SARS-CoV-2 Omicron variant: exploring healthcare workers' awareness and perception of vaccine effectiveness: a national survey during the first week of WHO variant alert BackgroundAs the SARS-CoV2 Omicron variant spreads in several countries, healthcare workers (HCWs) perceptions and worries regarding vaccine effectiveness and boosters warrant reassessment.

MethodsAn online questionnaire among HCWs in Saudi Arabia (KSA) was distributed from Dec 1st to 6th 2021 to assess their perceptions, vaccine advocacy to the Omicron variant, and their perception of the effectivness of infection prevention measures and vaccination to prevent its spread, their Omicron variant related worries in comparison to the other variants, and their agreement with mandatory vaccination in general for adults.

ResultsAmong the 1285 HCW participants, two-thirds were female, 49.8 % were nurses, 46.4% were physicians, and 50.0% worked in tertiary care hospitals. 66.9% considered vaccination to be the most effective way to prevent the spread of the Omicron variant and future variants. The respondents however perceived social distancing (78.0%), universal masking (77.8%), and avoiding unnecessary travel (71.4%) as slightly superior to vaccination to prevent the spread of SARS-CoV-2 variants. HCWs aging 55 or older agreed singficanlty with vaccine ineffictivness to control Omicron spread, while those who believed in non-pharmacolgical infection prevention measures agreed signifcantly with vaccination for that purpose. Male HCWs had a significant agreement with mandatory vaccination of all eligible adult populations. On the other hand, unwilling HCWs to receive the vaccine had strong disagreements with mandatory vaccination.

ConclusionsThe current study in the first week of Omicron showed that only two-thirds of HCWs felt that vaccination was the best option to prevent the spread of the Omicron variant, indicating the need for further motivation campaigns for vaccination and booster dose. HCWs had a strong belief in infection prevention measures to contain the spread of SARS-CoV-2 variants that should be encouraged and augmented.
Projected health impact of post-discharge malaria chemoprevention among children with severe malarial anaemia in Africa Children recovering from severe malarial anaemia (SMA) remain at high risk of readmission and death after discharge from hospital. However, a recent trial found that post-discharge malaria chemoprevention (PDMC) reduces this risk. We developed a mathematical model describing the daily incidence of uncomplicated and severe malaria requiring readmission among 0-5 year-old children after hospitalised SMA. We fitted the model to a multicentre clinical PDMC trial using Bayesian methods. We then modelled the potential impact of PDMC across malaria-endemic African countries. In the 19 highest-burden countries, we estimate that only 2-5 children need to be given PDMC to prevent one hospitalised malaria episode, and less than 100 to prevent one death. If all hospitalised SMA cases access PDMC, 37,000 (range 16,000-84,000) malaria-associated readmissions could be prevented annually, depending on access to hospital care. We estimate that recurrent SMA post-discharge constitutes 18-29% of all SMA episodes in higher transmission settings.
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. Monitoring socioeconomic inequalities across HIV knowledge, attitudes, behaviours and prevention in 18 sub-Saharan African countries ObjectivesSocioeconomic inequalities in HIV prevention services coverage constitute important barriers to global prevention targets, especially in sub-Saharan Africa (SSA). We aimed at monitoring these inequalities from population-based survey data in 18 SSA countries between 2010 and 2018.

MethodsWe defined eight HIV indicators aimed at capturing uptake of HIV prevention services among adult participants. Country-specific wealth-related inequalities were measured using the Relative and Slope Index of Inequalities (RII and SII, respectively) and then pooled using random-effects meta-analyses. We compared inequalities between African regions using the Wilcoxon rank-sum test.

ResultsThe sample consisted of 358,591 participants (66% women). Despite variability between countries and indicators, the meta-analysis revealed significant levels of relative and absolute inequalities in 6 out of 8 indicators: HIV-related knowledge, positive attitudes toward people living with HIV (PLHIV), condom use at last sexual intercourse, participation to prevention of mother-to-child transmission programs, medical male circumcision and recent HIV testing. The largest inequalities were reported in condom use, with condom use reported 5 times more among the richest versus the poorest (RII=5.02, 95% Confidence interval, CI: 2.79-9.05) and in positive attitudes toward PLHIV, with a 32-percentage point difference between the richest and poorest (SII=0.32, 95% CI: 0.26-0.39). Conversely, no significant inequalities were observed in multi-partnership and HIV seropositivity among youth. Overall, inequalities tended to be larger in West and Central vs. East and Southern African countries.

ConclusionsDespite efforts to scale-up HIV-prevention programs, socioeconomic inequalities remain substantial over the continuum of HIV primary and secondary prevention in several SSA countries. 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. 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. Post-COVID-19 Memory Complaints: Prevalence and Associated Factors IntroductionMemory complaints resulting from COVID-19 may have a significant impact on the survivors quality of life. Unfortunately, there is insufficient information available on memory loss and its relationship to COVID-19. Therefore, the purpose of this research was to determine the prevalence of memory complaints in post-COVID-19 patients and to find potential contributing factors.

MethodA cross-sectional survey was conducted on 401 individuals who had previously been diagnosed with COVID-19 at four COVID testing centers situated across Bangladesh. The MAC-Q questionnaire was used to evaluate memory. A binary logistic regression model was fit to study the variables related to memory complaints, with a p-value of <0.05 deemed statistically significant.

ResultMemory complaints was prevalent in 19.2% of the post-COVID patients. Individual predictor analysis revealed that among the treatment modalities, steroids and antibiotics were associated with impaired memory. Multiple logistic regression showed that individuals who recovered from COVID-19 within six to twelve months were more likely to have memory deficits. Even though age, sex, oxygen demand, and hospitalization were not linked with memory complaints, rural residents exhibited more significant memory complaints than urban residents.

ConclusionNearly one-fifth of the COVID-19 patients suffer from various degrees of memory complaints within one year. However, no association was found between COVID-19 severity to memory complaints. DNR orders in SARS-CoV-2 patients: a retrospective validation study in a Swiss COVID-19 Center BackgroundThe worldwide pandemic situation forced many hospitals to adapt COVID-19 management strategies. In this scenario, the Swiss Academy of Medical Sciences (SAMW/ASSM) organized national guidelines based on expert opinion to identify Do-Not-Resuscitate (DNR) patients, to reduce futile ICU admission and resource misuse. However, the practical impact of this standardized national protocol has not been yet evaluated. In our specialized COVID-19 Center, we investigated characteristics and mortality of DNR patients identified according to national standardized protocol, comparing them to non-DNR patients.

MethodsThis was a pilot retrospective validation study, evaluating consecutive hospital admitted COVID-19 patients. Primary outcome was 30-days survival of DNR patients in comparison to the control group. Secondary outcomes reported quality of treatment of deceased patients, especially of agitation/sedation and dyspnea, using respectively the Richmond Agitation-Sedation Scale - Palliative care (RASS-PAL) for sedation and agitation (+4/-5) and the modified Borg Scale for dyspnea (1-10).

ResultsFrom March 16 to April 1, 2020, 213 consecutive patients were triaged; at 30-days follow-up, 9 patients (22.5%) died in the DNR group, 4 (2.2%) in the control group. The higher mortality rate in the DNR group was further confirmed by Log-Rank Mantel-Cox (23.104, p < 0.0001). In the DNR-group deceased patients, end-of-life support was performed with oxygen (100%), opioids (100%) and sedatives (89%); the mean RASS-PAL improved from 2.2 to -1.8 (p < 0.0001) and the Borg scale improved from 5.7 to 4.7 (p = 0.581).

ConclusionA national standardized protocol identified patients at higher risk of short-term death. Although the legal status of DNRs varies from country to country, the implementation of national standardized protocol could be the way to guarantee a better treatment of COVID-19 patients in a pandemic situation with limited resources. Epicardial adipose tissue thickness is associated with increased COVID-19 severity and mortality BACKGROUNDIncreased adiposity and visceral obesity have been linked to adverse COVID-19 outcomes. The amount of epicardial adipose tissue (EAT) may have relevant implications given its proximity to the heart and lungs. Here, we explored the role of EAT in increasing the risk for COVID-19 adverse outcomes.

METHODSWe included 748 patients with COVID-19 attending a reference center in Mexico City. EAT thickness, sub-thoracic and extra-pericardial fat were measured using thoracic CT scans. We explored the association of each thoracic adipose tissue compartment with COVID-19 mortality and severe COVID-19 (defined as mortality and need for invasive mechanical ventilation), according to the presence or absence of obesity. Mediation analyses evaluated the role of EAT in facilitating the effect of age, body mass index and cardiac troponin levels with COVID-19 outcomes.

RESULTSEAT thickness was associated with increased risk of COVID-19 mortality (HR 1.18, 95%CI 1.01-1.39) independent of age, gender, comorbid conditions and BMI. Increased EAT was associated with lower SpO2 and PaFi index and higher levels of cardiac troponins, D-dimer, fibrinogen, C-reactive protein, and 4C severity score, independent of obesity. EAT mediated 13.1% (95%CI 3.67-28.0%) and 5.1% (95%CI 0.19-14.0%) of the effect of age and 19.4% (95%CI 4.67-63.0%) and 12.8% (95%CI 0.03-46.0%) of the effect of BMI on requirement for intubation and mortality, respectively. EAT also mediated the effect of increased cardiac troponins on myocardial infarction during COVID-19.

CONCLUSIONEAT is an independent risk factor for severe COVID-19 and mortality independent of obesity. EAT partly mediates the effect of age and BMI and increased cardiac troponins on adverse COVID-19 outcomes. Declines and pronounced state disparities in prescription opioid distribution in the United States BackgroundThe United States (US) opioid epidemic is a persistent and pervasive public health emergency as it continues to claim the lives of Americans through addiction and overdose. There have been sustained efforts to reverse this iatrogenic crisis over the past decade. This study analyzed the changes in prescription opioid distribution for pain and identified regional differences between 2010 and 2019.

Methods and FindingsOpioid production data was obtained from the DEAs annual production quotas. Total opioid production has decreased 41.5% from 2013 (87.6 morphine mg equivalent metric tons) to 2019 (51.3). Opioid distribution from 2010 to 2019 was collected for ten prescription opioids (codeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, and tapentadol) from the US Drug Enforcement Administrations Automation of Reports and Consolidated Orders System. Regional variance was expressed as the ratio of the 95th to 5th percentiles of opioid distribution per state, corrected for population. The peak year for all ten prescription opioids was identified, individually, as between 2010 and 2013, except for codeine (2015). There was a 51.96% overall decrease in opioid distribution per capita with the largest decrease in Florida (-61.61%) and smallest in Texas (-18.64%). The largest quantities of opioid distribution were observed in Tennessee (520.70 morphine mg equivalent or MME per person) and Delaware (251.45) in 2011 and 2019. The smallest was Nebraska (153.39) in 2011 and Minnesota (90.49) in 2019. The highest to lowest state ratio of total opioid use, corrected for population, was sizable in 2011 (5.25) and 2019 (2.78). Similarly, the mean 95th/5th ratio was relatively stable in from 2011 (4.78 +0.70) and 2019 (5.64+0.98). The 95th/5th ratio in 2019 was greatest for methadone (10.23) and oxymorphone (10.09) and smallest for morphine (2.20) and fentanyl (2.12). Southern states (e.g MS, TN, AL, AK, DE, and NC) had the highest per capita distribution for eight of the ten opioids in 2019. The strength of the correlation between per capita hydrocodone and codeine, and hydromorphone and codeine increased significantly from 2011 to 2019

ConclusionsThis study found a decline in total production and distribution for ten prescription opioids during the last half-decade. However, distribution was non-homogeneous at a state level. Analysis of regional differences revealed a three-fold difference in the 95th:5th percentile ratio between states which was unchanged over the past decade. Future research focused on identifying factors contributing to the observed regional variability could prove valuable to understanding, and potentially remediating, the pronounced disparities in prescription opioid use in the US. Signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas Genetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the COVID-19 pandemic. The recently described variant of concern designated Omicron (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of COVID-19 cases in many countries. Because Omicron was recognized very recently, many knowledge gaps exist about its epidemiology and clinical severity and disease course. A comprehensive genome sequencing study of SARS-CoV-2 in the Houston Methodist healthcare system identified 862 symptomatic patients with infections caused by Omicron from late November 2021 through December 18, 2021. Omicron very rapidly increased in only three weeks to cause 90% of all new COVID-19 cases. Compared to patients infected with either Alpha or Delta variants in our healthcare system, Omicron patients were significantly younger, had significantly increased vaccine breakthrough rates, and were significantly less likely to be hospitalized. Omicron patients required less intense respiratory support and had a shorter length of hospital stay, consistent with decreased disease severity. Although the number of Omicron patients we studied is relatively small, in the aggregate the data document the unusually rapid spread and increased occurrence of COVID-19 caused by the Omicron variant in metropolitan Houston, and provide information about disease character. Integrated multi-omics reveals anaplerotic insufficiency in methylmalonyl-CoA mutase deficiency Multi-layered omics approaches can help define relationships between genetic factors, biochemical processes and phenotypes thus extending research of inherited diseases beyond identifying their monogenic cause 1. We implemented a multi-layered omics approach for the inherited metabolic disorder methylmalonic aciduria (MMA). We performed whole genome sequencing, transcriptomic sequencing, and mass spectrometry-based proteotyping from matched primary fibroblast samples of 230 individuals (210 affected, 20 controls) and related the molecular data to 105 phenotypic features. Integrative analysis identified a molecular diagnosis for 84% (177/210) of affected individuals, the majority (148) of whom had pathogenic variants in methylmalonyl-CoA mutase (MMUT). Untargeted analysis of all three omics layers revealed dysregulation of the TCA cycle and surrounding metabolic pathways, a finding that was further corroborated by multi-organ metabolomics of a hemizygous Mmut mouse model. Integration of phenotypic disease severity indicated downregulation of oxoglutarate dehydrogenase and upregulation of glutamate dehydrogenase, two proteins involved in glutamine anaplerosis of the TCA cycle. The relevance of disturbances in this pathway was supported by metabolomics and isotope tracing studies which showed decreased glutamine-derived anaplerosis in MMA. We further identified MMUT to physically interact with both, oxoglutarate dehydrogenase complex components and glutamate dehydrogenase providing evidence for a multi-protein metabolon that orchestrates TCA cycle anaplerosis. This study emphasizes the utility of a multi-modal omics approach to investigate metabolic diseases and highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.

Take home messageCombination of integrative multi-omics technologies with clinical and biochemical features leads to an increased diagnostic rate compared to genome sequencing alone and identifies anaplerotic rewiring as a targetable feature of the rare inborn error of metabolism methylmalonic aciduria.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/22269972v2_ufig1.gif" ALT="Figure 1">
View larger version (23K):
org.highwire.dtl.DTLVardef@1cb2b0org.highwire.dtl.DTLVardef@176cfaorg.highwire.dtl.DTLVardef@1f3cda7org.highwire.dtl.DTLVardef@142ce84_HPS_FORMAT_FIGEXP  M_FIG C_FIG The kidney releases a non-polymerizing form of Uromodulin in the urine and circulation that retains the external hydrophobic patch domain Uromodulin (Tamm-Horsfall protein, THP) is a glycoprotein uniquely produced in the kidney. It is released by cells of the thick ascending limbs (TAL) apically in the urine, and basolaterally in the renal interstitium and systemic circulation. Processing of mature urinary THP, which polymerizes into supra-molecular filaments, requires cleavage of an external hydrophobic patch (EHP) at the C terminus. However, THP in the circulation is not polymerized, and it remains unclear if non-aggregated forms of THP exist natively in the urine. We propose that an alternative processing path, which retains the EHP domain, can lead to a non-polymerizing form of THP. We generated an antibody that specifically recognizes THP with retained EHP (THP+EHP) and established its presence in the urine in a non-polymerized native state. Proteomic characterization of urinary THP+EHP revealed its C-terminus to end at F617. In the human kidney, THP+EHP was not only detected in TAL cells, but also diffusely in the renal parenchyma. Using immunoprecipitation followed by proteomic sequencing and immunoblotting, we then demonstrated that serum THP has also retained EHP. In a small cohort of patients at risk for acute kidney injury (AKI), admission urinary THP+EHP was significantly lower in patients who subsequently developed AKI during hospitalization. Our findings uncover novel insights into uromodulin biology by establishing the presence of an alternative path for cellular processing, which could explain the release of non-polymerizing THP in the circulation. Larger studies are needed to establish the utility of urinary THP+EHP as a sensitive biomarker of kidney health and susceptibility to injury. Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. Colorectal Cancer Disparities Across the Continuum of Cancer Care with a Focus on Surgery and Black Patients: A Systematic Review and Meta-Analysis ImportanceDespite increases in screening among vulnerable populations, colorectal cancer disparities persist.

ObjectiveTo direct future efforts towards high impact opportunities in addressing these disparities, we performed a systematic review and meta-analysis of the colorectal cancer disparities literature with a focus on the utilization of Surgery, the primary treatment for colorectal cancer.

Data SourcesTwo electronic databases (PubMed and SCOPUS) were searched for prospective and retrospective studies reporting on colorectal cancer disparities between 2011 and March 29, 2021.

Study SelectionStudies for the systematic review were selected if: (1) reported on disparities within colorectal, colon, or rectal cancer (2) articles were published in the English language (3) articles used only United States-sourced data.

Studies for the meta-analysis were selected if: (1) reported on at least one of three utilization of surgery outcomes: receipt of colorectal, colon, or rectal surgery, refusal of surgery, or receipt of laparoscopic versus open surgery (2) Outcomes were reported as Odds ratio according to multivariate analysis.

Data Extraction and SynthesisQuality appraisal and data extraction were performed independently by 2 reviewers using the Newcastle-Ottawa Scale for quality assessment. For the meta-analysis, pooled multivariate odds ratios for the three outcomes regarding utilization of surgery were separately calculated according to fixed or random-effects models. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-analyses guidelines.

Main Outcomes and MeasuresSystematic Review: The volume of publications attributed to the following sectors of the colorectal cancer care continuum: (1) Prevention, Screening, or Diagnosis (2) Treatment (3) Survivorship (4) End-of-life Care. Meta-analysis: Receipt of Colorectal, Colon, or Rectal Surgery and Black Race, Refusal of Surgery and Black Race, or Receipt of Laparoscopic versus Open Surgery and Black Race.

ResultsThe systematic review included 1,199 relevant publications. Among them, 60% were focused on Prevention, Screening, or Diagnosis, followed by Survivorship (20%), Treatment (15%), and End-of-Life Care (1%). Within the studies reporting on treatment disparities, 46% were focused on Race/Ethnicity, followed by Socioeconomic Status (28%), Age (17%), Gender (6%), Disabilities/Comorbidities (3%), and LGBTQI+ (0%). A total of 16 studies, including 1,110,674 patients, were applied to three separate meta-analyses regarding utilization of Surgery. Patients of black race were less likely to receive colorectal, or colon, or rectal surgery (OR 0.75, 95% CI 0.67-0.83), less likely to receive laparoscopic versus open colorectal cancer surgery (OR 0.91, 95% CI 0.88-0.94), and twice as likely to refuse colon surgery (OR 2.41, 95% CI 1.91-3.06).

Conclusions and RelevanceThe majority of research, to date, related to colorectal cancer disparities is focused on prevention, screening, or diagnosis and a minimal amount is dedicated to treatment. Additionally, all of the limited publications related to colorectal cancer surgery, as a treatment modality, are observational in nature. The application of this knowledge of past efforts and current continuing adverse outcomes is required in order to shift the focus of the research community towards treatment. In particular, research addressing surgical disparities is necessary, as surgery remains the primary treatment for colorectal cancer. 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. Early Stopping in Experimentation with Real-time Functional Magnetic Resonance Imaging Using a Modified Sequential Probability Ratio Test IntroductionFunctional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically-driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed.

MethodsVoxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR).

ResultsUse of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 minutes on a 12 minute scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters.

ConclusionA systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects. Novel polygenic risk score links depression-related cortical transcriptomic changes to brain morphology and symptom severity Our group developed a transcriptome-based polygenic risk score (T-PRS) that uses common genetic variants to capture  depression-like shifts in cortical gene expression. Here, we mapped T-PRS onto diagnosis and symptom severity in major depressive disorder (MDD) cases and controls from the Psychiatric Genomics Consortium (PGC). To evaluate potential mechanisms, we further mapped T-PRS onto discrete measures of brain morphology and broad depression risk in healthy young adults. Genetic, self-report, and/or neuroimaging data were available in 29,340 PGC participants (59% women; 12,923 MDD cases, 16,417 controls) and 482 participants in the Duke Neurogenetics Study (DNS: 53% women; aged 19.8{+/-}1.2 years). T-PRS was computed from SNP data using PrediXcan to impute cortical expression levels of MDD-related genes from a previous post-mortem transcriptome meta-analysis. Sex-specific regressions were used to test effects of T-PRS on depression diagnosis, symptom severity, and Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index in the PGC and DNS samples, respectively. T-PRS did not predict depression diagnosis (OR=1.007, 95%CI=[0.997-1.018]); however, it correlated with symptom severity in men (rho=0.175, p=7.957x10-4) in one large PGC cohort (N=762, 48% men). In DNS, T-PRS was associated with smaller amygdala volume in women ({beta}=-0.186, t=-3.478, p=.001) and less prefrontal gyrification (max[&le;]-2.970, p[&le;].006) in both sexes. In men, prefrontal gyrification mediated an indirect effect of T-PRS on broad depression risk (b=.005, p=.029), indexed using self-reported family history of depression. Depression-like shifts in cortical gene expression predict symptom severity in men and may contribute to disease vulnerability through their effect on cortical gyrification. Pausing methotrexate improves immunogenicity of COVID-19 vaccination in elderly patients with rheumatic diseases ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).

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

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

ConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age. The incidence of delirium in an acute geriatric community hospital: an observational cohort feasibility study. ObjectivesDelirium in hospitalised older adults is associated with negative health outcomes. Admission to an alternative care setting may lower the incidence of delirium. The Acute Geriatric Community Hospital (AGCH) was recently opened in the Netherlands and uses a multi-component non-pharmacological intervention strategy to prevent delirium. The objective of this study was to describe the incidence of delirium at the AGCH and compare this incidence to existing rates from literature. If a possible effect on delirium is seen in this comparison this would support conducting a larger prospectively controlled study on delirium in this new care setting.

DesignProspective cohort feasibility study; exploratory meta-analysis of proportions.

Setting and ParticipantsThe AGCH is an acute geriatric unit in a skilled nursing facility for patients aged >65 years with acute medical conditions.

MethodsDelirium assessment using the Confusion Assessment Method (CAM) upon admission and on day one, two and three or until delirium had resolved. Patients charts were reviewed if CAM was missing. In an linear mixed-effects model, the delirium incidence rate in AGCH was compared to pooled delirium incidence rates from six studies found in a high-quality review.

Results214 patients from the AGCH (mean age 81.9 years, 47% male, 12% with a history of dementia) were included in the analysis. Delirium developed in 8% (18/214) (95% confidence interval [CI] 5-13%) of patients during AGCH admission compared to 16% (95% CI 12-21%) in hospitals. Admission to the AGCH was associated with a decreased delirium incidence rate compared to the hospital control group (OR[odds ratio]= 0.49, 95% CI 0.24-0.98, p-value=0.044).

Conclusions and implicationsThe delirium incidence in the AGCH was low compared to those incidences found in general hospitals in literature. Based on these findings a controlled observational or randomized study measuring delirium in this care setting is recommended. 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. Psychological factors associated with instrumental activities of daily living disability in older adults with knee osteoarthritis PurposeThe population of older adults with knee osteoarthritis (OA)-related disabilities is increasing globally. This study aimed to investigate the psychological factors associated with instrumental activities of daily living (IADL) disability in older adults with knee OA.

Materials and MethodsA cross-sectional study was conducted on 179 patients with knee OA aged [&ge;] 65 years. The six-item short form of the Pain Catastrophizing Scale (PCS-6), the four-item short form of the Pain Self-Efficacy Questionnaire (PSEQ-4), and the fifteen-item Geriatric Depression Scale (GDS-15) were used to assess psychological factors. IADL status was assessed using eight activity items. Participants were divided into IADL-disabled and non-disabled groups. Binary logistic regression analyses were performed with the IADL disability status as the dependent variable. The PCS-6, PSEQ-4, and GDS-15 tools were included as independent variables in the logistic regression model. Demographics, motor functions, and pain intensity were also included as confounders.

ResultsOf the total participants, 88 (49.1%) showed disability in conducting IADL. PSEQ-4 (odds ratio =0.90, 95%; confidence interval=0.82-0.99, p=0.02) was a significant independent variable among all psychological factors.

ConclusionOur study showed the importance of assessing self-efficacy using the PSEQ-4 in relation to IADL disability in older adults with knee OA. Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods BackgroundPreventing in-hospital mortality in Patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.

ObjectivesThe objective of our research was to to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods.

MethodsWe divide non-randomly the American population with acute STEMI into a training set, a test set,and a validation set. We converted the unbalanced data into balanc ed data. We used artificial intelligence methods to develop and externally validate the dia gnostic model of in-hospital mortality in acute STEMI patients. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluat e the pros and cons of the above models.

ResultsThe strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation(AF), ventricular fibrillation(VF),third degree atrioventricular block,in-hospital bleeding, underwent percutaneous coronary intervention(PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history.The F2 score of logistic regression in the training set, the test set, and the validation data set were 0.81, 0.6, and 0.59 respectively.The AUC of logistic regression in the training set, the test set, and the validation data set were 0.77, 0.78, and 0.8 respectively. The diagnostic model built by logistic regression was the best.

ConclusionWe had used artificial intelligence methods developed and externally validated the diagnostic model of in-hospital mortality in acute STEMI patients.

We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). Adaptation of HL7 FHIR for the exchange of patients' gene expression profiles High-throughput technologies, especially gene expression analyses can accurately capture the molecular state in patients under different conditions. Thus, their application in clinical routine gains increasing relevance and fosters patient stratification towards individualized treatment decisions. Electronic health records already evolved to capture genomic data within clinical systems and standards like FHIR enable sharing within, and even between institutions. However, FHIR only provides profiles tailored to variations in the molecular sequence, while expression patterns are neglected although being equally important for decision making. Here we provide an exemplary implementation of gene expression profiles of a microarray analysis of patients with acute myeloid leukemia using an adaptation of the FHIR genomics extension. Our results demonstrate how FHIR resources can be facilitated in clinical systems and thereby pave the way for usage for the aggregation and exchange of transcriptomic data in multi-center studies. Survey of Contaminated Percutaneous Injuries in Anesthesia Practitioners BackgroundAnesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.

MethodsAfter institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).

ResultsThe overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50-68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings years of anesthesia practice was 69% (95% CI, 44-94) for 5-10 years, 62.5% (95% CI, 29-96) for 10-15 years, and 79% (95% CI, 63- 95) for greater than 15 years of practice.

35% (95% CI, 26-44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65-85) reported the incident at the time of injury. 59% (95% CI, 48-70) of injuries were due to hollow bore needles. 50% (95% CI, 39-61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.

ConclusionMost anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting. SEPRES: Sepsis prediction via a clinical data integration system and real-world studies in the intensive care unit BackgroundSepsis is vital in critical care medicine, and early detection and intervention are key to survival. We aimed to establish an early warning system for sepsis based on a data integration system that can be implemented in the intensive care unit (ICU).

MethodsWe trained the LightGBM and multilayer perceptron on the open-source database Medical Information Mart for Intensive Care for sepsis prediction. An ensemble sepsis prediction model was established based on the transfer learning and ensemble learning technique on the private dataset of Ruijin Hospital. The Shapley Additive Explanations analysis was applied to present feature importance on the prediction inference. With the development of data-integrating hub to collect and transmit data from different brands of ICU medical devices, the data integration system was established to receive, integrate, standardize, and store the real-time clinical data. In this way, the sepsis prediction model developed in the ICU of the Ruijin Hospital for the real-world study of sepsis early warning on ICU management. The trial was registered with ClinicalTrials.gov (NCT05088850).

FindingsOur best early warning model achieved an area under the receiver operating characteristic curve (AUC) of 0{middle dot}9833 in the task of detecting sepsis in 4-h preceding on the open-source database, while our ensemble model achieved an AUC of 0{middle dot}9065-0{middle dot}9436 in the retrospective research from 1-5-h preceding on the private database, and 0{middle dot}8636-0{middle dot}8992 in real-time real-world studies using the data integration system in the ICU of the Ruijin Hospital. In the continuous early warning process of patients admitted to the ICU, 22 patients who met the diagnostic criteria for sepsis during hospitalization were predicted as positive cases; 29 patients without sepsis were predicted as negative cases. Additionally, 17 patients were predicted as false-positive cases; in six patients with sepsis during ICU stay, the predicted probabilities at different time nodes were all less than the warning threshold 0{middle dot}7 and predicted as false-negative cases.

InterpretationMachine learning models could allow accurate and real-time inference to detect sepsis onset within 5-h preceding at most with the help of the data integration system. We identified the features such as age, antibiotics, ventilation, and net balance to be important for the sepsis prediction inference. We argue that this system has promising potential to improve ICU management by helping medical practitioners identify at-sepsis-risk patients and prepare for timely diagnosis and intervention.

FundingShanghai Municipal Science and Technology Major Project, the ZHANGJIANG LAB, and the Science and Technology Commission of Shanghai Municipality.