Coverage and Effectiveness of mRNA COVID-19 Vaccines among Veterans ImportanceThe effectiveness of mRNA vaccination in a large and diverse American population, with older age and higher co-morbidity has not been assessed.

ObjectiveTo describe the scope of the mRNA vaccination rollout among the diverse U.S. Veterans population, and to study the mRNA COVID-19 vaccine effectiveness (VE) against infection, symptomatic disease, hospitalization, and death.

MethodsVaccination histories were obtained from medical records to determine if patients tested for SARS-CoV-2 were unvaccinated, partially vaccinated (first dose of mRNA COVID-19 vaccine), or fully vaccinated (two doses) at time of testing. First, coverage with any COVID-19 vaccination was described for all Veterans enrolled in Veterans Health Administration (VHA). Second, to evaluate VE, a matched test-negative case-control evaluation was conducted utilizing SARS-CoV-2 positive (cases [n=16,690]) and SARS-CoV-2 negative (controls [n=61,610]) tests from Veterans aged [&ge;]18 years old who routinely sought care at a VHA facility and were tested from December 14, 2020, through March 14, 2021. VE was calculated from odds ratios (ORs) with 95% confidence intervals (CI).

ResultsBy March 7, 2021, among 6,170,750 Veterans, 1,547,045 (23%) received at least one COVID-19 vaccination. mRNA COVID-19 VE against infection, regardless of symptoms, was 94% (95% CI 92-95) and 58% (95%CI 54-62) for full and partial vaccination (vs. no vaccination), respectively. VE against infection was similar across subpopulations, and it was not significantly different from VE against symptomatic disease. VE against COVID-19-related hospitalization and death for full vs. no vaccination was 89% (95%CI 81-93) and 99% (95%CI 87-100), respectively.

Conclusions and RelevanceThe VHAs efficient and equitable distribution of effective vaccines decreased COVID-19 infections, hospitalization, and mortality similarly for all Veterans, including Veterans with low income, homeless Veterans, immunocompromised, the elderly, minorities, and rural Veterans thus reducing health inequalities.
Could widespread use of antiviral treatment curb the COVID-19 pandemic? A modeling study. Despite the development of safe and effective vaccines, effective treatments for COVID-19 disease are still urgently needed. Several antiviral drugs have shown to be effective in reducing progression of COVID-19 disease. In the present work, we use an agent-based mathematical model to assess the potential population impact of the use of antiviral treatments in four countries with different demographic structure and current levels of vaccination coverage: Kenya, Mexico, United States (US) and Belgium. We analyzed antiviral effects on reducing hospitalization and death, and potential antiviral effects on reducing transmission. For each country, we varied daily treatment initiation rate (DTIR) and antiviral effect in reducing transmission (AVT). Irrespective of location and AVT, widespread antiviral treatment of symptomatic adult infections ([&ge;]20% DTIR) prevented the majority of COVID-19 deaths, and recruiting 6% of all adult symptomatic infections daily reduced mortality by a third in all countries. Furthermore, our model projected that targeting antiviral treatment to the oldest age group (65 years old and older, DTIR of 20%) can prevent over 47% of deaths. Our results suggest that early antiviral treatment (as soon as possible after inception of infection) is needed to mitigate transmission, preventing 50% more infections compared to late treatment (started 3 to 5 days after symptoms onset). Our results highlight the synergistic effect of vaccination and antiviral treatment: as the vaccination rate increases, antivirals have a larger relative impact on population transmission. These results suggest that antiviral treatments can become a strategic tool that, in combination with vaccination, can significantly reduce COVID-19 hospitalizations and deaths and can help control SARS-CoV-2 transmission.
Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study) Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

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

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years. The effects of modifiable maternal pregnancy exposures on offspring molar-incisor hypomineralisation: A negative control study ObjectivesO_LITo explore the associations between modifiable maternal pregnancy exposures: pre-pregnancy body mass index (BMI), pregnancy smoking and alcohol consumption with offspring molar-incisor hypomineralisation (MIH).
C_LIO_LITo explore for the presence of residual confounding using negative control analyses.
C_LI

MethodsThis study used data from Avon Longitudinal Study of Parents and Children (ALSPAC), a UK prospective birth cohort. We defined offspring MIH using prospectively collected questionnaire data. We used logistic regression to explore confounder adjusted associations between maternal pre-pregnancy BMI and smoking and alcohol consumption during pregnancy with MIH. We included negative control exposure (paternal BMI, smoking and alcohol around the time of pregnancy) and outcome (offspring dental trauma) analyses to explore for the presence of residual confounding.

Results5536 mother/offspring pairs were included (297 MIH cases [5.4%]). We found a positive association between maternal mean BMI and offspring MIH (OR per 1-kg/m2 difference in maternal BMI: 1.04, 95% CI: 1.00, 1.08). In subsequent analyses, we found evidence that this effect was non-linear and being driven by women in the highest BMI quintiles. In negative control analyses, we found no evidence of association between paternal BMI and offspring MIH (OR: 0.94, 95% CI: 0.89, 1.00) and maternal BMI and offspring dental trauma (OR: 0.99, 95% CI: 0.96, 1.02). There was no clear evidence of an association for maternal pregnancy smoking (OR: 0.76, 95%CI: 0.46, 1.22) and alcohol consumption (OR: 0.79, 95% CI: 0.56, 1.21) with offspring MIH with results imprecisely estimated.

ConclusionIn summary we found evidence of a possible intrauterine effect of high maternal pre-pregnancy BMI on offspring MIH. We did not find robust evidence for an intrauterine effect of maternal pregnancy smoking or alcohol consumption on offspring MIH. Our findings provide further support for women of reproductive age to maintain a healthy weight. Future studies are warranted to explore possible mechanisms on how the pregnancy environment may relate to offspring MIH. Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine Diffusion Kurtosis Imaging (DKI) has undisputed advantages over more classical diffusion Magnetic Resonance Imaging (dMRI), as witnessed by a fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized in Spinal Cord (SC) imaging because of its inherently demanding technological requirements.

Due to its extreme sensitivity to non-gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, and not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between SC region and the above brain, managing to apply such a method to neonatal cohort becomes of utmost importance.

This study will (i) review the current methodological challenges associated with application of advanced dMRI methods like DKI in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox (SCT) for handling with DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present preliminary results of its application in a pilot clinical case study.

Results of this application agree with findings achieved in a corresponding adult survey, thus confirming validity of adopted pipeline and diagnostic value of DKI in pediatrics. Gamma Frequency Sensory Stimulation in Probable Mild Alzheimer's Dementia Patients: Results of a Preliminary Clinical Trial Non-invasive Gamma ENtrainment Using Sensory stimuli (GENUS) at 40Hz reduced Alzheimers disease (AD) pathology, prevented cerebral atrophy and improved performance during behavioral testing in mouse models of AD. We report data from a safety study (NCT04042922) and a randomized, placebo-controlled trial in participants with probable mild AD dementia after 3 months of one-hour daily 40Hz light and sound GENUS (NCT04055376) to assess safety, compliance, entrainment and possible effects on brain structure, function, sleep and cognitive function. GENUS was well-tolerated and compliance was high in both groups. Electroencephalography recordings show that our GENUS device safely and effectively induced 40Hz entrainment in cognitively normal subjects and participants with mild AD. After 3 months of daily stimulation, participants with mild AD in the 40Hz GENUS group showed less ventricular enlargement and stabilization of the hippocampal size compared to the control group. Functional connectivity increased in both the default mode network and the medial visual network after 3 months of stimulation. Circadian rhythmicity also improved with GENUS. Compared to controls, the active group performed better on the face-name association delayed recall test. These results suggest that 40Hz GENUS can be used safely at home daily and shows favorable outcomes on cognitive function, daily rhythms, and structural and functional MRI biomarkers of AD-related degeneration. These results support further evaluation of GENUS in larger and longer clinical trials to evaluate its potential as a disease modifying therapeutic for Alzheimers disease. Using explainable machine learning to identifypatients at risk of reattendance at discharge from emergency departments Short-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance could help reduce the number of missed critical illnesses and could reduce avoidable utilization of emergency departments by enabling targeted post-discharge intervention. In this manuscript we present a retrospective, single-centre study where we created and evaluated an extreme gradient boosted decision tree model trained to identify patients at risk of reattendance within 72 hours of discharge from an emergency department (University Hospitals Southampton Foundation Trust, UK). Our model was trained using 35,447 attendances by 28,945 patients and evaluated on a hold-out test set featuring 8,847 attendances by 7,237 patients. The set of attendances from a given patient appeared exclusively in either the training or the test set. Our model was trained using both visit level variables (e.g., vital signs, arrival mode, and chief complaint) and a set of variables available in a patients electronic patient record, such as age and any recorded medical conditions. On the hold-out test set, our highest performing model obtained an AUROC of 0.747 (95% CI : 0.722-0.773) and an average precision of 0.233 (95% CI : 0.194-0.277). These results demonstrate that machine-learning models can be used to classify patients, with moderate performance, into low and high-risk groups for reattendance. We explained our models predictions using SHAP values, a concept developed from coalitional game theory, capable of explaining predictions at an attendance level. We demonstrated how clustering techniques can be used to investigate the different sub-groups of explanations present in our patient cohort. 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 Factors influencing self-harm thoughts and self-harm behaviours over the first year of the COVID-19 pandemic in the UK: a longitudinal analysis of 49,324 adults BackgroundThere is concern that the COVID-19 pandemic and its aftermath will result in excess suicides by increasing known risk factors such as self-harm, but evidence on how pandemic-related risk factors contribute to changes in these outcomes is lacking.

AimsTo examine how different COVID-19-related adverse experiences and adversity worries contribute to changes in self-harm thoughts and behaviours.

MethodData from 49,324 UK adults in the UCL COVID-19 Social Study were analysed (1 April 2020 to 17 May 2021). Fixed effects regressions explored associations between weekly within-person variation in five categories of adversity experiences and adversity worries with changes in self-harm thoughts and behaviours across age groups (18-29, 30-44, 45-59, and 60+ years).

Results26.1% and 7.9% respondents reported self-harm thoughts and behaviours, respectively, at least once over the study period. More adverse experiences were more strongly related to outcomes than worries. The largest specific adversity contributing to increases in both outcomes was having experienced physical or psychological abuse. Financial worries increased the likelihood of both outcomes in most age groups, whilst having had COVID-19 increased the likelihood of both outcomes in young (18-29 years) and middle-aged (45-59 years) adults.

ConclusionsFindings suggest that a significant portion of UK adults may be at increased risk for self-harm thoughts and behaviours during the pandemic. Given the likelihood that the economic and social consequences of the pandemic will accumulate, policy makers can begin adapting evidence-based suicide prevention strategies and other social policies to help mitigate its consequences. CD19+IgD+CD27- naive B Cells as predictors of humoral response to COVID 19 mRNA vaccination in immunocompromised patients Immunocompromised patients are considered high-risk and prioritized for vaccination against COVID-19. We aimed to analyze B-cell subsets in these patients to identify potential predictors of humoral vaccination response. Patients (n=120) suffering from hematologic malignancies or other causes of immunodeficiency and healthy controls (n=79) received a full vaccination series with an mRNA vaccine. B-cell subsets were analyzed prior to vaccination. Two independent anti-SARS-CoV-2 immunoassays targeting the receptor-binding domain (RBD) or trimeric S protein (TSP) were performed three to four weeks after the second vaccination. Seroconversion occurred in 100% of healthy controls, in contrast to 67% (RBD) and 82% (TSP) of immunocompromised patients, while only 32% (RBD) and 22% (TSP) achieved antibody levels comparable to those of healthy controls. The number of circulating CD19+IgD+CD27- naive B cells was strongly associated with antibody levels ({rho}=0.761, P<0.001) and the only independent predictor for achieving antibody levels comparable to healthy controls (OR 1.07 per 10-{micro}l increase, 95%CI 1.02-1.12, P=0.009). Receiver operating characteristic analysis identified a cut-off at [&ge;]61 naive B cells per {micro}l to discriminate between patients with and without an optimal antibody response. Consequently, measuring naive B cells in immunocompromised hematologic patients could be useful in predicting their humoral vaccination response. Global reports of takotsubo (stress) cardiomyopathy following COVID-19 vaccination: a systematic review and meta-analysis Background and aimsConcerns have been raised recently about takotsubo cardiomyopathy after receiving COVID-19 vaccines, particularly the messenger RNA (mRNA) vaccines. The goal of this study was to compile case reports in order to provide a comprehensive overview of takotsubo cardiomyopathy associated with COVID-19 vaccines.

MethodsFrom inception until March 10, 2022, a systematic literature search was conducted in PubMed and Google Scholar. The study included individuals who developed cardiac takotsubo cardiomyopathy as a result of receiving COVID-19 vaccinations, regardless of the type of vaccine or dose.

ResultsEight studies, including 8 cases, participated in the current systematic review. The median age was 61.6 years; 87.5% were female, while 12.5% were male. 75% of the patients received the mRNA COVID-19 vaccines, while 25% received other types. In addition, takotsubo cardiomyopathy occurred in 62.5% of patients after receiving the first dose and another 25% after the second dose of COVID-19 vaccines. Moreover, the mean number of days to the onset of symptoms was 2.62 days. All cases had an elevated troponin test and abnormal ECG findings. The left ventricular ejection fraction (LVEF) was above 50% among all cases. In terms of the average length of stay in the hospital, 62.5% stayed for 10.2 days, and all cases recovered from their symptoms.

ConclusionTakotsubo (stress) cardiomyopathy complications that are associated with COVID-19 vaccination are rare, they can be life-threatening. Chest pain should be considered an alarming symptom, especially in those who had received a second dose of the vaccine in the last 3 days. For diagnosis, CK-MB and troponin are better biomarkers to confirm myocarditis than CRP, ESR, and NT-proBNP. All of cases completely recovered. Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

MethodsThis prospective cross-sectional study recruited ocular-treatment-naive patients with type 2 diabetes mellitus (DM) registered in the community of Guangzhou, China. OCTA was used to obtain the measurements of FD and BVT in the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). Univariate and multivariate linear regression was used to analyse the correlation of FD and BVT in different layers with DR severity.

ResultsA total of 1282 patients with DM (1282 eyes), with a mean age of 64.2{+/-}7.8 years, were included. FD in the DCP decreased and BVT in the DCP increased in DR patients compared to non-DR patients, even after adjusting for confounding factors (P< 0.05). Trend analysis showed a significant decrease in the FD values as the DR progressed, while the BVT progressively increased with worsening DR severity (P< 0.01). The FD in DCP had a statistically significant positive correlation with FD in SCP and a negative correlation with BVT in SCP and BVT in DCP in all of the participants, including the non-DR group, moderate DR group and severe DR group (P< 0.01).

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. An ergonomic assessment tool for evaluating the effect of back exoskeletons on injury risk Low back disorders (LBDs) are a leading injury in the workplace. Back exoskeletons (exos) are wearable assist devices that complement traditional ergonomic controls and reduce LBD risks by alleviating musculoskeletal overexertion. However, there are currently no ergonomic assessment tools to evaluate risk for workers wearing back exos. Exo-LiFFT, an extension of the Lifting Fatigue Failure Tool, is introduced as a means to unify the etiology of LBDs with the biomechanical function of exos. We present multiple examples demonstrating how Exo-LiFFT can assess or predict the effect of exos on LBD risk without costly, time-consuming electromyography studies. For instance, using simulated and real-world material handling data we show an exo providing a 30 Nm lumbar moment is projected to reduce cumulative back damage by [~]70% and LBD risk by [~]20%. Exo-LiFFT provides a practical, efficient ergonomic assessment tool to assist safety professionals exploring back exos as part of a comprehensive occupational health program.

HIGHLIGHTSO_LIBack exos are wearable assist devices that complement ergonomic controls for reducing low back disorder (LBD) risks
C_LIO_LIHowever, no ergonomic assessment tools exist to evaluate LBD risks for workers wearing back exos
C_LIO_LIWe introduce Exo-LiFFT, an ergonomic assessment tool adapted from the Lifting Fatigue Failure Tool
C_LIO_LIExo-LiFFT is a practical tool that unifies the etiology of LBDs and biomechanical function of exos
C_LIO_LIExo-LiFFT can be used to assess or predict the effect of exos on LBD risk without EMG testing
C_LI Knee-extensor strength, symptoms, and need for surgery after two, four, or six exercise sessions/week using a home-based one-exercise program: A randomized dose-response trial of knee-extensor resistance exercise in patients eligible for knee replacement (the QUADX-1 trial). ObjectiveTo investigate firstly the efficacy of three different dosages of one home-based, knee-extensor resistance exercise on knee-extensor strength in patients eligible for knee replacement, and secondly, the influence of exercise on symptoms, physical function and decision on surgery.

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

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

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

Trial registrationClinicalTrials.gov identifier: NCT02931058. Preprint: https://doi.org/10.1101/2021.04.07.21254965. Correction of measurement error in a commercial multiple-breath washout device RationaleNitrogen multiple-breath washout (N2MBW) is an established technique to assess functional residual capacity (FRC) and ventilation inhomogeneity in the lung. Accurate measurement of gas concentrations is essential for the appropriate calculation of clinical outcomes.

ObjectivesWe investigated the accuracy of oxygen and carbon dioxide measurements used for the indirect calculation of nitrogen concentration in a commercial MBW device (Exhalyzer D, Eco Medics AG, Duernten, Switzerland) and its impact on FRC and lung clearance index (LCI).

MethodsHigh precision calibration gas mixtures and mass spectrometry were used to evaluate sensor output. We assessed the impact of corrected signal processing on FRC and LCI in a dataset of healthy children and children with cystic fibrosis using custom analysis software.

ResultsWe found inadequate correction for the cross sensitivity of the oxygen and carbon dioxide sensors in the Exhalyzer D device. This results in an overestimation of expired nitrogen concentration, and consequently FRC and LCI outcomes. Breath-by-breath correction of this error reduced mean (SD) FRC by 8.9 (2.2)% and LCI by 11.9 (4.0)%. It also resulted in almost complete disappearance of the tissue nitrogen signal at the end of measurements.

ConclusionsInadequate correction for cross sensitivity between the oxygen and carbon dioxide gas sensors of the Exhalyzer D device leads to an overestimation of FRC and LCI. Correction of this error is possible and could be applied by re-analysing the measurements breath-by-breath in an updated software version.

Grants, Gifts, Equipment, DrugsEco Medics AG (Duernten, Switzerland) provided a research version of their commercial software Spiroware 3.2.1 including insight on signal processing algorithms and helped with the acquisition of mass spectrometry measurements. This project was funded by the Swiss National Science Foundation, Grant Nr. 182719 (P. Latzin) and 168173 (K. Ramsey) "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

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

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

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need. Distilling a High Precision Drug Adverse Effect Benchmark Using Wikipedia's Wisdom of the Crowd BackgroundLarge datasets of relational medical data, such as the adverse effects of drugs or vaccines, typically attain their large size, by relying on automatic, or semi-automatic, methods for generation. This often comes with a compromise on the precision of the generated data, which can be at least partially alleviated by having experts curate the data.

AimSince having experts review a large dataset can be costly and time consuming, here we suggest using Wikipedia for this task - that is, augment the automatic generation step by an automatic curation step based on the expert knowledge accumulated in Wikipedia.

MethodsTo curate a dataset of adverse drug effects (ADEs), we suggest retrieving the Wikipedia page associated with the drug, and checking whether the ADE appears in the sections describing adverse effects. Drug indications, typically described in the opening paragraph of the page, are similarly filtered out.

ResultsWe use the method to curate two large adverse drug effect datasets and show that the obtained datasets have a much higher precision relative to their originating ones.

ConclusionsAlgorithms which aim to infer drug-ADE relations, should at the very least be able to identify the "clear cut" cases. The high-precision benchmark constructed herein may therefore be a valuable resource for the evaluation of such algorithms. 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. Real-time Updating of Dynamic Social Networks for COVID-19 Vaccination Strategies Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities. The Addiction Risk Factor: A Unitary Genetic Vulnerability Characterizes Substance Use Disorders and Their Associations with Common Correlates Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modelling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance specific Ns range: 82,707-435,563), while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology. Quantifying phenotype and genotype distributions in single muscle fibres from patients carrying the pathogenic mtDNA variant m.3243A>G Cells are thought to tolerate the presence of heteroplasmic pathogenic mitochondrial (mt)DNA variants, up to a threshold proportion with little or no functional consequence, only developing a detectable oxidative phosphorylation (OXPHOS) defect once this threshold is exceeded. We hypothesised that, given the highly variable phenotypic presentation and severity of disease caused by the most common heteroplasmic pathogenic mtDNA variant m.3243A>G, this threshold may vary between patients. To estimate this threshold we examined the relationship between m.3243A>G level and deficiency of respiratory complexes I and IV in hundreds of single skeletal muscle fibres captured by laser microdissection from 17 patients carrying the m.3243A>G variant. We confirmed that tissue homogenate m.3243A>G level is a poor surrogate for the broad and complex distributions of m.3243A>G level in single cells from individual patients. We used unsupervised machine learning to characterise the biochemical status of muscle fibres, based on immunocytochemical measurements and estimate that the m.3243A>G threshold proportion above which myofibres develop a respiratory complex defect is 82.8% (IQR:2.7%). We do not find any significant difference in threshold between individuals, however we demonstrate that the pattern of respiratory complex defect and the distribution of m.3243A>G varies considerably between patients. This observation suggests that the pathogenesis of m.3243A>G is more diverse than previously thought. Caffeine and Methylliberine: A Human Pharmacokinetic Interaction Study Methylliberine and theacrine are methylurates found in the leaves of various Coffea species and Camellia assamica var. kucha, respectively. We previously demonstrated that the methylxanthine caffeine increased theacrines oral bioavailability in humans. Consequently, we conducted a double-blind, placebo-controlled study pharmacokinetic study in humans administered methylliberine, theacrine, and caffeine to determine methylliberines pharmacokinetic interaction potential with either caffeine or theacrine. Subjects (n = 12) received an oral dose of either methylliberine (25 or 100 mg), caffeine (150 mg), methylliberine (100 mg) plus caffeine (150 mg), or methylliberine (100 mg) plus theacrine (50 mg) using a randomized, double-blind, crossover design. Blood samples were collected over 24 hours and analyzed for methylliberine, theacrine, and caffeine using UPLC-MS/MS. Methylliberine exhibited linear pharmacokinetics that were unaffected by co-administration of either caffeine or theacrine. However, methylliberine co-administration resulted in decreased oral clearance (41.9 {+/-} 19.5 vs. 17.1 {+/-} 7.80 L/hr) and increased half-life (7.2 {+/-} 5.6 versus 15 {+/-} 5.8 hrs) of caffeine. Methylliberine had no impact on caffeines maximum concentration (440 {+/-} 140 vs. 458 {+/-} 93.5 ng/mL) or oral volume of distribution (351 {+/-} 148 vs. 316 {+/-} 76.4 L). We previously demonstrated theacrine bioavailability was enhanced by caffeine, however, caffeine pharmacokinetics were unaffected by theacrine. Herein, we found that methylliberine altered caffeine pharmacokinetics without a reciprocal interaction, which suggests caffeine may interact uniquely with different methylurates. Understanding the mechanism(s) of interaction between methylxanthines and methylurates is of critical importance in light of the recent advent of dietary supplements containing both purine alkaloid classes. Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. The effect of stimulus duration on preferences for gain adjustments when listening to speech ObjectivesIn the personalisation of hearing aid fittings, gain is often adjusted to suit patient preferences using live speech. When using brief sentences as stimuli, the minimum gain adjustments necessary to elicit consistent preferences ( preference thresholds) were previously found to be much greater than typical adjustments in current practice. The current study examined the role of duration on preference thresholds.

DesignParticipants heard 2, 4 and 6-s segments of a continuous monologue presented successively in pairs. The first segment of each pair was presented at each individuals real-ear or prescribed gain. The second segment was presented with a {+/-}0-12 dB gain adjustment in one of three frequency bands. Participants judged whether the second was "better", "worse" or "no different" from the first.

Study SampleTwenty-nine adults, all with hearing-aid experience.

ResultsThe minimum gain adjustments needed to elicit "better" or "worse" judgments decreased with increasing duration for most adjustments. Inter-participant agreement and intra-participant reliability increased with increasing duration up to 4 s, then remained stable.

ConclusionsProviding longer stimuli improves the likelihood of patients providing reliable judgments of hearing-aid gain adjustments, but the effect is limited, and alternative fitting methods may be more viable for effective hearing-aid personalisation. 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.