Toward Development of Guidelines for Virtual Administration of Paediatric Standardized Language and Literacy Assessments: Recommendations for Clinicians and Researchers ObjectivesPrevious virtual care literature within the field of speech-language pathology has focused primarily on validating the virtual use of intervention programs. There are fewer articles addressing the validity of conducting standardized paediatric oral language and literacy assessments virtually. Additionally, there is a lack of practical recommendations available on how best to conduct these assessment measures virtually. Given the rapid rise in virtual care as a result of the COVID-19 pandemic, clinicians and researchers require guidance on best practices for virtual administration of these tools imminently.

MethodsWe identified six key themes for recommendations based on two sources (1) our lab meeting discussions and (2) the outcomes of a narrative review of the extant literature. We then conducted semi-structured interviews with a group of 12 clinicians, students and researchers who had administered standardized language and literacy assessments with a variety of monolingual and multilingual school-aged children, with and without speech and language difficulties, in clinical and research settings to generate recommendations within these themes. Subsequently, in line with the Guidelines International Network, these recommendations were rated by group members, and reviewed by external stakeholders. A quasi-delphi consensus procedure was used to reach agreement on ratings for recommendations.

ResultsWe have developed recommendations for the use of standardized language and literacy assessments in virtual care, across six key themes: candidacy for virtual assessment, communication and collaboration with caregivers, technology and equipment, virtual administration, ethics, consent and confidentiality, and considerations for bilingual populations.

ConclusionsThis paper is one of the first to share practical recommendations for virtual assessment in the domain of paediatric oral language and literacy assessment. We hope these recommendations will facilitate future clinical research and that as the body of research grows, that this paper will act as a basis for the development of formal Clinical Practice Guidelines.
Lower Risk of Multisystem Inflammatory Syndrome in Children (MIS-C) with the Delta and Omicron variants of SARS-CoV-2 Paediatric Inflammatory Multisystem Syndrome (PIMS-TS, also known as MIS-C) typically occurs 2-6 weeks after exposure to SARS-CoV-2. Early estimates suggested a risk of PIMS-TS of 1 in 3-4000 infected children. Whether this risk is sustained with new SARS-CoV-2 variants remains unknown.

We utilised prospective data from the NHS South Thames Paediatric Network (STPN), which manages all cases of PIMS-TS amongst 1.5 million children in South-East England, to assess trends over time. We compared PIMS-TS cases with two independent SARS-CoV-2 infection datasets. We used publicly available UK Health Security Agency case numbers weighted to child population distributions according to area population estimates from the Office for National Statistics (ONS). To avoid bias due to evolving testing behaviour, we also compared PIMS-TS cases to community infection rates, obtained from the ONS COVID-19 Infection Survey, which randomly selects individuals for fortnightly PCR tests. All three datasets were normalised to the peak of the Alpha wave, and plotted against time. PIMS-TS cases were plotted 40 days prior to hospitalisation, corresponding to the best fit of rising SARS-CoV-2 infection and PIMS-TS cases during the Alpha wave.

Compared with the Alpha wave, we found fewer cases of PIMS-TS relative to SARS-CoV-2 infections during both initial and subsequent Delta waves. This relative reduction continued into the Omicron wave.

Re-infection rates with the Alpha or Delta variants and vaccination rates were very low during the Delta wave. As a result, lower PIMS-TS rate relative to SARS-CoV-2 infections during the Delta wave is unlikely to be explained by population level immunity from prior infection or vaccination. It is most likely due to viral mutations in key antigenic epitopes responsible for triggering the hyperinflammatory response observed with PIMS-TS.
Statistical modeling for quality risk assessment of clinical trials: follow-up at the era of remote auditing BackgroundAs investigator site audits have largely been conducted remotely during the COVID-19 pandemic, remote quality monitoring has gained some momentum. To further facilitate the conduct of remote Quality Assurance (QA) activities for clinical trials, we developed new quality indicators, building on a previously published statistical modeling methodology.

MethodsWe modeled the risk of having an audit or inspection finding using historical audits and inspections data from 2011 - 2019. We used logistic regression to model finding risk for 4 clinical impact factor (CIF) categories: Safety Reporting, Data Integrity, Consent and Protecting Endpoints.

ResultsWe could identify 15 interpretable factors influencing audit finding risk of 4 out of 5 CIF categories. They can be used to realistically predict differences in risk between 25 and 43% for different sites which suffice to rank sites by audit and inspection finding risk.

ConclusionContinuous surveillance of the identified risk factors and resulting risk estimates could be used to complement remote QA strategies for clinical trials and help to manage audit targets and audit focus also in post-pandemic times. Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank ObjectivesTo evaluate the benefit of combining polygenic risk scores (PRS) with the QCancer-10 (colorectal cancer) non-genetic risk prediction model to identify those at highest risk of colorectal cancer (CRC).

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

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

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

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

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

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

What this study addsO_LIAdding PRS to the QCancer-10 (colorectal cancer) risk prediction model improves performance and clinical benefit, with greatest gain from the LDpred2 genome-wide PRS, to a level that suggests utility in stratifying CRC screening and prevention
C_LI Full vaccination is imperative to suppress SARS-CoV-2 delta variant mutation frequency COVID-19 vaccination resistance has become a major challenge to prevent global SARS-CoV-2 transmission. Here we report that the vaccination coverage rate is inversely correlated to the mutation frequency of the full genome (R2=0.878) and spike gene (R2=0.829) of SARS-CoV-2 delta variants in 16 countries, suggesting that full vaccination against COVID-19, with other mitigation strategies, is critical to suppress emergent mutations. Neutrality analysis of DH and Zengs E tests suggested that directional selection was the major driving force of delta variant evolution. To eliminate the homogenous effects (population expansion, selective sweep etc.), the synonymous (Dsyn) and nonsynonymous (Dnonsyn) polymorphisms of the delta variant spike gene were estimated with Tajimas D statistic. Both D ratio (Dnonsyn/Dsyn) and {Delta}D (Dsyn-Dnonsyn) have positive correlation with the full vaccination rate (R2= 0.723 and 0.505, respectively) in 19 countries, indicating that purifying selection pressure of SARS-CoV-2 spike gene increased as the vaccination coverage rate increased. Taken together, our data suggests that vaccination plays an important role in the purifying selection force of spike protein of SARS-CoV-2 delta variants. 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. Comparative Analysis of the Chemotherapy-related Cognitive Impairments in Patients with Breast Cancer: a Community-based Research PurposeWith increasing breast cancer (BC) survival rates, the survivors quality of life (QoL) has become an important issue. Chemotherapy-induced cognitive impairment, known as "chemobrain" has been addressed recently. Therefore, cognitive function as one of the determinants of QoL should be considered while prescribing chemotherapeutics. In this study, we aimed to evaluate the effects of two common chemotherapy regimens on BC survivors cognition.

MethodsThe participants comprised 35 BC patients who underwent two common chemotherapy regimens, AC-T and TAC, and 24 matched healthy volunteers. The participants were assessed regarding anxiety, depression, general health status, and cognitive function including aspects of concentration, verbal ability, reasoning, memory, and visuospatial skill through Addenbrookes Cognitive Examination (ACE-P) and Cambridge Brain Science (CBS) tests.

ResultsRegarding depression and anxiety, there were no significant differences between the three groups. However, BC patients significantly complained of chronic fatigue compared to healthy volunteers (P-value = 0.027). Besides, ACE-P revealed the language domain to be affected in the AC-T group in comparison with the TAC-treated cases (P-value = 0.036). Moreover, the patients receiving the AC-T regimen had worse performance in visuospatial working memory and attention domains compared to the TAC group considering CBS tests (P-value = 0.031 and 0.008, respectively).

ConclusionThe results represent the AC-T regimen to be more toxic than the TAC in domains of language, concentration, and visuospatial working memory.

Implications for cancer survivorsThe AC-T regimen should be prescribed with caution in BC patients suffering from baseline cognitive impairments to improve post-chemotherapy QoL.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/21262481v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@242c7eorg.highwire.dtl.DTLVardef@e53ba9org.highwire.dtl.DTLVardef@1aff274org.highwire.dtl.DTLVardef@56adec_HPS_FORMAT_FIGEXP  M_FIG C_FIG Impact of tozinameran (BNT162b2) mRNA vaccine on kidney transplant and chronic dialysis patients: 3-5 months followup BackgroundDetermining the humoral immunogenicity of tozinameran (BNT162b2) vaccine in patients requiring chronic renal replacement therapy, and its impact on COVID-19 morbidity several months after vaccination, will guide risk assessment and subsequent changes in vaccination policy.

MethodsIn a prospective post-vaccination cohort study with up to 5 months follow-up we studied outpatient dialysis and kidney transplant patients and respective healthcare teams. Outcomes were anti S1/S2 antibody response to vaccine or infection and infection rate during followup.

Results175 dialysis patients (40% women, 65{+/-}15 years), 252 kidney transplant patients (33% women, 54{+/-}14 years) and 71 controls (65% women, 44{+/-}14 years) were followed. Three months or longer after vaccination we detected anti S1/S2 IgG antibodies in 80% of dialysis patients, 44% of transplant recipients and 100% of controls, whereas respective rates after infection were 94%, 75% and 100%. Predictors of non-response were older age, diabetes, history of cancer, lower lymphocyte count and lower vitamin-D levels. Factors associated with lower titers in dialysis patients were modality (hemodialysis vs peritoneal) and high serum ferritin levels. In transplant patients, hypertension and higher calcineurin or mTOR inhibitor drug levels were linked with diminished antibody response. Vaccination associated with fewer subsequent infections (HR=0.23, p<0.05). Moreover, higher antibody titers associated with fewer events, HR 0.41 for each unit increased in log10titer (p<0.05).

ConclusionsDialysis patients, and more so kidney transplant recipients, mounted reduced antibody response to COVID-19 mRNA vaccination, and lesser humoral response associated with more infections. Measures to identify and protect non-responsive patients are urgently required.

SignificanceReports on the humoral immunogenicity of SARS-CoV-2 mRNA vaccines in patients with end stage renal disease are scarce, and association with subsequent COVID-19 morbidity is unknown. In this cohort study that included 175 patients treated with dialysis, 252 kidney transplant recipients and 71 control volunteers, the proportion achieving an antibody response was time- and group-dependent, reaching 80%, 44% and 100% at 3 months post prime inoculation. Personal history of vaccination, positive antibody responses and antibody titers associated with significantly lower risk of COVID-19 infection. Thus, in patients with end stage renal disease, SARS-CoV-2 antibody testing may be warranted after vaccination, to identify non-responders at higher risk for disease. Prospectively validated augmented intelligence for disease-agnostic predictions of clinical success for novel therapeutics Despite numerous superhuman achievements in complex challenges1,2, standalone AI does not free life science from the long-term bottleneck of linearly extracting new knowledge from exponentially growing new data3, severely limiting the success rate of drug discovery4. Inspired by the state-of-the-art AI training methods, we trained a human-centric hybrid augmented intelligence5 (HAI) to learn a foundation model6 that extracts all-encompassing knowledge of human physiology and diseases. To evaluate the quality of HAIs extracted knowledge, we designed the public, prospective prediction of pivotal ongoing clinical trial outcomes at large scale (PROTOCOLS) challenge to benchmark HAIs real-world performance of predicting drug clinical efficacy without access to human data. HAI achieved a 10.5-fold improvement from the baseline with 99% confidence7 in the PROTOCOLS validation, readily increasing the average clinical success rate of investigational new drugs from 7.9%8 to 90% for almost any human diseases9,10. The validated HAI confirms that exponentially extracted knowledge alone is sufficient for accurately predicting drug clinical efficacy, effecting a total reversal of Erooms law4. HAI is also the worlds first clinically validated model of human aging that could substantially speed up the discovery of preventive medicine for all age-related diseases11. Our results demonstrate that disruptive breakthroughs necessitate the smallest team size to attain the largest HAI for optimal knowledge extraction from high-dimensional low-quality data space, thus establishing the first prospective proof of the previous discovery that small teams disrupt12. The global adoption of training HAI provides a well-beaten economic path to mass-produce scientific and technological breakthroughs via exponential knowledge extraction and better designs of data labels for training better-performing AI13. Vaccination or restriction?: COVID-19 vaccine hesitancy and vaccine passports ObjectivesWhile the development of vaccines against the novel coronavirus (COVID-19) brought the hope of establishing herd immunity, which might help end the global pandemic, vaccine hesitancy can hinder the progress towards herd immunity. In this study, we assess the determinants of vaccine hesitancy, reasons for hesitation, and effectiveness of vaccine passports in relaxing public health restrictions.

MethodsThrough an online survey that includes a conjoint experiment of a demographically representative sample of 5,000 Japanese adults aged 20-74, we assess the determinants of vaccine hesitancy, reasons for hesitation, and effectiveness of hypothetical vaccine passports.

ResultsWe found that about 30% of respondents did not intend to vaccinate or have not yet decided, with major reasons for vaccine hesitancy being related to concerns about the safety and side effects of the vaccine. In line with previous findings, younger age, lower socioeconomic status, and psychological factors such as weaker COVID-19 fear were associated with vaccine hesitancy. The easing of public health restrictions such as travel, wearing face masks, and dining out at night was associated with an increase in vaccine acceptance by 4-10%.

ConclusionVaccine hesitancy can be reduced by mitigating the concerns about vaccine safety and side effects, as well as by relaxing public health restrictions. However, the feasibility of vaccine passports needs to be sufficiently assessed, taking the ethical issues of passports and the public health impacts of the relaxation of restrictions into careful consideration.

Strengths and limitations of this study{square} This study includes timely data on COVID-19 vaccine hesitancy, obtained from a demographically representative sample of 5,000 Japanese adults.
{square}A conjoint experiment allows assessing the effectiveness of easing public health restrictions on vaccine acceptance.
{square}Actual behaviour may diverge from the survey responses or fluctuate due to the pandemic situation and the timing of the survey.
{square}Results may not be applicable in other countries, since the pandemic situation, government responses to the pandemic, and reasons for vaccine hesitancy can vary across countries. 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. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. Serum but not mucosal antibody responses are associated with pre-existing SARS-CoV-2 spike cross-reactive CD4+ T cells following BNT162b2 vaccination in the elderly Advanced age is a main risk factor for severe COVID-19. However, low vaccination efficacy and accelerated waning immunity have been reported in this age group. To elucidate age-related differences in immunogenicity, we analysed human cellular, serological and salivary SARS-CoV-2 spike glycoprotein-specific immune responses to BNT162b2 COVID-19 vaccine in old (69-92 years) and middle-aged (24-57 years) vaccinees compared to natural infection (COVID-19 convalescents, 21-55 years). Serological humoral responses to vaccination exceeded those of convalescents but salivary anti-spike subunit 1 (S1) IgA and neutralizing capacity were less durable in vaccinees. In old vaccinees, we observed that pre-existing spike-specific CD4+ T cells are associated with efficient induction of anti-S1 IgG and neutralizing capacity in serum but not saliva. Our results suggest pre-existing SARS-CoV-2 cross-reactive CD4+ T cells as predictor of an efficient COVID-19 vaccine-induced humoral immune response in old individuals. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Treatment interruption is a risk factor for sickness presenteeism: a large-scale cross-sectional study during the COVID-19 pandemic ObjectivesThis study examined the relationship between interruption to routine medical care during the coronavirus disease 2019 pandemic and sickness presenteeism among workers in Japan.

MethodsA cross-sectional study using data obtained from an internet monitor questionnaire was conducted. Interruption to medical care was defined based on the response "I have not been able to go to the hospital or receive treatment as scheduled." The fraction of sickness presenteeism days in the past 30 days was employed as the primary outcome. A fractional logit model was used for analysis to treat bounded data.

ResultsOf the 27,036 participants, 17,526 (65%) were workers who did not require routine medical care, 8,451 (31%) were using medical care as scheduled, and 1,059 (4%) experienced interrupted medical care. The adjusted odds ratio (aOR) of sickness presenteeism was significantly higher among workers who experienced interrupted medical care (3.44; 95% confidence interval [CI]: 3.04-3.89) than those who did not require routine medical care. In terms of symptoms, the highest aOR was observed among workers with mental health symptoms (aOR: 5.59, 95%CI: 5.04-6.20).

ConclusionsThis study suggests the importance of continuing necessary treatment during a pandemic to prevent presenteeism. Hepatic resection versus transarterial chemoembolization for the intermediate stage hepatocellular carcinoma：A cohort study BackgroundThe selection criterion for hepatic resection(HR) in intermediate-stage(IM) hepatocellular carcinoma(HCC) is still controversial. We used real-world data to evaluate the overall survival (OS) treated with HR or TACE.

MethodsIn all, 942 patients with IM-HCC were categorized in HR and TACE groups. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score- matched (PSM) analyses. The smooth curve was performed through the generalized additive model. The interaction test was performed to evaluate the HR impact on OS concerning risk factors. Also, we used multiple imputation to deal with the missing data.

ResultsTotally, 23.0% (n=225) of patients received HR. At a median overall survival of 23.7 months, HR was associated with the improved OS on multivariate analysis (hazard ratio, 0.45; 95%CI: 0.35, 0.58; after PSM: 0.56; 95%CI: 0.41, 0.77). Landmark analyses limited to long-term survivors of [&ge;] 6 months, [&ge;] 1, and [&ge;] 2 years demonstrated better OS with HR in all subsets (all P<0.05). After PSM analysis, however, HR increased 20% risk of death (HR, 1.20; 95%CI: 0.67, 2.15) in the subgroup of LDH [&le;]192 U/L (P for interaction = 0.037). Furthermore, the significant interaction was robust between the LDH and the HR with respect to 1-, 3-, and 5-year observed survival rate (all P<0.05).

ConclusionHepatic resection was superior to TACE for intermediate-stage HCC in the range of LDH level > 192 U/L. Moreover, TACE might be suitable for patients with LDH level [&le;] 192 U/L.

SynopsisO_LIHepatectomy was superior to TACE for BCLC-B HCC.
C_LIO_LIHepatectomy increased 20% risk of death for LDH < 192 U/L after matching.
C_LIO_LIA significant interaction was robust between LDH and with respect to hepatectomy the 1-, 3-, and 5-year observed survival rate.
C_LI Short Practical Regimen of Acupuncture for Melasma: A Prospective Cohort Study in a Tertiary Hospital in Thailand BackgroundMelasma is a common skin pigmentation disorder. Acupuncture shows benefits for patients with melasma, although no standardized method or optimal number of sessions have been determined.

ObjectiveTo comparatively assess clinical outcomes of melasma between five vs ten standard acupuncture sessions.

MethodsWe performed a prospective observational cohort study in all melasma patients at the Acupuncture Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. All patients were treated with standard acupuncture procedure twice a week and were evaluated after the fifth and the tenth sessions of acupuncture, with a follow-up one week after the last session. Participants were divided into two treatment groups: Groups A and B received five and ten acupuncture sessions respectively. Melasma outcomes were assessed by using the Melanin Index (MI), Melasma Area and Severity Index (MASI), patient-reported improvement scores and acupuncture-related adverse events.

ResultsOf 113 participants, 67 received five sessions of acupuncture treatment while 39 received ten sessions. 7 participants did not finish treatment. After five sessions of acupuncture in Group A, the mean MI decreased by 28.7 (95%CI -38.5 to -18.8), whereas the median MASI decreased by 3.4 (-6.9, -1.2) points. After ten sessions of acupuncture in Group B, the mean MI decreased by 31.3 (95%CI -45.0 to -17.6), whereas the median MASI decreased by 5.4 (-9.9, - 3.0) points. The first five sessions of acupuncture had a higher effect on the change in magnitude than the last five sessions, although there was no statistically significant difference. However, ten-session of acupuncture, had not reached the peak benefit on melasma yet. Further studies should be done with a higher number of sessions to determine the optimal rounds of treatment. Twenty-nine participants reported minor side effects, mostly consisting of persistent pain and small hematoma. Group B had RR of having adverse events 1.8 times (95% CI 1.0-3.4) compared to group A.

ConclusionAcupuncture has a potential dose-response effect on clinical and patient-reported melasma outcomes with minor side effects. Human lipoproteins comprise at least 12 different classes that are lognormally distributed. Lipoproteins in medical samples have been measured by enzymatic methods that coincide with conventional ultracentrifugation. However, the high gravity and time required for ultracentrifugation can cause sample degradation. This study presents the results of HPLC, a gentler and rapid separation method, for 55 human serum samples. The elution patterns were analysed parametrically, and the attribute of each class was confirmed biochemically. Human samples contained 12 classes of lipoproteins, each of which may consist primarily of proteins. There are three classes of VLDLs. The level of each class was distributed lognormally, and the standard amount and the 95% range were estimated. Enzymatic methods measure the levels of several mixed classes. This lognormal character suggests that the levels are controlled by the synergy of multiple factors. Using explainable machine learning to identifypatients at risk of reattendance at discharge from emergency departments Short-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance could help reduce the number of missed critical illnesses and could reduce avoidable utilization of emergency departments by enabling targeted post-discharge intervention. In this manuscript we present a retrospective, single-centre study where we created and evaluated an extreme gradient boosted decision tree model trained to identify patients at risk of reattendance within 72 hours of discharge from an emergency department (University Hospitals Southampton Foundation Trust, UK). Our model was trained using 35,447 attendances by 28,945 patients and evaluated on a hold-out test set featuring 8,847 attendances by 7,237 patients. The set of attendances from a given patient appeared exclusively in either the training or the test set. Our model was trained using both visit level variables (e.g., vital signs, arrival mode, and chief complaint) and a set of variables available in a patients electronic patient record, such as age and any recorded medical conditions. On the hold-out test set, our highest performing model obtained an AUROC of 0.747 (95% CI : 0.722-0.773) and an average precision of 0.233 (95% CI : 0.194-0.277). These results demonstrate that machine-learning models can be used to classify patients, with moderate performance, into low and high-risk groups for reattendance. We explained our models predictions using SHAP values, a concept developed from coalitional game theory, capable of explaining predictions at an attendance level. We demonstrated how clustering techniques can be used to investigate the different sub-groups of explanations present in our patient cohort. Deep learning for caries detection using optical coherence tomography Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries. Effectiveness of a short term induction regimen of a biosimilar Adalimumab in the long term management of symptomatic Ankylosing Spondylitis Symptomatic Ankylosing Spondylitis: A Community Based Proof of Concept Observational Study IntroductionCost and drug toxicity often deter prolonged therapeutic use of anti-TNF agents in ankylosing spondylitis (AS). A planned study was completed to endorse our clinic based observation of long term relief following short-term administration of anti-TNF agent.

Methods50 consenting patients with symptomatic active chronic AS under rheumatology care in a community clinic were enrolled. They had no past history of anti-TNF use. 40 mg standard biosimilar adalimumab (BS-ADA, Exemptia trade name)was injected subcutaneously every fortnight for six injections (10 weeks). Patients were monitored at several time points. Improvement was assessed at regular interval as per protocol which included standard indices (Bath and Assessment Spondyloarthritis International Society /ASAS). An intention to treat analysis with significant p<0.05 was carried out.

ResultsPatients showed early and substantial significant improvement in pain, NSAID requirement, function and in several indices (ASAS 20 & 40, ASAS partial remission, BASDAI, BASFI, ASDAS) which persisted after stopping injections. 84% and 52 % of patients respectively showed ASAS 20 improvement at week 12 and 48: corresponding ASAS partial remission 34% and 24%. Over 50% patients maintained prolonged improvement and provided proof of concept (defined a-priori). Serum Interleukin-6 assay showed a sharp reduction at 24 weeks. None developed TB or serious drug toxicity. 11 patients withdrew (mostly inadequate response). Absence of control was a limitation.

ConclusionA ten-week administration of biosimilar adalimumab in difficult to treat AS showed early substantial improvement which often persisted for 24 weeks. This unconventional strategy was socioeconomically appealing. It merits further validation and acceptance especially in resource strained settings. What delirium detection tools are used in routine clinical practice in the United Kingdom? Survey results from 91% of acute healthcare organisations. PurposeOur aim was to collect information on delirium assessment processes and pathways in non-intensive care settings in the United Kingdom (UK).

MethodsWe sent a Freedom of Information request to 169 UK National Health Service (NHS) hospitals, trusts and health boards (units) in July 2020 to obtain data on usage of delirium assessment tools in clinical practice and delirium pathways or guidelines.

ResultsWe received responses from 154/169 units (91% response rate). Of these, 146/154 (95%) units reported use of formal delirium assessment processes and 131/154 (85%) units had guidelines or pathways in place. The 4  As Test (4AT) was the most widely used tool, with 117/146 (80%) units reporting use. The Confusion Assessment Method was used in 65/146 (45%) units, and the Single Question to identify Delirium (SQiD) in 52/146 (36%) units.

ConclusionsOur findings show that the 4AT is the most commonly used tool in the UK, with 80% of units reporting use. This study adds to our knowledge of real-world uptake of delirium detection methods at scale. Future studies should evaluate real-world implementation of delirium assessment tools further via (i) tool completion rates and (ii) rates of positive scores against the expected prevalence delirium in the clinical population concerned.

KEY SUMMARY POINTSO_ST_ABSAimC_ST_ABSTo seek information on delirium assessment processes and pathways in non-intensive clinical care settings in the United Kingdom (UK), and to assess usage of specific delirium assessment tools: the 4  As Test (4AT), Confusion Assessment Method and Single Question to identify Delirium (SQiD).

FindingsIn total, 95% of National Health Service (NHS) units (hospitals, trusts and health boards) reported use of formal delirium assessment processes and 85% of units had guidelines or pathways in place. The 4AT was the most widely used tool, with 80% of units reporting use; the Confusion Assessment Method was reportedly used in 45% of units and the SQiD in 36% of units.

MessageThis study shows real-world, large-scale uptake of delirium detection methods and delirium guidelines in UK hospitals, which contributes to ongoing efforts to improve delirium care. Culture and understanding the role of feedback for health professions students: Realist synthesis protocol. IntroductionClinical education has moved to a "competency-based" model with an emphasis on workplace-based learning and assessment which, in turn, depends on feedback to be effective. Further, the understanding of feedback has changed from information about a performance directed to the learner performing the task, to a dialogue, which enables the learner to act and develop.

In health professional education, feedback is a complex interaction between trainee, supervisor, and the healthcare system. Most published research on feedback in health professional education originates in Europe and North America. Our interest is on the impact of Culture on this process, particularly in the context of Asian cultures.

The (scientific) realist approach of Pawson and Tilley provides a means to examine complex interventions in social situations, and thus is an appropriate lens to use for this study. This is a protocol for a realist synthesis which asks how, why and in what circumstances do Asian Cultures influence health professional trainees to seek, respond to and use feedback given in the clinical environment, if at all.

Methods and analysisAn initial search was performed to help define the scope of the review question and develop our initial program theory. The formal electronic search was carried out in February 2020 and included: CINAHL, ERIC, MEDLINE, and PsycInfo, and repeated in October 2020.

Retrieved articles were imported into Covidence for screening and data extraction, after which components of the Context - Mechanisms - Outcomes configurations will be sought to refine the initial program theory.

Ethics and DisseminationAs this study is a literature review, ethics approval is not required.

The findings will be documented in line with the RAMESES publications standards for Realist syntheses,[41] and we plan to disseminate the findings by means of a peer-reviewed journal article and conference presentation(s).

Strengths and limitations of this studyO_LIThe synthesis aims to identify the how and why Asian Cultures may influence feedback seeking and provision to health professional trainees, if at all.
C_LIO_LITo our knowledge, there are few studies of feedback seeking and provision to health professional trainees in Asia.
C_LIO_LIA Realist approach has the potential to help explain the complex nature of Cultures impact on feedback.
C_LIO_LIOnly studies published in the English language will be included, so transferability of our findings to non-English speaking environments may be lacking.
C_LIO_LIIn addition to formal literature database searches, we will need to conduct citation mining to locate other relevant resources.
C_LI Inflammasome-related markers at the ICU admission are not associated with outcome in the critically ill COVID-19 patients. PurposeDevelopment of targeted biological therapies for COVID-19 requires reliable biomarkers that could help indicate the responding patients. Hyperactivation of the inflammasome by SARS-CoV2 virus is hypothesized to contribute to severe course of the COVID-19 disease. Therefore, we aimed to evaluate the prognostic value of several inflammasome-related cytokines and proteins at the admission to the intensive care unit (ICU).

Patients and methodsPlasma samples were obtained from 45 critically ill COVID-19 patients and from 10 patients any without any signs of infection (TBI, traumatic brain injury) on admission to the ICU. The concentration of IL-1, IL-1{beta}, IL-18, IL-1RA, galectin-1, ASC, LDH, ferritin, and gasdermin D were analyzed. A novel cell-free caspase-1 plasma assay was developed by inhibitor-based immunoprecipitation followed by Western Blot. Demographic and clinical characteristics were recorded.

ResultsIn-hospital mortality in COVID-19 patients reached 62%. Galectin-1 was 1.8-fold lower in COVID-19 than in TBI patients (17101.84 vs. 30764.20 pg/ml, p=0.007), but other inflammasome-related biomarkers were at similar concentrations. Patients with SOFA score of >9 on admission who were at high risk of death had significantly higher galectin-1 but lower IL-1RA in comparison to low-risk patients (25551.3 pg/ml vs 16302.7 pg/ml, p=0.014; 14.5 pg/ml vs 39.4 pg/ml, p=0.04, respectively). Statistically significant correlations were observed between: IL-1 and platelets (r=-0.37), IL-1{beta} and platelets (r=-0.36), ferritin and INR (r=0.39). Activated caspase-1 p35 was detectable in 12/22 COVID-19 patients but in none of the TBI patients. Its presence was related with higher fibrinogen and lower D-dimers. Moreover, the densitometric analysis showed a significantly higher amount of p35 in patients with SOFA> 9.

ConclusionOur results indicate that the systemic markers of activation of the inflammasome in critically ill COVID-19 patients is not directly related with outcome. Therefore, potential interventions aimed at the inflammasome pathway in this group of patients may be of limited effectiveness and should be biomarker-guided.