Do school closures and school reopenings affect community transmission of COVID-19? A systematic review of observational studies BackgroundSchool closures are associated with significant negative consequences and exacerbate inequalities. They were implemented worldwide to control SARS-CoV-2 in the first half of 2020, but their effectiveness, and the effects of lifting them, remain uncertain. This review summarises observational evidence of the effect of school closures and school reopenings on SARS-CoV-2 community transmission.

MethodsThe study protocol was registered on Prospero (ID:CRD42020213699). On 07 January 2021 we searched PubMed, Web of Science, Scopus, CINAHL, the WHO Global COVID-19 Research Database, ERIC, the British Education Index, the Australian Education Index, and Google. We included observational studies with quantitative estimates of the effect of school closures/reopenings on SARS-CoV-2 community transmission. We excluded prospective modelling studies and intra-school transmission studies. We performed a narrative synthesis due to data heterogeneity. We used the ROBINS-I tool to assess risk of bias.

FindingsWe identified 7,474 articles, of which 40 were included, with data from 150 countries. Of these 32 studies assessed school closures, and 11 examined reopenings. There was substantial heterogeneity between school closure studies, with half of the studies at lower risk of bias reporting reduced community transmission by up to 60%, and half reporting null findings. The majority (n=3 out of 4) of school reopening studies at lower risk of bias reported no associated increases in transmission.

ConclusionsSchool closure studies were at risk of confounding and collinearity from other non-pharmacological interventions implemented around the same time as school closures, and the effectiveness of closures remains uncertain. School reopenings, in areas of low transmission and with appropriate mitigation measures, were generally not accompanied by increasing community transmission. With such varied evidence on effectiveness, and the harmful effects, policymakers should take a measured approach before implementing school closures; and should look to reopen schools in times of low transmission, with appropriate mitigation measures.
Does COVID-19 vaccination improve mental health? A difference-in-difference analysis of the Understanding Coronavirus in America study BackgroundMental health problems increased during the COVID-19 pandemic. Knowledge that one is less at risk after being vaccinated may alleviate distress, but this hypothesis remains unexplored. Here we test whether psychological distress declined in those vaccinated against COVID-19 in the US and whether changes in perceived risk mediated any association.

MethodsA nationally-representative cohort of U.S. adults (N=5,792) in the Understanding America Study were interviewed every two weeks from March 2020 to June 2021 (28 waves). Difference-in-difference regression tested whether getting vaccinated reduced distress (PHQ-4 scores), with mediation analysis used to identify potential mechanisms, including perceived risks of infection, hospitalization, and death.

ResultsVaccination was associated with a 0.09 decline in distress scores (95% CI:-0.15 to -0.04) (0-12 scale), a 5.7% relative decrease compared to mean scores in the wave prior to vaccination. Vaccination was also associated with an 8.44 percentage point reduction in perceived risk of infection (95% CI:-9.15% to -7.73%), a 7.44-point reduction in perceived risk of hospitalization (95% CI:-8.07% to -6.82%), and a 5.03-point reduction in perceived risk of death (95% CI:-5.57% to -4.49%). Adjusting for risk perceptions decreased the vaccination-distress association by two-thirds. Event study models suggest vaccinated and never vaccinated respondents followed similar PHQ-4 trends pre-vaccination, diverging significantly post-vaccination. Analyses were robust to individual and wave fixed effects, time-varying controls, and several alternative modelling strategies. Results were similar across sociodemographic groups.

ConclusionReceiving a COVID-19 vaccination was associated with declines in distress and perceived risks of infection, hospitalization, and death. Vaccination campaigns could promote these additional benefits of being vaccinated.
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. An Updated Systematic Review and Meta-Analysis of Mortality, Need for ICU admission, Use of Mechanical Ventilation, Adverse effects and other Clinical Outcomes of Ivermectin Treatment in COVID-19 Patients ImportanceRepurposing Ivermectin, a known anti-parasitic agent, for treating COVID-19 has demonstrated positive results in several studies. We aim to evaluate the benefit and risk of Ivermectin in COVID-19.

MethodsWe conducted a systematic search for full-text manuscripts published from February 1, 2020, to August 15th, 2021 focusing on Ivermectin therapy against COVID-19. The primary outcomes were mortality, need for intensive care unit (ICU) admission; secondary outcomes were - adverse effects, need for mechanical ventilation, viral clearance, time to viral clearance, need for hospitalization, and length of hospital stay. Random-effects models were used for all analyses.

ResultsWe included a total of 52 studies (n=17561) in the qualitative analysis, out of these, 44 studies (n=14019) were included in the meta-analysis. In the mortality meta-analysis (N=29), odds of death were lower in the Ivermectin-arm compared to control (OR 0.54, p=0.009). Although lower odds of mortality were observed in various subgroup analyses of RCTs, they did not reach statistical significance: therapeutic RCTs: mild-moderate COVID-19 (OR 0.31, p=0.06), therapeutic RCTs: severe/critical COVID-19 (OR 0.86, p=0.56), inpatient RCTs: mild-moderate COVID-19 (OR 0.18, p=0.08), inpatient RCTs: severe/critical COVID-19 (OR 0.86, p=0.56). Ivermectin, mostly as adjuvant therapy, was associated with higher odds of viral clearance (N=22) (OR 3.52, p=0.0002), shorter duration to achieve viral clearance (N=8) (MD - 4.12, p=0.02), reduced need for hospitalization (N=6) (OR 0.34, p=008).

ConclusionOur meta-analysis suggests that the mortality benefit of Ivermectin in COVID-19 is uncertain. But as adjuvant therapy, Ivermectin may improve viral clearance and reduce the need for hospitalization.

HighlightsO_ST_ABSWhat We Already Know about This TopicC_ST_ABSO_LICOVID-19 is an ongoing global pandemic, for which Ivermectin has been tried on a therapeutic and prophylactic basis.
C_LIO_LIResults from several clinical trials and observational studies suggest that Ivermectin may improve survival and clinical outcomes with a good safety profile when compared with other treatments; however, the current evidence is limited..
C_LI

What This Article Tells Us That Is NewO_LIThis systematic review and meta-analysis provide a summary of the latest literature on the efficacy and safety of Ivermectin use for COVID-19.
C_LIO_LIBased on our analysis of the latest evidence, we found that Ivermectins benefit in reducing mortality cannot be concluded with confidence. However, as an adjuvant therapy it may help reduce the need for hospitalization, duration for viral clearance while increasing the likelihood of achieving viral clearance.
C_LIO_LIWe need more high-quality data for conclusive evidence regarding the benefit of Ivermectin in reducing the need for ICU admissions, mechanical ventilation and duration of hospital stay in COVID-19 patients.
C_LI Human lipoproteins comprise at least 12 different classes that are lognormally distributed. Lipoproteins in medical samples have been measured by enzymatic methods that coincide with conventional ultracentrifugation. However, the high gravity and time required for ultracentrifugation can cause sample degradation. This study presents the results of HPLC, a gentler and rapid separation method, for 55 human serum samples. The elution patterns were analysed parametrically, and the attribute of each class was confirmed biochemically. Human samples contained 12 classes of lipoproteins, each of which may consist primarily of proteins. There are three classes of VLDLs. The level of each class was distributed lognormally, and the standard amount and the 95% range were estimated. Enzymatic methods measure the levels of several mixed classes. This lognormal character suggests that the levels are controlled by the synergy of multiple factors. 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. Correcting the Reproduction Number for Time-Varying Tests: a Proposal and an Application to COVID-19 in France We provide a novel way to correct the effective reproduction number for the time-varying amount of tests, using the acceleration index as a simple measure of viral spread dynamics (Baunez et al., 2021). Not doing so results in the reproduction number being a biased estimate of viral acceleration and we provide a formal decomposition of the resulting bias, involving the useful notions of test and infectivity intensities. When applied to French data for the COVID-19 pandemic (May 13 - November 19, 2020), our decomposition shows that the reproduction number, when considered alone, consistently underestimates the resurgence of the pandemic since the summer of 2020, compared to the acceleration index which accounts for the time-varying volume of tests. Because the acceleration index aggregates all relevant information and captures in real time the sizable time variation featured by viral circulation, it is a more parsimonious indicator to track the dynamics of an infectious disease outbreak in real time, compared to the equivalent alternative which would be to complement the reproduction number with the test and infectivity intensities. In situ transcriptional profile of a germinal center plasmablastic burst hints at MYD88/CD79B mutants-enriched Diffuse Large B-cell Lymphomas. The germinal center (GC) reaction results in the selection of B-cells acquiring effector Ig secreting ability by progressing towards plasmablastic differentiation. This transition is associated with exclusion from the GC microenvironment. The aberrant expansion of plasmablastic elements within the GC fringes configures an atypical condition, the biological characteristics of which have not been defined yet. We investigated the in situ immunophenotypical and transcriptional characteristics of a non-clonal germinotropic expansion of plasmablastic elements (GEx) occurring in the tonsil of a young patient. Compared to neighboring GC and peri-follicular regions, the GEx showed a distinctive signature featuring key regulators of plasmacytic differentiation, cytokine signaling, and cell metabolism. The GEx signature was tested in the setting of diffuse large B-cell lymphoma (DLBCL) as a prototypical model of lymphomagenesis encompassing transformation at different stages of GC and post-GC functional differentiation. The signature outlined DLBCL clusters with different immune microenvironment composition and enrichment in genetic subtypes.

SignificanceThis report represents the first insight into the transcriptional features of a germinotropic plasmablastic burst, shedding light into the molecular hallmarks of B cells undergoing plasmablastic differentiation and aberrant expansion within the non-canonical setting of the GC microenvironment. Genetic factors affecting immune phenotypes in type 1 diabetes Large inter-individual variability in immunological cell composition and function determines immune responses in general and susceptibility to immune-mediated diseases in particular. While much has been learned about the genetic variants relevant for type 1 diabetes, the pathophysiological mechanisms through which these variations exert their effects are unknown. In this study, we characterize the genetic factors influencing immune responses in patients with type 1 diabetes. Genetic variants that determine susceptibility to T1D significantly affect T cell composition. Specifically, the CCR5+ regulatory T cells associate with T1D through the CCR region, suggesting a shared genetic regulation. Genome-wide quantitative trait loci (QTL) mapping analysis of immune traits revealed 15 genetic loci that influence immune responses in T1D. Among them, 12 have never been reported in healthy population studies, implying a disease-specific genetic regulation. Altogether this study provides new insights into the genetic factors that affect immunological responses in T1D. What delirium detection tools are used in routine clinical practice in the United Kingdom? Survey results from 91% of acute healthcare organisations. PurposeOur aim was to collect information on delirium assessment processes and pathways in non-intensive care settings in the United Kingdom (UK).

MethodsWe sent a Freedom of Information request to 169 UK National Health Service (NHS) hospitals, trusts and health boards (units) in July 2020 to obtain data on usage of delirium assessment tools in clinical practice and delirium pathways or guidelines.

ResultsWe received responses from 154/169 units (91% response rate). Of these, 146/154 (95%) units reported use of formal delirium assessment processes and 131/154 (85%) units had guidelines or pathways in place. The 4  As Test (4AT) was the most widely used tool, with 117/146 (80%) units reporting use. The Confusion Assessment Method was used in 65/146 (45%) units, and the Single Question to identify Delirium (SQiD) in 52/146 (36%) units.

ConclusionsOur findings show that the 4AT is the most commonly used tool in the UK, with 80% of units reporting use. This study adds to our knowledge of real-world uptake of delirium detection methods at scale. Future studies should evaluate real-world implementation of delirium assessment tools further via (i) tool completion rates and (ii) rates of positive scores against the expected prevalence delirium in the clinical population concerned.

KEY SUMMARY POINTSO_ST_ABSAimC_ST_ABSTo seek information on delirium assessment processes and pathways in non-intensive clinical care settings in the United Kingdom (UK), and to assess usage of specific delirium assessment tools: the 4  As Test (4AT), Confusion Assessment Method and Single Question to identify Delirium (SQiD).

FindingsIn total, 95% of National Health Service (NHS) units (hospitals, trusts and health boards) reported use of formal delirium assessment processes and 85% of units had guidelines or pathways in place. The 4AT was the most widely used tool, with 80% of units reporting use; the Confusion Assessment Method was reportedly used in 45% of units and the SQiD in 36% of units.

MessageThis study shows real-world, large-scale uptake of delirium detection methods and delirium guidelines in UK hospitals, which contributes to ongoing efforts to improve delirium care. Impact of HIV Infection on COVID-19 Outcomes Among Hospitalized Adults in the U.S. BackgroundWhether HIV infection is associated with differences in clinical outcomes among people hospitalized with COVID-19 is uncertain.

ObjectiveTo evaluate the impact of HIV infection on COVID-19 outcomes among hospitalized patients.

MethodsUsing the American Heart Associations COVID-19 Cardiovascular Disease registry, we used hierarchical mixed effects models to assess the association of HIV with in-hospital mortality accounting for patient demographics and comorbidities and clustering by hospital. Secondary outcomes included major adverse cardiac events (MACE), severity of illness, and length of stay (LOS).

ResultsThe registry included 21,528 hospitalization records of people with confirmed COVID-19 from 107 hospitals in 2020, including 220 people living with HIV (PLWH). PLWH were younger (56.0+/-13.0 versus 61.3+/-17.9 years old) and more likely to be male (72.3% vs 52.7%), Non-Hispanic Black (51.4% vs 25.4%), on Medicaid (44.5% vs 24.5), and active tobacco users (12.7% versus 6.5%).

Of the study population, 36 PLWH (16.4%) had in-hospital mortality compared with 3,290 (15.4%) without HIV (Risk ratio 1.06, 95%CI 0.79-1.43; risk difference 0.9%, 95%CI -4.2 to 6.1%; p=0.71). After adjustment for age, sex, race, and insurance, HIV was not associated with in-hospital mortality (aOR 1.13; 95%CI 0.77-1.6; p 0.54) even after adding body mass index and comorbidities (aOR 1.15; 95%CI 0.78-1.70; p=0.48). HIV was not associated with MACE (aOR 0.99, 95%CI 0.69-1.44, p=0.91), severity of illness (aOR 0.96, 95%CI 0.62-1.50, p=0.86), or LOS (aOR 1.03; 95% CI 0.76-1.66, p=0.21).

ConclusionHIV was not associated with adverse outcomes of COVID-19 including in-hospital mortality, MACE, or severity of illness.

Condensed AbstractWe studied 21,528 patients hospitalized with COVID-19 at 107 hospitals in AHAs COVID-19 registry to examine the association between HIV and COVID-19 outcomes. More patients with HIV were younger, male, non-Hispanic Black, on Medicaid and current smokers. HIV was not associated with worse COVID-19 in-hospital mortality (Risk ratio 1.06, 95%CI 0.79-1.43; p=0.71) even after adjustment (aOR 1.15; 95%CI 0.78-1.70; p=0.48). HIV was also not associated with MACE (aOR 0.99, 95%CI 0.69-1.44, p=0.91) or severity of illness (aOR 0.96, 95%CI 0.62-1.50, p=0.86. Our findings do not support that HIV is a major risk factor for adverse COVID-19 outcomes. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. 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.) 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. Knee-extensor strength, symptoms, and need for surgery after two, four, or six exercise sessions/week using a home-based one-exercise program: A randomized dose-response trial of knee-extensor resistance exercise in patients eligible for knee replacement (the QUADX-1 trial). ObjectiveTo investigate firstly the efficacy of three different dosages of one home-based, knee-extensor resistance exercise on knee-extensor strength in patients eligible for knee replacement, and secondly, the influence of exercise on symptoms, physical function and decision on surgery.

MethodOne-hundred and forty patients eligible for knee replacement were randomized to three groups: 2, 4 or 6 home-based knee-extensor resistance exercise-sessions per week (group 2, 4 and 6 respectively) for 12 weeks. Primary outcome: isometric knee-extensor strength. Secondary outcomes: Oxford Knee Score, Knee injury and Osteoarthritis Outcome Score, average knee pain last week (0-10 numeric rating scale), 6-minute walk test, stair climbing test, exercise adherence and "need for surgery".

ResultsPrimary analysis: Intention-to-treat analysis of 140 patients did not find statistically significant differences between the groups from baseline to after 12 weeks of exercise in isometric knee-extensor strength: Group 2 vs. 4 (0.003 Nm/kg (0.2%) [95% CI -0.15 to 0.15], P=0.965) and group 4 vs. 6 (-0.04 Nm/kg (-2.7%) [95% CI -0.15 to 0.12], P=0.628). Secondary analysis: Intention-to-treat analyses showed statistically significant differences between the two and six sessions/week groups in favor of the two sessions/week group for Oxford Knee Score: 4.8 OKS points (15.2%) [1.3 to 8.3], P=0.008) and avg. knee pain last week (NRS 0-10): - 1.3 NRS points (-19.5%) [-2.3 to -0.2], P=0.018. After the 12-week exercise intervention, data were available for 117 patients (N=39/group): 38 (32.5%) patients wanted surgery and 79 (67.5%) postponed surgery. This was independent of exercise dosage.

ConclusionIn patients eligible for knee-replacement we found no between-group differences in isometric knee extensor strength after 2, 4 and 6 knee-extensor resistance exercise sessions per week. We saw no indication of an exercise dose-response relationship for isometric knee-extensor strength and only clinically irrelevant within group changes. For some secondary outcome (e.g. KOOS subscales) we found clinically relevant within group changes, which could help explain why only one in three patients decided to have surgery after the simple home-based exercise intervention.

Trial registrationClinicalTrials.gov identifier: NCT02931058. Preprint: https://doi.org/10.1101/2021.04.07.21254965. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

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

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

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Echocardiographic characterisation in critical Covid19 - an observational study ObjectiveWe aimed to investigate the acute cardiac effects of severe SARS-CoV-2.

MethodsThis is an observational study generated from the first 79 patients admitted to Uppsala intensive care due to respiratory failure with SARS-CoV-2 infection. 34 underwent echocardiography of which 25 were included in the study and compared to 44 non-echo patients. Exclusion was based on absence of normofrequent sinus rhythm and mechanical respiratory support. Biomarker analysis was carried out on all patients.

ResultsMortality was increased in the echo compared to non-echo group (44 % vs. 16%, p<0.05). Right sided dimensions and functional parameters were not affected. Tricuspid regurgitation velocity indicated how increased pulmonary artery pressure was associated with mortality (survivors (n=5): 2.51 {+/-} 0.01 m/s vs. non-survivors (n=5): 3.06 {+/-} 0.11 m/s, p<0.05). Cardiac markers and D-dimer correlated to initiation of echocardiography (hs-TnI (ng/L): echo (n=23): 133 {+/-} 45 vs. non-echo (n=41): 81.3 {+/-} 45, p<0.01; NTproBNP (ng/L): echo (n=25): 2959 {+/-} 573 vs. non-echo (n=42): 1641 {+/-} 420, p<0.001; D-dimer (mg/L): echo (n=25): 16.1 {+/-} 3.7 vs. non-echo (n=43: 6.1 {+/-} 1.5, p<0.01) and mortality (hs-TnI (ng/L): survivors (n=48): 59.1 {+/-} 21 vs. non-survivors (n=17): 211 {+/-} 105, p<0.0001; NT-proBNP (ng/L): survivors (n=47): 1310 {+/-} 314 vs. non-survivors (n=20): 4065 {+/-} 740, p<0.0001; D-dimer (mg/L): survivors (n=50): 7.2 {+/-} 1.5 vs. non-survivors (n=18): 17.1 {+/-} 4.8, p<0.01). All intervals refer to standard error of the mean. Tricuspid regurgitation velocity was correlated with troponin I (r=0.93, r2=0.74, p<0.001, n=10).

ConclusionsThese results suggest that there is no clear negative effect on cardiac function in critical SARS-CoV-2. There are indications that pulmonary pressure elevation carries a negative predictive outcome suggesting pulmonary disease as the driver of mortality. Cardiac biomarkers as well as D-dimer carry predictive value.

Trial registration numberPatients were included in "Clinical trials NCT04316884"

Article summaryO_ST_ABSStrength and limitations of this studyC_ST_ABS- The patient body is recruited from all patients admitted to ICU in need of mechanical respiratory support independent of background which makes it relevant to clinical practice.
- The echocardiographic image acquisition was carried out by hospital assigned agents on clinical indication, which makes the results applicable in a clinical setting.
- Since the image acquisition was carried out on a clinical indication, the results may be skewed towards the false positive if applied to all Covid19 patients. Generalized Prediction of Hemodynamic Shock in Intensive Care Units Early prediction of hemodynamic shock in the ICU can save lives. Several studies have leveraged a combination of vitals, lab investigations, and clinical data to construct early warning systems for shock. However, these have a limited potential of generalization to diverse settings due to reliance on non-real-time data. Monitoring data from vitals can provide an early real-time prediction of Hemodynamic shock which can precede the clinical diagnosis to guide early therapy decisions. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups (adult and pediatric), ICU-types, and geographies. We trained, validated, and tested a shock prediction model on the publicly available eICU dataset on 208 ICUs across the United States. Data from 156 hospitals passed the eligibility criteria for cohort building. These were split hospital-wise in a five-fold training-validation-test set. External validation of the model was done on a pediatric ICU in New Delhi and MIMIC-III database with more than 0.23 million and one million patient-hours vitals data, respectively. Our models identified 92% of all the shock events more than 8 hours in advance with AUROC of 86 %(SD= 1.4) and AUPRC of 93% (SD =1.2) on the eICU testing set. An AUROC of 87 % (SD =1.8), AUPRC 92 % (SD=1.6) were obtained in external validation on the MIMIC-III cohort. The New Delhi Pediatric SafeICU data achieved an AUROC of 87 % (SD =4) AUPRC 91% (SD=3), despite being completely different geography and age group. In this first, we demonstrate a generalizable model for predicting shock, and algorithms are publicly available as a pre-configured Docker environment at https://github.com/tavlab-iiitd/ShoQPred. A collaborative maternity and newborn dashboard (CoMaND) for the COVID-19 pandemic: a protocol for timely, adaptive monitoring of perinatal outcomes in Melbourne, Australia BackgroundThe COVID-19 pandemic has resulted in a range of unprecedented disruptions to the delivery of maternity care globally and has been associated with regional changes in perinatal outcomes such as stillbirth and preterm birth. Metropolitan Melbourne endured one of the longest and most stringent lockdowns in 2020. This paper presents the protocol for a collaborative maternity dashboard project to monitor perinatal outcomes in Melbourne, Australia, during the COVID-19 pandemic.

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

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

Strengths and weaknesses of this study This project is the first clinician-led, multi-centre perinatal data collection system for metropolitan Melbourne.
 It complements the state government data collection, with the significant benefits of more timely and flexible reporting of outcomes, and granular detail on emerging areas of concern.
 The study relies on primary source coding of exposure and outcomes from each hospital that have not been internally validated during the study period.
 Data from private maternity hospitals, containing 25% of Melbourne births, are not available.
 This resource will support data-informed hospital pandemic responses through to the end of 2022. 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. The socioeconomic factors that led to unemployment under COVID-19 pandemic among Japanese workers: a prospective cohort study ObjectivesTo examine the relationship between socioeconomic factors and unemployment among workers during COVID-19 pandemic in Japan.

DesignA prospective cohort study, follow-up from December 22-25, 2020 through February 18-19, 2021.

SettingThe panelists registered with an Internet survey company

ParticipantsA cluster random sample of 33,087 workers with stratification by sex, job type, and region among Japans working population

Main outcomes and measuresUnemployment between December 2020 and February 2021

ResultsAmong the 19,941 participants, 725 (3.6%) had experienced unemployment. Multivariate analysis showed that the significant high unemployment for women (compared to men); younger age (compared to older age); being married (spouse not working), bereaved or divorced, and unmarried (compared to married (spouse working)); annual household income less than 6 million yen, (compared to more than 10 million yen); junior high or high school, vocational school, junior college, or technical school (compared to graduate school); and temporary or contract employees, self-employed, agriculture, forestry, or fishing (compared to general employees).

ConclusionsCOVID-19 appears to have created difficulties for the vulnerable groups. This suggests the need for employment and economic support for such individuals.

Strengths and limitations of this studyUnder the pandemic of COVID-19, we found that unemployment was associated with socioeconomic factors such as age, sex, marriage, income, education and occupation.

Our findings suggest that in the event of a major epidemic, resulting in unemployment among vulnerable segments of the labour market, regardless of whether workers themselves are infected.

It was unclear why the participants had experienced unemployment

This study was conducted as an Internet survey, so the generalizability of our results is limited. Spatial Allocation of Scarce COVID-19 Vaccines The COVID-19 Vaccines Global Access (COVAX) is an initiative led by the World Health Organization (WHO) and other partners that aims for an equitable access of COVID-19 vaccines. Despite a potential heterogeneous disease burden across space, countries receiving allotments of vaccines via COVAX may want to follow WHOs allocation rule and distribute vaccines to their jurisdictions based on the jurisdictions relative population size. Utilizing economic-epidemiological modeling, we benchmark the performance of this ad hoc allocation rule by comparing it to the rule that minimizes the economic damages and expenditures over time, including a penalty cost representing the social costs of deviating from the ad hoc allocation. Under different levels of vaccine scarcity and different demographic characteristics, we consider scenarios where length of immunity and compliance to travel restrictions vary, and consider the robustness of the rules when assumptions regarding these factors are incorrect. The benefits from deviating are especially high when immunity is permanent, when there is compliance to travel restrictions, when the supply of vaccine is low, and when there is heterogeneity in demographic characteristics. Interestingly, a lack of compliance to travel restrictions pushes the optimal allocations of vaccine towards the ad hoc and improves the relative robustness of the ad hoc rule, as the mixing of the populations reduces the spatial heterogeneity in disease burden.

JEL ClassificationC61, H12, H84, I18, Q54 Characterization of small fiber neuropathy in hypermobile Ehlers Danlos Syndrome Ehlers Danlos syndromes (EDS) are heritable connective tissue disorders. The hypermobile form (hEDS) is the most frequent, yet the only one without an identified genetic mutation. Patients suffering from symptomatic joint hypermobility, yet not fulfilling the hEDS criteria, enter the Hypermobility Spectrum Disorder (HSD) category. In addition to musculoskeletal pain affecting joints, hEDS/HSD patients often describe painful sensations, hypoesthesia, and autonomic symptoms suggesting a neuropathic component. Small fiber neuropathy (SFN) refers to the dysfunction or damage of A-{delta} and C-fibers, which relay thermal and nociceptive information as well as mediating autonomic function. SFN has been suggested by prior studies in hEDS but these early findings (case series N[&le;]20) with sole reliance on intraepidermal nerve fiber density (IENFD) called for a larger sample combined with functional testing.

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

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

These results add strong evidence for a peripheral neuropathic contribution to pain symptoms in hEDS/HSD, in addition to the known nociceptive and central sensitization components. Such neuropathic contribution could raise the hypothesis of a neurological cause of hEDS, the only EDS syndrome still without a known genetic cause. Hence, our data is leading the way to a better stratification of this very heterogeneous population, which could improve symptommanagement and expand pathophysiological research.