National Data Research Articles

Trends in the hand hygiene practices using alcohol-based hand rubs in Japanese hospitals before and after the novel coronavirus pandemic: an observational study using national surveillance data

Healthcare-associated infections (HAIs) are a global concern in healthcare facilities, and hand hygiene (HH) using alcohol-based hand rubs (ABHR) is fundamentally crucial for their prevention. While previous studies report improvements in HH compliance amid the COVID-19 pandemic, the real situation in Japanese medical settings remains unclear. This observational study sought data from the Japanese national surveillance, focusing on ABHR use in hospitals before and after the COVID-19 pandemic. Data were retrieved from facilities certified to receive the Additional Healthcare Reimbursements for Infection Prevention and Control I. The study spanned five years (2019-2023), segmented quarterly, and employed Joinpoint regression analysis to assess the annual percentage change (APC). Overall, ABHR use per patient per day significantly increased both in critical care units and general wards amid the pandemic. However, the APC in the critical care units demonstrated a downward trend from Q4 of 2021 to Q1 of 2023, and ABHR use in general wards remained below the amount of WHO recommendations. This trend analysis highlighted recent patterns of ABHR use in Japanese hospitals by comparing pre- and post-COVID-19 periods. Although increases in ABHR use were observed over time, sustained efforts to promote HH compliance are necessary, particularly in general wards.

MONDEP: A unified SpatioTemporal MONitoring Framework for National DEPression Forecasting

Depression has become a prevalent mental disorder that significantly affects a person's emotions, behaviors, physical health, ability to perform daily tasks, and ability to maintain healthy relationships. Untreated depression can escalate the risk of suicide, making the situation even worse. Despite an abundance of models previously proposed for forecasting depression, the issue of foretelling the overall number of patients at each administrative level remains under-investigated. Therefore, in this paper, we propose a simple but effective SpatioTemporal Monitoring Framework for National Depression Forecasting (MONDEP). In particular, we analyze national depression statistics data in Thailand as a case study and create prediction models for a real-time depression forecasting system using machine learning and deep learning approaches. In order to forecast the prevalence of depression at various administrative levels, we use the hierarchical structure of depression aggregation. The proposed framework consists of three modules: Data Pre-processing to extract and pre-process the raw data, Exploratory Data Analysis (EDA) to visualize and analyze the data to get insight, and Model Training and Testing to predict future depression cases. The objective of our research is to construct a comprehensive MONDEP framework that utilizes machine learning and deep learning to predict depression profiles at the district and national levels using multivariate time series across various administrative levels. Our study illustrates the considerable association between a spatial-temporal component and demonstrates how depression profiles may be represented by employing lower administrative-level data to estimate the general level of mental health across the nation. Additionally, the best performance across all criteria is obtained when a deep learning model is used to exploit multivariate time series, showing a 13% improvement in MAE measure compared to the SARIMAX baseline. We believe the proposed framework could be used as a point of reference for decision-making regarding the management of depression and has the potential to be incredibly helpful for policymakers in successfully managing mental health services on time.

Robust SARS-CoV-2-neutralizing antibodies sustained through 6 months post XBB.1.5 mRNA vaccine booster

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies are substantially expanded 1month after a shot of XBB.1.5 monovalent mRNA vaccine (XBB.1.5 MV) booster, but the durability of this response remains unknown. Here, we address this question by performing neutralization assays on four viral variants (D614G, BA.5, XBB.1.5, and JN.1) using sera from participants obtained at ∼1month, ∼3months, and ∼6months post an XBB.1.5 MV booster. Our findings indicate that the resulting neutralizing antibody titers are robust and generally remain at stable levels for the study period, similar to those following XBB infection. Importantly, this durability of neutralizing antibody titers contrasts with the decline observed after a booster of the original monovalent or BA.5 bivalent mRNA vaccine. Our results are in line with the recent national data from the Centers for Disease Control and Prevention, showing that the efficacy against symptomatic SARS-CoV-2 infection is sustained for up to 4months after an XBB.1.5 MV booster.

Antimicrobial Resistance in Sepsis Cases Due to Escherichia coli and Klebsiella pneumoniae: Pre-Pandemic Insights from a Single Center in Southwestern Romania.

To determine the resistance profile of Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) strains isolated in sepsis cases diagnosed at the Infectious Diseases Clinic in Craiova, Romania. The bacteria responsible for sepsis cases were identified using the Vitek 2 Systems version 06.01, which was then employed to assess their antimicrobial susceptibility (Global CLSI and Phenotypic 2017). We have identified 989 patients diagnosed with bacterial sepsis. Among these, 953 cases were caused by Gram-negative rods, with 415 attributed to E. coli and 278 to K. pneumoniae. High levels of resistance to ampicillin were recorded for E. coli strains isolated in sepsis cases (64.6%); adding sulbactam lowers the level of resistance to 41.8%. Resistance to 3rd generation cephalosporins varied between 7.47 and 14.6% and another 3.41 to 11.1% are dose-dependent susceptibility strains. Resistance to carbapenems (i.e., ertapenem, meropenem) is low-2.18-2.42%. More than 95% of the tested K. pneumoniae strains were resistant to ampicillin and adding sulbactam as a β-lactamase inhibitor only halves that level. Resistance to 3rd generation cephalosporins varied between 20.7% and 22.5%; resistance levels for K. pneumoniae were notably higher than those for E. coli. Over 95% of K. pneumoniae strains showed resistance to ampicillin, and resistance to 3rd generation cephalosporins varied between 20.7% and 22.5%. Additionally, K. pneumoniae exhibited higher resistance to carbapenems (13.7-19.5%) compared to E. coli (2.18-2.42%). Antimicrobial resistance levels are generally lower than continental and national data, except for ampicillin and carbapenems (meropenem and ertapenem). K. pneumoniae strains are significantly more resistant than E. coli strains.

Predicting Marginalized Students’ Mathematics Achievement in High School

ABSTRACT The current study is a conceptual replication of the influence of an advanced educational opportunity and several student propensities to learn on a college-readiness assessment for mathematics (ACT scores) among an important and under-studied group of students. We focused on a sample of predominantly Black students from economically-disadvantaged homes in the U.S. (n = 329; 80% Black, 59% female, 66% whose parents had a high-school diploma or less). Accelerated course placement (high-school math course in 8th grade) was a unique predictor of math ACT scores above and beyond prior math achievement and other variables (B = 1.5). In line with a fade-out model, executive function skill in 6th grade was not a unique predictor with other predictors in the model. In line with emerging findings with marginalized students, mathematics self-concept in 6th grade was also not a unique predictor. Finally, students’ mathematics achievement at age 4 predicted their math ACT scores in 12th grade (B = .69), as did their middle-school mathematics achievement in number, algebra, and geometry (B = .43–.67), which mediated the relation between mathematics achievement at age 4 and math ACT scores. Findings highlight the importance of advanced academic opportunities, which national data indicates marginalized students are less likely to receive, the diminishing role of individual differences in executive function skill as children develop domain knowledge, the diminished role of math self-concept for predicting achievement among marginalized students, and the strong stability in math achievement.

Accelerating imaging research at large-scale scientific facilities through scientific computing.

To date, computed tomography experiments, carried-out at synchrotron radiation facilities worldwide, pose a tremendous challenge in terms of the breadth and complexity of the experimental datasets produced. Furthermore, near real-time three-dimensional reconstruction capabilities are becoming a crucial requirement in order to perform high-quality and result-informed synchrotron imaging experiments, where a large amount of data is collected and processed within a short time window. To address these challenges, we have developed and deployed a synchrotron computed tomography framework designed to automatically process online the experimental data from the synchrotron imaging beamlines, while leveraging the high-performance computing cluster capabilities to accelerate the real-time feedback to the users on their experimental results. We have, further, integrated it within a modern unified national authentication and data management framework, which we have developed and deployed, spanning the entire data lifecycle of a large-scale scientific facility. In this study, the overall architecture, functional modules and workflow design of our synchrotron computed tomography framework are presented in detail. Moreover, the successful integration of the imaging beamlines at the Shanghai Synchrotron Radiation Facility into our scientific computing framework is also detailed, which, ultimately, resulted in accelerating and fully automating their entire data processing pipelines. In fact, when compared with the original three-dimensional tomography reconstruction approaches, the implementation of our synchrotron computed tomography framework led to an acceleration in the experimental data processing capabilities, while maintaining a high level of integration with all the beamline processing software and systems.

Empowering air quality prediction through "AI + big data technology" in the perspective of environmental lawA quasi-natural experiment analysis based on the "national big data comprehensive experimental zone" pilot program

The current environmental legal system primarily focuses on environmental pollution and ecological damage, yet it does not adequately address climate change as an environmental risk issue. Consequently, environmental law struggles to directly respond to air pollution and climate change. Due to the complexity of air pollution regulation, there is a need for legal frameworks that extend beyond conventional environmental pollution controls. The advent of "AI + Big Data" has provided new momentum and opportunities for predicting and improving air quality. This paper, viewed through the lens of environmental law and based on the policy of the National Big Data Comprehensive Experimental Zone, combined with the Difference-in-Differences (DID) model, outlines the impact mechanisms of Big Data and Artificial Intelligence in empowering air quality prediction and improvement. It also explores the path choices for achieving the objectives of accuracy and effectiveness in air quality prediction from the perspective of environmental law.

Energy consumption decomposition analysis using European official statistics: Methodology and input data

Deciphering energy efficiency is a critical component for the sustainability and energy policies of the European Union (EU) and its Member States. Decomposition analysis is a key method that helps distinguish real energy efficiency gains from other external factors. This article presents a decomposition analysis method using official EU statistics, its results, and associated limitations. Although separating structural changes and activity levels from energy efficiency poses a challenge, an adapted Logarithmic Mean Divisia Index (LMDI) method was utilised to isolate and highlight energy efficiency. This article outlines this method and how the European official statistics were exploited. Firstly, it examines the factors affecting energy consumption in various sectors within EU-27. Secondly, it examines the factors affecting energy consumption in various sectors. In doing so, it also addresses potential obstacles in data collection, and presents improvements to the LMDI analysis. The findings in this study make a substantial contribution to the fields of national statistics, methodological applications, and energy data analysis in the context of the EU’s energy policies.

Adjusting mobile phone data to account for children's travel and the impact on measles dynamics in Zambia.

Models of measles transmission can be used to identify areas of high risk to tailor immunization strategies. Estimates of spatial connectivity can be derived from data such as mobile phone records, however it is not clear how this maps to the movement of children who are more likely to be infected. Using travel surveys across two districts in Zambia and national mobile phone data, we compared estimates of out-of-district travel for the population captured in the mobile phone data and child-specific travel from travel surveys. We then evaluated the impact of unadjusted and adjusted connectivity measures on simulated measles virus introduction events across Zambia. The number of trips made by children from the travel survey was three to five times lower than the general population estimates from mobile phone data. This decreased the percentage of districts with measles virus introduction events from 78% when using unadjusted data to 51% - 64% following adjustment. Failure to account for age-specific heterogeneities in travel estimated from mobile phone data resulted in overestimating subnational areas at high risk of introduction events, which could divert mitigation efforts to districts that are at lower risk.

Flexibility Stigma Across Europe: How National Contexts can Shift the Extent to which Flexible Workers are Stigmatised

AbstractAlthough flexible working has expanded rapidly, especially during the pandemic, biased views against flexible workers – namely, flexibility stigma - are still prevalent and returning. Flexibility stigma hinders worker’s take up of flexible working arrangements and can make flexible working arrangements result in negative outcomes for worker’s well-being and productivity. This study examines how national cultural and policy contexts shape flexibility stigma levels within a country. We use a multilevel approach using the Eurobarometer dataset of 2018, covering 28 European countries, matched with national level aggregate data on policy and culture. Results show that in countries with a more work-life balance work culture and egalitarian gender norms, we see less prevalence of flexibility stigma. Similarly, in countries with generous family-friendly policies, workers are less likely to have negative perception towards flexible working. Finally, stronger bargaining positions of workers, may it be through stronger union power or through better labour market conditions, helps remove stigmatised views around workers who use flexible working arrangements. This study evidences the importance of contexts that shape views around flexible working, to help us better understand policy changes needed to ensure better flexible working practices.

Utilizing a Dashboard for Efficient Biodiversity Data Overview and Gap-Filling Effort

Taiwan Biodiversity Information Facility has been leading the effort to integrate and mobilize biodiversity data nationally. We recently accomplished the integration of local databases and successfully developed a data portal that efficiently links to the most comprehensive biodiversity database in Taiwan: the Taiwan Biodiversity Information Alliance Data Portal. However, we identified an emerging challenge following this development. Preliminary analyses have revealed several gaps in the current dataset, impeding robust data use. For instance, land data dominates over sea data, and bird records are more abundant than those of other taxonomic groups. In our endeavour to enhance national biodiversity data coverage, we are actively exploring methodologies to address these existing data gaps. Here, we broadly define data gap as the absence of required data or information for use. Our primary objective is to empower users to identify these gaps, thereby facilitating efficient, informed survey planning and eventually filling these gaps. For this purpose, we are evaluating the effectiveness of a user-friendly dashboard, tailored for biodiversity survey planning in Taiwan. We developed and deployed a R Shiny dashboard*1 that provides users with insightful data visualizations that highlight spatial, temporal, and taxonomical data overviews. It also offers customizable filtering options, such as by major taxon groups and habitat types, for easy viewing. Additionally, the dashboard includes a download function, so users can access spatial and taxon gap information in their survey planning efforts. After deploying the dashboard, we conducted user interviews to collect feedback aimed at refining its usability and effectiveness. In addition to helping survey planning, we anticipate that this tool will also aid data users in promptly assessing data integrity within the national biodiversity data portal, thereby enabling them to identify potential data gaps and biases that may affect subsequent use. Through this presentation, we aim to share our experience in developing an interactive dashboard tailored for public use. Preliminary results had indicated that the dashboard highlighted some visible data gaps and biases, particularly in underrepresented areas such as marine habitats and less-studied taxonomic groups. Additionally, user interviews revealed a demand for a feature that provides single species data overviews, suggesting a potential area for further development to enhance the tool's utility. Some challenges remain, such as the need to enhance data granularity and user interface usability. Future work will focus on incorporating more real-time data integration and expanding the range of customizable filters. We believe these efforts will further empower users in Taiwan to conduct more informed and efficient biodiversity surveys, ultimately supporting research and policy-making to address critical biodiversity data gaps.

Validity of an expert-based job exposure matrix of hand-wrist physical exposures and their prospective associations with carpal tunnel syndrome.

Epidemiological studies of occupational risk factors for rare disorders require large study populations with adequate exposure estimates. Job exposure matrices (JEMs) linked to national information on standardized job titles may enable such large studies. We aimed to establish and validate a JEM for occupational hand-wrist exposures that could be linked to Danish national register data on job titles and hand-wrist disorders. We developed a JEM for hand-wrist repetition, force, vibration, and computer work in 96 job groups covering 91% of the 2227 occupational titles in the Danish version of the International Standard Classification of Occupation-88, and examined inter-rater reliability of five expert ratings. Poisson regression models were used to estimate incidence rate ratios for the association of carpal tunnel syndrome (CTS) with the level of repetitive movements, force, vibration, and hours of computer work described by the JEM, adjusted for relevant confounders. The JEM based on expert ratings had fair to good interrater reliability. The incidence of CTS increased with increasing levels of force, hand-wrist repetition, and vibration, Exposure-response patterns for repetition and vibration became less consistent after adjustment for force. The interaction between repetition and force was complex and did not support an overall positive interaction. Computer work was negatively associated with incident CTS. The JEM was able to identify known risk factors for CTS consistent with current evidence, and provided further associations on exposure-response patterns, mutual exposure adjustment, and interaction effects between repetition and force. The reliability of expert assessments of hand-wrist physical exposures was fair to good.

Body dissatisfaction widens the racial disparities of Benzophenone-3, a chemical biomarker of personal care and consumer product usage.

Body dissatisfaction can drive individuals to use personal care products, exposing themselves to Benzophenone-3 (BP3). Yet, no study has examined the link between body dissatisfaction and elevated chemical exposures. Our study examines how body dissatisfaction impacts the racial differences in BP3 exposures. Using NHANES 2003-2016 data for 3,072 women, we ascertained body dissatisfaction with a questionnaire on weight perception. We ran two generalized linear models with log10-transformed urinary concentrations of BP3 as the outcome variable and the following main predictors: one with race/ethnicity and another combining race/ethnicity and body dissatisfaction. We also conducted stratified analyses by race/ethnicity. We adjusted for poverty income ratio, BMI, urinary creatinine, and sunscreen usage. BP3 levels in Mexican American, Other Hispanic, Other Race, non-Hispanic White, and non-Hispanic Asian women were on average 59%, 56%, 33%, 16%, and 9% higher, respectively, compared to non-Hispanic Black women. Racial differences in BP3 levels are accentuated with body dissatisfaction. For example, Other Hispanic women perceiving themselves as overweight had 69% higher BP3 levels than non-Hispanic Black women (p-value = 0.01), while those perceiving themselves as at the right weight had 32% higher levels (p-value = 0.31). Moreover, minority women perceiving themselves as overweight tended to have higher BP3 levels than those who do not. For example, BP3 levels in Other Hispanic women perceiving themselves as overweight are significantly higher compared to those who do not (73%, p-value = 0.03). In contrast, such differences in the non-Hispanic White women are minimal (-0.5%, p-value = 0.98). Minority women with body dissatisfaction show elevated BP3 exposure independent of sunscreen usage, implying that their elevated exposures may stem from using other personal care and consumer products. Further research is needed to determine if increases of exposure to potential toxicants occur among minority women with body dissatisfaction. First integration of measures of body dissatisfaction with national chemical biomonitoring dataAnalyzed data from a diverse US nationally representative sample of 3,072 womenMinority women with body dissatisfaction show higher BP3 levels independent of sunscreen use and BMIMinimal differences in BP3 levels by body dissatisfaction in non-Hispanic White womenDeveloped a visualization tool to show how racial disparities widen due to body dissatisfaction.

Conflict or Coordination? A Coupling Study of China’s Population–Urbanization–Ecological Environment

Whether the new type of urbanization implemented in China in the past decade has been effective in regulating urbanization and balancing human development and environmental protection remains to be verified. Therefore, this study develops a framework for assessing population-urbanization–ecological environment interactions by combining the coupling coordination degree model and the decoupling index. Firstly, the proposed framework establishes an indicator system of population, economy, society, space, environmental pressure, ecological governance, ecological status, and ecological services based on two sets of national census data; secondly, this study combines the coupling coordination degree model and decoupling index to comprehensively understand the coupling coordination relationship and the decoupling relationship of the population–urbanization–ecological environment across time and space. Overall, this study contributes to a deepened understanding of coupled population–urbanization–ecological environment interactions and provides a scientific basis for effective guidance on urban–rural management and the balance between human development and environmental protection.

The Health Status of Undocumented Immigrants from Asian Countries in the United States: A Scoping Review and Recommendations for Future Directions.

Immigrants from Asian countries are the fastest-growing undocumented population in the United States (U.S.), yet not much is known about their health. This scoping review identifies the nature and extent of scientific literature on the health of undocumented Asian immigrants in the U.S. We conducted a comprehensive search of six electronic databases in 2024. Inclusion criteria were empirical articles written in English, published in peer-reviewed scientific journals from 2010 to 2024, and focused on a health outcome or health-related issue involving undocumented Asian immigrants. Results are summarized narratively. We identified 13 peer-reviewed publications. Nine studies were quantitative, and four were qualitative. Eight studies were conducted in California; two studies used national secondary data sources. Studies were mixed in their research focus. They covered a range of health outcomes and issues, such as mental health (n = 4), health services and access (n = 2), contraceptive use (n = 1), COVID-19 (n = 2), and HIV (n = 1). Three studies measured self-rated health alongside other conditions, such as disability, health insurance coverage, chronic health conditions, and obesity. Scholarship on the health of undocumented Asian immigrants is a growing research area. Given the small number of studies identified, future research with larger diverse samples, more robust methodology, and greater topical variety are warranted to understand the health of this population better and reduce potential inequities.

An observational study of therapeutic procedures and in-hospital outcomes among patients admitted for acute myocardial infarction in Spain, 2016–2022: the role of diabetes mellitus

BackgroundWe used the Spanish national hospital discharge data from 2016 to 2022 to analyze procedures and hospital outcomes among patients aged ≥ 18 years admitted for ST-elevation myocardial infarction (STEMI) and non–ST-elevation myocardial infarction (NSTEMI) according to diabetes mellitus (DM) status (non-diabetic, type 1-DM or type 2-DM).MethodsWe built logistic regression models for STEMI/NSTEMI stratified by DM status to identify variables associated with in-hospital mortality (IHM). We analyzed the effect of DM on IHM.ResultsSpanish hospitals reported 201,950 STEMIs (72.7% non-diabetic, 0.5% type 1-DM, and 26.8% type 2-DM; 26.3% female) and 167,285 NSTEMIs (61.6% non-diabetic, 0.6% type 1-DM, and 37.8% type 2-DM; 30.9% female). In STEMI, the frequency of percutaneous coronary intervention (PCI) increased among non-diabetic people (60.4% vs. 68.6%; p < 0.001) and people with type 2-DM (53.6% vs. 66.1%; p < 0.001). In NSTEMI, the frequency of PCI increased among non-diabetic people (43.7% vs. 45.7%; p < 0.001) and people with type 2-DM (39.1% vs. 42.8%; p < 0.001). In NSTEMI, the frequency of coronary artery by-pass grafting (CABG) increased among non-diabetic people (2.8% vs. 3.5%; p < 0.001) and people with type 2-DM (3.7% vs. 5.0%; p < 0.001). In the entire population, lower IHM was associated with undergoing PCI (odds ratio [OR] [95% confidence interval] = 0.34 [0.32–0.35] in STEMI; 0.24 [0.23–0.26] in NSTEMI) or CABG (0.33 [0.27–0.40] in STEMI; 0.45 [0.38–0.53] in NSTEMI). IHM decreased over time in STEMI (OR = 0.86 [0.80–0.93]). Type 2-DM was associated with higher IHM in STEMI (OR = 1.06 [1.01–1.11]).ConclusionsPCI and CABG were associated with lower IHM in people admitted for STEMI/NSTEMI. Type 2-DM was associated with IHM in STEMI.

US Real-World Effectiveness Study of Nirmatrelvir/Ritonavir in Preventing Hospitalization of High-Risk COVID-19 Patients

PurposeWe describe nirmatrelvir/ritonavir (NMV/r) effectiveness in preventing hospitalization among COVID-19 patients at high risk of severe disease. MethodsAn ongoing US population-based observational cohort study with retrospective and prospective collection of national electronic healthcare data collected from the US Optum® deidentified COVID-19 Electronic Health Record dataset during December 22, 2021−July 20, 2022. Participants were ≥12 years old; had a positive SARS-CoV-2 test, COVID-19 diagnosis, or NMV/r prescription; and were at high risk of severe COVID-19 based on demographic/clinical characteristics. Potential confounders between groups were balanced using propensity score matching. Immortal time bias was addressed. Hospitalization rates within 30 days from COVID-19 diagnosis were evaluated. Sensitivity analyses included 15-day hospitalization, chart review to investigate incidental hospitalization effects, and exclusion of patients identified as having COVID-19 based on NMV/r prescription alone. Outcomes were also evaluated by race, age, and COVID-19 vaccine status. FindingsOverall, 12,440 and 234,123 patients were included in the NMV/r and non-NMV/r groups, respectively. After propensity score matching, baseline characteristics were well balanced across groups (NMV/r, n = 12,439; non-NMV/r, n = 36,490). Incidence of hospitalization (95% CI) within 30 days was 0.90% (0.74%−1.08%) for the NMV/r group and 5.91% (5.67%−6.16%) for the non-NMV/r group, with relative risk (95% CI) of 0.15 (0.13−0.18; 85% risk reduction). NMV/r was comparably effective in Black patients (relative risk, 0.19 [0.10−0.34]; 81% risk reduction). Sensitivity analyses supported the main outcomes. ImplicationsReal-world NMV/r effectiveness against hospitalization during Omicron predominance among COVID-19 patients at high risk of severe disease supports demonstrated clinical trial efficacy. Black patients underutilized NMV/r despite high effectiveness.

A national Australian Congenital Heart Disease registry; methods and initial results

BackgroundAlthough several National Data Registries for Congenital Heart Disease (CHD) exist, few are comprehensive and contemporary. A National Australian CHD Registry has been developed that aims to redress this by creating the first comprehensive data collection for CHD children and adults, initially across Australia. MethodsWe defined and collected a minimum dataset of demographics, diagnoses, and procedures from people with CHD presenting at participating quaternary CHD services Australia-wide. Data were collected from a range of clinical data sources. Diagnoses and procedures were standardised to the European Paediatric Congenital Code – Short List. Methodological limitations were carefully documented. ResultsFrom 8 participating institutions, an initial 359,084 patient records were assessed for eligibility and 68,234 unique individuals with structural CHD have been included in the current dataset. There were 20,395 (30 %) people with mild CHD, 25,157 (37 %) with moderate CHD, and 13,530 (20 %) with severe CHD (6 % unknown complexity). The most common diagnoses were Ventricular Septal Defect (16,781, 25 %), Atrial Septal Defect (6,607, 10 %), Aortic Valve Disorders (5516 8 %), Coarctation of the Aorta (5,321, 8 %), Tetralogy of Fallot (4,489, 7 %), Transposition of the Great Arteries (4,009, 6 %). ConclusionThe data presented here represents the most comprehensive cohort collected for the Australian CHD population thus far and is comparable with the largest contemporary CHD registries around the world. This Registry represents a key resource for improved understanding of the CHD population and will drive better care and outcomes for people living with CHD.

Colorectal cancer mortality trend analysis in Montenegro from 1990 to 2018.

Colorectal cancer (CRC) is the second leading cause of cancer-related death in Europe. This study aimed to investigate CRC mortality trends in Montenegro from 1990 to 2018 and critically review the impact of preventive activities on cancer suppression in this country. We used the national CRC mortality data categorized by sex and age. Mortality rates were age-standardized according to the World Standard Population. The trends were described using regression techniques. In the period from 1990 to 2018, there was a significant increase in CRC mortality (P < .05). The death rates and the number of deaths from CRC were constantly increasing for both the overall level and gender, with the mean annual percentage change for the rates respectively average annual percent change (95% confidence interval-CI): 2.6% (1.9-3.2), 2.6% (1.8-3.5); 2.3% (1.3-3.3), and for the number of cases, respectively: 4.2% (3.5-4.9), 4.3% (3.3-5.3), 4.3% (3.2-5.5). The most affected age groups were 65 to 74 years (33%), followed by those aged 75 to 84 years (25%) and the age group 55 to 64 (22%). In Montenegro, CRC mortality trends are increasing among both men and women over the age of 45. Additional research on the risk factors and mechanisms that contribute to the unfavorable trends in CRC mortality in Montenegro is necessary.

Assessing olaparib efficacy in U.S. Veterans with metastatic prostate cancer utilizing a time-indifferent g-rate method ideal for real-world analyses

We aimed to assess real-world efficacy of the PARP inhibitor, olaparib, in US Veterans with metastatic prostate cancer (mPC) by leveraging the national data repository and evaluate a novel approach to assess treatment efficacy in tumors considered rare or harboring rare mutations. Included Veterans had 1) mPC with somatic or germline alterations/mutations in genes involved in homologous recombination repair (HRR), 2) received olaparib monotherapy as well as a novel hormonal therapy/androgen receptor pathway inhibitors (NHT/ARPI), and/or chemotherapy, and 3) estimable rates of tumor growth (g-rate) using PSA values obtained while receiving treatment. Previous work has shown an excellent inverse correlation of g-rate with survival. Using g-rate, we determined tumor doubling time (DT) and DT ratios (DT on olaparib/DT on prior medication). We postulated that a DT ratio≥ 1 was associated with benefit. We identified 139 Veterans, including 42 Black males with tumors harboring mutations/alterations in HRR genes who received olaparib: BRCA2 (50), ATM (32), BRCA1 (10), other mutations (47). 62/139 (45%) of all and 21/42 (50%) of Black Veterans had DT ratios ≥1, including 31, 10, 2, and 19 with BRCA2, ATM, BRCA1, and other mutations, respectively (p=0.006). Median survival with DT ratios ≥1 was superior, being 24.5 vs. 11.4 months for DT ratio <1 (p=0.01, HR 0.50, 95% CI 0.29-0.85). Benefit from olaparib, defined as DT ratio ≥1, was not observed for germline status, starting PSA value, number of prior therapies, or immediate prior therapy. Compared to matched cohorts, tumors in the olaparib cohort had shorter DTs with enzalutamide in first line (367 vs. 884 days; p=0.0043). Using equations indifferent to timing of assessments ideal for real-world efficacy analyses, we showed DT ratio ≥1 representing slower tumor growth on olaparib relative to the prior therapy correlates with improved survival. Olaparib efficacy in Veterans with mPC harboring mutations/alterations in HRR genes emulates clinical trial results. Black men had comparable results. Compared to matched cohorts, in first line, enzalutamide was less efficacious in tumors harboring mutations/alterations in HRR genes. American Society of Clinical Oncology Conquer Cancer Foundation (ASCO CCF), the Blavatnik Family Foundation and the Prostate Cancer Foundation (PCF).