Convergence of Comorbidity and COVID-19 Infection to Fatality: An Investigation Based on Concurrent Health Status Evaluation among Older Adults ObjectiveTo investigate the impact of age, comorbidity, and vaccination in the fatality of older COVID-19 patients in the state of Kerala, India, based on their comorbidity and vaccination status.

MethodsIt is a cross sectional study adopting a mixed method approach conducted among the older population in Kerala. To study the health profile, 405 older people were surveyed, and 102 people were interviewed in-depth at their households, between June to November 2020. The results of the study were triangulated with elderly COVID-19 fatality data, available from the citizen-science dashboards of the research team and Department of Health, Kerala. Vaccination data was retrieved from cowin.gov.in to study its impact. The data was analysed using the IBM SPSS version 22.0.

ResultsAge is a predictor of COVID-19 fatality. Diabetes, hypertension, heart diseases, CKD and COPD are the significant predictors of elderly COVID-19 fatality. The current comorbidity profile of the total older population matches with the comorbidities of the COVID-19 elderly death cases. Vaccination has impacted COVID-19 mortality after vaccinating 65 percent (first dose) of the elderly.

ConclusionsAge and comorbidities can predict potential fatality among older COVID-19 patients. Timely and accurate health data and better knowledge of high-risk factors such as comorbidity can easily guide the healthcare system and authorities to efficient prevention and treatment methodologies. Knowledge on prevailing NCDs can drive early preparedness before it converges with an epidemic like the present zoonotic disease. Priority must be given for elderly vaccination to bring down the mortality rates.
Effectiveness of BNT162b2 and mRNA-1273 COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe COVID-19 outcomes in Ontario, Canada: a test-negative design study ObjectivesTo estimate the effectiveness of mRNA COVID-19 vaccines against symptomatic infection and severe outcomes.

DesignWe applied a test-negative design study to linked laboratory, vaccination, and health administrative databases, and used multivariable logistic regression adjusting for demographic and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness (VE) against symptomatic infection and severe outcomes.

SettingOntario, Canada between 14 December 2020 and 19 April 2021.

ParticipantsCommunity-dwelling adults aged [&ge;]16 years who had COVID-19 symptoms and were tested for SARS-CoV-2.

InterventionsPfizer-BioNTechs BNT162b2 or Modernas mRNA-1273 vaccine.

Main outcome measuresLaboratory-confirmed SARS-CoV-2 by RT-PCR; hospitalization/death associated with SARS-CoV-2 infection.

ResultsAmong 324,033 symptomatic individuals, 53,270 (16.4%) were positive for SARS-CoV-2 and 21,272 (6.6%) received [&ge;]1 vaccine dose. Among test-positive cases, 2,479 (4.7%) had a severe outcome. VE against symptomatic infection [&ge;]14 days after receiving only 1 dose was 60% (95%CI, 57 to 64%), increasing from 48% (95%CI, 41 to 54%) at 14-20 days after the first dose to 71% (95%CI, 63 to 78%) at 35-41 days. VE [&ge;]7 days after 2 doses was 91% (95%CI, 89 to 93%). Against severe outcomes, VE [&ge;]14 days after 1 dose was 70% (95%CI, 60 to 77%), increasing from 62% (95%CI, 44 to 75%) at 14-20 days to 91% (95%CI, 73 to 97%) at [&ge;]35 days, whereas VE [&ge;]7 days after 2 doses was 98% (95%CI, 88 to 100%). For adults aged [&ge;]70 years, VE estimates were lower for intervals shortly after receiving 1 dose, but were comparable to younger adults for all intervals after 28 days. After 2 doses, we observed high VE against E484K-positive variants.

ConclusionsTwo doses of mRNA COVID-19 vaccines are highly effective against symptomatic infection and severe outcomes. Single-dose effectiveness is lower, particularly for older adults shortly after the first dose.
Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

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

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

DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. 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 Estimating real-world COVID-19 vaccine effectiveness in Israel using aggregated counts The vaccination roll-out of the COVID-19 vaccines in Israel has been highly successful. By February 22th, approximately 47% of the population has already been administered at least one dose of the BNT162b2 vaccine. Efforts to estimate the true real-world effectiveness of the vaccine have been hampered by disease dynamics and social-economic discrepancies. Here, using counts of positive and hospitalized cases of vaccinated individuals, we conduct a sensitivity analysis of the vaccine effectiveness. Under an assumption of no effectiveness on the first two weeks after the 1st dose, we observe very low effectiveness on the third week. After the 2nd dose, on weeks 1 and 2 we find 73-85% effectiveness in reducing positive cases, hospitalizations, and severe cases, which increase to 89-97% effectiveness 14 days after the 2nd dose. As more granular data will be available, it will be possible to extract more exact estimates; however, the emerging evidence suggests that the vaccine is highly effective. 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. 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/. Molecular analysis suggests oligoclonality and metastasis of endometriosis lesions across anatomically defined subtypes. Endometriosis symptoms are heterogeneous with controversy on whether it constitutes a single disease or multiple distinct types. Our previous work found recurrent somatic cancer-driver alterations in endometriosis; however, these have not been found ubiquitously. A handful of cases spread across studies also suggest mutations might be shared (clonal) between lesions of the same type. As current classification systems correlate poorly with symptoms or outcomes, somatic genomics may improve the current system. Here, we investigate heterogeneity of somatic cancer-driver mutations within patients and across endometriosis types. We examined anatomically distinct types of endometriosis (ovarian, deep infiltrating, and superficial endometriosis) in 27 individual patients all of whom had at least two types of endometriosis. Specimens were analyzed using high-sensitivity targeted sequencing with orthogonal validation from droplet digital PCR and mutation-surrogate immunohistochemistry. Results found 13/27 patients had informative somatic driver mutation in endometriosis, 9/13 had identical mutations across distinct lesions. Endometriomas tended to have a higher mutational complexity, with functionally redundant driver mutations in same gene and within the same lesions.

Our data are consistent with clonality across endometriosis lesions regardless of subtype. Further the finding of redundancy in mutations with the same gene and lesions is also consistent with endometriosis representing an oligoclonal disease with dissemination likely to consist of multiple epithelial clones travelling together. This suggests the current anatomically defined classification of endometriosis does not fully recognize the etiology of the disease. A novel classification should take into account genomic and other molecular features. These findings could further contribute to development of a more personalized endometriosis diagnosis and care. 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. The CT Scan Lung Severity Score and Vaccination Status in COVID-19 patients in India: Perspective of an Independent Radiology Practice BackgroundThe COVID-19 patients often undergo a high-resolution CT scan to determine extent of their lung involvement. The aim of this study was to determine lung involvement in confirmed/suspected COVID-19 patients (encountered at an independent radiology practice) and its correlation to vaccination status amidst the second COVID-19 wave in India.

MethodsWe retrospectively queried our data since April 2021 to identify adult patients (>17 years) who had confirmed (positive RT-PCR or antigen test) or suspected COVID-19 (classic symptoms but negative RT-PCR) and received a high-resolution CT scan to determine the extent of their lung involvement using the CT severity (CT-SS) score. Patients were classified in 3 groups based on their vaccination status to determine its correlation with the CT-SS score: fully vaccinated, partially vaccinated, and unvaccinated. Basic descriptive statistics, univariate tests and multivariate linear regression analysis were used.

ResultsWe identified 229 patients (median age 45 years, 60% male) of which 205 (89%) had confirmed COVID-19 (positive RT-PCR) and 24 had suspected disease (negative RT-PCT but classic symptoms). Of the 229 patients 29 (13%) had complete vaccination, 38 (17%) had partial vaccination and 162 (70%) had no vaccination. The CT score of the completely vaccinated patients was significantly lower compared to partially or unvaccinated patients (median 0 v. 3.5 v. 10, respectively p<.01). A multivariate linear regression model showed that partial or fully vaccinated patients had lower CT severity score compared to unvaccinated patients (adjusted R squared = 0.47).

ConclusionWe present here the real-world findings from an independent radiology practice (a unique and common practice model), in India amid the second COVID-19 wave showing significantly lower CT severity score in fully or partially vaccinated patients compared to unvaccinated patients. Complete vaccination in patients could be critical in preventing severe lung disease. Comparative profiles of SARS-CoV-2 Spike-specific human milk antibodies elicited by mRNA- and adenovirus-based COVID-19 vaccines Numerous COVID-19 vaccines are authorized globally. To date, [~]71% of doses are comprised of the Pfizer/BioNTech vaccine, and [~]17% the Moderna/NIH vaccine, both of which are mRNA-based. The chimpanzee Ad-based Oxford/AstraZeneca (AZ) vaccine comprises [~]9%, while the Johnson & Johnson/Janssen (J&J) human adenovirus (Ad26) vaccine ranks 4th at [~]2% [1]. No COVID-19 vaccines are yet available for children 0-4. One method to protect this population may be passive immunization via antibodies (Abs) provided in the milk of a lactating vaccinated person. Our early work [2] and other reports [3-5] have demonstrated that unlike the post-SARS-CoV-2 infection milk Ab profile, which is rich in specific secretory (s)IgA, the vaccine response is highly IgG-dominant. In this report, we present a comparative assessment of the milk Ab response elicited by Pfizer, Moderna, J&J, and AZ vaccines. This analysis revealed 86% -100% of mRNA vaccine recipient milk exhibited Spike-specific IgG endpoint titers, which were 12 - 28-fold higher than those measured for Ad vaccine recipient milk. Ad-based vaccines elicited Spike-specific milk IgG in only 33%-38% of recipients. Specific IgA was measured in 52%-71% of mRNA vaccine recipient milk and 17%-23% of Ad vaccine recipient milk. J&J recipient milk exhibited significantly lower IgA than Moderna recipients, and AZ recipients exhibited significantly lower IgA titers than Moderna and Pfizer. <50% of milk of any group exhibited specific secretory Ab, with Moderna recipient IgA titers measuring significantly higher than AZ. Moderna appeared to most frequently elicit >2-fold increases in specific secretory Ab titer relative to pre-vaccine sample. These data indicate that current Ad-based COVID-19 vaccines poorly elicit Spike-specific Ab in milk compared to mRNA-based vaccines and that mRNA vaccines are preferred for immunizing the lactating population. This study highlights the need to design vaccines better aimed at eliciting an optimal milk Ab response. COMPARISON OF sPLA2-IIA PERFORMANCE WITH HIGH-SENSITIVE CRP, NEUTROPHIL PERCENTAGE, PCT AND LACTATE TO IDENTIFY BACTERIAL INFECTION: A PROSPECTIVE STUDY Early bacterial infection (BI) identification in resource-limiting Emergency Departments (ED) is challenging especially in low- and middle-income counties (LMIC). Misdiagnosis predisposes to antibiotic overuse and propagates antimicrobial resistance. This study evaluates new emerging biomarkers, secretory phospholipase A2 group IIA (sPLA2-IIA), and compares with other biomarkers on their performance characteristic of BI detection in Malaysia, an LMIC. A prospective cohort study was conducted involving 151 consecutive patients admitted to the ED. A single measurement was taken upon patient arrival in ED and was analysed for serum levels of sPLA2-IIA, high-sensitive C-reactive protein (CRP), procalcitonin (PCT), neutrophil percentage (N%), and lactate. All biomarkers performance was compared for the outcomes using area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The performance of sPLA2-IIA (AUROC 0.93 [95% CI: 0.89-0.97]; Sn 80% [95% CI: 72-87] Sp 94% [95% CI: 81-89]) was the highest among all. It was comparable with high-sensitive CRP (AUROC 0.93 [95% CI: 0.88-0.97]; Sn 75% [95% CI: 66-83]; Sp 91 [95% CI: 77-98]) but had a higher Sn and Sp. The sPLA2-IIA was also found superior to N%, PCT, and lactate. This finding suggested sPLA2-IIA was recommended biomarkers for BI detection in LMIC. EDUCATIONAL NEEDS OF MEDICAL PRACTITIONERS ABOUT MEDICAL BILLING: A SCOPING REVIEW OF THE LITERATURE. IntroductionThe World Health Organization has suggested the solution to health system waste caused by incorrect billing and fraud is policing and prosecution. However, a growing body of evidence suggests leakage may not always be fraudulent or corrupt, with researchers suggesting medical practitioners may sometimes struggle to understand increasingly complex legal requirements around health financing and billing transactions, which may be improved through education. To explore this phenomenon further, we undertook a scoping review of the literature to identify the medical billing education needs of medical practitioners and whether those needs are being met.

MethodsEligible records included English language materials published between 1 January 2000 and 4 May 2020. Searches were conducted on MEDLINE, PubMed, Google Scholar, CINAHL, LexisNexis and Heinonline.

ResultsWe identified 74 records as directly relevant to the search criteria. Despite undertaking a comprehensive, English language search, with no country restrictions, studies meeting the inclusion criteria were limited to three countries (Australia, Canada, U.S), indicating a need for further work internationally. The literature suggests the education needs of medical practitioners in relation to medical billing compliance are not being met and medical practitioners desire more education on this topic. Evidence suggests education may be effective in improving medical billing compliance and reducing waste in health systems. There is broad agreement amongst medical education stakeholders in multiple jurisdictions that medical billing should be viewed as a core competency of medical education, though there is an apparent inertia to include this competency in medical education curricula. Penalties for non-compliant medical billing are serious and medical practitioners are at risk of random audits and investigations for breaches of sometimes incomprehensible, and highly interpretive regulations they may never have been taught.

ConclusionDespite acknowledged significance of waste in health systems due to poor practitioner knowledge of billing practices, there has been very little research to date on education interventions to improve health system efficiency at a practitioner level. SARS-CoV-2 variant exposures elicit antibody responses with differential cross-neutralization of established and emerging strains including Delta and Omicron The wide spectrum of SARS-CoV-2 variants with phenotypes impacting transmission and antibody sensitivity necessitates investigation of the immune response to different spike protein versions. Here, we compare the neutralization of variants of concern, including B.1.617.2 (Delta) and B.1.1.529 (Omicron) in sera from individuals exposed to variant infection, vaccination, or both. We demonstrate that neutralizing antibody responses are strongest against variants sharing certain spike mutations with the immunizing exposure. We also observe that exposure to multiple spike variants increases the breadth of variant cross-neutralization. These findings contribute to understanding relationships between exposures and antibody responses and may inform booster vaccination strategies.

SUMMARYThis study characterizes neutralization of eight different SARS-CoV-2 variants, including Delta and Omicron, with respect to nine different prior exposures, including vaccination, booster, and infections with Delta, Epsilon, and others. Different exposures were found to confer substantially differing neutralization specificity. Gene-level germline contributions to clinical risk of recurrence scores in Black and White breast cancer patients Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer (BC). Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to BC disparities, evidence for biological and germline contributions is emerging. We investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N=1,043 WW, 1083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; Proliferation Score; ROR-P: ROR-S plus Proliferation Score) on imputed Genetically-Regulated tumor eXpression (GReX). Using Bayesian multivariate regression and adaptive shrinkage, we tested GReX-prioritized genes for associations with PAM50 tumor expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, we detected 7 and 1 GReX-prioritized genes among WW and BW. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower Proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among BC patients, we find differential germline associations with CRS by race, underscoring the need for larger, diverse datasets in molecular studies of BC. Our findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings.

SIGNIFICANCEWe find race-specific genetic associations with breast cancer risk-of-recurrence scores (CRS). Follow-up analyses suggest mediation of these associations by PAM50 molecular subtype and gene expression, with implications for clinical interpretation of CRS. Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes BackgroundIndividuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

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

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

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

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

Research in context

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

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

Implications of all the available evidenceWith further validation in several cohorts, the prediction models presented here have the potential for early diagnosis of CKD in persons with diabetes, thus enabling appropriate decisions on the available therapies. It is envisaged that these algorithms will be trialed and support clinicians with precision diagnosis and treatments. 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. Mitigating Covid-19 aerosol infection risk in school buildings: the role of natural ventilation, classroom volume, occupancy and face masks Issues linked to aerosol physics within school buildings and related infection risk still lack a proper recognition in school safety regulations. In this theoretical work we try to shed more light on the critical role of air ventilation, classroom volume, occupancy, and face mask types (surgical vs ffp2) in controlling airborne transmission risk in educational settings. Limited spaces available in many schools require to precisely assess the occupancy/volume ratio in each classroom and to investigate the specific risk levels from aerosolization of viral loads from infective sources. Moreover, most schools are not provided with mechanical HVAC systems. Fundamental questions are therefore: how the specific classroom volume affects the long-range contagion risk in a given classroom? is linear social distancing the right way to assess a volumetric risk problem? How effective are other countermeasures like reduced speaking volume or equipping teachers with microphones? We present here the results of a numerical analysis based on the Gammaitoni-Nucci infection risk model and the consolidated Wells-Riley like approach, with SARS-CoV2 input data and geometric data from a typical high-school classroom in Italy. We investigated separately the case of infective asymptomatic student and infective asymptomatic teacher as source of viral quanta, taking into account thermal gradient effects on the air ventilation rates. First recommendations based on the volumetric nature of aerosol risk are suggested to extend the linear social distancing approach applied so far. Finally we discuss the concept of "cumulative infection risk" over multiple lesson+break cycles in Wells-Riley-like infection models. We believe that any attempt to proper model infection risk in closed environments with cycled changes of the source and the susceptible individuals, should carefully consider this point, particularly when modelling air ventilation breaks in classrooms. Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank ObjectivesTo evaluate the benefit of combining polygenic risk scores (PRS) with the QCancer-10 (colorectal cancer) non-genetic risk prediction model to identify those at highest risk of colorectal cancer (CRC).

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

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

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

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

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

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

What this study addsO_LIAdding PRS to the QCancer-10 (colorectal cancer) risk prediction model improves performance and clinical benefit, with greatest gain from the LDpred2 genome-wide PRS, to a level that suggests utility in stratifying CRC screening and prevention
C_LI 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. Reflex single-gene non-invasive prenatal testing significantly increases the cost-effectiveness of carrier screening ObjectiveTo evaluate the clinical and cost savings benefits of adoption of a carrier screen with reflex single-gene non-invasive prenatal test (sgNIPT) in prenatal care.

MethodA decision-analytic model was developed to compare carrier screen with reflex sgNIPT (maternal carrier status and fetal risk reported together) as first-line carrier screening to the traditional carrier screening workflow (positive maternal carrier screen followed by paternal screening to evaluate fetal risk). The model compared the clinical outcomes and cost effectiveness between the two screening methods. These results were used to simulate appropriate pricing for reflex sgNIPT.

ResultsReflex sgNIPT carrier screening detected 108 of 110 affected pregnancies per 100,000 births (98.5% sensitivity), whereas traditional carrier screening detected 46 of 110 affected pregnancies (41.5% sensitivity). The cost to identify one affected pregnancy was reduced by 62% in the reflex sgNIPT scenario compared to the traditional scenario. Adding together the testing cost savings and the savings from earlier clinical intervention made possible by reflex sgNIPT, the total cost savings was $37.6 million per 100,000 pregnancies. Based on these cost savings, we simulated appropriate reflex sgNIPT pricing range: if the cost to identify one affected pregnancy is the unit cost, carrier screening with reflex sgNIPT can be priced up to $1,859 per test (or $7,233 if sgNIPT is billed separately); if the cost per 100,000 pregnancies is the unit cost, carrier screening with sgNIPT can be priced up to $1,070 per test (or $2,336 if sgNIPT is billed separately).

ConclusionUsing the carrier screen with reflex sgNIPT as first-line screening improves the detection of affected fetuses by 2.4-fold and can save costs for the healthcare system. A real-life experience will be needed to assess the clinical utility and exact cost savings of carrier screen with reflex sgNIPT. How has the prevalence of smoking cigarettes among HIV-infected patients changed over the last decade? Single-center analysis. IntroductionThe WHO report from 2016 estimates the prevalence of smoking as 22% worldwide and 28% in Poland. The prevalence of smoking in HIV-infected persons is 2-3 times higher than in the general population. The study conducted in 2009 in our department among n=116 HIV-infected patients showed 87.1% smoking cigarettes at least 2.5 pack-years (85.0% of males and 93.5% of females). The aim of the present study was to evaluate the change in the prevalence of cigarette smoking among HIV-infected patients over the last decade.

MethodsWe analyzed data from the survey conducted in n=204 HIV-infected patients hospitalized from November 2018 to November 2019 in our department. The survey included: age; sex, number of cigarettes smoked daily presently and in the past, the number of years as a smoker; the influence of HIV diagnosis on the number of cigarettes smoked.

ResultsAmong all n=204 patients current smokers n=78/204 (38.2%) with n=65/176 (36.9%) males and n=13/28 (46.4%) females. Among all n=115 current smokers and ex-smokers n=29 (25.2%) diagnosing the HIV infection had an impact on their smoking habits: n=26 (89.7%) increased and n=3 - all males (10.3%) decreased the number of smoked cigarettes.

ConclusionThe prevalence of smoking cigarettes among HIV-infected individuals in our department has decreased since 2009 but is still much higher than in the general population. The outcome indicates the need to improve smoking education provided by HIV care professionals. Smoking cessation guidance or treatment should become an integral part of HIV care for patients to fully benefit from antiretroviral therapy. 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.) Uncovering the gastrointestinal passage, intestinal epithelial cellular uptake and Ago2 loading of milk miRNAs in neonates using xenobiotic tracers BackgroundExclusive breastfeeding is the best source of nutrition for most infants, but it is not always possible. Enteral nutrition influences intestinal gene regulation and the susceptibility for inflammatory bowel disorders, such as necrotizing enterocolitis (NEC). In modern neonatology it is observed that lactase activity increases during intestinal maturation, but formula-fed infants exhibit lower activity levels than milk-fed infants.

ObjectiveWe interrogate the transmissibility of milk miRNAs, since human breast milk has a high miRNA content in comparison to other body fluids. Our data contribute to the controversial discussion whether milk miRNAs could influence gene regulation in term and preterm neonates and thus might vertically transmit developmental relevant signals.

DesignFollowing their cross-species profiling via miRNA deep-sequencing we utilized dietary xenobiotic taxon-specific milk miRNA as tracers in human and porcine neonates, followed by functional studies in primary human fetal intestinal epithelial cells (HIEC-6) using Ad5-mediated miRNA-gene transfer.

ResultsWe show that mammals have in common many milk miRNAs yet exhibit taxon-specific miRNA fingerprints. We traced intact bovine-specific miRNAs from formula-nutrition in human preterm stool and 9 days after the onset of enteral feeding in intestinal cells of preterm piglets. Few hours after introducing enteral feeding in preterm piglets with supplemented reporter miRNAs (cel-miR-39-5p/-3p), we observed enrichment of the xenobiotic cel-miR in blood serum and in Ago2-immunocomplexes from intestinal biopsies. In contrast, we did not observe xenobiotic miRNAs in neonatal porcine cerebrospinal fluid.

ConclusionsTaken together, our data point to a transmissibility of milk miRNA signals, which could be relevant at least for intestinal maturation. Ad5-based miRNA-gene transfer into HIEC-6 revealed putative milk miRNA targets on the protein and transcriptome levels. Results suggest that milk miRNAs could influence gene expression in intestinal epithelia of neonates under special conditions.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/21262525v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@8e0435org.highwire.dtl.DTLVardef@1b6747corg.highwire.dtl.DTLVardef@1998821org.highwire.dtl.DTLVardef@b84a04_HPS_FORMAT_FIGEXP  M_FIG C_FIG It is already known that exclusive breastfeeding is the best source of nutrition for neonates.Human breast milk has a high miRNA content in comparison to other body fluids. It is controversially discussed whether they could influence gene regulation in term and preterm neonates and thus might vertically transmit developmental relevant signals. Here, we contribute important new findings: Mammals have in common a significant number of milk miRNAs yet exhibit taxon-specific fingerprints. These differences allowed us to exploit xenobiotic miRNAs as tracers in human preterm neonates, who routinely received formula-supplemented nutrition in addition to breast milk. Tracer miRNAs survived the gastrointestinal (GI) transit in human preterm neonates. In a preterm piglet model the reporter miRNA did not only survive GI transit, but accumulated in the bloodstream few hours post-feeding. Moreover, we show that, cel-mir-39-5p and cel-miR-39-3p became loaded to Ago2 in intestinal tissue samples, which is prerequisite for milk microRNAs biological relevance. Adenovirus type 5-based miRNA-gene transfer into HIEC-6 allowed us to examine predicted bovine milk miRNA targets on the protein and transcriptome levels. Distinct time courses and pathogenic contributions of alveolar epithelial and endothelial injury in acute respiratory distress syndrome with COVID-19: evidence from circulating biomarkers The time course and specific contributions of alveolar epithelial and endothelial injury to the pathogenesis of acute respiratory distress syndrome (ARDS) with coronavirus disease (COVID-19) remain unclear. Here, we evaluated the characteristics of circulating markers of alveolar epithelial and endothelial injury in serum samples from eleven ARDS patients and ten non-ARDS patients, all with COVID-19. Our results indicates that the alveolar epithelial injury at the very early disease stage and the endothelial injury which continues to exacerbate during the later disease stage seem to be the hallmarks of ARDS with COVID-19.