Full vaccination against COVID-19 suppresses SARS-CoV-2 delta variant and spike gene mutation frequencies and generates purifying selection pressure COVID-19 vaccination resistance has become a major challenge to prevent global SARS-CoV-2 transmission. Here we report that the vaccination coverage rate is inversely correlated to the mutation frequency of the full genome (R2=0.878) and spike gene (R2=0.829) of SARS-CoV-2 delta variants in 16 countries, suggesting that full vaccination against COVID-19, with other mitigation strategies, is critical to suppress emergent mutations. Neutrality analysis of DH and Zengs E tests suggested that directional selection was the major driving force of delta variant evolution. To eliminate the homogenous effects (population expansion, selective sweep etc.), the synonymous (Dsyn) and nonsynonymous (Dnonsyn) polymorphisms of the delta variant spike gene were estimated with Tajimas D statistic. Both D ratio (Dnonsyn/Dsyn) and {Delta}D (Dsyn-Dnonsyn) have positive correlation with the full vaccination rate (R2= 0.723 and 0.505, respectively) in 19 countries, indicating that purifying selection pressure of SARS-CoV-2 spike gene increased as the vaccination coverage rate increased. Taken together, our data suggests that vaccination plays an important role in the purifying selection force of spike protein of SARS-CoV-2 delta variants.
The source of individual heterogeneity shapes infectious disease outbreaks There is known heterogeneity between individuals in infectious disease transmission patterns. The source of this heterogeneity is thought to affect epidemiological dynamics but studies tend not to control for the overall heterogeneity in the number of secondary cases caused by an infection. To explore the role of individual variation in infection duration and transmission rate on parasite emergence and spread, while controlling for this potential bias, we simulate stochastic outbreaks with and without parasite evolution. As expected, heterogeneity in the number of secondary cases decreases the probability of outbreak emergence. Furthermore, for epidemics that do emerge, assuming more realistic infection duration distributions leads to faster outbreaks and higher epidemic peaks. When parasites require adaptive mutations to cause large epidemics, the impact of heterogeneity depends on the underlying evolutionary model. If emergence relies on within-host evolution, decreasing the infection duration variance decreases the probability of emergence. These results underline the importance of accounting for realistic distributions of infection rates to anticipate the effect of individual heterogeneity on epidemiological dynamics.
Hyperreflective foci, OCT progression indicators in age-related macular degeneration, include transdifferentiated retinal pigment epithelium PurposeBy optical coherence tomography (OCT) imaging, hyperreflective foci (HRF) indicate progression risk for advanced age-related macular degeneration (AMD) and are in part attributable to ectopic retinal pigment epithelium (RPE). We hypothesized that ectopic RPE are molecularly distinct from in-layer cells and that their cross-retinal course follows Muller glia.

MethodIn clinical OCT (61 eyes, 44 AMD patients, 79.4 {+/-} 7.7 years; 29 female; follow-up = 4.7 {+/-} 0.9 years) one HRF type, RPE plume, was reviewed. Twenty eyes of 20 donors characterized by ex vivo OCT were analyzed by histology (normal, 4; early/intermediate AMD, 7; geographic atrophy (GA), 6; 3 neovascular AMD (nvAMD). Cryosections were stained with antibodies to retinoid (RPE65, CRALPB) and immune (CD68, CD163) markers. In published RPE cellular phenotypes, red immunoreactivity was assessed semi-quantitatively by one observer (none, some cells, all cells).

ResultsTrajectories of RPE plume and cellular debris paralleled Muller glia, whether ordered or subsident, near atrophy borders. RPE corresponding to HRF lost immunoreactivity for retinoid markers and gained immunoreactivity for immune markers. Aberrant immunoreactivity appeared in individual in-layer RPE cells and extended to all abnormal phenotypes. Muller glia remained CRALBP-positive. Plume cells approached and contacted retinal capillaries.

ConclusionGain- and loss-of-function starts with individual in-layer RPE cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may impair rod vision while Muller glia sustain cone vision. Evidence for RPE transdifferentiation, possibly due to ischemia, supports a proposed process of epithelial-mesenchyme transition. Data can propel new biomarkers and therapeutic strategies for AMD.

PrecisHyperreflective foci (HRF) are OCT progression risk indicators in age-related macular degeneration. Abnormal RPE cells including some that correspond to HRF lose immunoreactivity for retinoid markers and gain immunoreactivity for immune markers, indicating molecular transdifferentiation. 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. 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/. Hairpin structure facilitates multiplex high-fidelity DNA amplification in real-time PCR Clinically and biologically, it is essential to detect rare DNA-sequence variants for early cancer diagnosis or drug-resistance mutations identification. Some of the common quantitative PCR (qPCR)-based variant detection methods are restricted in the limit of detection (LoD) because the DNA polymerases used have a high polymerase misincorporation rate, thus the detection sensitivity is sometimes unsatisfactory. With the proofreading activity, high-fidelity (HiFi) DNA polymerases have a 50- to 250-fold higher fidelity. However, there are currently no proper probe-based designs as the fluorescence indicator allowing multiplexed HiFi qPCR reactions, thus restricting the application of HiFi DNA polymerases like the variant detection. We presented the Occlusion System, composed of a 5-overhanged primer with fluorophore modification and a probe with a short-stem hairpin and a 3 quencher modification. We demonstrated that the Occlusion System allowed multiplexing HiFi qPCR reaction, and it was compatible with the current variant-enrichment method to improve the LoD up to 10-fold. Thus, the Occlusion System satisfactorily functioned as efficient fluorescence indicator in HiFi qPCR reactions and allowed application of HiFi DNA polymerases in variant detection methods to improve detection sensitivity. The antibody response to SARS-CoV-2 infection persists over at least 8 months in symptomatic patients The factors involved in the persistence of antibodies to SARS-CoV-2 are unknown. We evaluated the antibody response to SARS-CoV-2 in personnel from 10 healthcare facilities and its association with individuals characteristics and COVID-19 symptoms in an observational study. We enrolled 4735 subjects (corresponding to 80% of all personnel) for three time points over a period of 8-10 months. For each participant, we determined the rate of antibody increase or decrease over time in relation to 93 features analyzed in univariate and multivariate analyses through a machine learning approach. In individuals positive for IgG ([&ge;] 12 AU/mL) at the beginning of the study, we found an increase [p= 0.0002] in antibody response in symptomatic subjects, particularly with anosmia/dysgeusia (OR 2.75, 95% CI 1.753 - 4.301), in a multivariate logistic regression analysis. This may be linked to the lingering of SARS-CoV-2 in the olfactory bulb. Deep Covid -Covid Diagnosis Using Deep Neural Networks and Transfer Learning Coronavirus is a global emergency as of May 2021. If not acted upon by drugs at the right time, coronavirus may result in the death of individuals. Hence early diagnosis is very important along the progress of the disease. This paper focuses on coronavirus detection using x-ray images, for automating the diagnosis pipeline using convolutional neural networks and transfer learning. This could be deployed in places where radiologists are not easily available in order to detect the disease at very early stages. In this study we propose our deep learning architecture for the classification task, which is trained with modified images, through multiple steps of preprocessing. Our classification method uses convolutional neural networks and transfer learning architecture for classifying the images. Our findings yield an accuracy value of 91.03%, precision of 89.76 %, recall value of 96.67% and F1 score of 93.09%. Serum Vitamin D levels are associated with increased COVID-19 severity and mortality independent of whole-body and visceral adiposity INTRODUCTIONCoronavirus disease (COVID-19) is a global pandemic. Vitamin D deficiency has been associated with susceptibility to infectious disease. In this study, the association between COVID-19 outcomes and vitamin D levels in patients attending a COVID-19 reference center in Mexico City are examined.

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

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

CONCLUSIONVitamin D deficiency ([&le;]12ng/mL or <30nmol/L), is independently associated with COVID-19 mortality after adjustment for visceral fat (epicardial fat thickness). Low vitamin D may contribute to a pro-inflammatory and pro-thrombotic state, increasing the risk for adverse COVID-19 outcomes. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

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

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

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

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. Fractality of tics as a quantitative assessment tool for Tourette syndrome. Tics manifest as brief, purposeless, and unintentional movements or noises that, for many individuals, can be suppressed temporarily with effort. Peterson and Leckman (1998) hypothesized that the chaotic temporal nature of tics could possess an inherent fractality, that is, have neighbor-to-neighbor correlation at all levels of time scale. However, demonstrating this phenomenon has eluded researchers for more than two decades, primarily because of the challenges associated with estimating the scale-invariant, power law exponent - called the fractal dimension Df - from fractional Brownian noise. Here, we confirm this hypothesis and establish the fractality of tics by examining two tic time series datasets collected 6-12 months apart in children with tics, using one-dimensional random walk models. We find that Df increases from [~]1.4 to 1.75 in order of decreasing tic severity, and is correlated with tic severity as measured by the YGTTS total tic score. We demonstrate Df to be a sensitive parameter in examining the effect of several tic suppression conditions on the tic time series. We confirm the fractal nature of tics in Tourette syndrome (TS) and extend the finding to Provisional Tic Disorder. Our findings pave the way for utilizing the fractal nature of tics as a robust quantitative tool for estimating tic severity and treatment effectiveness, as well as a marker for differentiating typical from functional tics. Detection of COVID-19 and age-dependent dysosmia with paired crushable odorant ampules BackgroundSigns of anosmia can help detect COVID-19 infection when testing for viral positivity is not available. Inexpensive mass-produced disposable olfactory sensitivity tests suitable for worldwide use might serve not only as a screening tool for potential infection but also to identify cases at elevated risk of severe disease as anosmic COVID-19 patients have a better prognosis.

Methods and FindingsWe adopted paired crushable ampules with two concentrations of a standard test odorant (n-butanol) as standard of care in several clinics as community prevalence of COVID-19 infection waxed and waned. This was not a clinical trial; a chart review was undertaken to evaluate the operating characteristics and potential utility of the test device as RT-PCR testing became routine. The risk of anosmia was greater in COVID-19 patients. Olfactory sensitivity was concentration-dependent and decreased with aging. Hyposmia was detected across a wider age range than expected from the literature, and tests can be optimized to characterize different age groups.

Conclusionsn-Butanol at 0.32 and 3.2% in crushable ampules can be used to characterize olfactory function quickly and inexpensively and thus has potential benefits in pandemic screening, epidemiology, and clinical decision-making. Impact of COVID 19 on the quality of life (QoL) of patients living with Sickle Cell Disorder (SCD) in Lagos Nigeria The study aimed to assess the impact of the COVID-19 pandemic on Quality of Life (QoL) in persons living with Sickle Cell Disorder (SCD) in Lagos, Nigeria and to determine how they coped during the pandemic, particularly during the period of total lockdown with the additional "SHIELDING" measures to which they had to adhere. Data was collected using a standardized protocol PedsQL, Sickle Cell Disease Module version.3.0 designed for youth within the ages of (13-18) years, (19-35) years and their parents/Guardian if underage. The survey captured data on patients pain impact, hurts, management, treatments, communication with their caregivers and their Guardians perception. The survey was performed online, or Face-to-Face/telephone interview if online was not possible. Contacts of patients and parents were obtained from the database of Sickle Cell Foundation Nigeria. A total of 105 (80 patients and 25 parents) participants responded to the survey. The age distribution of respondents was highest at 56 % in the age bracket of 13 - 18 years old. Pain crisis were very common amongst patients. The survey revealed that the type of treatment or care received at these times determined whether or not the patients visited the hospital when they had pain crises. In addition, as patients reports an increase in ill-treatment they experienced in the hands of health care givers, so did the fear of accessing treatment during the COVID pandemic. It was observed that the frequency of pain crises experienced by SCD patients was proportional to the patients quality of life (the higher the frequency of pains, the worse the QoL). As a follow-up, a more detailed study would be required, as this study was limited in the capturing of the demographics, sex and number of participants; Considering the number of persons living with SCD that visit the Sickle Cell Foundation Nigeria, (about 3,000 patients), the number of responses in this study was low (105). It is believed that a higher number of responses would have given more information about the Sickle Cell burden and the QoL of persons living with SCD in Lagos during the COVID-19 pandemic. Lagos was the epicentre of the COVID-19 pandemic in Nigeria. Relationship Between Patient Sex and Serum Tumor Necrosis Factor Antagonist Drug and Anti-Drug Antibody Concentrations in Inflammatory Bowel Disease; A Nationwide Cohort Study BackgroundAnti-drug antibodies to infliximab (ATI) and adalimumab (ATA) are associated with loss of response to tumor necrosis factor antagonist (anti-TNF) therapy in inflammatory bowel disease (IBD). We evaluated the relationship between patient sex and serum TNF antagonist drug and antibody concentrations in inflammatory bowel disease

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

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

ConclusionIn patients receiving infliximab, anti-drug antibodies were higher in males than females. Consistent with this, serum drug concentrations were lower in males than females on infliximab. There was no difference in anti-drug antibody and serum drug concentrations among males and females on adalimumab. In addition, no difference in anti-drug antibodies between males and females receiving anti-TNF combination therapy was observed. 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. A Cross-Sectional Examination of Conflict-of-Interest Disclosures of Physician-Authors Publishing in High-Impact US Medical Journals ObjectiveTo assess the accuracy of self-reported financial conflict-of-interest (COI) disclosures in the New England Journal of Medicine (NEJM) and Journal of the American Medical Association (JAMA) within the requisite disclosure period prior to article submission.

DesignCross-sectional investigation.

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

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

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

ConclusionsHigh payment amounts, as well as high proportions of undisclosed financial compensation, regardless of amount received, comprised potential COIs for two influential US medical journals. Further research is needed to explain why such high proportions of general payments were undisclosed and whether journals that rely on self-reported COI disclosure need to reconsider their policies. Sequencing individual genomes with recurrent genomic disorder deletions: an approach to characterize genes for autosomal recessive rare disease traits In medical genetics, discovery and characterization of disease trait contributory genes and alleles depends on genetic reasoning, study design, and patient ascertainment; we now suggest a segmental haploid genetics approach to enhance gene discovery and molecular diagnostics. We present novel genomic insights to enhance discovery in the challenging context of autosomal recessive (AR) traits and bi-allelic variation. We demonstrate computationally that new mutation mediated by nonallelic homologous recombination (NAHR), involving recurrent deletions at 30 genomic regions, likely drives recessive disease burden for over 70% of loci within these segmental deletions or at least 2% of loci genome wide. Meta-analyses of literature-reported patients implicate that NAHR-deletions are depleted from the ascertained pool of AR trait alleles. Exome reanalysis of personal genomes from subjects harboring recurrent deletions uncovered new disease-contributing variants in genes including COX10, ERCC6, PRRT2 and OTUD7A. Our data demonstrate that genomic sequencing of personal genomes with NAHR-deletions could dramatically foment allele and gene discovery, enhance clinical molecular diagnosis, and could potentially enable human haploid genetics screens as an approach to disease biology. "If somebody had told me I'd feel like I do now, I wouldn't have believed them"    Older adults' experiences of the BELL trial: a qualitative study ObjectivesThis study examined older adults experiences of participating in the BELL trial, involving 12-weeks of group-based hardstyle kettlebell training.

MethodsIn the BELL trial, 28 insufficiently active older adults (15 women, 13 men, 59-79 years) completed 6 weeks of face-to-face group training, and 6 weeks of home-based training. In-depth semi-structured interviews were audio recorded and transcribed, inductively coded, with themes constructed thematically from patterns of shared meaning.

ResultsFour higher-order themes were developed that reflect older adults experiences participating in a group-exercise program of hardstyle kettlebell training. These included: (1) "Its one of the best things weve done" - enjoying the physical and psychosocial benefits, (2) "Its improved it tremendously!" - change in a long-term health condition, (3) "It put me on a better course" - overcoming challenges, (4) "I wasnt just a number" - feeling part of a group/community.

DiscussionFindings highlight the perceived physical and psychological benefits of participating in hardstyle group kettlebell training, the value attributed to being part of an age-matched community of like-minded people engaged in group-exercise, as well as the challenges participants faced, and the sense of achievement in overcoming them. Implications for program design and delivery, and future research are discussed. Covid-19 Associated Hepatitis in children (CAHC) during the second wave of SARS-CoV-2 infections in Central India: Is it a complication or transient phenomenon. Objective: While pediatric population has largely remained free of severe COVID-19, in some cases SARS-CoV-2 infection has been associated with complications like Multiple Inflammatory Syndrome in children (MIS-C). We mention another unique presentation subsequent to asymptomatic infection of SARS-CoV-2, a unique form of hepatitis designated by us as COVID-19 Associated Hepatitis in Children (CAH-C). The contrasting clinical presentations, temporal association and viral parameters of CAH-C cases, to the MIS-C cases are presented here. Methods: As a retrospective and follow-up observational study we reviewed all children testing positive for SARS-CoV-2 during study period. Children presenting with sudden onset of hepatitis, elevated transaminases, non-obstructive jaundice, lacking marked inflammatory responses and without evidence of (a) other known causes of acute hepatitis or previous underlying liver disease (b) multi-system involvement were classified as CAH-C, are described here. Results: Among 475 children who tested positive, 47 patients presented with hepatitis, 37 patients who had features of CAH-C, having symptoms of hepatitis only, with un-elevated inflammatory markers and uneventful recovery following supportive treatment. Whereas remaining 10 MIS-C hepatitis had protracted illness, multiple system involvement, required admission to critical care, and had mortality of 30%. Conclusion: With the emergence of newer variants of concern (VOC) including the Delta variant which predominated the second wave of infections in India and has now spread to more than 142 countries with changing presentations, CAH-C might be one of them. Cases of such new entities need to be identified early and differentiated from other emerging syndromes in children during the ongoing pandemic for preventing adversities by timely intervention. Spatial Allocation of Scarce COVID-19 Vaccines The COVID-19 Vaccines Global Access (COVAX) is an initiative led by the World Health Organization (WHO) and other partners that aims for an equitable access of COVID-19 vaccines. Despite a potential heterogeneous disease burden across space, countries receiving allotments of vaccines via COVAX may want to follow WHOs allocation rule and distribute vaccines to their jurisdictions based on the jurisdictions relative population size. Utilizing economic-epidemiological modeling, we benchmark the performance of this ad hoc allocation rule by comparing it to the rule that minimizes the economic damages and expenditures over time, including a penalty cost representing the social costs of deviating from the ad hoc allocation. Under different levels of vaccine scarcity and different demographic characteristics, we consider scenarios where length of immunity and compliance to travel restrictions vary, and consider the robustness of the rules when assumptions regarding these factors are incorrect. The benefits from deviating are especially high when immunity is permanent, when there is compliance to travel restrictions, when the supply of vaccine is low, and when there is heterogeneity in demographic characteristics. Interestingly, a lack of compliance to travel restrictions pushes the optimal allocations of vaccine towards the ad hoc and improves the relative robustness of the ad hoc rule, as the mixing of the populations reduces the spatial heterogeneity in disease burden.

JEL ClassificationC61, H12, H84, I18, Q54 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. 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 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. Deep learning for caries detection using optical coherence tomography Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries.