Infection spread simulation technology in a mixed state of multi variant viruses ATLM was extended to simulate the spread of infection in a mixed state of mutant virus and conventional virus. It is applied to the 4th wave of infection spread in Tokyo, and (1) the 4th wave bottoms out near the end of the state of emergency, and the number of infected people increases again. (2) The rate of increase will be mainly by L452R virus, while the increase by N501Y virus will be suppressed. (3) It is anticipated that the infection will spread during the Olympic Games. (4) When mutant virus competes, the infection of highly infectious virus rises sharply while the infection by weakly infectious ones has converged. (5) It is effective as an infection control measure to find an infected person early and shorten the period from infection to quarantine by PCR test or antigen test as a measure other than vaccine.
The prevalence of adaptive immunity to COVID-19 and reinfection after recovery, a comprehensive systematic review and meta-analysis ObjectivesThis study aims to estimate the prevalence and longevity of detectable SARS-CoV-2 antibodies as well as memory cells T and B after recovery. In addition, the prevalence of COVID-19 reinfection, and the preventive efficacy of previous infection with SARS-CoV-2 were investigated.

Methods and analysesA synthesis of existing research was conducted. The Cochrane Library for COVID-19 resources, the China Academic Journals Full Text Database, PubMed, and Scopus as well as preprint servers were searched for studies conducted between 1 January 2020 to 1 April 2021. We included studies with the relevant outcomes of interest. All included studies were assessed for methodological quality and pooled estimates of relevant outcomes were obtained in a meta-analysis using a bias adjusted synthesis method. Proportions were synthesized with the Freeman-Tukey double arcsine transformation and binary outcomes using the odds ratio (OR). Heterogeneity between included studies was assessed using the I2 and Cochrans Q statistics and publication bias was assessed using Doi plots.

ResultsFifty-four studies, from 18 countries, with around 12 000 000 individuals, followed up to 8 months after recovery were included. At 6-8 months after recovery, the prevalence of SARS-CoV-2 specific immunological memory remained high; IgG - 90.4% (95%CI 72.2-99.9, I2=89.0%, 5 studies), CD4+ - 91.7% (95%CI 78.2 - 97.1, one study), and memory B cells 80.6% (95%CI 65.0-90.2, one study) and the pooled prevalence of reinfection was 0.2% (95%CI 0.0 - 0.7, I2 = 98.8, 9 studies). Individuals previously infected with SARS-CoV-2 had an 81% reduction in odds of a reinfection (OR 0.19, 95% CI 0.1 - 0.3, I2 = 90.5%, 5 studies).

ConclusionAround 90% of people previously infected with SARS-CoV-2 had evidence of immunological memory to SARS-CoV-2, which was sustained for at least 6-8 months after recovery, and had a low risk of reinfection.

RegistrationPROSPERO: CRD42020201234

What is already known on this topicIndividuals who recover from COVID-19 may have immunity against future infection but the proportion who develop immunity is uncertain. Further, there is uncertainty about the proportion of individuals who get reinfected with COVID-19.

What this study addsUsing data from 54 studies with follow up time up to 8 months after recovery, during the period February 2020-February 2021, we found that, post-COVID-19, up to 90% of individuals had antibodies and memory T and B cells against SARS-CoV-2. We also found a pooled prevalence of reinfection of 0.2%, and that infection conferred an 81% decrease in odds of reinfection with SARS-CoV-2, compared to unimmunized individuals without previous COVID-19.

This review of 12 million individuals presents evidence that most individuals who recover from COVID-19 develop immunological memory to SARS-CoV-2, which was still detectable for up to 8 months. Further, reinfection after recovery from COVID-19 was rare during the first 8 months after recovery, with a prevalence below 1%, while prior infection confers protection with an odds ratio of 0.19 and a preventive efficacy of 80% at a baseline prevalence of 5% for COVID-19 in a community.

Implications of all the available evidenceIndividuals with a history of COVID-19 infection have immunity against the disease for up to 8 months, although this period could be longer. These individuals could be prioritized last for COVID-19 vaccinations or considered for single dose vaccinations.

StrengthsThis comprehensive review addresses key questions on prevalent immunological memory and risk of reinfection in individuals with prior confirmed COVID-19 using robust systematic review methods.

LimitationsSome of the included studies which examined prevalent immunological memory were small studies which were affected by loss to follow up. The review did not examine evidence for immunity against the new divergent variants, which may be more likely to have immune evasion behaviour and may present a higher risk of reinfection. Lastly, the review did not examine the effect of the severity of COVID-19 on both immunological memory and the risk of reinfection.
Evaluation of the effectiveness of remdesivir in severe COVID-19 using observational data from a prospective national cohort study BackgroundRemdesivir has been evaluated in clinical trial populations, but there is a sparsity of evidence evaluating effectiveness in general populations.

MethodsAdults eligible to be treated with remdesivir, requiring oxygen but not ventilated, were identified from UK patients hospitalised with COVID-19. Patients treated with remdesivir within 24h of hospitalisation were compared with propensity-score matched controls; estimates of effectiveness were calculated for short-term outcomes (14-day mortality, 28-day mortality, time-to-recovery among others) using multivariable modelling.

Results9,278 out of 39,330 patients satisfied eligibility criteria. 1,549 patients were identified as  treated and matched with 4,964 controls. Patients were 62% male, mean (SD) age 63.1 (15.6) years, 80%  White ethnicity, and symptomatic for a median of 6 days prior to baseline. There was no statistically significant benefit of remdesivir at 14 days in terms of mortality or clinical status; there were signals of effectiveness in time-to-recovery after day 9, and a reduction in 28-day mortality.

ConclusionIn a real-world setting, initiation of remdesivir within 24h of hospitalisation in conjunction with standard of care was not associated with a benefit at 14 days but supports clinical trial evidence of a potential reduction in 28-day mortality. 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. 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. Effects of repeated injection of 1% lidocaine vs. radial extra-corporeal shock wave therapy for treating myofascial trigger points: a randomized controlled trial Background and ObjectivesThis study tested the hypothesis that treatment of myofascial trigger points (MTrPs) in the upper trapezius muscle (UTM) with repeated injection of 1% lidocaine results in better alleviation of muscular stiffness and soreness as well as improved metabolism in the hypercontracted MTrP area than treatment with radial extracorporeal shock wave therapy (rESWT).

Materials and MethodsA single-blinded, prospective, randomized controlled trial was conducted on patients suffering from MTrPs in the UTM. Thirty patients were treated with repeated injection of 2 ml of 1% lidocaine (three injections; one injection per week). Another 30 patients were treated with rESWT (three treatment sessions; one treatment session per week; 2000 radial extracorporeal shock waves per treatment session; positive energy flux density = 0.10 mJ/mm2). The primary outcome measure was pain severity using the VAS score. The secondary outcome measures included muscle elasticity index, pressure pain threshold and neck disability index. Evaluation was performed at baseline (T1), 15-30 minutes after the first treatment in order to register immediate treatment effects (T2), before the second treatment (i.e., one week after baseline) (T3) and one week after the third treatment (i.e., four weeks after baseline) (T4).

ResultsThere were no statistically significant differences in the primary and secondary outcome measures between the patients in the lidocaine arm and the patients in the rESWT arm at T1 and T4. Within the arms, the mean differences of all outcomes were statistically significant (P < 0.001) when comparing the data obtained at T1 with the data obtained at T3 and the data obtained at T4.

ConclusionsThe results of this pilot study suggest that the use of rESWT in patients with MTrPs in the UTM is safe and leads to reduced pain and improved muscle elasticty, pressure pain threshold and neck disability index, without adverse effects. Larger trials are necessary to verify this. Clinicians should consider rESWT instead of injections of lidocaine in the treatment of MTrPs in the UTM. COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness BackgroundMultiple COVID-19 vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh province, Pakistan (population: 48 million).

Methods and FindingsWe fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalization outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario.

We project that one-year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5 year duration of protection is likely to avert around 0.9 (95% Credible Interval: 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Varying these assumptions, we generally find that prioritizing the older (65+) population prevents more deaths, but broad distribution from the outset is economically comparable in many scenarios, and either scheme can be cost-effective for low per-dose costs. However, high vaccine prices ($10/dose) may not be cost-effective.

The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses.

These projections are limited by the mechanisms present in the model. Because the model is a single-population compartmental model, detailed impacts of non-pharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritizing groups like healthcare or other essential workers. Additionally, because the future impact and implementation cost of NPIs is uncertain, how these would interact with vaccination remains an open question.

ConclusionsCOVID-19 vaccination can have a considerable health impact, and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact, but the advantage of focusing initially on older, high-risk populations may be smaller in generally younger populations where many people have already been infected, typical of many low- and -middle income countries, as long as vaccination gives good protection against infection as well as disease.

Author SummaryO_ST_ABSWhy Was This Study Done?C_ST_ABS- The evidence base for health and economic impact of COVID-19 vaccination in low- and middle-income settings is limited.
- Searching PubMed, medRxiv, and econLit using the search term ("coronavirus" OR "covid" OR "ncov") AND ("vaccination" OR "immunisation") AND ("model" OR "cost" OR "economic") for full text articles published in any language between 1 January 2020 and 20 January 2021, returned 29 (PubMed), 1,167 (medRxiv) and 0 (econLit) studies: 20 overall were relevant, with only 4 exclusively focused on low- or middle-income countries (India, China, Mexico), while 3 multi-country analyses also included low- or middle-income settings,
- However only three of these studies are considered economic outcomes, all of them comparing the costs of vaccination to the costs of non-pharmaceutical interventions and concluding that both are necessary to reduce infections and maximise economic benefit.
- The majority of studies are set in high-income settings and conclude that targeting COVID-19 vaccination to older age groups is the preferred strategy to minimise mortality, particularly when vaccine supplies are constrained, while other age- or occupational risk groups should be priorities when vaccine availability increases or when other policy objectives are pursued.


What Did the Researchers Do and Find?- We combined epidemiological and economic analysis of COVID-19 vaccination based on real-world disease and programmatic information in the Sindh province of Pakistan.
- We found vaccination in this setting is likely to be highly cost-effective, and even cost saving, as long as the vaccine is reasonably priced and efficacy is high.
- Unlike studies in high-income settings, we also found that vaccination programmes targeting all adults may have almost as much benefit as those initially targeted at older populations, likely reflecting the higher previous infection rates and different demography in these settings.


What Do These Findings Mean?- Lower- and middle-income countries (LMICs) and international bodies providing guidance for LMICs need to consider evidence specific to these settings when making recommendations about COVID-19 vaccination.
- Further data and model-based analyses in such settings are urgently needed in order to ensure that vaccination decisions are appropriate to these contexts. Cell graph neural networks enable the digital staging of tumor microenvironment and precise prediction of patient survival in gastric cancer Gastric cancer is one of the deadliest cancers worldwide. Accurate prognosis is essential for effective clinical assessment and treatment. Spatial patterns in the tumor microenvironment (TME) are conceptually indicative of the staging and progression of gastric cancer patients. Using spatial patterns of the TME by integrating and transforming the multiplexed immunohistochemistry (mIHC) images as Cell-Graphs, we propose a novel graph neural network-based approach, termed Cell-Graph Signature or CGSignature, powered by artificial intelligence, for digital staging of TME and precise prediction of patient survival in gastric cancer. In this study, patient survival prediction is formulated as either a binary (short-term and long-term) or ternary (short-term, medium-term, and long-term) classification task. Extensive benchmarking experiments demonstrate that the CGSignature achieves outstanding model performance, with Area Under the Receiver-Operating Characteristic curve (AUROC) of 0.960{+/-}0.01, and 0.771{+/-}0.024 to 0.904{+/-}0.012 for the binary- and ternary-classification, respectively. Moreover, Kaplan-Meier survival analysis indicates that the  digital-grade cancer staging produced by CGSignature provides a remarkable capability in discriminating both binary and ternary classes with statistical significance (p-value < 0.0001), significantly outperforming the AJCC 8th edition Tumor-Node-Metastasis staging system. Using Cell-Graphs extracted from mIHC images, CGSignature improves the assessment of the link between the TME spatial patterns and patient prognosis. Our study suggests the feasibility and benefits of such artificial intelligence-powered digital staging system in diagnostic pathology and precision oncology. Using Adversarial Images to Assess the Stability of Deep Learning Models Trained on Diagnostic Images in Oncology PurposeDeep learning (DL) models have rapidly become a popular and cost-effective tool for image classification within oncology. A major limitation of DL models is output instability, as small perturbations in input data can dramatically alter model output. The purpose of the study is to investigate the robustness of DL models in the oncologic image domain through the application of adversarial images: manipulated images with small pixel-level perturbations designed to assess the stability of DL models.

Experimental DesignWe examined the impact of adversarial images on the classification accuracies of DL models trained to classify cancerous lesions across three common oncologic imaging modalities (CT, mammogram, and MRI). The CT model was trained to classify malignant lung nodules using the LIDC dataset. The mammogram model was trained to classify malignant breast lesions using the DDSM dataset. The MRI model was trained to classify brain metastases using an institutional dataset. We also explored the utility of an iterative adversarial training approach to improve the stability of DL models to small pixel-level changes.

ResultsOncologic images showed instability with small pixel-level changes. A pixel-level of perturbation of .004 resulted in a majority of oncologic images to be misclassified by their respective DL models (CT 25.64%, mammogram 23.93%, MRI 6.36%). Adversarial training mitigated improved the stability and robustness of DL models trained on oncologic images compared to naive models [(CT 67.72% vs 26.92%), mammogram (63.39% vs 27.68%), MRI (87.20% vs 24.32%)].

ConclusionsDL models naively trained on oncologic images exhibited dramatic instability to small pixel-level changes resulting in substantial decreases in accuracy. Adversarial training techniques improved the stability and robustness of DL models to such pixel-level changes. Prior to clinical implementation, adversarial training should be considered to proposed DL models to improve overall performance and safety. Serum Vitamin D levels are associated with increased COVID-19 severity and mortality independent of whole-body and visceral adiposity INTRODUCTIONCoronavirus disease (COVID-19) is a global pandemic. Vitamin D deficiency has been associated with susceptibility to infectious disease. In this study, the association between COVID-19 outcomes and vitamin D levels in patients attending a COVID-19 reference center in Mexico City are examined.

METHODSConsecutive patients with confirmed COVID-19 were evaluated. All patients underwent clinical evaluation and follow-up, laboratory measurements and a thoracic computerized tomography, including the measurement of epicardial fat thickness. Low vitamin D was defined as levels <20ng/mL (<50nmol/L) and deficient Vitamin D as a level [&le;]12ng/mL (<30nmol/L)

RESULTSOf the 551 patients included, low vitamin D levels were present in 45.6% and deficient levels in 10.9%. Deficient Vitamin D levels were associated with mortality (HR 2.11, 95%CI 1.24-3.58, p=0.006) but not with critical COVID-19, adjusted for age, sex, body-mass index and epicardial fat. Using model-based causal mediation analyses the increased risk of COVID-19 mortality conferred by low vitamin D levels was partly mediated by its effect on D-dimer and cardiac ultrasensitive troponins. Notably, increased risk of COVID-19 mortality conferred by low vitamin D levels was independent of BMI and epicardial fat.

CONCLUSIONVitamin D deficiency ([&le;]12ng/mL or <30nmol/L), is independently associated with COVID-19 mortality after adjustment for visceral fat (epicardial fat thickness). Low vitamin D may contribute to a pro-inflammatory and pro-thrombotic state, increasing the risk for adverse COVID-19 outcomes. Evaluating a first fully automated interview grounded in Multiple Mini Interview (MMI) methodology: results from a feasibility study ObjectivesGlobal, Covid-driven restrictions around face-to-face interviews for healthcare student selection have forced admissions staff to rapidly adopt adapted online systems before supporting evidence is available. We have developed, what we believe is, the first fully automated interview grounded in Multiple Mini-Interview (MMI) methodology. This study aimed to explore test re-test reliability, acceptability and usability of the system.

Design, setting and participantsmixed-methods feasibility study in Physician Associate (PA) programmes from two UK and one US university during 2019 - 2020.

Primary, secondary outcomesFeasibility measures (test retest reliability acceptability and usability) were assessed using intra-class correlation (ICC), descriptive statistics, thematic and content analysis.

MethodsVolunteers took (T1), then repeated (T2), the automated MMI, with a seven-day interval (+/- 2) then completed an evaluation questionnaire. Admissions staff participated in focus group discussions.

ResultsSixty-two students and seven admission staff participated; 34 students and four staff from UK and 28 students and three staff from US universities.

Good-excellent test-retest reliability was observed with T1 and T2 ICC between 0.62-0.81 (p<0.001) when assessed by individual total scores (range 80.6-119), station total scores 0.6-0.91, p<0.005, individual site (all ICC[&ge;] 0.76 p<0.001) and mean test retest across sites 0.82 p<0.001 (95% CI 0.7-0.9).

Admissions staff reported potential to reduce resource costs and bias through a more objective screening tool for pre-selection or to replace some MMI stations in a  hybrid model. Maintaining human interaction through  touch points was considered essential.

Users positively evaluated the system, stating it was intuitive with an accessible interface. Concepts chosen for dynamic probing needed to be appropriately tailored.

ConclusionThese preliminary findings suggest that the system is reliable, generating consistent scores for candidates and is acceptable to end-users provided human touchpoints are maintained. Thus, there is evidence for the potential of such an automated system to augment healthcare student selection processes. Applying Benford's law to COVID-19 data: The case of the European Union Previous studies have used Benfords distribution to assess whether there is misreporting of COVID-19 cases and deaths. Data inaccuracies provide false information to the media, undermine global response, and hinder the preventive measures taken by countries worldwide. In this study, daily new cases and deaths from all the countries of the European Union were analyzed and the conformance to Benfords distribution was estimated. For each country, two statistical tests and two measures of deviation were calculated to determine whether the reported statistics comply with the expected distribution. Four country-level developmental indexes were also included, the GDP per capita, health expenditures, the Universal Health Coverage index, and the full vaccination rate. Regression analysis was implemented to show whether the deviation from Benfords distribution is affected by the aforementioned indexes. The findings indicate that four countries were in line with the expected distribution, Bulgaria, Croatia, Lithuania, and Romania. For the daily cases, Denmark, Greece, and Ireland, showed the greatest deviation from Benfords distribution and for deaths, Malta, Cyprus, Greece, Italy, and Luxemburg exhibited the highest deviation from Benfords law. Furthermore, it was found that the vaccination rate is positively associated with deviation from Benfords distribution. These results suggest that overall, official data provided by authorities are not confirming Benfords law, yet this approach is not conclusive; it acts as a preliminary tool for data verification. More extensive studies should be made with a more thorough investigation of countries that showed the greatest deviation. "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

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

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

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need. 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. Relationship Between Patient Sex and Serum Tumor Necrosis Factor Antagonist Drug and Anti-Drug Antibody Concentrations in Inflammatory Bowel Disease; A Nationwide Cohort Study BackgroundAnti-drug antibodies to infliximab (ATI) and adalimumab (ATA) are associated with loss of response to tumor necrosis factor antagonist (anti-TNF) therapy in inflammatory bowel disease (IBD). We evaluated the relationship between patient sex and serum TNF antagonist drug and antibody concentrations in inflammatory bowel disease

MethodsA nationwide multicenter retrospective cohort study was conducted by evaluating patients charts from July 2018 until September 2021. The effect of patient sex on anti-drug antibodies and serum drug concentration in patients with IBD across 7 hospitals was investigated. A subgroup analysis also investigated the effect of anti-TNF combination therapy. Geometric means were calculated, and multiple linear regression was used to estimate the adjusted ratio of geometric means (RoGM) and their 95% confidence intervals (CI).

ResultsIn the total study sample (n = 1093), males receiving infliximab had higher anti-drug antibody concentrations (38.3 vs. 22.3 AU/ml; aRoGM = 1.72, 95% CI: 1.30-2.27, p-value <0.001) compared to females. Additionally, infliximab serum drug concentrations among males were lower compared to females (2.6 vs. 4.1 ug/ml; aRoGM = 0.62, 95% CI: 0.44-0.88, p-value = 0.007). In the subgroup analysis (n = 359), male compared to female patients on combination therapy with infliximab and immunomodulators had similar anti-drug antibody concentrations (30.2 vs. 21.9 AU/ml; aRoGM = 1.38, 95% CI: 0.79-2.40, p-value = 0.254). There was no difference in the anti-drug antibody and serum drug concentrations among males and females on adalimumab.

ConclusionIn patients receiving infliximab, anti-drug antibodies were higher in males than females. Consistent with this, serum drug concentrations were lower in males than females on infliximab. There was no difference in anti-drug antibody and serum drug concentrations among males and females on adalimumab. In addition, no difference in anti-drug antibodies between males and females receiving anti-TNF combination therapy was observed. 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.) 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. Hepatic resection versus transarterial chemoembolization for the intermediate stage hepatocellular carcinoma：A cohort study BackgroundThe selection criterion for hepatic resection(HR) in intermediate-stage(IM) hepatocellular carcinoma(HCC) is still controversial. We used real-world data to evaluate the overall survival (OS) treated with HR or TACE.

MethodsIn all, 942 patients with IM-HCC were categorized in HR and TACE groups. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score- matched (PSM) analyses. The smooth curve was performed through the generalized additive model. The interaction test was performed to evaluate the HR impact on OS concerning risk factors. Also, we used multiple imputation to deal with the missing data.

ResultsTotally, 23.0% (n=225) of patients received HR. At a median overall survival of 23.7 months, HR was associated with the improved OS on multivariate analysis (hazard ratio, 0.45; 95%CI: 0.35, 0.58; after PSM: 0.56; 95%CI: 0.41, 0.77). Landmark analyses limited to long-term survivors of [&ge;] 6 months, [&ge;] 1, and [&ge;] 2 years demonstrated better OS with HR in all subsets (all P<0.05). After PSM analysis, however, HR increased 20% risk of death (HR, 1.20; 95%CI: 0.67, 2.15) in the subgroup of LDH [&le;]192 U/L (P for interaction = 0.037). Furthermore, the significant interaction was robust between the LDH and the HR with respect to 1-, 3-, and 5-year observed survival rate (all P<0.05).

ConclusionHepatic resection was superior to TACE for intermediate-stage HCC in the range of LDH level > 192 U/L. Moreover, TACE might be suitable for patients with LDH level [&le;] 192 U/L.

SynopsisO_LIHepatectomy was superior to TACE for BCLC-B HCC.
C_LIO_LIHepatectomy increased 20% risk of death for LDH < 192 U/L after matching.
C_LIO_LIA significant interaction was robust between LDH and with respect to hepatectomy the 1-, 3-, and 5-year observed survival rate.
C_LI 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. Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of 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. COVID-19 vaccine-associated cerebral venous thrombosis in Germany ObjectiveReports of cerebral sinus and venous thrombosis (CVT) after ChAdOx1 vaccination against SARS-CoV-2 have raised safety concerns. We aimed to estimate the incidence of CVT within one month from first dose administration and the frequency of vaccine-induced immune thrombotic thrombocytopenia (VITT) as the underlying mechanism after vaccination with BNT162b2, ChAdOx1, and mRNA-1273, in Germany.

MethodsA web-based questionnaire was e-mailed to all Departments of Neurology. We asked to report cases of CVT within one month of a COVID-19 vaccination. Other cerebral events could also be reported. Incidence rates of CVT were calculated by using official statistics of nine German States.

ResultsA total of 45 CVT cases were reported. In addition, 9 primary ischemic strokes, 4 primary intracerebral hemorrhages, and 4 other neurological events were recorded. Of the CVT patients, 35 (77.8%) were female, and 36 (80.0%) were below the age of 60 years. Fifty-three events were observed after vaccination with ChAdOx1 (85.5%), 9 after BNT162b2 (14.5%), and none after mRNA-1273 vaccination. After 7,126,434 first vaccine doses, the incidence rate of CVT within one month from first dose administration was 6.5 (95% CI, 4.4-9.2) per 100,000 person-years for all vaccines and 17.9 (11.8-26.1) for ChAdOx1 (after 2,320,535 ChAdOx1 first doses). The adjusted incidence rate ratio was 9.68 (3.46-34.98) for ChAdOx1 compared to mRNA-based vaccines and 3.14 (1.22-10.65) for women compared to non-women. In 26/45 patients with CVT (57.8%), VITT was graded highly probable.

ConclusionsGiven an incidence of 0.22-1.75 per 100,000 person-years for CVT in the general population, these findings point towards a higher risk for CVT after ChAdOx1 vaccination, especially for women. A novel echo-parameter supersedes the Society of Thoracic Surgeons risk score in predicting post transcatheter aortic valve replacement mortality ObjectiveTo accurately predict post-TAVR mortality, we proposed a family of new echo-parameters (augmented blood pressure) derived from blood pressure and aortic valve gradient measurements and examined them in this study.

Patients and MethodsPatients in the Mayo Clinic National Cardiovascular Diseases Registry-TAVR database who underwent TAVR between January 1, 2012, and June 30, 2017, were identified to retrieve baseline demographics, echocardiographic and mortality data. Augmented blood pressure parameters and valvulo-arterial impedance were evaluated by univariate and multivariate Cox regression. Receiver operating characteristic curve analysis was used to assess the model performance against the Society of Thoracic Surgeons (STS) risk score.

ResultsThe final cohort contained 974 patients with a mean age of 81.4{+/-}8.3 years old, and 56.6% were male. The mean STS risk score was 8.2{+/-}5.2. The median follow-up duration was 354 days, and the one-year all-cause mortality rate was 14.2%. Both univariate and multivariate Cox regression showed that augmented systolic blood pressure and augmented mean arterial pressure (AugMAP) parameters were independent predictors for 1-year post-TAVR mortality (all p<0.0001). A univariate model of AugMAP1 supersedes the STS score model in predicting 1-year post-TAVR mortality (area under curve: 0.700 vs. 0.587, p=0.0051).

ConclusionAugmented mean arterial pressure provides a simple but effective approach for clinicians to quickly estimate the clinical outcome of TAVR patients. It can be incorporated in the assessment of TAVR candidacy. Virtual reality intervention alleviates dyspnea in patients recovering from COVID pneumonia BackgroundImmersive virtual reality (iVR)-based digital therapeutics (DTx) are gaining clinical attention in the field of pain management. Based on known analogies between pain and dyspnea, we investigated the effects of visual-respiratory feedback, on persistent dyspnea in patients recovering from COVID-19 pneumonia.

MethodsWe performed a controlled, randomized, single-blind, cross-over clinical study to evaluate an iVR-based intervention to alleviate dyspnea in patients recovering from COVID-19 pneumonia. Included patients reported persistent dyspnea ([&ge;]5 on a 10-point scale) and preserved cognitive function (MoCA>24). Assignment was random and concealed. Patients received synchronous (intervention) or asynchronous (control) feedback of their breathing, embodied via a gender-matched virtual body. Outcomes were assessed using questionnaires and breathing recordings. COVVR is registered with ClinicalTrials.gov (NCT04844567).

FindingsStudy enrollment was open between November 2020 and April 2021. Twenty-six patients were enrolled (27% women; age: median=55, interquartile range (IQR)=18). Data were available for 24 of 26 patients. The median (IQR) rating on a 7-point Likert-scale of breathing comfort improved from 1(2) at baseline, to 2(1) for synchronous feedback, but remained unchanged at 1(1.5) for asynchronous feedback (p<0.05) between iVR conditions). Moreover, 91.2% of all patients were satisfied with the intervention (p<0.0001) and 66.7% perceived it as beneficial for their breathing (p<0.05). No adverse events were reported.

InterpretationBased on these findings, our iVR-based DTx presents a feasible and safe respiratory rehabilitation tool that improves breathing comfort in patients recovering from COVID-19 infection presenting with persistent dyspnea. Future research should investigate the DTxs generalizability to persistent dyspnea with other etiologies and its potential for preventing chronification.

FundingMarie Sklodowska-Curie Individual Fellowship (H2020-MSCA-IF-2019 894111/ RESPVR), Bertarelli Foundation Statistical modeling for quality risk assessment of clinical trials: follow-up at the era of remote auditing BackgroundAs investigator site audits have largely been conducted remotely during the COVID-19 pandemic, remote quality monitoring has gained some momentum. To further facilitate the conduct of remote Quality Assurance (QA) activities for clinical trials, we developed new quality indicators, building on a previously published statistical modeling methodology.

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

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

ConclusionContinuous surveillance of the identified risk factors and resulting risk estimates could be used to complement remote QA strategies for clinical trials and help to manage audit targets and audit focus also in post-pandemic times. A protocol for a multicentre observational study across an integrated care system to understand the effect of living with frailty on access to video consultations Risks for digital exclusion include older age, disability, and deprivation. No literature exists examining frailty as an additional possible risk factor. Many studies have shown frailty to be a more accurate predictor of adverse outcome in healthcare than age alone. Understanding risk factors for digital exclusion may help healthcare services appropriately tailor interventions. The Healthier Together integrated care system (HTICS) in Bristol is developing video consultations for clinics. The aim of this prospective observational cross-sectional study is to identify whether living with frailty is a risk factor of digital exclusion from video consultation. Data will be collected using a structured survey including patients from three sites across the Heal secondary care services at North Bristol Trust, and then two subsequent sites will be included across HTICS. Data will be collected on known risk factors for digital exclusion, frailty using the Clinical Frailty Scale, and will cover four domains for digital exclusion as defined by NHS Digital: access, skill, motivation, and confidence. Data will be presented with descriptive statistics. The association between frailty and outcomes will be analysed with a multivariable logistic regression.

Key Study Contacts

O_TBL View this table:
org.highwire.dtl.DTLVardef@134f5d7org.highwire.dtl.DTLVardef@1f8149forg.highwire.dtl.DTLVardef@11dbf0org.highwire.dtl.DTLVardef@7e854borg.highwire.dtl.DTLVardef@61272f_HPS_FORMAT_FIGEXP  M_TBL C_TBL Study Summary

O_TBL View this table:
org.highwire.dtl.DTLVardef@53a9f0org.highwire.dtl.DTLVardef@b9e76dorg.highwire.dtl.DTLVardef@108bd12org.highwire.dtl.DTLVardef@b500ddorg.highwire.dtl.DTLVardef@14be1d8_HPS_FORMAT_FIGEXP  M_TBL C_TBL Funding and Support in Kind

O_TBL View this table:
org.highwire.dtl.DTLVardef@d86811org.highwire.dtl.DTLVardef@1985973org.highwire.dtl.DTLVardef@118ca5corg.highwire.dtl.DTLVardef@8d7839org.highwire.dtl.DTLVardef@1cff6e1_HPS_FORMAT_FIGEXP  M_TBL C_TBL Role of Study Sponsor and FunderThe pilot at North Bristol Trust (NBT) is overseen by Neuromusculoskeletal (NMSK) Division governance. NBT NMSK Division takes responsibility for ensuring that the design of the study meets appropriate standards and that arrangements are in place to ensure appropriate conduct and reporting. Governance oversight for Hospital at Home was registered with NBT NMSK, and for primary care with Horfield Health Centre.

Roles and Responsibilities

Study Flow Chart

O_TBL View this table:
org.highwire.dtl.DTLVardef@594232org.highwire.dtl.DTLVardef@904b3org.highwire.dtl.DTLVardef@138af7org.highwire.dtl.DTLVardef@10898a3org.highwire.dtl.DTLVardef@15d2719_HPS_FORMAT_FIGEXP  M_TBL C_TBL