Omicron Impact in India: Analysis of the Ongoing COVID-19 Third Wave Based on Global Data The Omicron variant of coronavirus has caused major disruptions world-wide with countries struggling to manage the overwhelming number of infections. Omicron is found to be significantly more transmissible compared to its predecessors and therefore almost every impacted country is exhibiting new infection peaks than seen earlier. In this work, we analyze the global statistics of Omicron-impacted countries including South Africa, the United Kingdom, the United States, France, and Italy to quantitatively estimate the intensity and severity of recent waves. Next, these statistics are used to estimate the impact of Omicron in India, which is experiencing an intense third wave of COVID-19 since 28 Dec., 2021. The rapid surge in the daily number of infections, comparable to the global trends, strongly suggests the dominance of the Omicron variant in infections in India. The logarithmic regression suggests the early growth rate of infections in this wave is nearly four times that in the second wave. Another notable difference in this wave is the relatively concurrent arrival of outbreaks all across the country; the effective reproduction number (Rt) although has significant variations among different regions. The test positivity rate (TPR) also displays a rapid growth in the last 10 days in several states. Preliminary estimates with the Susceptible-Infected-Removed (SIR) model suggest that the peak in India to occur in late January 2022 with a caseload exceeding that in the second wave. Although global Omicron trends, as analyzed in this work, suggest a decline in case fatality rate and hospitalizations compared to Delta, a sudden accumulation of active infections can potentially choke the already stressed healthcare infrastructure for the next few weeks.
Burden of Post-COVID-19 Syndrome and Implications for Healthcare Service Planning: A Population-based Cohort Study BackgroundLonger-term consequences after SARS-CoV-2 infection are becoming an important burden to societies and healthcare systems. Data on post-COVID-19 syndrome in the general population are required for the timely planning of healthcare services and resources. The objective of this study was to assess the prevalence of impaired health status and physical and mental health symptoms among individuals at least six months after SARS-CoV-2 infection, and to characterize their healthcare utilization.

MethodsThis population-based prospective cohort study (Zurich SARS-CoV-2 Cohort) enrolled 431 adults from the general population with polymerase chain reaction-confirmed SARS-CoV-2 infection reported to health authorities between 27 February 2020 and 05 August 2020 in the Canton of Zurich, Switzerland. We evaluated the proportion of individuals reporting not to have fully recovered since SARS-CoV-2 infection, and the proportion reporting fatigue (Fatigue Assessment Scale), dyspnea (mMRC dyspnea scale) or depression (DASS-21) at six to eight months after diagnosis. Furthermore, the proportion of individuals with at least one healthcare contact after their acute illness was evaluated. Multivariable logistic regression models were used to assess factors associated with these main outcomes.

ResultsSymptoms were present in 385 (89%) participants at diagnosis and 81 (19%) were initially hospitalized. At six to eight months, 111 (26%) reported not having fully recovered. 233 (55%) participants reported symptoms of fatigue, 96 (25%) had at least grade 1 dyspnea, and 111 (26%) had DASS-21 scores indicating symptoms of depression. 170 (40%) participants reported at least one general practitioner visit related to COVID-19 after acute illness, and 10% (8/81) of initially hospitalized individuals were rehospitalized. Individuals that have not fully recovered or suffer from fatigue, dyspnea or depression were more likely to have further healthcare contacts. However, a third of individuals (37/111) that have not fully recovered did not seek further care.

ConclusionsIn this population-based study, a relevant proportion of participants suffered from longer-term consequences after SARS-CoV-2 infection. With millions infected across the world, our findings emphasize the need for the timely planning of resources and patient-centered services for post-COVID-19 care.

RegistrationISRCTN14990068
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. Treatment interruption is a risk factor for sickness presenteeism: a large-scale cross-sectional study during the COVID-19 pandemic ObjectivesThis study examined the relationship between interruption to routine medical care during the coronavirus disease 2019 pandemic and sickness presenteeism among workers in Japan.

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

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

ConclusionsThis study suggests the importance of continuing necessary treatment during a pandemic to prevent presenteeism. 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. 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. Pausing methotrexate improves immunogenicity of COVID-19 vaccination in elderly patients with rheumatic diseases ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).

MethodsNeutralising SARS-CoV-2 antibodies were measured after second vaccination in 64 rheumatic patients on methotrexate therapy, 31 of whom temporarily paused medication without a fixed regimen. The control group consisted of 21 AIRD patients without immunosuppressive medication.

ResultsMTX patients showed a significantly lower median antibody response compared to AIRD patients without immunosuppressive therapy (p< 0.001). Young age (<60 years) and MTX-hold after vaccination were found to be the main factors influencing antibody response after vaccination, while BMI or MTX dose demonstrated no effect. For patients taking MTX, age correlated negatively with immune response (r=-0.49; p<0.001) and all patients with antibody levels (14 %) below the cut-off were older than 60 years. Patients who held MTX during at least one vaccination showed significantly higher median neutralising antibody levels after second vaccination, compared to patients who continued MTX therapy during both vaccinations (68.82 %, 92.73 %, p=<0.001). This effect was particularly pronounced in patients older than 60 years (p=0.0016). The impact of the time period after vaccination was greater than of the time before vaccination with the critical cut-off being 10 days.

ConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age. Immuno-fibrotic drivers of impaired lung function in post-acute sequelae of SARS-CoV-2 infection (PASC) IntroductionSubjects recovering from COVID-19 frequently experience persistent respiratory ailments; however, little is known about the underlying biological factors that may direct lung recovery and the extent to which these are affected by COVID-19 severity.

MethodsWe performed a prospective cohort study of subjects with persistent symptoms after acute COVID-19, collecting clinical data, pulmonary function tests, and plasma samples used for multiplex profiling of inflammatory, metabolic, angiogenic, and fibrotic factors.

ResultsSixty-one subjects were enrolled across two academic medical centers at a median of 9 weeks (interquartile range 6-10) after COVID-19 illness: n=13 subjects (21%) mild/non-hospitalized, n=30 (49%) hospitalized/non-critical, and n=18 subjects (30%) hospitalized/intensive care ("ICU"). Fifty-three subjects (85%) had lingering symptoms, most commonly dyspnea (69%) and cough (58%). Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and diffusing capacity for carbon monoxide (DLCO) declined as COVID-19 severity increased (P<0.05), but did not correlate with respiratory symptoms. Partial least-squares discriminant analysis of plasma biomarker profiles clustered subjects by past COVID-19 severity. Lipocalin 2 (LCN2), matrix metalloproteinase-7 (MMP-7), and hepatocyte growth factor (HGF) identified by the model were significantly higher in the ICU group (P<0.05) and inversely correlated with FVC and DLCO (P<0.05), and were confirmed in a separate validation cohort (n=53).

ConclusionsSubjective respiratory symptoms are common after acute COVID-19 illness but do not correlate with COVID-19 severity or pulmonary function. Host response profiles reflecting neutrophil activation (LCN2), fibrosis signaling (MMP-7), and alveolar repair (HGF) track with lung impairment and may be novel therapeutic or prognostic targets.

FundingThe study was funded in part by the NHLBI (K08HL130557 to BDK and R01HL142818 to HJC), the DeLuca Foundation Award (AP), a donation from Jack Levin to the Benign Hematology Program at Yale, and Divisional/Departmental funds from Duke University. A Cross-Sectional Examination of Conflict-of-Interest Disclosures of Physician-Authors Publishing in High-Impact US Medical Journals ObjectiveTo assess the accuracy of self-reported financial conflict-of-interest (COI) disclosures in the New England Journal of Medicine (NEJM) and Journal of the American Medical Association (JAMA) within the requisite disclosure period prior to article submission.

DesignCross-sectional investigation.

Data SourcesOriginal clinical-trial research articles published in NEJM (n = 206) or JAMA (n = 188) from January 1 to December 31, 2017; self-reported COI disclosure forms submitted to NEJM or JAMA with the authors published articles; Open Payments website (from database inception; latest search: August 2019).

Main outcome measuresFinancial data reported to Open Payments from 2014 to 2016 (time period that included all subjects requisite disclosure windows) were compared to self-reported disclosure forms submitted to the journals. Payments were defined as those not associated with a research study or formal research funding. Payment types were categorized as "disclosed," "undisclosed," "indeterminate," or "unrelated."

ResultsThirty-one articles from NEJM and 31 articles from JAMA met inclusion criteria. The physician-authors (n = 118) received a combined total of $7.48 million. Of the 106 authors (89.8%) who received payments, 86 (81.1%) received undisclosed payments. The top 23 most highly compensated received $6.32 million, of which $3.00 million (47.6%) was undisclosed. Disclosure rates were the equivalent between the top 23 and the entire sample.

ConclusionsHigh payment amounts, as well as high proportions of undisclosed financial compensation, regardless of amount received, comprised potential COIs for two influential US medical journals. Further research is needed to explain why such high proportions of general payments were undisclosed and whether journals that rely on self-reported COI disclosure need to reconsider their policies. 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.) A blood-based miRNA signature with prognostic value for overall survival in advanced stage non-small cell lung cancer treated with immunotherapy Immunotherapies have recently gained traction as highly effective therapies in a subset of late-stage cancers. Unfortunately, only a minority of patients experience the remarkable benefits of immunotherapies, whilst others fail to respond or even come to harm through immune related adverse events. For immunotherapies within the PD-1/PD-L1 inhibitor class, patient stratification is currently performed using tumor (tissue-based) PD-L1 expression. However, PD-L1 is an accurate predictor of response in only [~]30% of cases. There is pressing need for more accurate biomarkers for immunotherapy response prediction.

We sought to identify peripheral blood biomarkers, predictive of response to immunotherapies against lung cancer, based on whole blood microRNA profiling. Using three well characterized cohorts consisting of a total of 334 stage IV NSCLC patients, we have defined a 5 microRNA risk score (miRisk) that is predictive of overall survival following immunotherapy in training and independent validation (HR 2.40, 95% CI 1.37-4.19; P < 0.01) cohorts. We have traced the signature to a myeloid origin and performed miRNA target prediction to make a direct mechanistic link to the PD-L1 signalling pathway and PD-L1 itself. The miRisk score offers a potential blood-based companion diagnostic for immunotherapy that outperforms tissue-based PD-L1 staining. The Acute Treatment of Migraine with Low-Dose Naltrexone and acetaminophen Combinations and Each Component: Findings of a Small, Randomized, Double-Blind, and Placebo-Controlled Clinical Trial We tested two low-dose naltrexone and acetaminophen combinations and each component in the acute treatment of migraine. The patients use a single-dose of the study medication for a moderate or severe pain intensity migraine attack. Patients were adults with migraine with or without aura experiencing 2 to 20 (average 6.4) monthly migraine days. The co-primary endpoints were pain-freedom and absence of prospectively-identified most bothersome migraine-associated symptom 2 hours after dosing. We randomized 92 patients; 72 completed the study (mean age, 43 years; 75% women). Pain-freedom at 2 hours was 10.2% higher than placebo with naltrexone 2.25 mg/acetaminophen 325 mg, 10.9% with naltrexone 3.25 mg/acetaminophen 325 mg, 17.3% with naltrexone 2.25 mg, and 31.3% with acetaminophen 325 mg. The treatment groups migraine burden at baseline was unbalanced due to randomized patients uneven study completion. The acetaminophen group had the lowest migraine burden, giving its results lower credibility.

Saliently, Low-dose naltrexone alone (n=19) had a 17.3% higher response rate for headache pain-freedom at 2 hours than placebo (n=17). The naltrexone and the placebo groups were the largest and had a balanced disease burden, implying higher credibility to the naltrexone group results. We found low-dose naltrexone and acetaminophen combination, low-dose naltrexone, and acetaminophen had higher response rates than placebo in treating headache pain. The most commonly reported adverse events were sedation, nausea, and dizziness. We postulate that naltrexones toll-like receptor (TLR4) antagonism properties prevent pro-inflammatory cytokines production in the trigeminal ganglion averting "overactive nerves" (laymans term) and migraine. Although this trial used low-dose naltrexone (defined as 1 - 5 mg/day), future phase 3 studies will test a range of naltrexone and acetaminophen combination doses. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

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

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

SettingPrimary and Express care clinics in a Pennsylvania health system.

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

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

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

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/. 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. Predictors of uncertainty and unwillingness to receive the COVID-19 booster vaccine: an observational study of 22,139 fully vaccinated adults in the UK BackgroundThe continued success of the COVID-19 vaccination programme in the UK will depend on widespread uptake of booster vaccines. However, there is evidence of hesitancy and unwillingness to receive the booster vaccine, even in fully vaccinated adults. Identifying factors associated with COVID-19 booster vaccine intentions specifically in this population is therefore critical.

MethodsWe used data from 22,139 fully vaccinated adults who took part in the UCL COVID-19 Social Study. Multinomial logistic regression examined predictors of uncertainty and unwillingness (versus willingness) to receive a COVID-19 booster vaccine (measured 22 November 2021 to 6 December 2021), including (i) socio-demographic factors, (ii) COVID-19 related factors (e.g., having been infected with COVID-19), and (iii) initial intent to receive a COVID-19 vaccine in the four months following the announcement in the UK that the vaccines had been approved (2 December 2020 to 31 March 2021).

Findings4% of the sample reported that they were uncertain about receiving a COVID-19 booster vaccine, and a further 4% unwilling. Initial uncertainty and unwillingness to accept the first COVID-19 vaccine in 2020-21 were each associated with over five times the risk of being uncertain about and unwilling to accept a booster vaccine. Healthy adults (those without a pre-existing physical health condition) were also more likely to be uncertain or unwilling to receive a booster vaccine. In addition, low levels of current stress about catching or becoming seriously ill from COVID-19, consistently low compliance with COVID-19 government guidelines during periods of strict restrictions (e.g., lockdowns), lower levels of educational qualification, lower socio-economic position, and age below 45 years were all associated with uncertainty and unwillingness.

InterpretationOur findings highlight that there are a range of factors that predict booster intentions, with the strongest predictor being previous uncertainty and unwillingness. Two other concerning patterns also emerged from our results. First, administration of booster vaccinations may increase social inequalities in experiences of COVID-19 as adults from lower socio-economic backgrounds are also most likely to be uncertain or unwilling to accept a booster vaccine as well as most likely to be seriously affected by the virus. Second, some of those most likely to spread COVID-19 (i.e., those with poor compliance with guidelines) are most likely to be uncertain and unwilling. Public health messaging should be tailored specifically to these groups.

FundingThe Nuffield Foundation [WEL/FR-000022583], the MARCH Mental Health Network funded by the Cross-Disciplinary Mental Health Network Plus initiative supported by UK Research and Innovation [ES/S002588/1], and the Wellcome Trust [221400/Z/20/Z and 205407/Z/16/Z]. 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. 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. I wanna live and not think about the future; What place for advance care planning for people living with severe multiple sclerosis and their families? A qualitative study BackgroundLittle is known about how people with multiple sclerosis and their families comprehend advance care planning (ACP) and its relevance in their lives.

AimTo explore under what situations, with whom, how, and why do people with MS and their families engage in ACP

MethodsWe conducted a qualitative study comprising interviews with people living with MS and their families followed by an ethical discussion group with five health professionals representing specialties working with people affected by MS and their families. Twenty-seven people with MS and 17 family members were interviewed between June 2019 and March 2020. Interviews and the ethical discussion group were audio-recorded and transcribed verbatim. Data were analysed using the framework approach.

ResultsParticipants narratives focused on three major themes :(i) planning for an uncertain future; (ii) perceived obstacles to engaging in ACP that included uncertainty concerning MS disease progression, negative previous experiences of ACP discussions and prioritising symptom management over future planning; (iii) Preferences for engagement in ACP included a trusting relationship with a health professional and that information then be shared across services. Health professionals accounts from the ethical discussion group departed from viewing ACP as a formal document to that of an ongoing process of seeking preferences and values. They voiced similar concerns to people with MS about uncertainty and when to initiate discussions. Some shared concerns of a lack of confidence when having ACP discussions.

ConclusionThese findings support the need for a whole systems strategic approach where information about the potential benefits of ACP in all its forms can be shared with people with MS. Moreover, they highlight the need for health professionals to be skilled and trained in engaging in ACP discussions and where information is contemporaneously and seamlessly shared across services. The Association of Opening K-12 Schools with the Spread of COVID-19 in the United States: County-Level Panel Data Analysis AO_SCPLOWBSTRACTC_SCPLOWThis paper empirically examines how the opening of K-12 schools and colleges is associated with the spread of COVID-19 using county-level panel data in the United States. Using data on foot traffic and K-12 school opening plans, we analyze how an increase in visits to schools and opening schools with different teaching methods (in-person, hybrid, and remote) is related to the 2-weeks forward growth rate of confirmed COVID-19 cases. Our debiased panel data regression analysis with a set of county dummies, interactions of state and week dummies, and other controls shows that an increase in visits to both K-12 schools and colleges is associated with a subsequent increase in case growth rates. The estimates indicate that fully opening K-12 schools with in-person learning is associated with a 5 (SE = 2) percentage points increase in the growth rate of cases. We also find that the positive association of K-12 school visits or in-person school openings with case growth is stronger for counties that do not require staff to wear masks at schools. These results have a causal interpretation in a structural model with unobserved county and time confounders. Sensitivity analysis shows that the baseline results are robust to timing assumptions and alternative specifications. Subpopulation-specific Machine Learning Prognosis for Underrepresented Patients with Double Prioritized Bias Correction Many clinical datasets are intrinsically imbalanced, dominated by overwhelming majority groups. Off-the-shelf machine learning models that optimize the prognosis of majority patient types (e.g., healthy class) may cause substantial errors on the minority prediction class (e.g., disease class) and demographic subgroups (e.g., Black or young patients). For example, our work found that missed death cases are 3.14 times higher than missed survival cases in a mortality prediction model. In the typical one-machine-learning-model-fits-all paradigm, racial and age disparities are likely to exist, but unreported. What makes it worse is the deceptive nature of widely used whole-population metrics, such as AUC-ROC. We show that some metrics fail to reflect serious prediction deficiencies. To mitigate representational biases, we design a double prioritized (DP) bias correction technique. Our method trains customized models for specific ethnicity or age groups, a substantial departure from the one-model-predicts-all convention. We report our findings on four prognosis tasks over two imbalanced clinical datasets. DP reduces relative disparities among race and age groups, 5.6% to 86.8% better than the 8 existing sampling solutions being compared, in terms of the minority class' recall. In depth analysis of patients with severe SARS-CoV-2 in sub-Saharan Africa demonstrates distinct clinical and immunological profiles Although the COVID-19 pandemic has left no country untouched there has been limited research to understand clinical and immunological responses in African populations. Here we comprehensively characterise patients hospitalised with suspected or confirmed COVID-19, and healthy community controls. PCR-confirmed COVID-19 participants were more likely to receive dexamethasone and a beta-lactam antibiotic, and survive to hospital discharge than PCR-/IgG+ and PCR-/IgG-participants. PCR-/IgG+ participants exhibited a nasal and systemic cytokine signature analogous to PCR-confirmed COVID-19 participants, but increased propensity for Staphylococcus aureus and Streptococcus pneumoniae colonisation. We did not find evidence that HIV co-infection in COVID-19 participants was associated with mortality or altered cytokine responses. The nasal immune signature in PCR-/IgG+ and PCR-confirmed COVID-19 participants was distinct and predominated by chemokines and neutrophils. In addition, PCR-/IgG+ individuals with high COVID-19 clinical suspicion had inflammatory profiles analogous to PCR-confirmed disease and potentially represent a target population for COVID-19 treatment strategies. Factors affecting first return to work following arthroscopic rotator cuff repair: A retrospective observational study in an occupational medicine clinic and single-surgeon practice BackgroundReturn to work (RTW) following arthroscopic rotator cuff repair (aRCR) within New South Wales (NSW), Australia, under compensable schemes has not been reported.

AimsDetermine factors affecting RTW status and time in patients treated with aRCR under state-based compensation schemes, compared to those outside such schemes.

MethodsPatients undergoing aRCR by one surgeon with minimum 1-year follow-up were grouped into those under (CP) or outside (non-CP) workers or vehicle accident compensation schemes, matched by age and gender. RTW status and time were assessed using chi-square analysis and multivariable linear regression.

ResultsOf 1054 available patients, 90 CP patients were identified with 29 consented and matched to non-CP (N=29). A higher proportion of CP patients (17.2 vs 0%, P<0.001) never returned to work and a lower proportion resumed pre-injury duties at first RTW (3 vs 52%, P<0.01). Median time to first RTW did not differ between CP and non-CP groups (5.1 vs 4.4, P=0.86). Smoking (P=0.007) and post-injury activity level (P=0.004) were significantly associated with longer time to first RTW, whereas compensation status was not.

ConclusionsCP patients undergoing aRCR in NSW are at risk of not returning to work. For those that return, there is no significant difference compared to non-CP in time to first RTW. Particularly, patient and management factors associated with extended time to first RTW have been identified. Interventions aimed at modifiable factors such as smoking cessation and increasing preoperative activity may improve future outcomes.

What is already known about this subjectO_LIWork-related injury and disease present a significant financial burden to the Australian economy ($AUD61.8billion per annum), with shoulder conditions due to body stressing accounting for 7% of this total cost (>$AUD4.2billion)
C_LIO_LIPatients receiving compensation appear to have poorer outcomes and take longer to return to work than their non-compensated counterparts, but the degree to which this occurs is variably reported in the literature
C_LIO_LIThe effect of modifiable factors on return to work status and time remain unclear, and have not previously been reported for the Australian population under the New South Wales workers compensation scheme
C_LI

What this study addsO_LIPatients receiving arthroscopic rotator cuff repair under a compensable scheme in New South Wales are at increased risk of not returning to work compared to patients presenting outside of a compensable scheme and patients in equivalent schemes internationally
C_LIO_LIPatients reporting a longer duration of symptoms and smokers are at increased risk of extended time to first return to work
C_LI

What impact this may have on practice or policyO_LIThe study has identified smoking and pre-surgery activity levels as key targets for intervention in patients receiving arthroscopic rotator cuff repair under a workers compensation scheme in New South Wales
C_LIO_LIBy further investigating whether interventions designed to modify these factors are able to favourably affect patient outcomes, there is potential to return patients to their preoperative level of work sooner
C_LI Prognostication for prelabor rupture of membranes and the time of delivery in nationwide insured women: development, validation, and deployment ImportancePrognostic predictions of prelabor rupture of membranes lack proper sample sizes and external validation.

ObjectiveTo develop, validate, and deploy statistical and/or machine learning prediction models using medical histories for prelabor rupture of membranes and the time of delivery.

DesignA retrospective cohort design within 2-year period (2015 to 2016) of a single-payer, government-owned health insurance database covering 75.8% individuals in a country

SettingNationwide healthcare providers (n=22,024) at primary, secondary, and tertiary levels

Participants12-to-55-year-old women that visit healthcare providers using the insurance from [~]1% random sample of insurance holders stratified by healthcare provider and category of family: (1) never visit; (2) visit only primary care; and (3) visit all levels of care

PredictorsMedical histories of diagnosis and procedure (International Classification of Disease version 10) before the latest visit of outcome within the database period

Main Outcomes and MeasuresPrelabor rupture of membranes prognostication (area under curve, with sensitivity, specificity, and likelihood ratio), the time of delivery estimation (root mean square error), and inference time (minutes), with 95% confidence interval

ResultsWe selected 219,272 women aged 33 {+/-} 12 years. The best prognostication achieved area under curve 0.73 (0.72 to 0.75), sensitivity 0.494 (0.489 to 0.500), specificity 0.816 (0.814 to 0.818), and likelihood ratio being positive 2.68 (2.63 to 2.75) and negative 0.62 (0.61 to 0.63). This outperformed models from previous studies according to area under curve of an external validation set, including one using a biomarker (area under curve 0.641; sensitivity 0.419; sensitivity 0.863; positive likelihood ratio 3.06; negative likelihood ratio 0.67; n=1177). Meanwhile, the best estimation achieved {+/-} 2.2 and 2.6 weeks respectively for predicted events and non-events. Our web application only took 5.14 minutes (5.11 to 5.18) per prediction.

Conclusions and RelevancePrelabor rupture of membranes and the time of delivery were predicted by medical histories; but, an impact study is required before clinical application.

Key PointsO_ST_ABSQuestionC_ST_ABSCan we use medical histories of diagnosis and procedure in electronic health records to predict prelabor rupture of membranes and the time of delivery before the day in nationwide insured women?

FindingsIn this prognostic study applying retrospective cohort paradigm, a significant predictive performance was achieved and validated. The area under receiver operating characteristics curve was 0.73 with the estimation errors of {+/-} 2.2 and 2.6 weeks for the time of delivery.

MeaningPreliminary prediction can be conducted in a wide population of insured women to predict prelabor rupture of membranes and estimate the time of delivery.