Cell graph neural networks enable the digital staging of tumor microenvironment and precise prediction of patient survival in gastric cancer Gastric cancer is one of the deadliest cancers worldwide. Accurate prognosis is essential for effective clinical assessment and treatment. Spatial patterns in the tumor microenvironment (TME) are conceptually indicative of the staging and progression of gastric cancer patients. Using spatial patterns of the TME by integrating and transforming the multiplexed immunohistochemistry (mIHC) images as Cell-Graphs, we propose a novel graph neural network-based approach, termed Cell-Graph Signature or CGSignature, powered by artificial intelligence, for digital staging of TME and precise prediction of patient survival in gastric cancer. In this study, patient survival prediction is formulated as either a binary (short-term and long-term) or ternary (short-term, medium-term, and long-term) classification task. Extensive benchmarking experiments demonstrate that the CGSignature achieves outstanding model performance, with Area Under the Receiver-Operating Characteristic curve (AUROC) of 0.960{+/-}0.01, and 0.771{+/-}0.024 to 0.904{+/-}0.012 for the binary- and ternary-classification, respectively. Moreover, Kaplan-Meier survival analysis indicates that the  digital-grade cancer staging produced by CGSignature provides a remarkable capability in discriminating both binary and ternary classes with statistical significance (p-value < 0.0001), significantly outperforming the AJCC 8th edition Tumor-Node-Metastasis staging system. Using Cell-Graphs extracted from mIHC images, CGSignature improves the assessment of the link between the TME spatial patterns and patient prognosis. Our study suggests the feasibility and benefits of such artificial intelligence-powered digital staging system in diagnostic pathology and precision oncology.
Quantification of T- and B-cell immune receptor distribution diversity characterizes immune cell infiltration and lymphocyte heterogeneity in clear cell renal cell carcinoma Immune-modulating systemic therapies are often used to treat advanced cancer such as metastatic clear cell renal cell carcinoma (ccRCC). Used alone, sequence-based biomarkers neither accurately capture patient dynamics nor the tumor immune microenvironment. To better understand the tumor ecology of this immune microenvironment, we quantified tumor infiltration across two distinct ccRCC patient tumor cohorts using complementarity determining region-3 (CDR3) sequence recovery counts in tumor-infiltrating lymphocytes and a generalized diversity index (GDI) for CDR3 sequence distributions. GDI can be understood as a curve over a continuum of diversity scales which allows sensitive characterization of distributions to capture sample richness, evenness, and subsampling uncertainty, along with other important metrics that characterize tumor heterogeneity. For example, richness quantified the total unique sequence count, while evenness quantified similarities across sequence frequencies. Significant differences in receptor sequence diversity across gender and race revealed that patients with larger and more clinically aggressive tumors had increased richness of recovered tumoral CDR3 sequences, specifically in those from T-cell receptor alpha and B-cell immunoglobulin lambda light chain. The GDI inflection point (IP) allowed for a novel and robust measure of distribution evenness. High IP values associated with improved overall survival, suggesting that normal-like sequence distributions lead to better outcomes. These results propose a new quantitative tool that can be used to better characterize patient-specific differences related to immune cell infiltration, and to identify unique characteristics of tumor-infiltrating lymphocyte heterogeneity in ccRCC and other malignancies.
How Informative Were Early SARS-CoV-2 Treatment and Prevention Trials? A longitudinal cohort analysis of trials registered on clinicaltrials.gov BackgroundEarly in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

MethodsWe created a cohort of SARS-CoV-2 treatment and prevention efficacy trials that were initiated from 2020-01-01 to 2020-06-30 using ClinicalTrials.gov registration records. We evaluated trials on 3 criteria of informativeness: potential redundancy, design quality and feasibility of patient-participant recruitment. The study protocol was prospectively registered with the Open Science Framework (https://osf.io/fp726/).

ResultsWe included 500 trials in our cohort, 58% of which were Phase 2 and 84.8% were directed towards the treatment of SARS-CoV-2. Close to one third of trials met all three criteria and were deemed informative (29.0% (95% Confidence Interval 23.7 - 36.9)). The proportion of potentially redundant trials in our cohort was 4.1%. Over half of the trials in our cohort (56.2%) did not meet our criteria for high quality trial design. The proportion of trials with infeasible patient-participant recruitment was 22.6%.

ConclusionsLess than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic. Benchmarking saliency methods for chest X-ray interpretation Saliency methods, which "explain" deep neural networks by producing heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. Although many saliency methods have been proposed for medical imaging interpretation, rigorous investigation of the accuracy and reliability of these strategies is necessary before they are integrated into the clinical setting. In this work, we quantitatively evaluate three saliency methods (Grad-CAM, Grad-CAM++, and Integrated Gradients) across multiple neural network architectures using two evaluation metrics. We establish the first human benchmark for chest X-ray interpretation in a multilabel classification set up, and examine under what clinical conditions saliency maps might be more prone to failure in localizing important pathologies compared to a human expert benchmark. We find that (i) while Grad-CAM generally localized pathologies better than the two other saliency methods, all three performed significantly worse compared with the human benchmark; (ii) the gap in localization performance between Grad-CAM and the human benchmark was largest for pathologies that had multiple instances, were smaller in size, and had shapes that were more complex; (iii) model confidence was positively correlated with Grad-CAM localization performance. Our work demonstrates that several important limitations of saliency methods must be addressed before we can rely on them for deep learning explainability in medical imaging. 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. Decision curve analysis to identify optimal candidates of liver resection for intermediate-stage hepatocellular carcinoma with hepatitis B cirrhosis：A cohort study BackgroundThe selection criterion for liver resection (LR) in intermediate-stage (IM) hepatocellular carcinoma (HCC) is still controversial. This study aims to compare LR and transarterial chemoembolization in the range of predicted death risk

MethodsThe multivariable Cox regression model (MVR) was estimated to predict mortality at 5yr. The cut-off values were determined by a two-piece-wise linear regression model, decision curve analysis with MVR model, and hazard ratio curve for treatment plotted against the predicted mortality.

Results825 IM-HCC with hepatitis B cirrhosis were included for analysis (TACE, n=622; LR, n=203). The 5-yr overall survival rate of LR patients was higher than the TACE group (52.8% vs. 20.8%; P<0.0001). The line of LR and TACE were crossing with predicted death risk at 100% (P for interaction =0.008). The benefit of LR versus TACE decreased progressively as predicted death risk>0.55 (95%CI: 0.45,0.62). When predicted death risk over 0.7, decision curve analysis suggested that LR and TACE did not increase net benefit. Patients were then divided into four subgroups by the cut-off values (<0.45, 0.45[&ge;] /<0.62, 0.62[&ge;] /<0.7, [&ge;] 0.7). The stratified analysis of treatment in different subgroups, hazard ratios were 0.39 (95%CI: 0.27, 0.56), 0.36 (95%CI: 0.23, 0.56), 0.51 (95%CI: 0.27, 0.98), and 0.46 (95%CI: 0.27, 0.80), respectively.

ConclusionsLR reached the maximal relative utility in the interval of 0.45 to 0.62, and both LR and TACE did not increase net benefit at the 5-yr death risk over 0.7. 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. 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. In depth analysis of patients with severe SARS-CoV-2 in sub-Saharan Africa demonstrates distinct clinical and immunological profiles Although the COVID-19 pandemic has left no country untouched there has been limited research to understand clinical and immunological responses in African populations. Here we comprehensively characterise patients hospitalised with suspected or confirmed COVID-19, and healthy community controls. PCR-confirmed COVID-19 participants were more likely to receive dexamethasone and a beta-lactam antibiotic, and survive to hospital discharge than PCR-/IgG+ and PCR-/IgG-participants. PCR-/IgG+ participants exhibited a nasal and systemic cytokine signature analogous to PCR-confirmed COVID-19 participants, but increased propensity for Staphylococcus aureus and Streptococcus pneumoniae colonisation. We did not find evidence that HIV co-infection in COVID-19 participants was associated with mortality or altered cytokine responses. The nasal immune signature in PCR-/IgG+ and PCR-confirmed COVID-19 participants was distinct and predominated by chemokines and neutrophils. In addition, PCR-/IgG+ individuals with high COVID-19 clinical suspicion had inflammatory profiles analogous to PCR-confirmed disease and potentially represent a target population for COVID-19 treatment strategies. Risk scores for predicting HIV incidence among adult heterosexual populations in sub-Saharan Africa: a systematic review and meta-analysis IntroductionSeveral HIV risk scores have been developed to identify individuals for prioritised HIV prevention in sub-Saharan Africa. We systematically reviewed HIV risk scores to: (i) identify factors that consistently predicted incident HIV infection, (ii) review inclusion of community-level HIV risk in predictive models, and (iii) examine predictive performance.

MethodsWe searched nine databases from inception until February 15, 2021 for studies developing and/or validating HIV risk scores among the heterosexual adult population in sub-Saharan Africa. Studies not prospectively observing seroconversion or recruiting only key populations were excluded. Record screening, data extraction, and critical appraisal were conducted in duplicate. We used random-effects meta-analysis to summarise hazard ratios and the area under the receiver-operating characteristic curve (AUC-ROC).

ResultsFrom 1563 initial search records, we identified 14 risk scores in 13 studies. Seven studies were among sexually active women using contraceptives enrolled in randomised-controlled trials, three among adolescent girls and young women (AGYW), and three among cohorts enrolling both men and women. Consistently identified HIV prognostic factors among women were younger age (pooled adjusted hazard ratio: 1.62 [95% Confidence Interval: 1.17, 2.23], compared to above-25), single/not cohabiting with primary partners (2.33 [1.73, 3.13]) and having sexually transmitted infections (STIs) at baseline (HSV-2: 1.67 [1.34, 2.09]; curable STIs: 1.45 [1.17; 1.79]). Among AGYW only STIs were consistently associated with higher incidence, but studies were limited (n=3). Community-level HIV prevalence or unsuppressed viral load strongly predicted incidence but were only considered in three of 11 multi-site studies. The AUC-ROC ranged from 0.56 to 0.79 on the model development sets. Only the VOICE score was externally validated by multiple studies, with pooled AUC-ROC 0.626 [0.588, 0.663] (I2: 64.02%).

ConclusionsYounger age, non-cohabiting, and recent STIs were consistently identified as predicting future HIV infection. Both community HIV burden and individual factors should be considered to quantify HIV risk. However, HIV risk scores had only low-to-moderate discriminatory ability and uncertain generalisability, limiting their programmatic utility.

Further evidence on the relative value of specific risk factors, studies populations not restricted to  at-risk individuals, and data outside South Africa will improve the evidence base for risk differentiation in HIV prevention programmes.

PROSPERO NumberCRD42021236367 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. Thromboembolic risk in hospitalised and non-hospitalised Covid-19 patients: A self-controlled case series analysis of a nation-wide cohort ObjectiveAn unexpectedly large number of people infected with Covid-19 had experienced a thrombotic event. This study aims to assess the associations between Covid-19 infection and thromboembolism including myocardial infarction (MI), ischaemic stroke, deep-vein thrombosis (DVT), and pulmonary embolism (PE).

Patients and MethodsA self-controlled case-series study was conducted covering the whole of Scotlands general population. The study population comprised individuals with confirmed (positive test) Covid-19 and at least one thromboembolic event between March 2018 and October 2020. Their incidence rates during the risk interval (5 days before to 56 days after the positive test) and the control interval (the remaining periods) were compared intra-personally.

ResultsAcross Scotland, 1,449 individuals tested positive for Covid-19 and experienced a thromboembolic event. The risk of thromboembolism was significantly elevated over the whole risk period but highest in the 7 days following the positive test (IRR 12.01, 95% CI 9.91-14.56) in all included individuals. The association was also present in individuals not originally hospitalised for Covid-19 (IRR 4.07, 95% CI 2.83-5.85). Risk of MI, stroke, PE and DVT were all significantly higher in the week following a positive test. The risk of PE and DVT was particularly high and remained significantly elevated even 56 days following the test.

ConclusionConfirmed Covid-19 infection was associated with early elevations in risk with MI, ischaemic stroke, and substantially stronger and prolonged elevations with DVT and PE both in hospital and community settings. Clinicians should consider thromboembolism, especially PE, among people with Covid-19 in the community. Combination of Mifepristone and Methotrexate for the Treatment of Ectopic Pregnancy: A Systematic Review Protocol AimThe increase in ectopic pregnancies (EP) in recent years and their impact on female fertility forces physicians to find an effective medical treatment that can avoid surgery as soon as possible. Methotrexate and mifepristone are widely used in conservative treatments, but the effectiveness of this combination is not completely clear. Therefore, the aims in this meta-analysis are to systematically analyze the efficacy of mifepristone combined with methotrexate in the treatment of EP through existing studies and draw a conclusion, to evaluate the advantages and disadvantages of inclusion trials and propose improvement measures and scientific designing schemes.

MethodsSix databases will be searched, including PubMed, Embase, Cochrane Library, the China National Knowledge Infrastructure(CNKI), Chinese Science and Technology Periodical Database (VIP), and Wanfang Database (WF). Randomized controlled trials published up to October 2020 will be selected. Search terms include mifepristone, methotrexate, EP, and random (free word/synonym expansion). We will include trials in which the experimental group was treated with combination of mifepristone and methotrexate, and the control group was treated with mifepristone alone. Revman 5.4 will be used to evaluate the quality of the trials, and the effect model will be selected to analyze the results. Cure rate will be the main outcome index.

ResultOnly when we finish this meta analysis can we get the result.

DiscussionThe results of this study will provide evidence for the efficacy of mifepristone combined with methotrexate therapy in the treatment of EP. The site of onset of pregnancy should be taken into account.

PROSPERO registration numberCRD42021246757 Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

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

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

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. Oxygen provision to severely ill COVID-19 patients at the peak of the 2020 pandemic in a Swedish district hospital Oxygen is a low-cost and life-saving therapy for patients with COVID-19. Yet, it is a limited resource in many hospitals in low income countries and in the 2020 pandemic even hospitals in richer countries reported oxygen shortages. An accurate understanding of oxygen requirements is needed for capacity planning. The World Health Organization estimates the average flow-rate of oxygen to severe COVID-19-patients to be 10 l/min. However, there is a lack of empirical data about the oxygen provision to patients. This study aimed to estimate the oxygen provision to COVID-19 patients with severe disease in a Swedish district hospital.

A retrospective, medical records-based cohort study was conducted in March to May 2020 in a Swedish district hospital. All adult patients with severe COVID-19 - those who received oxygen in the ward and had no ICU-admission during their hospital stay - were included. Data were collected on the oxygen flow-rates provided to the patients throughout their hospital stay, and summary measures of oxygen provision calculated.

One-hundred and twenty six patients were included, median age was 70 years and 43% were female. On admission, 27% had a peripheral oxygen saturation of [&le;]91% and 54% had a respiratory rate of [&ge;]25/min. The mean oxygen flow-rate to patients while receiving oxygen therapy was 3.0 l/min (SD 2.9) and the mean total volume of oxygen provided per patient admission was 16,000 l (SD 23,000).

In conclusion, the provision of oxygen to severely ill COVID-19-patients was lower than previously estimated. Further research is required before global estimates are adjusted. Croup during the COVID-19 Omicron Variant Surge Croup is a common upper respiratory disease usually associated with parainfluenza virus, resulting in stridor, hoarse voice, barky cough, and variable respiratory distress. Here we examine the data at our center confirming a sharp increase in cases of croup associated with the Omicron variant. Data was retrospectively extracted from patient charts among those seen in the Emergency Department at Seattle Childrens Hospital. Inclusion criteria were patients who were assigned a diagnosis containing "croup" during either 5/30/2021-11/30/2021, a time period correlating with predominance of the COVID-19 Delta variant (B.1.617.2), or the initial phase of the Omicron variant surge (12/1/2021-1/15/2022). Contemporaneous publicly available local data on the proportion of SARS-CoV-2 samples in surrounding King County, Washington, with spike gene target failure on TaqPath PCR assays was used as a proxy for the proportion of infections caused by the Omicron variant. A total of 401 patients were diagnosed with croup during the Delta surge and 107 patients were diagnosed with croup during the Omicron surge. Patients who presented during the Omicron surge were more likely to test positive for COVID-19 (48.2% vs 2.8%, p < 0.0001). Children with a clinical diagnosis of croup during the Omicron surge were more likely to be prescribed racemic epinephrine as part of their care (21.5% vs 13.0%, p = 0.032). There were no differences in presenting age, rate of admission, rate of return to the ED within 72 hours, or admission among those who returned within 72 hours. During the Omicron surge, the incidence of croup nearly doubled compared to the rate in prior months, while at the same time the number of cases of parainfluenza virus identified decreased. Consistent with prior case reports, we have identified a sharp rise in cases of croup seen in our pediatric ED in parallel with the replacement of the SARS-CoV-2 Delta variant by Omicron as the dominant variant in our community. Effects of repeated injection of 1% lidocaine vs. radial extra-corporeal shock wave therapy for treating myofascial trigger points: a randomized controlled trial Background and ObjectivesThis study tested the hypothesis that treatment of myofascial trigger points (MTrPs) in the upper trapezius muscle (UTM) with repeated injection of 1% lidocaine results in better alleviation of muscular stiffness and soreness as well as improved metabolism in the hypercontracted MTrP area than treatment with radial extracorporeal shock wave therapy (rESWT).

Materials and MethodsA single-blinded, prospective, randomized controlled trial was conducted on patients suffering from MTrPs in the UTM. Thirty patients were treated with repeated injection of 2 ml of 1% lidocaine (three injections; one injection per week). Another 30 patients were treated with rESWT (three treatment sessions; one treatment session per week; 2000 radial extracorporeal shock waves per treatment session; positive energy flux density = 0.10 mJ/mm2). The primary outcome measure was pain severity using the VAS score. The secondary outcome measures included muscle elasticity index, pressure pain threshold and neck disability index. Evaluation was performed at baseline (T1), 15-30 minutes after the first treatment in order to register immediate treatment effects (T2), before the second treatment (i.e., one week after baseline) (T3) and one week after the third treatment (i.e., four weeks after baseline) (T4).

ResultsThere were no statistically significant differences in the primary and secondary outcome measures between the patients in the lidocaine arm and the patients in the rESWT arm at T1 and T4. Within the arms, the mean differences of all outcomes were statistically significant (P < 0.001) when comparing the data obtained at T1 with the data obtained at T3 and the data obtained at T4.

ConclusionsThe results of this pilot study suggest that the use of rESWT in patients with MTrPs in the UTM is safe and leads to reduced pain and improved muscle elasticty, pressure pain threshold and neck disability index, without adverse effects. Larger trials are necessary to verify this. Clinicians should consider rESWT instead of injections of lidocaine in the treatment of MTrPs in the UTM. Patterns of brain degeneration in early-stage relapsing-remitting multiple sclerosis Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in early-stage RRMS using volumetry and voxel-based morphometry (VBM).

RRMS patients (N=354) underwent 3T structural MRI at diagnosis and 1-year follow-up, as part of the Scottish multicentre  FutureMS study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the cerebrum, cerebellum and brainstem.

Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, multiple subcortical structures, cerebellar GM and the brainstem. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 28 regions and 17/28; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal lobe and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe.

Widespread neurodegeneration was observed in early-stage RRMS; particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions. Volumetric and VBM results emphasise different as well as overlapping patterns of longitudinal change, and provide potential response markers for existing therapies and trials of neuroprotective agents. Caffeine and Methylliberine: A Human Pharmacokinetic Interaction Study Methylliberine and theacrine are methylurates found in the leaves of various Coffea species and Camellia assamica var. kucha, respectively. We previously demonstrated that the methylxanthine caffeine increased theacrines oral bioavailability in humans. Consequently, we conducted a double-blind, placebo-controlled study pharmacokinetic study in humans administered methylliberine, theacrine, and caffeine to determine methylliberines pharmacokinetic interaction potential with either caffeine or theacrine. Subjects (n = 12) received an oral dose of either methylliberine (25 or 100 mg), caffeine (150 mg), methylliberine (100 mg) plus caffeine (150 mg), or methylliberine (100 mg) plus theacrine (50 mg) using a randomized, double-blind, crossover design. Blood samples were collected over 24 hours and analyzed for methylliberine, theacrine, and caffeine using UPLC-MS/MS. Methylliberine exhibited linear pharmacokinetics that were unaffected by co-administration of either caffeine or theacrine. However, methylliberine co-administration resulted in decreased oral clearance (41.9 {+/-} 19.5 vs. 17.1 {+/-} 7.80 L/hr) and increased half-life (7.2 {+/-} 5.6 versus 15 {+/-} 5.8 hrs) of caffeine. Methylliberine had no impact on caffeines maximum concentration (440 {+/-} 140 vs. 458 {+/-} 93.5 ng/mL) or oral volume of distribution (351 {+/-} 148 vs. 316 {+/-} 76.4 L). We previously demonstrated theacrine bioavailability was enhanced by caffeine, however, caffeine pharmacokinetics were unaffected by theacrine. Herein, we found that methylliberine altered caffeine pharmacokinetics without a reciprocal interaction, which suggests caffeine may interact uniquely with different methylurates. Understanding the mechanism(s) of interaction between methylxanthines and methylurates is of critical importance in light of the recent advent of dietary supplements containing both purine alkaloid classes. Changes in CD163+, CD11b+, and CCR2+ peripheral monocytes relate to Parkinson's disease and cognition 1.Alpha-synuclein pathology is associated with immune activation and neurodegeneration in Parkinsons disease. The immune activation involves not only microglia but also peripheral immune cells, such as mononuclear phagocytes found in blood and infiltrated in the brain. Understanding peripheral immune involvement is essential for developing immunomodulatory treatment. Therefore, we aimed to study circulating mononuclear phagocytes in early- and late-stage Parkinsons disease, defined by disease duration of less or more than five years, respectively, and analyze their association with clinical phenotypes. We performed a cross-sectional multi-color flow cytometry study on 78 sex-balanced individuals with sporadic Parkinsons disease, 28 controls, and longitudinal samples from seven patients and one control. Cell frequencies and surface marker expressions on natural killer cells, monocyte subtypes, and dendritic cells were compared between groups and correlated with standardized clinical scores. We found elevated frequencies and surface levels of migration-(CCR2, CD11b) and phagocytic-(CD163) markers, particularly on classical and intermediate monocytes in early Parkinsons disease. HLA-DR expression was increased in advanced stages of the disease, whereas TLR4 expression was decreased in women with Parkinsons Disease. The disease-associated immune changes on CCR2 and CD11b correlated with worse cognition. Increased TLR2 expression was related to worse motor symptoms. In conclusion, our data highlights the TLR2 relevance in the symptomatic motor presentation of the disease and a role for peripheral CD163+ and migration-competent monocytes in Parkinsons disease cognitive defects. Our study suggests that the peripheral immune system is dynamically altered in Parkinsons disease stages and directly related to both symptoms and the sex bias of the disease.

HighlightsO_LITLR2 expression increased in patients with worse motor symptoms.
C_LIO_LIIncreased CD163 and HLA-DR monocytic expression in patients with long PD duration.
C_LIO_LISexual-dimorphism for CCR2, CD11b, and TLR4 expression on PD monocytes.
C_LIO_LICCR2 and CD11b expression are associated with cognitive impairment in PD.
C_LI Exploring the experiences of loneliness in adults with mental health problems: a participatory qualitative interview study BackgroundMany mental health conditions are associated with loneliness, which is both a potential trigger and an exacerbating factor in mental health conditions. Richer evidence about how people with mental health problems experience loneliness, and about what exacerbates or alleviates it, is needed to underpin research on strategies to help with loneliness in this context.

MethodsOur aim was to explore experiences of loneliness, as well as what contributes to or helps address it, among a diverse sample of adults living with mental health problems in the UK. We recruited purposively via online networks and community organisations. Qualitative semi-structured interviews were conducted with 59 consenting participants by video call or telephone. Researchers with relevant lived experience were involved at all stages, including design, data collection, analysis and writing up of results.

FindingsAnalysis led to identification of four overarching themes: 1. What the word "lonely" meant to participants, 2. Contributory factors to ongoing loneliness, 3. Connections between loneliness & mental health, 4. Ways of reducing loneliness. Central aspects of loneliness were lack of meaningful connections with others and lack of a sense of belonging to valued groups and communities. Some drivers of loneliness, such as losses and transitions, were universal, but specific links were made between living with mental health problems and being lonely. These included direct effects of psychiatric symptoms, the need to withdraw to cope with mental health problems, and impacts of stigma and poverty.

ConclusionsThe multiplicity of contributors to loneliness that we identified, and of potential strategies for reducing it, suggest that a variety of approaches are relevant to reducing loneliness among people with mental health problems, including peer support and supported self-help, psychological and social interventions, and strategies to facilitate change at community and societal levels. The views and experiences of adults living with mental health problems are a rich source for understanding why loneliness is a frequent experience in this context and what may address it. Co-produced approaches to developing and testing interventions have potential to draw on this experiential knowledge in formulating effective approaches to loneliness. Evaluation of Clinical Threshold Policies for Cataract Surgery and the Regional Variation in Rates of Surgery Background/AimsTo characterise the national patterns in rates of cataract surgery across England, review clinical thresholds against NICE guidance, and determine how far variable access to cataract surgery is attributable to regional variation in policy stringency and social deprivation.

Methods127 Clinical Commissioning Groups ("CCGs") provided cataract surgery data and threshold policies in response to a Freedom of Information request. Local cataract surgery rates were grouped by threshold stringency and analysed on an age group-corrected basis. ANOVA testing was used to assess effect of policy stringency on regional rates of cataract surgery.

ResultsIn England, rates of cataract surgery vary threefold across CCGs, from 1,980 to 6,427 per 100,000 population over 60, with a standard deviation (784.76) of 22% of the mean value, 3,598. Threshold policies vary across CCGs: 33 had no policy, 45 utilised policies accessible on the basis of Quality of Life ("QoL") impact, and 39, against NICE guidance, required a Visual Acuity ("VA") threshold be exceeded. Rates of surgery by CCG were negatively correlated with restrictiveness of policy ({eta}2=0.18, p<0.01), and positively correlated with the Index of Multiple Deprivation (IMD), (r2{square}={square}0.11, p<0.01). Prior approval processes are not significantly associated with reduced rates of surgery.

ConclusionOver two-thirds of CCGs continue to use threshold-based policies for access to cataract surgery, with one-third doing so solely on the basis of VA requirements, despite NICE guidance to the contrary. For NHS operations, variation in policy restrictiveness accounts for more of the variation in surgery rates than socioeconomic deprivation. 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/. 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.