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Gaps in immunization coverage at school entry and after two years of school attendance among immigrant and refugee children in Ontario, Canada

Background Foreign-born children may face greater barriers to accessing routine immunizations in Canada or their country of birth, but provincial surveillance data on immigration status are lacking. Using our provincial immunization repository linked to administrative data, we assessed immunization coverage among immigrant and refugee children in Ontario, Canada, compared with Ontario-born children and identified factors associated with being up-to-date (UTD). Methods We conducted a retrospective cohort study of children entering school during the 2012/13–2014/15 school years. We calculated UTD coverage for measles (2 doses), diphtheria (4 doses), and polio (3 doses) vaccines at school entry and two years after school attendance. We compared UTD coverage between immigrant/refugee children and Ontario-born children using standardized differences (SD). Results In a cohort of 363,662 children, 15,114 (4.2%) were immigrants/refugees (82.1% immigrants, 17.9% refugees). UTD coverage for all antigens combined was 59.2% among immigrant/refugee children compared with 87.9% among Ontario-born children at school entry (SD = 0.69), increasing to 84.9% and 94.3%, respectively, two years after school entry (SD = 0.31). Coverage was lower with greater disparities between immigrant/refugee and Ontario-born children for measles (87.9% vs. 94.8%, SD = 0.25) and diphtheria (94.6% vs. 97.4%, SD = 0.15) after two years than polio (97.1% vs. 98.4%, SD = 0.09). Among immigrant/refugee children, coverage was lowest in refugees (vs. immigrants), recent immigrants, and those born in certain regions. Conclusions Immunization coverage among foreign-born children lagged behind their Ontario-born peers, even after two years of school attendance. Findings varied by vaccine, immigration category, time spent in Ontario, and country of birth.

Influence of cold atmospheric pressure plasma treatment on germination and plant biomass of Trifolium pratense L.

Treatment of seeds with cold atmospheric pressure plasma (CAPP) is in its proof-of-concept phase with regard to its effect on germination and plant growth. To increase the germination of hardseeded red clover (Trifolium pratense L.), seeds are usually scarified, which is time-consuming and labour-intensive. The aim of this study was to compare the effect of different CAPP devices (indirect treatment: plasma processed air, direct treatment: corona discharge, argon and air dielectric barrier discharge) on germination and early growth of different long-term stored red clover accessions and to determine whether germination can be increased to meet seed management requirements. Sixty different red clover seed lots (diverse accessions and harvest years) with different initial germination percentages were divided into three batches of 20 lots each and the effect of the different plasma treatments on germination and development were examined in laboratory and greenhouse. The overall results indicate a plasma discharge- and accession-depended enhancement of germination speed which was detected in all batches but most pronounced in Batch 1. While direct treatments, especially with corona discharge-plasma, increased germination speed (up to 58% germination seven days after sowing vs. 44% in control in laboratory conditions), treatment with plasma processed air resulted partially in reduced germination speed (42%). Despite a small but significant increase in total germination of maximum five percentage points, no treatment led to an increase from 62% or 70% in control (depending on experiment) to at least 80% germination percentage to meet storage requirements for seed banks. Stimulating effects on biomass of young plants under greenhouse cultivation conditions were observed in Batch 1, but were absent in Batch 2 and 3 and therefore inconclusive. Future research is needed to elucidate influencing factors on plasma effects in red clover seed lots which include but are not limited to the effect of seed coat compounds and seed coat thickness.

An agent-based model to advance the science of collaborative learning health systems

Improving the healthcare system is a persistent and pressing challenge. Collaborative Learning Health Systems, or Learning Health Networks (LHNs), are a novel, replicable organizational form in healthcare delivery that show substantial promise for improving health outcomes. To realize that promise requires a scientific understanding that can serve LHNs’ improvement and scaling. We translated social and organizational theories of collaboration to a computational (agent-based) model to develop a computer simulation of an LHN and demonstrate the potential of this new tool for advancing the science of LHNs. Model sensitivity analysis showed a small number of parameters with outsized effect on outcomes. Contour plots of these influential parameters allow exploration of alternative strategies for maximizing model outcomes of interest. A simulated trial of two common health system interventions – pre-visit planning and use of a registry – suggested that the efficacy of these could depend on LHN current state. By translating heuristic theories of LHNs to a specifiable, reproducible, and explicit model, this research advances the scientific study of LHNs using tools available from complex systems science.

9,000-year-old barley consumption in the foothills of central Asia

Scholars are increasingly favoring models for the origins of agriculture that involve a protracted process of increasing interdependence within a series of mutualistic relationships between humans and plants, as opposed to a rapid single event or innovation. Nonetheless, these scholars continue to debate over when people first started foraging for grass seeds, when they began to readily utilize sickles, how prominent the early selection pressures were, and when the first traits of domestication fully introgressed into the cultivated grass population. Here, we present complementary archaeobotanical and archaeological (stone tool) evidence for cereal foragers from Toda-1 Cave in the Surkhan Darya, dating to 9200 cal BP. We conclude that early Holocene foragers were processing grains along with nuts and fruits as far north as the rich river valleys of southern Uzbekistan. These data expand the known range that preagricultural cereal foragers covered in the early Holocene, adding to our understanding of the cultural processes that led to farming. Additionally, we present the earliest evidence for people interacting with the progenitors for pistachios and apples (or a close apple relative). The complex foraging behaviors that led to cultivation were being undertaken by people during the early Holocene across a wider area of Eurasia than previously thought.

Momentum, volume and investor sentiment study for u.s. technology sector stocks—A hidden markov model based principal component analysis

In this paper, we study the impact of momentum, volume and investor sentiment on U.S. tech sector stock returns using Principal Component Analysis-Hidden Markov Model (PCA-HMM) methodology. Price and volume are two well-known aspects in general equilibrium model. Momentum effect arises from the determination of prices in the market equilibrium. By studying momentum, volume and investor sentiment, we intuitively connect theoretical finance model with modern behavior finance topic. Instead of predicting future stock returns using machine learning models and doing comparisons, we apply the PCA-HMM method to reveal the hidden force in the financial and macroeconomic time series to calibrate different regimes. Combining the traditional financial study methods with modern machine learning techniques, we show investor sentiment effect show the primary effect on tech sector stock return which outweighs volume effect and momentum effect. The volume effect also has ineligible impact on stock return. The investor sentiment effect and volume effect show most impact on tech stocks with large or medium market shares. In contrast, momentum effect has very trivial correlation with tech sector stock return, from both stock level and individual state level. We also discuss the underlying mechanisms behind above findings according to tech sectors’ unique characteristics, as well as raise risk management concerns. Using such PCA-HMM method, we reveal the unique patterns in tech sector stock returns. The PCA-HMM method can especially help us to identify those edge cases under which market behaves irregularly.

Exploring the interplay between circadian rhythms and obesity: A Boolean network approach to understanding metabolic dysregulation

This study investigates the interaction between circadian rhythms and lipid metabolism disruptions in the context of obesity. Obesity is known to interfere with daily rhythmicity, a crucial process for maintaining brain homeostasis. To better understand this relationship, we analyzed transcriptional data from mice fed with normal or high-fat diet, focusing on the mechanisms linking genes involved with those regulating circadian rhythms. We performed biological enrichment analysis and Boolean network modeling to identify direct interactions between these genes. The resulting mathematical model provided a comprehensive system of gene interactions, primarily highlighting lipid metabolism. Our findings revealed key insights into the effects of obesity on circadian rhythm genes, particularly the under-expression of core genes such as Bmal1 and Clock. Crucially, we identified a reciprocal interaction between obesity and circadian genes, where disruptions on one exacerbated the dysfunction in the other. This mechanism suggests that the disruption of circadian rhythms plays a pivotal role in worsening the metabolic disturbances associated with obesity, providing new perspectives for targeting circadian pathways in obesity-related metabolic disorders.

Physicochemical, microbiological, and microstructural changes in germinated wheat grain

This study investigates the physicochemical, microbiological, and microstructural changes in soft wheat grain during germination under varying moisture conditions: moderately dry, moist, and wet. Pre-harvest sprouting can severely compromise grain quality and usability; however, understanding germination-induced changes offers insights into potential utilization strategies. Physical parameters—including thousand-kernel weight, test weight, and falling number—showed strong correlation with germination time, decreasing by 8.2%, 22%, and 74%, respectively. Microstructural analyses using optical microscopy, scanning electron microscopy (SEM), and Raman spectroscopy revealed substantial degradation of starch granule morphology and kernel structure, with compact vitreous endosperm becoming porous and disorganized as germination progressed. To optimize germination conditions for technological application, a central composite design with three factors (moisture, temperature, and time) was employed, analyzed using Statgraphics Centurion 19. Response surface modeling identified optimal conditions for starch content (22% moisture, 31°C, 84 h), protein content (21% moisture, 30°C, 72 h), and minimal microbial contamination (14% moisture, 33°C, 8 h). These findings provide a foundation for processing germinated soft wheat grain into value-added products, even when exposed to unfavorable harvest conditions.

Correction: Characteristics of the effects of Polygonati Rhizoma on gut microbiota and metabolites in vitro associated with poor dietary habits in pregnant women

Unprecedented 2020 coral bleaching reveals unexpected taxa-specific responses in the central Red Sea

Sea surface temperature of the Red Sea has increased by up to 0.45 °C per decade over the last 30 years, and coral bleaching events are becoming more frequent. A reef bleaching event was observed in October 2020, whereby some parts of the Red Sea experienced more than 12 °C-weeks. The study sites spanned nearly three degrees of latitude along the central Saudi Arabian Red Sea and were surveyed via structure-from-motion photogrammetry in October 2020 during the bleaching event and again in October 2022 to track the fate of the coral colonies. The in situ temperatures in 2020 ranged from 31.9 °C to 32.7 °C, and overall, 65% of the colonies exhibited some bleaching. Nearly half of the colonies exhibited partial or complete mortality in 2022, although 18% exhibited complete mortality. Approximately 27% of the colonies presented no visible change in coloration over the study period, whereas 21% presented recovery over the two years. Porites, Montipora, Pocillopora, and Stylophora were classified as winners, whereas Acropora, Goniastrea, Xeniidae, and Sclerophytum were classified as losers. At the time of this study, this research was the first to assess the longest-term changes in coral colonies following a major reef bleaching event in the central Saudi Arabian Red Sea. The results suggest that the 2020 bleaching event may be the most severe event on record for the region at the time of the study, and our data underscore the need for enhanced monitoring of corals and environmental data to better understand coral reef ecosystem resilience in a historically data scarce region.

Enhancing fake news detection with transformer-based deep learning: A multidisciplinary approach

The widespread dissemination of fake news presents a critical challenge to the integrity of digital information and erodes public trust. This urgent problem necessitates the development of sophisticated and reliable automated detection mechanisms. This study addresses this gap by proposing a robust fake news detection framework centred on a transformer-based architecture. Our primary contribution is the application of the Bidirectional Encoder Representations from Transformers (BERT) model, uniquely enhanced with a progressive training methodology that allows the model to incrementally learn and refine its understanding of the linguistic nuances that differentiate factual reporting from fabricated content. The framework was rigorously trained and evaluated on the large-scale WELFake dataset, comprising 72,134 articles. Our findings demonstrate the model’s exceptional performance, achieving an accuracy of 95.3%, an F1-score of 0.953, precision of 0.952, and recall of 0.954. Comparative analysis confirms that our approach significantly outperforms traditional machine learning classifiers and other standard transformer-based implementations, highlighting its superior ability to capture complex contextual dependencies. These results underscore the efficacy of our enhanced BERT framework as a powerful and scalable solution in the ongoing fight against digital misinformation.

Young women’s experience of personal recovery following acute myocardial infarction: A qualitative study

Background Rates of acute myocardial infarction (AMI) morbidity and mortality have increased in young women aged ≤55 years but little is known about their experience recovering from and living with AMI. A personal recovery (experience of an identity shift manifested in both losses and gains) has been reported among general AMI survivors. Our objective was to gain insights into young women’s perspectives on long-term post-AMI recovery, under the patient-centered personal recovery framework. Methods and results The study used a participatory, phenomenological approach. In-depth interviews were conducted with 18 young women (18–55 years at the time of their AMI) who were readmitted within the first year post-AMI; these were audio-recorded, transcribed verbatim, and analyzed in collaboration with two women with lived experience of AMI. Study findings revealed that young women’s experience did not deviate largely from the personal recovery framework from the general AMI survivors (i.e., an identity shift manifested with both losses and gains). However, certain aspects in the psychosocial domain were highlighted and further articulated to address young women’s experience. Specifically, within the three categories of the personal recovery framework, two of which (i.e., loss, and gain) can be further classified, eight themes were identified around the topics of loss of safety and security, self-worth, social roles, (both the loss and gain of) hope and optimism, and gain of connection, strategies to manage emotions, and meaning and purpose. Conclusion Findings validated the utility of personal recovery framework in capturing the experience of young women with AMI, and highlighted themes that address young women’s distinguished ways of meaning-making, which anchors around social roles and personal identity. Identifying opportunities to improve awareness of self-care and facilitating social support for young women after AMI represents important targets for future intervention.

Spatiotemporal disparities and dynamic transition characteristics of China’s national standard development contribution levels—Based on machine splitting and location assignment technology

This study examines China’s national standard development from 2001 to 2023. Using machine splitting and location assignment technology, the Dagum Gini coefficient and its decomposition methods, and traditional and spatial Markov chain estimation methods, we identify the spatiotemporal disparities and dynamic transition characteristics of the contribution levels to national standard development across China’s eight comprehensive economic zones. The findings provide a reference for promoting regional coordinated sustainable development and high-quality economic transformation. The study reveals three key findings. (1) Contribution levels of China’s eight comprehensive economic zones to national standard development have significantly increased. The Northern Coastal comprehensive economic zone has the highest contribution levels, followed by the Eastern and Southern Coastal zones, whereas the Northwestern and Northeastern zones have lower contribution levels. (2) The overall regional disparity in national standard development contribution levels is decreasing, with the largest intraregional disparities found in the Northern and Southern Coastal zones. Significant interregional disparities persist between the Northern Coastal and Northwestern zones, the Eastern Coastal and Northwestern zones, and the Southern Coastal and Northwestern zones, with interregional disparities being the primary driver of the overall regional gap. (3) When spatial correlation effects are not considered, contribution levels exhibit clear signs of club convergence and asymmetric distribution. However, when spatial correlation effects are considered, the transition characteristics of contribution levels show significant spatial dependence. This study makes three key contributions. First, it illustrates the spatiotemporal differentiation and dynamic transition characteristics of the contribution levels of China’s eight comprehensive economic zones to national standard development, addressing gaps in existing quantitative research. Second, it introduces novel techniques and decomposition methods. Third, it identifies the primary causes of regional disparities and dynamic transition characteristics, providing empirical evidence to support policy decisions for regional coordinated sustainable development and high-quality economic transformation.

Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling

Freshwater mussels are critical to the health of freshwater systems, but their populations are declining dramatically throughout the world. The limited resources available for freshwater mussel conservation necessitates the geographic prioritization of conservation-related actions. However, lack of knowledge about freshwater mussel spatial distributions hinders decision making in this context. In this study, we assessed the distribution of twelve native freshwater mussel species across six Northeastern states (Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine) in the United States using data collected from lentic and lotic environments by eight state agencies. We first modeled individual distributions using a maximum entropy (MaxEnt) model and then compiled distribution models to assess the distribution of freshwater mussel species richness. We also determined geographic prioritization for three conservation-related actions: species surveys, land protection, and population restoration of species of high conservation concern. We found that the percent of catchments predicted to have species occurrence (based on a probability threshold) varied across species, with Elliptio complanata (Eastern elliptio) predicted to occur in the greatest percent of available catchments (33.92%) and Alasmidonta heterodon (Dwarf wedgemussel) expected in the smallest percent (5.30%). The predicted overall species richness within our modeled catchments ranged from zero to all twelve species, with an average of two species per catchment. Although conservation priorities vary depending on the conservation action of interest, we found some areas of consistent importance including much of Maine and the southern reaches of the Connecticut River. An improved understanding of freshwater mussel distribution in a landscape framework will enable managers to implement more precise and efficient conservation interventions for these essential aquatic species.

Intracellular lymphocyte protein biomarkers for early radiological triage in the human population

In the event of a large-scale radiological or nuclear emergency, a rapid, high-throughput screening tool will be essential for efficient triage of potentially exposed individuals, optimizing scarce medical resources and ensuring timely care. The objective of this work was to characterize the effects of age and sex on two intracellular lymphocyte protein biomarkers, BAX and p53, for early radiation exposure classification in the human population, using an imaging flow cytometry-based platform for rapid biomarker quantification in whole blood samples. Peripheral blood samples from male and female donors, across three adult age groups (young adult, middle-aged, senior) and a juvenile cohort, were X-irradiated (0–5 Gy), and biomarker expression was quantified at two- and three-days post-exposure. Mixed-effects modeling and ensemble machine learning approaches were employed to evaluate the influence of Age and Sex on biomarker expression and develop predictive models for radiation exposure classification. Although some Age and Sex effects on biomarker expression levels were observed when the data was stratified by targeted conditions of biomarker, day, age group, and sex, these variables were ultimately not retained as significant predictors of exposure classification. A single ensemble model successfully classified radiation exposure across all tested cohorts, with ROC AUC values ranging from 0.85 to 0.95 at the 1 Gy threshold and 0.81 to 0.87 at the 2 Gy threshold, high sensitivity values (91–96%) and low false-negative rates across all classifications. These findings support the use of BAX and p53 biomarkers in a blood test for efficient triage in large-scale emergencies, excluding individuals below exposure thresholds from unnecessary medical care with minimal risk of denying care to those truly exposed.

Prevalence and factors influencing drug-resistant tuberculosis in four regions of Ghana

Introduction The alarming rate of drug-resistant tuberculosis (DR-TB) globally is a threat to treatment success among positive tuberculosis (TB) cases. Studies aimed at determining the prevalence, trend of DR-TB and socio-demographic and clinical risk factors contributing to DR-TB in the four regions of Ghana are currently unknown. This study sought to determine the prevalence and trend of DR-TB, identify socio-demographic and clinical risk factors that influence DR-TB, and analyse the relationship between underweight and adverse drug reactions and treatment outcomes among DR-TB patients in four regions of Ghana. Method It was a retrospective review conducted over 5 years, from January 2018 to the end of December 2022. The data were retrieved from the DR-TB registers and folders at the Directly Observed Treatment (DOT) centres in the four regions. Analysis of the data was conducted using STATA version 17. Results The prevalence of DR-TB in Ashanti was 10.1%, Eastern 5.3%, 27.8% in Central, and 2.7% in the Upper West region for the year 2022. The overall prevalence rate of DR-TB for the period 2018–2022 was 13.8%. The socio-demographic and clinical risk factors that influence DR-TB in the four regions are: age, marital status (aOR 3.58, P-value< 0.00, 95% CI 2.86–4.48), Senior High School (SHS) level of education (aOR 2.09, P-value = 0.01, 95% CI 1.21–3.63), alcohol intake (aOR 0.49, P-value <0.00, 95% CI 0.38–0.63), previously treated (aOR 22.03, P-value<0.00, CI 16.58–29.26), major adverse drug reaction (aOR 125.50, P-value<0.00, 95% CI 58.05–271.34), and minor adverse drug reaction (aOR 23.59, P-value<0.00, 95% CI 18.32–30.39); treatment outcome, cure (aOR 0.52, P-value<0.00, 95% CI 0.41–0.66), completed (aOR 9.67, P-value<0.00, 95% CI 6.56–14.28), relapsed (aOR 2.62, P-value = 0.01, 95% CI 1.33–5.18), Lost-to-Follow-up (LTFU) (aOR 0.45, P-value<0.00, 95% CI 0.29–0.70), and failure (aOR 35.24, P-value<0.00, 95% CI 7.76–159.99). Also, there was an association between underweight and adverse drug reaction (RRR 5.74, P-value<0.00, 95% CI 4.86–6.79) and treatment outcome (RRR 0.79, P-value<0.00, 95% CI 0.74–0.86). Conclusion The study shows that the prevalence of DR-TB in Ghana is low, probably not because the cases have reduced but due to inadequate GeneXpert machines to detect the cases. Age, marital status, education, alcohol intake, previously treated TB cases, adverse drug reactions, underweight, and treatment outcome are factors influencing the development of DR-TB. Therefore, interventions aimed at improving the nutritional status of DR-TB cases and minimising adverse drug reactions will improve treatment outcomes.

Kinship verification via correlation calculation-based multi-task learning

Previous studies have demonstrated that metric learning approaches yield remarkable performance in the field of kinship verification. Nevertheless, a prevalent limitation of most existing methods lies in their over-reliance on learning exclusively from specified types of given kin data, which frequently results in information isolation. Although generative-based metric learning methods present potential solutions to this problem, they are hindered by substantial computational costs. To address these challenges, this paper proposes a novel correlation calculation-based multi-task learning (CCMTL) method specifically designed for kinship verification. It has been observed that kin members often exhibit a high degree of similarity in key facial organs, such as eyes, mouths, and noses. Given this similarity, similar facial features between kin members with different kin relationships frequently demonstrate certain correlations. Inspired by this observation, our proposed method aims to learn a set of metrics by leveraging both the specified kinship data and the correlations among various kinship types. These correlations are determined through an in-depth investigation of the spatial distribution relationship between the specified kinship data and other kinship types. Furthermore, we develop an efficient algorithm within the multi-task learning framework that integrates correlation exploitation with metric learning. This innovative approach effectively resolves the issue of information isolation while minimizing computational overhead. Extensive experimental validation conducted on the KinFaceW dataset demonstrates that the proposed CCMTL method achieves superior or comparable results to those of existing methods.

Towards a definition of an existential approach in cancer patients: a co-produced scoping review

Background Attention to existential needs has become part of daily treatment. Studies have described the concepts of existential experiences and existential interventions. However, a consensus or conceptual clarity regarding an existential approach in cancer patients is currently missing. This scoping review investigates the term existential approach and suggests a definition. Methods We searched PubMed, Embase, Web of Science, and PsycINFO databases until March 2024. We used the Joanna Briggs Institute guidance, and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews to conduct the review in a systematic manner. The review was conducted in collaboration with patient colleagues who were diagnosed with cancer. Two categories were included: 1) articles investigating elements that are present in existential approaches according to patients and 2) articles investigating elements that are not yet present in existential approaches but recommended by patients. Results 2791 articles were identified for title and abstract screening, of which 90 were screened for full text. Seventeen articles were eligible for inclusion. Elements were identified that led to the following definition of an existential approach: ‘Medical practice based on a holistic and interdisciplinary view wherein the personal alliance provides room for mutual sharing of thoughts, acknowledging existential issues besides medical issues, whilst paying attention to personal values and what matters most’. Conclusions This definition provides a framework and therefore makes an existential approach more applicable. Different healthcare providers (e.g., nurses/physicians) can be part of an existential approach. To provide an existential approach in daily treatment, future studies should focus on training in communication skills.

Predictors of sexual satisfaction among Social Security and National Insurance Trust pensioners in the Greater Accra Region of Ghana

The population of pensioners remains on the rise in Ghana coupled with an intrinsic need for sexual activity and satisfaction. However, data on factors associated with sexual satisfaction among pensioners are limited in Ghana. The aim of this study was to examine the predictors of sexual satisfaction among Social Security and National Insurance Trust pensioners in the Greater Accra Region of Ghana. We employed a cross-sectional survey design in this study. Participants were recruited using cluster and stratified sampling techniques. Our analytical sample was 410 participants. Ordinal logistic regressions were employed to determine predictors of sexual satisfaction among the participants. The significance of the test was set at a p-value ≤ 0.05. The results showed that participants who were household head (AOR: 1.874, 95% CI: 1.037–3.388), who did not incur any expenditure on their household in a month (AOR: 6.290, 95% CI: 1.758–22.511) and those who undertake daily exercises were significantly (AOR: 1.981, 95% CI: 1.276–3.075) more likely to fall in one of the higher categories of sexual satisfaction compared to their counterparts. Also, the study revealed that those with secondary education (AOR:.503, 95% CI:.253-.0.999), who were in the public sector (AOR:.449, 95% CI:.237 −.850), who were very dissatisfied with health service access/use (AOR:.032, 95% CI:.002−.421) and not able to determine whether they were satisfied or dissatisfied with their health status (AOR:.518, 95% CI:.329−.816) were significantly less likely to fall in one of the higher categories of sexual satisfaction. Findings of this study suggest that household headship, education level, employment sector, expenditure on household, satisfaction with health services/use, daily exercises intake and satisfaction with health status were associated with sexual satisfaction among the participants. In relation to our findings, the implications for policy, practice and future research have been discussed for the attention of policy makers and researchers.

Age does not improve the predictive ability of the Hospital Frailty Risk Score for length of stay

Background The Hospital Frailty Risk Score (HFRS) has been widely used to identify patients at high risk of poor outcomes and to predict poor outcomes for older people. Although poor health outcomes are associated more with frailty than age, HFRS has been validated only for older people. This study aimed to explore for the first time whether age influences the predictive power of Hospital Frailty Risk Score to predict a long length of stay. Methods A retrospective cohort study analysing data collected at Queen Alexandra Hospital in Portsmouth, UK, between January 1, 2010 and December 31, 2019. Data included people aged ≥16 years. We assessed the correlation between the HFRS and age using Pearson’s correlation coefficient. We used logistic regression models to develop prediction models (HFRS alone and HFRS +age) for nine periods of length of stay, in nine age groups data to assess association and influences age on Hospital Frailty Risk Score. Results The correlation between Hospital Frailty Risk Score and age was weak in eight age groups, correlation coefficient ranged from 0.01 to 0.17. In each age groups, the proportion of the intermediate and high risk of frailty increased with a longer length of stay. Adjusted models (HFRS+age) did not show a better discriminative power compared with HFRS alone in all age groups (AUROCs ranging from 0.772 to 0.932). The odds ratio values from HFRS alone models were higher than adjusted models. Conclusions This study concluded that in this patients’ population, age does not improve the power of Hospital Frailty Risk Score to predict long length of stay.

The SURVIVE study (NCT05658172): Bringing breast cancer aftercare to the 21stcentury: Study protocol of a Phase III clinical trial comparing liquid biopsy guided vs. Standard of care surveillance for intermediate to high-risk breast cancer survivors

Background Current aftercare in breast cancer survivors aims to detect local recurrences or contralateral disease, while the detection of distant metastases has not been a central focus due to a lack of evidence supporting an effect on overall survival. However, the data underpinning these guidelines are mainly from trials of the 1980s/1990s and have not been updated to reflect the significant advancements in diagnostic and therapeutic options that have emerged over the past 40 years. In this trial, the aim is to test whether a liquid biopsy-based detection of (oligo-) metastatic disease at an early pre-symptomatic stage followed by timely treatment can impact overall survival compared to current standard aftercare. Methods In this partially double-blinded superiority study, intensified liquid biopsy-guided surveillance will be assessed versus standard surveillance in medium-to-high-risk early breast cancer patients. Intensive surveillance comprises 3-monthly tests of circulating free tumor DNA (ctDNA), circulating tumor cells (CTC) and serum tumor markers CEA, CA 27.29 and CA125. Upon positivity of biomarker and/or symptoms, staging examinations are initiated. In total, 3500 patients will be randomized in a 1:1 ratio after completion of primary antineoplastic therapy. Co-primary endpoints are overall survival (OS) and the overall lead time effect. The trial will be accompanied by an extensive translational research program. Discussion A risk-based aftercare and regular screening for asymptomatic metastatic disease with molecular markers in the absence of any radiological findings can potentially revolutionize current follow-up care of breast cancer survivors and enable potential treatment even before patients suffer from symptomatic, incurable disease.