crucial for informing public health policy, providing valuable signals for implementing interventions and identifying emerging pathogenic variants or important population-level behavioural shifts. Increases in epidemic transmissibility, parametrised by the time-varying reproduction number, R, commonly signify resurgence. While many studies have improved computational methods for inferring R from case data, to enhance real-time resurgence detection, few have examined what limits, if any, fundamentally restrict our ability to perform this inference. We apply optimal Bayesian detection algorithms and sensitivity tests and discover that resurgent (upward) R-changes are intrinsically more difficult to detect than equivalent downward changes indicating control. This asymmetry derives from the often lower and stochastically noisier case numbers that associate with resurgence, and induces detection delays on the order of the disease generation time. We prove these delays only worsen if spatial or demographic differences in transmissibility are modelled. As these fundamental limits exist even if case data are perfect, we conclude that designing integrated surveillance systems that fuse potentially timelier data sources (e.g., wastewater) may be more important than improving R-estimation methodology and deduce that there may be merit (subject to false alarm costs) in conservative resurgence response initiatives. 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. 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 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.) Developing and testing an arts-based, digital knowledge translation tool for parents about childhood croup Croup is a common viral illness affecting 80,000 children annually in Canada. Between 7-31% of children seen in an ED for croup are admitted to hospital due to health care provider apprehension. However, over 60% of children with croup experience mild symptoms that can be safely managed at home. Emerging evidence suggests that initiatives targeting healthcare consumers (i.e., patients, parents, families) can inform decision making and shape treatment expectations. Previous research demonstrates that innovative media are superior to traditional standard health sheets for transferring information to consumers.

The purpose of this project was to develop, refine, and test the usability of a whiteboard animation video for parents about childhood croup. Parents rated the tools highly across all usability items, suggesting that creative tools developed using multi-method development processes can help facilitate the uptake of health information in parents.