Registration Information Research Articles

Serum iron dynamics and mortality in patients with heart failure: A population-based cohort study

Abstract Background Iron deficiency (ID) is common among patients with heart failure (HF). Little is known about the impact of serum iron dynamics on mortality in HF. Methods Using a previously validated territory-wide clinical information registry, all eligible patients with HF (N = 112, 938) from 1996 to 2020 were enrolled. The index date was defined as the date of which HF was first diagnosed. Iron, ferritin and transferrin saturation (TSAT) values were retrieved both at baseline (1 year before index date) and during follow-up period (1 year after the index date until study end). The association between iron levels and risk of mortality was evaluated both on a continuous scale using restricted cubic spline curves and by categories using Cox proportional hazards regression model with competing risk as appropriate. Cut-points of iron were determined by the optimal equal-HR method. Inverse probability of treatment weighting (IPTW) was used to balance the covariates among iron groups. Changes in iron from baseline to follow-up were expressed by Sankey curve. The outcome was all-cause mortality. Results The mean age of the cohort was 73.0±12.2 years and 51,340 (45.5%) were male. The association between iron levels and the risk of all-cause mortality was a U-shaped curve. The risk of all-cause mortality reached a nadir between iron levels of 8.2 umol/L and 25.8 umol/L and was lowest at 13.5 umol/L. Accordingly, iron levels were divided into 3 groups: low iron (≤8.2 umol/L), midrange (8.2-25.8 umol/L), high iron (>25.8 umol/L). Compared to those who remained at midrange iron level during follow-up, risk of mortality was higher in those with persistently low and persistently high iron levels (HR 1.32, 95%CI 1.27 to 1.38; HR 2.24, 95%CI 1.74 to 2.89, respectively). Further, changes in iron levels from low to high (HR 1.41, 95%CI 1.24 to 1.61); mid to low (HR 1.15, 95%CI 1.10 to 1.20), mid to high (HR 1.29, 95%CI 1.13 to 1.49); high to low (HR 1.36, 95%CI 1.15-1.60), or high to mid (HR 1.18, 95%CI 1.00-1.38) also demonstrated higher risks of mortality. (Table 1) Conclusion The prevalence of low iron status is high among patients with HF. Both low or high iron levels at baseline, and changes to the lower or higher ends of the iron level spectrum during follow-up were associated with higher risks of all-cause mortality.cubic spline curve

Association between triglyceride with all-cause mortality and cardiovascular outcomes in heart failure patients

Abstract Background Remnant cholesterol, identified by triglyceride-rich lipoprotein, is increasingly acknowledged as a significant causal risk factor for ischemic heart diseases. The association with cause-specific outcomes in heart failure (HF) settings remains unexplored. This study aims to determine the association between triglyceride levels with all-cause mortality and cardiovascular outcomes in patients with HF. Methods Using a previously validated territory-wide clinical information registry, all eligible patients with HF (N = 127124) from 1996 to 2020 were enrolled. Triglyceride levels associated with risk of mortality were evaluated on a continuous scale using restricted cubic spline curves and by categories of triglyceride using Cox proportional hazards regression model with competing risks as appropriate. The primary outcomes were all-cause mortality and cardiovascular death (CVD). Secondary outcomes included ASCVD (a composite of myocardial infarction, unstable angina, arterial revascularization or ischemic stroke) and HF readmission or death. Results The mean age of the study population was 71.4±12.2 years and 65869 (51.8%) were male. Notably, when we investigated the association of triglyceride levels with admission or death for ASCVD, a positive relationship was seen in high triglyceride levels and ASCVD admission or death while neutral in low triglyceride levels. Conversely, when we investigated the association with readmission or death for HF, an inverse relationship was found where lower triglyceride levels were associated with higher risks of HF readmission. Together, the association between triglyceride levels and the risk of all-cause mortality and CVD was an U-shaped curve. The risk of all-cause mortality reached a nadir between triglyceride levels of 1.12 mmol/L and 3.28 mmol/L and was lowest at 1.95 mmol/L. Conclusion In the HF population, low and high levels of triglyceride were associated with increased risks of all-cause mortality and CVD compared with those with midrange levels. Triglyceride was positively associated with ASCVD while inversely associated with HF admission or death. The lowest risk of all-cause mortality was found at a triglyceride concentration of 1.95 mmol/L.TG and mortalityTG and CVD

Real-life studies and registries of severe asthma: The advent of digital technology

Severe asthma is a chronic and heterogeneous disease that negatively affects the quality of life of our patients and health care utilization. Given the remaining burden of uncontrolled disease in many of these patients, better understanding of its epidemiology, disease mechanisms, effectiveness of novel therapies such as biologics are still highly needed. Asthma treatment guidelines are largely informed by randomized controlled trials (RCTs) and meta analyses of RCTs, however inclusion criteria of many efficacy RCTs of asthma treatments often exclude a high number of patients with asthma in the community. Data from real-life studies and registries of severe asthma can complement efficacy studies by not only providing evidence on how a treatment performs in everyday clinical practice, post marketing safety information, data to support subsequent clinical trial design, but also helping to delineate the natural history of a disease and supporting important translational research endeavors. In the current review, we summarise available national and international collaborative studies and registries, the variables studies and the novel data and insights they provide. The key source of information for most asthma registries are real-life data from patient's electronic health records. Advent of digital technology in collecting data and their analysis is obvious and we draw attention to generation of new knowledge from registries of severe asthma to improve current diagnostic and therapeutic guidelines and asthma control.

Operation Status of the Mutual Aid Human Milk Bank for Preterm Infants and Data Analysis.

This study aimed to investigate the matching degree between the donated supply and demand, clinical characteristics of both donors and recipients, along with the operation cost. From January 1, 2018 to December 31, 2021, the data on human milk donation and usage, the clinical characteristics of donors and recipients, and the cost of each operating center were collected from the Manual Donation Registration Form and Information Management System of the selected human milk bank. During the four years that the human milk bank was in operation, the volume of donated milk was slightly greater than the volume of consumed milk. A total of 1364 donors donated 2434.63 liters of qualified human milk, for RMB 1,791,000 (USD 257, 202), ie, RMB 385.3 (USD 55.3)/L; 97.8% of the donors were preterm puerperae, and 59% of the donors donated between 1 week and 1 month after delivery. All recipients were preterm infants and received donated human milk for a duration of 9.4 days on average. During the four years of operation, the proportion of donors who had previously received donated milk among all donors showed an overall increasing trend, while the incidence of NEC in preterm infants gradually decreased. The increasingly optimized structure of donors, the more economical operation, and the fact that the use of donated milk may not affect breastfeeding of the recipients have made it a human milk bank operation mode worthy of promotion.

Risk for anxiety and depression among men with prostate cancer.

280 Background: Men with prostate cancer (PC) commonly experience symptoms of anxiety, depression, and suicidality; yet, identifying men in need of mental health support can be difficult, particularly as gender role socialization may deter men from seeking care. We aimed to identify sociodemographic, clinical, and social factors associated with risk for clinically significant anxiety and depression among men with PC. Methods: 118 men with PC completed the Cancer Experience Registry, provided sociodemographic and clinical information, degree of symptom and side effect (SSE) burden in the prior month (16 items), completed the CancerSupportSource Risk for Anxiety and Risk for Depression 2-item subscales , and PROMIS Emotional Support and Instrumental Support 4-item subscales. Bivariate analysis was used to identify significant variables associated with risk for anxiety or depression to be included in subsequent models. Multivariable logistic regression was used to determine which factors significantly predicted risk (1=At risk; 0=Not) for 1) anxiety and 2) depression Independent variables included sociodemographic (age, race/ethnicity, employment, income, marital status), and clinical factors (time since diagnosis, staging, treatment status, history of recurrence, radical prostatectomy, chemotherapy, hormone or radiation therapy, total SSE burden), and social support (caregiver (Y/N), emotional and instrumental support). Results: The sample was 84% Non-Hispanic (NH) White, 9% NH Black. Mean age was 66 years ( SD=9.8). 42% NED, 23% localized, 26% metastatic disease. 53% were retired, 35% employed, and 10% unemployed due to disability (UDTD). 31% were at risk for clinical levels of anxiety; 25% were at risk for clinical levels of depression. In multivariable logistic regression analysis: significant predictors of risk for anxiety ( p<.001) included age (OR =0.88, p<.01), not having a caregiver (OR =5.02, p=.02), and emotional support (OR =0.81, p=.04). Risk for depression ( p<.001) was significantly predicted by instrumental support (OR=0.67, p=.01) and higher among those with active, localized disease compared to NED (OR =10.84, p=.02), and among those UDTD compared to employed (OR =11.09, p=.03). Significant correlates of risk for anxiety and depression in bivariate but not multivariate analysis: marital status, time since diagnosis, and total SSE burden. Conclusions: Younger age, UDTD, localized cancer status, social support, and not having a caregiver were significant predictors of risk for clinical levels of anxiety or depression. Routine risk assessment for anxiety and depression, coupled with multidimensional distress screening can help triage patients to tailored care. Further, those with greater social support and those with a caregiver had lower odds of being at risk for anxiety or depression, emphasizing the need for connecting men with cancer to emotional and instrumental supportive services in their community.

Family resources and children’s skills: development of a skills attainment model

ABSTRACT The association between parental SES and children’s educational outcomes is one of the key topics in stratification research. Although most differences between social groups are explained by initial differences in performance, the influence of family resources associated with children’s basic skills is still poorly understood. We therefore developed a skills attainment model, focusing on the relative contribution of three family resources: parents’ own basic skills at age 12, other parental skills developed in education and financial resources in the household. In addition, we examine potential heterogeneity across social groups. We develop a unique dataset, the Intergenerational Transmission of Skills dataset, covering 25,000 Dutch parents and 41,000 children. It includes high-quality test scores in math and language, similarly measured among parents and children, and detailed register information on educational attainment and income. Using structural equation modeling, we find that about one-fifth of children’s basic skills is explained by the three parental resources. Of this explained variance, 69 percent is related to parent’s basic skills, 21 percent to other parental skills developed in education and 10 percent to household income. We find no substantial differences in the transmission across sex, between low- and high-income families and between low- and high-educated parents.

INFOGRAFIS KEPENDUDUKAN KOTA MAKASSAR MENGGUNAKAN ALGORITMA K-MEANS

Makassar City is the fourth-largest city in Indonesia and the largest in Eastern Indonesia with an area of 175.77 square km and a population of ±1.5 people in 2019, divided into 15 districts and 143 sub-districts. Uneven population density in each sub-district has an impact on the emergence of social problems in society such as: unhealthy environment, chaotic building management, population registration information that is not updated. To overcome this problem, it is necessary to have population info graphics that show the population, age of the population, education, etc. With info graphic data on the population of Makassar city that can be accessed online, people looking for data can use it as a reference. To achieve the objectives of this research, the K-means algorithm method is used to divide observations into K clusters where each observation is a member of the cluster with the closest average value, through an iterative process until the grouping converges. The K-means algorithm can be used on population data. For example, the grouping of population data is divided into three clusters, namely (cluster 1) dense, (cluster 2) medium and (cluster 3) not dense. The results obtained show that five districts: Mariso, Mamajang, Makassar, Bontoala and Tallo are the districts with the densest populations.

JYNNEOS vaccine safety monitoring in the Republic of Korea, 2022: a cross-sectional study.

With the recent global mpox outbreak, the JYNNEOS vaccine (Modified Vaccinia Ankara-Bavarian Nordic) was developed as a third-generation smallpox vaccine and initially favored for mpox immunization. Vaccine-associated side effects contribute to vaccine hesitancy. Consequently, tracking adverse events post-immunization is crucial for safety management. This study used data from the national active vaccine safety surveillance conducted in Korea from August 25 to November 24, 2022 to detect potential safety signals and adverse events. Data on health conditions following vaccination were gathered from web-based surveys and reported via active surveillance through the Immunization Registry Information System. This follow-up system functioned via a text message link, surveying adverse events and health conditions beginning on the second day post-vaccination. Information about specific adverse events, including both local and systemic reactions, was collected. The study included 86 healthcare workers who had received at least 1 dose of the JYNNEOS vaccine. Among the respondents, 79.1% reported experiencing at least 1 adverse event, with the majority being local reactions at the injection site. The incidence of adverse events was higher following the first dose (67.9%) than after the second dose (34.4%). The most frequently reported adverse event for both doses was mild pain at the injection site. The study provides crucial information on the safety of the JYNNEOS vaccine, demonstrating that most adverse events were manageable and predominantly localized to the injection site. Nonetheless, additional research is needed on the safety of various vaccine administration techniques and the vaccine's effects on broader demographics.

Development of a Data-Based Machine Learning Model for Classifying and Predicting Property Damage Caused by Fire

Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage grade prediction by fire based on simplified building information. This paper’s primary objective is to propose and verify a framework for predicting the scale of property damage caused by fire using machine learning (ML). Korean public datasets are collected and preprocessed, and ML algorithms are trained with only 15 input data using building register and fire scenario information. Four models (artificial neural network (ANN), decision tree (DT), k-nearest neighbor (KNN), and random forest (RF)) are used for ML. The RF model is the most suitable for this study, with recall and precision of 74.2% and 73.8%, respectively. Structure, floor, causes, and total floor area are the critical factors that govern the fire size. This study proposes a novel approach by utilizing ML models to accurately and rapidly predict the size of fire damage based on basic building information. By analyzing domestic fire incident data and creating fire scenarios, a similar ML model can be developed.

Triglyceride-glucose index, low-density lipoprotein levels, and cardiovascular outcomes in chronic stable cardiovascular disease: results from the ONTARGET and TRANSCEND trials.

The triglyceride-glucose index (TyG) has been proposed as an alternative to insulin resistance and as a predictor of cardiovascular outcomes. Little is known on its role in chronic stable cardiovascular disease and its predictive power at controlled low density lipoprotein (LDL) levels. Our study population consisted of 29 960 participants in the ONTARGET and TRANSCEND trials that enrolled patients with known atherosclerotic disease. Triglycerides and glucose were measured at baseline. TyG was calculated as the logarithmized product of fasting triglycerides and glucose divided by 2. The primary endpoint of both trials was a composite of cardiovascular death, myocardial infarction, stroke, or hospitalization for heart failure. The secondary endpoint was all-cause death and the components of the primary endpoint. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) with extensive covariate adjustment for demographic, medical history, and lifestyle factors. During a mean follow-up of 4.3 years, 4895 primary endpoints and 3571 all-cause deaths occurred. In fully adjusted models, individuals in the highest compared to the lowest quartile of the TyG index were at higher risk for the primary endpoint (HR 1.14; 95% CI 1.05-1.25) and for myocardial infarction (HR 1.30; 95% CI 1.11-1.53). A higher TyG index did not associate with the primary endpoint in individuals with LDL levels < 100 mg/dL. A higher TyG index is associated with a modestly increased cardiovascular risk in chronic stable cardiovascular disease. This association is largely attenuated when LDL levels are controlled. www.clinicaltrials.gov: NCT00153101.

Implementation of the Concept of Infotainment into the Practice of the Event Industry: Definition of the Problem

The purpose of the article is to consider the defining trends and aspects connected with the implementation of the conception of infotainment in the practice of the event industry. The research methodology predicts the usage of, firstly, the descriptive level combined with an analytical method to characterise the current stage of the event industry, its events category B2C and B2B, secondly, context-structural analysis of infotainment as a concept and model thanks to which the author has managed to identify the causal links between certain types of event activities and essential features of infotainment, which is the condition for the possibility of implementing the practice of the event industry. Scientific novelty is, first of all, that on the article level, the problem of implementation of the conception of infotainment in the practice of the event industry was actualised, which was mainly considered in the context of journalism and TV. Conclusions. It is affirmed that the concept of infotainment is one of the methodological platforms that can be used for reasoning and explanation of the logic of deployment and the content specifics of individual event activities, and also their place in modern (world and national) mass culture. The author suggests the statement according to which the given model of the media culture helps in registration content and information creates favourable conditions for the development of event management through synthesis educational-cognition and entertainment components in event activities, helps to decode and perceive complex meanings and images in their continuous flow and frantic information dynamics. It is underlined that initiating cultural-intellectual “game”, infotainment stimulates heuristic potential of thinking, especially in terms of perception and assimilation of cultural codes, and with the help of fragmenting the content, activates the initiative of event participants in terms of creatively completing the full picture of what is happening.&#x0D; Keywords: infotainment, event industry, event activities, entertainment, game, mass culture, media culture.

Perancangan Sistem Informasi Pendaftaran Pasien Rawat Jalan Pada Rumah Sakit Ibu dan Anak Gizar Berbasis Mobile

In accordance with the Regulation of the Minister of Health of the Republic of Indonesia Number 82 of 2013 concerning Hospital Management Information Systems, that every Hospital is required to organize SIMRS. SIMRS regulation aims to improve efficiency, effectiveness, professionalism, performance, and hospital access and services. RSIA Gizar will start implementing SIMRS in 2021, but the current system is still not optimal because patient registration is still done directly at the hospital, cannot be done online, which makes patient registration services slow. The method of data collection used in the preparation of this Final Project is the method of observation, interviews, literature study and the software development model using the waterfall method. So that the Design of an Outpatient Patient Registration Information System uses the waterfall method. At RSIA Gizar, it was made aiming to make it easier for patients to register online through a mobile-based application and also to make it easier for admin staff to register patients, manage medical record data and in making patient registration reports so that more effective and efficient..&#x0D;

Relationship between night shift and sleep problems, risk of metabolic abnormalities of nurses: a 2 years follow-up retrospective analysis in the National Nurse Health Study (NNHS)

Background and purposeEfforts to improve nurses’ physical and mental health are critical to ensuring the safety and quality of the healthcare system. Long-term studies targeting the relevancy of nurses’ occupation characteristics with health conditions remain insufficient. This study aimed to examine the relationship between nurses’ night shift and sleep problems and metabolic abnormalities risk.MethodsThis study was a part of the National Nurse Health Study, an ambispective cohort study in China, in 2021. Based on an integration physical examination data system, this study carried out a retrospective analysis of 730 nurses from 2018 to 2020 and combined with a questionnaire survey in 2021. The STROBE guidelines were adopted for reporting.ResultsIn the 23 (23.0, 24.0) months follow-up, higher night shift load was associated with more sleep problems such as shortened sleep duration, sleep disorders, poor sleep quality, and sleep deprivation. Moreover, night shift load was associated with chronic diseases risk factors, increasing body mass index and body fat, with more night shift density, increasing the occurrence of low levels of high-density lipoprotein cholesterol, high triglyceride, triglyceride/high-density lipoprotein cholesterol ratio, and serum uric acid.ConclusionThe night shift load has become an occupational health concern, contributing to chronic diseases relevant metabolic risk factors and negative influence on sleep health. Focus on the strategies to improve the sleep quality of nurses undergoing night shift work, optimize work scheduling and ongoing monitor the relevant risk factors are essential to enhance the stability and well-being of the nursing workforce.Clinical Trials registration information: NCT04572347, on October 1, 2020. https://www.clinicaltrials.gov/ct2/show/NCT04572347

Educational attainment and symptoms of anxiety and depression in young adulthood

Abstract Background Young adulthood is a life phase when mental health problems are common. Although education is known to exert an influence on health, increased knowledge about the links between educational attainment and mental health problems in young adults is needed. The aim of this study was to analyse if educational attainment at the end of upper secondary (U.S.) school (i.e. age 19) predicted self-reported anxiety and depression symptoms two years later. Methods Data was derived from the Swedish population-based cohort study Futura01 (n = 3247; 56% women). Anxiety and depression were measured by self-reports in 2022 (age 21) through the Patient Health Questionnaire (PHQ-4). Educational attainment was measured through linked registry information from 2020 (age 19). Linear regression analysis was used. Covariates included parental country of birth, parental education and family type. Results Co-occurring symptoms of anxiety and depression were more common among young adults with a compulsory than a U.S. academic degree (women: b = 0.79, 95% CI 0.49, 1.09; men: b = 0.77, 95% CI 0.37, 1.17). Symptoms of depression only were more common among women with a compulsory degree (b = 0.60, 95% CI 0.20, 1.00), and among participants with a U.S. vocational degree (women: b = 0.51, 95% CI 0.09, 0.94; men: b = 0.50, 95% CI 0.08, 0.91), compared to those with a U.S. academic degree. Symptoms of anxiety only were, in contrast, less common among men and women with a compulsory degree compared to those with a U.S. academic degree, although statistically significant only among women (b=-0.50, 95% CI -0.88, -0.12). Conclusions Educational level in young adulthood was clearly associated with subsequent symptoms of anxiety and depression but the social patterning varied between symptoms. Lower educational level was linked to a higher reporting of co-occurring anxiety and depression and of depression only, while a higher educational level was linked to a higher reporting of anxiety only. Key messages • Young adult educational attainment was negatively associated with symptoms of co-occurring anxiety and depression and of depression only, but positively associated with symptoms of anxiety only. • In young adulthood educational level is associated with anxiety and depression in complex ways. Efforts to improve educational attainment and/or mental health need to consider this complexity.

The Development of Chatbot Provided Registration Information Services for Students in Distance Learning

In recent years, chatbots have become crucial, particularly for assisting students with real-time registration information. This research focused on 1) synthesizing registry works related to information provided for students, 2) designing chatbots and conversation structures in the form of interactive conversations between students and robots for answering questions and providing information tailored to their needs, and 3) examining and evaluating the use of chatbots in providing information services to students, while analyzing the accuracy and suitability of the developed chatbot. This study, based on research and development, utilized a sample consisting of 16 staff directly involved in the provision of registration information to students and 255 undergraduate students from Sukhothai Thammathirat Open University, with respondents being selected through a simple random sampling technique. The synthesis of the research results revealed the following findings: 1) A qualitative study revealed that the registration information related to students, called STOU Journey, consisted of 10 issues, and was required for the whole learning period. 2) The result of the design and development of the chatbot revealed that the developer chatbot could be used on both the website and the LINE application. It was also found that the chatbot could answer most questions correctly and completely. The chatbot responded quickly and was easy to use. The chatbot used language that was easy to understand and natural, while 3) satisfactory evaluation results from 255 undergraduate students showed that overall, students who had used the completed version of the chatbot were satisfied with the use of the chatbot at a high level (Mean = 4.19, SD = 0.98) while they also felt that the chatbot was easy to use (Mean = 4.33, SD = 0.95) and the using the chatbot felt like a natural conversation (Mean = 4.22, SD = 0.99).

ResearchMatch on FHIR: Development and evaluation of a recruitment registry and electronic health record system interface for volunteer profile completion.

Obtaining complete and accurate information in recruitment registries is essential for matching potential participants to research studies for which they qualify. Since electronic health record (EHR) systems are required to make patient data available to external systems, an interface between EHRs and recruitment registries may improve accuracy and completeness of volunteers' profiles. We tested this hypothesis on ResearchMatch (RM), a disease- and institution-neutral recruitment registry with 1357 studies across 255 institutions. We developed an interface where volunteers signing up for RM can authorize transfer of demographic data, medical conditions, and medications from the EHR into a registration form. We obtained feedback from a panel of community members to determine acceptability of the planned integration. We then developed the EHR interface and performed an evaluation study of 100 patients to determine whether RM profiles generated with EHR-assisted adjudication included more conditions and medications than those without the EHR connection. Community member feedback revealed that members of the public were willing to authenticate into the EHR from RM with proper messaging about choice and privacy. The evaluation study showed that out of 100 participants, 75 included more conditions and 69 included more medications in RM profiles completed with the EHR connection than those without. Participants also completed the EHR-connected profiles in 16 fewer seconds than non-EHR-connected profiles. The EHR to RM integration could lead to more complete profiles, less participant burden, and better study matches for many of the over 148,000 volunteers who participate in ResearchMatch.

Trust and Psychosomatic Complaints in Adolescence: Findings From a Swedish Cohort Study.

Objectives: To examine the cross-sectional and longitudinal associations between generalised and institutional trust and psychosomatic complaints in mid and late adolescence. Methods: Data were derived from the Swedish cohort study Futura01, using survey information collected amongst 3,691 grade 9 students (∼15-16years, t1) who were followed-up 2years later (∼17-18years, t2). Registry information on sociodemographic characteristics was linked to the data. Linear regression analyses were performed. The longitudinal analyses applied the first difference (FD) approach as well as the lagged dependent variable (LDV) approach. Covariates included gender, family type, parental education, parental country of birth, and upper secondary programme. Results: Higher levels of generalised and institutional trust were cross-sectionally associated with lower levels of psychosomatic complaints at both time points. The FD analyses showed that increases in generalised and in institutional trust between ages 15-16 and 17-18years were associated with corresponding decreases in psychosomatic complaints. The LDV analyses demonstrated reciprocal temporal associations between trust and psychosomatic complaints. Conclusion: The findings indicate that trust is a social determinant of psychosomatic complaints in adolescents, but also that health may affect trust.

One-Year Outcomes and Their Relationship to Residual Mitral Regurgitation After Transcatheter Edge-to-Edge Repair With MitraClip Device: Insights From the OCEAN-Mitral Registry.

Background Limited data are available about clinical outcomes and residual mitral regurgitation (MR) after transcatheter edge-to-edge repair in the large Asian-Pacific cohort. Methods and Results From the Optimized Catheter Valvular Intervention (OCEAN-Mitral) registry, a total of 2150 patients (primary cause of 34.6%) undergoing transcatheter edge-to-edge repair were analyzed and classified into 3 groups according to the residual MR severity at discharge: MR 0+/1+, 2+, and 3+/4+. The mortality and heart failure hospitalization rates at 1 year were 12.3% and 15.0%, respectively. Both MR and symptomatic improvement were sustained at 1 year with MR ≤2+ in 94.1% of patients and New York Heart Association functional class I/II in 95.0% of patients. Compared with residual MR 0+/1+ (20.4%) at discharge, both residual MR 2+ (30.2%; P < 0.001) and 3+/4+ (32.4%; P = 0.007) were associated with the higher incidence of death or heart failure hospitalization (adjusted hazard ratio [HR], 1.59; P < 0.001, and adjusted HR, 1.73; P = 0.008). New York Heart Association class III/IV at 1 year was more common in the MR 3+/4+ group (20.0%) than in the MR 0+/1+ (4.6%; P < 0.001) and MR 2+ (6.4%; P < 0.001) groups, and the proportion of New York Heart Association class I is significantly higher in the MR 1+ group (57.8%) than in the MR 2+ group (48.3%; P = 0.02). Conclusions The OCEAN-Mitral registry demonstrated favorable clinical outcomes and sustained MR reduction at 1 year in patients undergoing transcatheter edge-to-edge repair. Both residual MR 2+ and 3+/4+ after transcatheter edge-to-edge repair at discharge were associated with worse clinical outcomes compared with residual MR 0+/1+. Registration Information https://upload.umin.ac.jp. Identifier: UMIN000023653.

In search of founding era registers: automatic modeling of registers from the corpus of Founding Era American English

Abstract Registers are situationally defined text varieties, such as letters, essays, or news articles, that are considered to be one of the most important predictors of linguistic variation. Often historical databases of language lack register information, which could greatly enhance their usability (e.g. Early English Books Online). This article examines register variation in Late Modern English and automatic register identification in historical corpora. We model register variation in the corpus of Founding Era American English (COFEA) and develop machine-learning methods for automatic register identification in COFEA. We also extract and analyze the most significant grammatical characteristics estimated by the classifier for the best-predicted registers and found that letters and journals in the 1700s were characterized by informational density. The chosen method enables us to learn more about registers in the Founding Era. We show that some registers can be reliably identified from COFEA, the best overall performance achieved by the deep learning model Bidirectional Encoder Representations from Transformers with an F1-score of 97 per cent. This suggests that deep learning models could be utilized in other studies concerned with historical language and its automatic classification.

Validation of the PREDICT Prognostication Tool in US Patients With Breast Cancer.

PREDICT is an online prognostication tool derived from breast cancer registry information on approximately 6,000 women treated in the United Kingdom that estimates the postsurgical treatment benefit of surgery alone, chemotherapy, trastuzumab, endocrine therapy, and/or adjuvant bisphosphonates in early-stage breast cancer. Our aim was to validate the PREDICT algorithm in predicting 5- and 10-year overall survival (OS) probabilities using real-world outcomes among US patients with breast cancer. A retrospective study was performed including women diagnosed with unilateral breast cancer in 2004 through 2012. Women with primary unilateral invasive breast cancer were included. Patients with bilateral or metastatic breast cancer, no breast surgery, or missing critical clinical information were excluded. Prognostic scores from PREDICT were calculated and external validity was approached by assessing statistical discrimination through area under time-dependent receiver-operator curves (AUC) and comparing the predicted survival to the observed OS in relevant subgroups. We included 708,652 women, with a median age of 58 years. Most patients were White (85.4%), non-Hispanic (88.4%), and diagnosed with estrogen receptor-positive breast cancer (79.6%). Approximately 50% of patients received adjuvant chemotherapy, 67% received adjuvant endocrine therapy, 60% underwent a partial mastectomy, and 59% had 1 to 5 axillary sentinel nodes removed. Median follow-up time was 97.7 months. The population's 5- and 10-year OS were 89.7% and 78.7%, respectively. Estimated 5- and 10-year median survival with PREDICT were 88.3% and 73.8%, and an AUC of 0.77 and 0.76, respectively. PREDICT performed most poorly in patients with high Charlson-Deyo comorbidity scores (2-3), where PREDICT overestimated OS. Sensitivity analysis by year of diagnosis and HER2 status showed similar results. In this prognostic study utilizing the National Cancer Database, the PREDICT tool accurately predicted 5- and 10-year OS in a contemporary and diverse population of US patients with nonmetastatic breast cancer.