The Design of GNSS/IMU Loosely-Coupled Integration Filter for Wearable EPTS of Football Players.

This study presents the filter design of GNSS/IMU integration for wearable EPTS (Electronic Performance and Tracking System) of football players. EPTS has been widely used in sports fields recently, and GNSS (Global Navigation Satellite System) and IMU (Inertial Measurement Unit) in wearable EPTS have been used to measure and provide players' athletic performance data. A sensor fusion technique can be used to provide high-quality analysis data of athletic performance. For this reason, the integration filter of GNSS data and IMU data is designed in this study. The loosely-coupled strategy is considered to integrate GNSS and IMU data considering the specification of the wearable EPTS product. Quaternion is used to estimate a player's attitude to avoid the gimbal lock singularity in this study. Experiment results validate the performance of the proposed GNSS/IMU loosely-coupled integration filter for wearable EPTS of football players.

Traditional risk factors and premature acute coronary syndromes in South Eastern Europe: a multinational cohort study.

Background: The age-standardized death rates under 65 years from ischemic heart disease in South Eastern Europe are approximately twice as high than the Western Europe average, but the reasons are not completely recognized. The aim of the present study was to address this issue by collecting and analyzing data from a large, multinational cohort. Methods: We enrolled 70,953 Caucasian patients with first acute coronary syndrome, from 36 urban hospital in 7 South Eastern European countries and assessed their life expectancy free of acute coronary syndrome and mortality within 30 days after hospital admission from acute coronary syndrome as estimated in relation to dichotomous categories of traditional risk factors (current smoking, hypertension, diabetes and hypercholesterolemia) stratified according to sex. Findings: Compared with patients without any baseline traditional risk factors, the presence of all four risk factors was associated with a 5-year shorter life expectancy free of acute coronary syndrome (women: from 67.1 ± 12.0 to 61.9 ± 10.3 years; r = -0.089; p < 0.001 and men: from 62.8 ± 12.2 to 58.9 ± 9.9 years; r = -0.096; p < 0.001). Premature acute coronary syndrome (women <67 years and men <63 years) was remarkably related to current smoking and hypercholesterolemia among women (RRs: 3.96; 95% CI: 3.72-4.20 and 1.31; 95% CI: 1.25-1.38, respectively) and men (RRs: 2.82; 95% CI: 2.71-2.93 and 1.39; 95% CI: 1.34-1.45, respectively). Diabetes was most strongly associated with death from premature acute coronary syndrome either in women (RR: 1.52; 95% CI: 1.29-1.79) or men (RR: 1.63; 95% CI: 1.41-1.89). Interpretation: Public health policies in South Eastern Europe should place significant emphasis on the four traditional risk factors and the associated lifestyle behaviors to reduce the epidemic of premature ischemic heart disease. Funding: None.

Coronary revascularization and sex differences in cardiovascular mortality after myocardial infarction in 12 high and middle-income European countries.

BACKGROUND: Existing data on female sex and excess cardiovascular mortality after myocardial infarction (MI) mostly come from high-income countries (HICs). This study aimed to investigate how sex disparities in treatments and outcomes vary across countries with different income levels. METHODS: Data from the ISACS-Archives registry included 22 087 MI patients from 6 HICs and 6 middle-income countries (MICs). MI data were disaggregated by clinical presentation: ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI). The primary outcome was 30-day mortality. RESULTS: Among STEMI patients, women in MICs had nearly double the 30-day mortality rate of men (12.4% versus 5.8%; adjusted risk ratio [RR] 2.30, 95% CI 1.98-2.68). This difference was less pronounced in HICs (6.8% versus 5.1%; RR 1.36, 95% CI 1.05-1.75). Despite more frequent treatments and timely revascularization in MICs, sex-based mortality differences persisted even after revascularization (8.0% versus 4.1%; RR 2.05, 95% CI, 1.68-2.50 in MICs and 5.6% versus 2.6%; RR 2.17, 95% CI 1.48-3.18) in HICs. Additionally, women from MICs had higher diabetes rates compared to HICs (31.8% versus 25.1%, standardized difference = 0.15). NSTEMI outcomes were relatively similar between sexes and income groups. CONCLUSIONS: Sex disparities in mortality rates following STEMI are more pronounced in MICs compared to HICs. These disparities cannot be solely attributed to sex-related inequities in revascularization. Variations in mortality may also be influenced by sex differences in socioeconomic factors and baseline comorbidities.

Early coronary revascularization among "stable" patients with non-ST-segment elevation acute coronary syndromes: the role of diabetes and age.

AIMS: To investigate the impact of an early coronary revascularization (<24 hours) compared with initial conservative strategy on clinical outcomes in diabetic patients with non-ST elevation acute coronary syndrome (NSTE-ACS) who are in stable condition at hospital admission. METHODS AND RESULTS: The ISACS-TC database was queried for a sample of diabetic and nondiabetic patients with diagnosis of NSTE-ACS. Patients with cardiac arrest, hemodynamic instability, and serious ventricular arrhythmias were excluded. The characteristics between groups were adjusted using logistic regression and inverse probability of treatment weighting models. Primary outcome measure was all cause 30-day mortality. Risk ratios (RRs) and odds ratios (ORs) with their 95% CIs were employed. Of the 7,589 NSTE-ACS patients identified, 2,343 were diabetics. The data show a notable reduction in mortality for the elderly (> 65 years) undergoing early revascularization compared to those receiving an initial conservative strategy both in the diabetic (3.3% versus 6.7%; RR: 0.48; 95% CI: 0.28-0.80) and nondiabetic patients (2.7% versus 4.7%: RR: 0.57; 95% CI: 0.36-0.90). In multivariate analyses, diabetes was a strong independent predictor of mortality in the elderly (OR: 1.43; 95% CI: 1.03-1.99), but not in the younger patients OR: 1.04; 95% CI: 0.53-2.06). CONCLUSIONS: Early coronary revascularization does not lead to any survival advantage within 30 days from admission in young NSTE-ACS patients who present to hospital in stable conditions with and without diabetes. An early invasive management strategy may be best reserved for the elderly. Factors beyond revascularization are of considerable importance for outcome in elderly diabetic subjects with NSTE-ACS. REGISTRATION: ClinicalTrials.gov: NCT01218776.

EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records.

Privacy concerns often arise as the key bottleneck for the sharing of data between consumers and data holders, particularly for sensitive data such as Electronic Health Records (EHR). This impedes the application of data analytics and ML-based innovations with tremendous potential. One promising approach for such privacy concerns is to instead use synthetic data. We propose a generative modeling framework, EHR-Safe, for generating highly realistic and privacy-preserving synthetic EHR data. EHR-Safe is based on a two-stage model that consists of sequential encoder-decoder networks and generative adversarial networks. Our innovations focus on the key challenging aspects of real-world EHR data: heterogeneity, sparsity, coexistence of numerical and categorical features with distinct characteristics, and time-varying features with highly-varying sequence lengths. Under numerous evaluations, we demonstrate that the fidelity of EHR-Safe is almost-identical with real data (<3% accuracy difference for the models trained on them) while yielding almost-ideal performance in practical privacy metrics.

Sex Differences in Heart Failure Following Acute Coronary Syndromes.

Background: There have been conflicting reports regarding outcomes in women presenting with an acute coronary syndrome (ACS). Objectives: The objective of the study was to examine sex-specific differences in 30-day mortality in patients with ACS and acute heart failure (HF) at the time of presentation. Methods: This was a retrospective study of patients included in the International Survey of Acute Coronary Syndromes-ARCHIVES (ISACS-ARCHIVES; NCT04008173). Acute HF was defined as Killip classes ≥2. Participants were stratified according to ACS presentation: ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation ACS (NSTE-ACS). Differences in 30-day mortality and acute HF presentation at admission between sexes were examined using inverse propensity weighting based on the propensity score. Estimates were compared by test of interaction on the log scale. Results: A total of 87,812 patients were included, of whom 30,922 (35.2%) were women. Mortality was higher in women compared with men in those presenting with STEMI (risk ratio [RR]: 1.65; 95% CI: 1.56-1.73) and NSTE-ACS (RR: 1.18; 95% CI: 1.09-1.28; P interaction <0.001). Acute HF was more common in women when compared to men with STEMI (RR: 1.24; 95% CI: 1.20-1.29) but not in those with NSTE-ACS (RR: 1.02; 95% CI: 0.97-1.08) (P interaction <0.001). The presence of acute HF increased the risk of mortality for both sexes (odds ratio: 6.60; 95% CI: 6.25-6.98). Conclusions: In patients presenting with ACS, mortality is higher in women. The presence of acute HF at hospital presentation increases the risk of mortality in both sexes. Women with STEMI are more likely to present with acute HF and this may, in part, explain sex differences in mortality. These findings may be helpful to improve sex-specific personalized risk stratification.

Relationship Between Azithromycin and Cardiovascular Outcomes in Unvaccinated Patients With COVID-19 and Preexisting Cardiovascular Disease.

Background Empiric antimicrobial therapy with azithromycin is highly used in patients admitted to the hospital with COVID-19, despite prior research suggesting that azithromycin may be associated with increased risk of cardiovascular events. Methods and Results This study was conducted using data from the ISACS-COVID-19 (International Survey of Acute Coronavirus Syndromes-COVID-19) registry. Patients with a confirmed diagnosis of SARS-CoV-2 infection were eligible for inclusion. The study included 793 patients exposed to azithromycin within 24 hours from hospital admission and 2141 patients who received only standard care. The primary exposure was cardiovascular disease (CVD). Main outcome measures were 30-day mortality and acute heart failure (AHF). Among 2934 patients, 1066 (36.4%) had preexisting CVD. A total of 617 (21.0%) died, and 253 (8.6%) had AHF. Azithromycin therapy was consistently associated with an increased risk of AHF in patients with preexisting CVD (risk ratio [RR], 1.48 [95% CI, 1.06-2.06]). Receiving azithromycin versus standard care was not significantly associated with death (RR, 0.94 [95% CI, 0.69-1.28]). By contrast, we found significantly reduced odds of death (RR, 0.57 [95% CI, 0.42-0.79]) and no significant increase in AHF (RR, 1.23 [95% CI, 0.75-2.04]) in patients without prior CVD. The relative risks of death from the 2 subgroups were significantly different from each other (Pinteraction=0.01). Statistically significant association was observed between AHF and death (odds ratio, 2.28 [95% CI, 1.34-3.90]). Conclusions These findings suggest that azithromycin use in patients with COVID-19 and prior history of CVD is significantly associated with an increased risk of AHF and all-cause 30-day mortality. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT05188612.

Sex differences and disparities in cardiovascular outcomes of COVID-19.

AIMS: Previous analyses on sex differences in case fatality rates at population-level data had limited adjustment for key patient clinical characteristics thought to be associated with coronavirus disease 2019 (COVID-19) outcomes. We aimed to estimate the risk of specific organ dysfunctions and mortality in women and men. METHODS AND RESULTS: This retrospective cross-sectional study included 17 hospitals within 5 European countries participating in the International Survey of Acute Coronavirus Syndromes COVID-19 (NCT05188612). Participants were individuals hospitalized with positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from March 2020 to February 2022. Risk-adjusted ratios (RRs) of in-hospital mortality, acute respiratory failure (ARF), acute heart failure (AHF), and acute kidney injury (AKI) were calculated for women vs. men. Estimates were evaluated by inverse probability weighting and logistic regression models. The overall care cohort included 4499 patients with COVID-19-associated hospitalizations. Of these, 1524 (33.9%) were admitted to intensive care unit (ICU), and 1117 (24.8%) died during hospitalization. Compared with men, women were less likely to be admitted to ICU [RR: 0.80; 95% confidence interval (CI): 0.71-0.91]. In general wards (GWs) and ICU cohorts, the adjusted women-to-men RRs for in-hospital mortality were of 1.13 (95% CI: 0.90-1.42) and 0.86 (95% CI: 0.70-1.05; pinteraction = 0.04). Development of AHF, AKI, and ARF was associated with increased mortality risk (odds ratios: 2.27, 95% CI: 1.73-2.98; 3.85, 95% CI: 3.21-4.63; and 3.95, 95% CI: 3.04-5.14, respectively). The adjusted RRs for AKI and ARF were comparable among women and men regardless of intensity of care. In contrast, female sex was associated with higher odds for AHF in GW, but not in ICU (RRs: 1.25; 95% CI: 0.94-1.67 vs. 0.83; 95% CI: 0.59-1.16, pinteraction = 0.04). CONCLUSIONS: Women in GW were at increased risk of AHF and in-hospital mortality for COVID-19 compared with men. For patients receiving ICU care, fatal complications including AHF and mortality appeared to be independent of sex. Equitable access to COVID-19 ICU care is needed to minimize the unfavourable outcome of women presenting with COVID-19-related complications.

Algorithmic fairness in pandemic forecasting: lessons from COVID-19.

Racial and ethnic minorities have borne a particularly acute burden of the COVID-19 pandemic in the United States. There is a growing awareness from both researchers and public health leaders of the critical need to ensure fairness in forecast results. Without careful and deliberate bias mitigation, inequities embedded in data can be transferred to model predictions, perpetuating disparities, and exacerbating the disproportionate harms of the COVID-19 pandemic. These biases in data and forecasts can be viewed through both statistical and sociological lenses, and the challenges of both building hierarchical models with limited data availability and drawing on data that reflects structural inequities must be confronted. We present an outline of key modeling domains in which unfairness may be introduced and draw on our experience building and testing the Google-Harvard COVID-19 Public Forecasting model to illustrate these challenges and offer strategies to address them. While targeted toward pandemic forecasting, these domains of potentially biased modeling and concurrent approaches to pursuing fairness present important considerations for equitable machine-learning innovation.

Concerns about the use of digoxin in acute coronary syndromes.

AIMS: The use of digitalis has been plagued by controversy since its initial use. We aimed to determine the relationship between digoxin use and outcomes in hospitalized patients with acute coronary syndromes (ACSs) complicated by heart failure (HF) accounting for sex difference and prior heart diseases. METHODS AND RESULTS: Of the 25 187 patients presenting with acute HF (Killip class ≥2) in the International Survey of Acute Coronary Syndromes Archives (NCT04008173) registry, 4722 (18.7%) received digoxin on hospital admission. The main outcome measure was all-cause 30-day mortality. Estimates were evaluated by inverse probability of treatment weighting models. Women who received digoxin had a higher rate of death than women who did not receive it [33.8% vs. 29.2%; relative risk (RR) ratio: 1.24; 95% confidence interval (CI): 1.12-1.37]. Similar odds for mortality with digoxin were observed in men (28.5% vs. 24.9%; RR ratio: 1.20; 95% CI: 1.10-1.32). Comparable results were obtained in patients with no prior coronary heart disease (RR ratio: 1.26; 95% CI: 1.10-1.45 in women and RR ratio: 1.21; 95% CI: 1.06-1.39 in men) and those in sinus rhythm at admission (RR ratio: 1.34; 95% CI: 1.15-1.54 in women and RR ratio: 1.26; 95% CI: 1.10-1.45 in men). CONCLUSION: Digoxin therapy is associated with an increased risk of early death among women and men with ACS complicated by HF. This finding highlights the need for re-examination of digoxin use in the clinical setting of ACS.

Reduced Heart Failure and Mortality in Patients Receiving Statin Therapy Before Initial Acute Coronary Syndrome.

BACKGROUND: There is uncertainty regarding the impact of statins on the risk of atherosclerotic cardiovascular disease (ASCVD) and its major complication, acute heart failure (AHF). OBJECTIVES: The aim of this study was to investigate whether previous statin therapy translates into lower AHF events and improved survival from AHF among patients presenting with an acute coronary syndrome (ACS) as a first manifestation of ASCVD. METHODS: Data were drawn from the International Survey of Acute Coronary Syndromes Archives. The study participants consisted of 14,542 Caucasian patients presenting with ACS without previous ASCVD events. Statin users before the index event were compared with nonusers by using inverse probability weighting models. Estimates were compared by test of interaction on the log scale. Main outcome measures were the incidence of AHF according to Killip class and the rate of 30-day all-cause mortality in patients presenting with AHF. RESULTS: Previous statin therapy was associated with a significantly decreased rate of AHF on admission (4.3% absolute risk reduction; risk ratio [RR]: 0.72; 95% CI: 0.62-0.83) regardless of younger (40-75 years) or older age (interaction P = 0.27) and sex (interaction P = 0.22). Moreover, previous statin therapy predicted a lower risk of 30-day mortality in the subset of patients presenting with AHF on admission (5.2 % absolute risk reduction; RR: 0.71; 95% CI: 0.50-0.99). CONCLUSIONS: Among adults presenting with ACS as a first manifestation of ASCVD, previous statin therapy is associated with a reduced risk of AHF and improved survival from AHF. (International Survey of Acute Coronary Syndromes [ISACS] Archives; NCT04008173).

Statins for primary prevention among elderly men and women.

AIMS: We undertook a propensity match-weighted cohort study to investigate whether statin treatment recommendations for statins translate into improved cardiovascular (CV) outcomes in the current routine clinical care of the elderly. METHODS AND RESULTS: We included in our analysis (ISACS Archives -NCT04008173) a total of 5619 Caucasian patients with no known prior history of CV disease who presented to hospital with a first manifestation of CV disease with age of 65 years or older. The risk of ST-segment elevation myocardial infarction (STEMI) was much lower in statin users than in non-users in both patients aged 65-75 years [14.7% absolute risk reduction; relative risk (RR): 0.55, 95% CI 0.45-0.66] and those aged 76 years and older (13.3% absolute risk reduction; RR: 0.58, 95% CI 0.46-0.72). Estimates were similar in patients with and without history of hypercholesterolaemia (interaction test; P-values = 0.24 and 0.35). Proportional reductions in STEMI diminished with female sex in the old (P for interaction = 0.002), but not in the very old age (P for interaction = 0.26). We also observed a remarkable reduction in the risk of 30 day mortality from STEMI with statin therapy in both age groups (10.2% absolute risk reduction; RR: 0.39; 95% CI 0.23-0.68 for patients aged 76 or over and 3.8% absolute risk reduction; RR 0.37; 95% CI 0.17-0.82 for patients aged 65-75 years old; interaction test, P-value = 0.46). CONCLUSIONS: Preventive statin therapy in the elderly reduces the risk of STEMI with benefits in mortality from STEMI, irrespective of the presence of a history of hypercholesterolaemia. This effect persists after the age of 76 years. Benefits are less pronounced in women. Randomized clinical trials may contribute to more definitively determine the role of statin therapy in the elderly.

Smoking and sex differences in first manifestation of cardiovascular disease.

BACKGROUND AND AIMS: An increasing proportion of women believe that smoking few cigarettes daily substantially reduces their risk of developing cardiovascular (CV) related disorders. The effect of low intensity smoking is still largely understudied. We investigated the relation among sex, age, cigarette smoking and ST segment elevation myocardial infarction (STEMI) as initial manifestation of CV disease. METHODS: We analyzed data of 50,713 acute coronary syndrome patients with no prior manifestation of CV disease from the ISACS-Archives (NCT04008173) registry. We compared the rates of STEMI in current smokers (n = 11,530) versus nonsmokers (n = 39,183). RESULTS: In the young middle age group (<60 years), there was evidence of a more harmful effect in women compared with men (RR ratios: 1.90; 95% CI: 1.69-2.14 versus 1.68; 95% CI: 1.56-1.80). This association persisted even in women who smoked 1 to 10 packs per year (RR ratios: 2.02; 95% CI: 1.65 to 2.48 versus 1.38; 95% CI: 1.22 to 1.57). In the older group, rates of STEMI were similar for women and men (RR ratios: 1.36; 95% CI: 1.22-1.53 versus 1.39; 95% CI: 1.28-1.50). STEMI was associated with a twofold higher 30-day mortality rate in young middle age women compared with men of the same age (odds ratios, 5.54; 95% CI, 3.83-8.03 vs. 2.93; 95% CI, 2.33-3.69). CONCLUSIONS: Low intensity smoking provides inadequate protection in young - middle age women as they still have a substantially higher rate of STEMI and related mortality compared with men even smoking less than 10 packs per year. This finding is worrying as more young - middle age women are smoking, and rates of smoking among young-middle age men continue to fall.

A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan.

The COVID-19 pandemic has highlighted the global need for reliable models of disease spread. We propose an AI-augmented forecast modeling framework that provides daily predictions of the expected number of confirmed COVID-19 deaths, cases, and hospitalizations during the following 4 weeks. We present an international, prospective evaluation of our models' performance across all states and counties in the USA and prefectures in Japan. Nationally, incident mean absolute percentage error (MAPE) for predicting COVID-19 associated deaths during prospective deployment remained consistently <8% (US) and <29% (Japan), while cumulative MAPE remained <2% (US) and <10% (Japan). We show that our models perform well even during periods of considerable change in population behavior, and are robust to demographic differences across different geographic locations. We further demonstrate that our framework provides meaningful explanatory insights with the models accurately adapting to local and national policy interventions. Our framework enables counterfactual simulations, which indicate continuing Non-Pharmaceutical Interventions alongside vaccinations is essential for faster recovery from the pandemic, delaying the application of interventions has a detrimental effect, and allow exploration of the consequences of different vaccination strategies. The COVID-19 pandemic remains a global emergency. In the face of substantial challenges ahead, the approach presented here has the potential to inform critical decisions.

Dynamic Prediction in Clinical Survival Analysis Using Temporal Convolutional Networks.

Accurate prediction of disease trajectories is critical for early identification and timely treatment of patients at risk. Conventional methods in survival analysis are often constrained by strong parametric assumptions and limited in their ability to learn from high-dimensional data. This paper develops a novel convolutional approach that addresses the drawbacks of both traditional statistical approaches as well as recent neural network models for survival. We present Match-Net: a missingness-aware temporal convolutional hitting-time network, designed to capture temporal dependencies and heterogeneous interactions in covariate trajectories and patterns of missingness. To the best of our knowledge, this is the first investigation of temporal convolutions in the context of dynamic prediction for personalized risk prognosis. Using real-world data from the Alzheimer's disease neuroimaging initiative, we demonstrate state-of-the-art performance without making any assumptions regarding underlying longitudinal or time-to-event processes-attesting to the model's potential utility in clinical decision support.

Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data.

Currently available risk prediction methods are limited in their ability to deal with complex, heterogeneous, and longitudinal data such as that available in primary care records, or in their ability to deal with multiple competing risks. This paper develops a novel deep learning approach that is able to successfully address current limitations of standard statistical approaches such as landmarking and joint modeling. Our approach, which we call Dynamic-DeepHit, flexibly incorporates the available longitudinal data comprising various repeated measurements (rather than only the last available measurements) in order to issue dynamically updated survival predictions for one or multiple competing risk(s). Dynamic-DeepHit learns the time-to-event distributions without the need to make any assumptions about the underlying stochastic models for the longitudinal and the time-to-event processes. Thus, unlike existing works in statistics, our method is able to learn data-driven associations between the longitudinal data and the various associated risks without underlying model specifications. We demonstrate the power of our approach by applying it to a real-world longitudinal dataset from the U.K. Cystic Fibrosis Registry, which includes a heterogeneous cohort of 5883 adult patients with annual follow-ups between 2009 to 2015. The results show that Dynamic-DeepHit provides a drastic improvement in discriminating individual risks of different forms of failures due to cystic fibrosis. Furthermore, our analysis utilizes post-processing statistics that provide clinical insight by measuring the influence of each covariate on risk predictions and the temporal importance of longitudinal measurements, thereby enabling us to identify covariates that are influential for different competing risks.

Anonymization Through Data Synthesis Using Generative Adversarial Networks (ADS-GAN).

The medical and machine learning communities are relying on the promise of artificial intelligence (AI) to transform medicine through enabling more accurate decisions and personalized treatment. However, progress is slow. Legal and ethical issues around unconsented patient data and privacy is one of the limiting factors in data sharing, resulting in a significant barrier in accessing routinely collected electronic health records (EHR) by the machine learning community. We propose a novel framework for generating synthetic data that closely approximates the joint distribution of variables in an original EHR dataset, providing a readily accessible, legally and ethically appropriate solution to support more open data sharing, enabling the development of AI solutions. In order to address issues around lack of clarity in defining sufficient anonymization, we created a quantifiable, mathematical definition for "identifiability". We used a conditional generative adversarial networks (GAN) framework to generate synthetic data while minimize patient identifiability that is defined based on the probability of re-identification given the combination of all data on any individual patient. We compared models fitted to our synthetically generated data to those fitted to the real data across four independent datasets to evaluate similarity in model performance, while assessing the extent to which original observations can be identified from the synthetic data. Our model, ADS-GAN, consistently outperformed state-of-the-art methods, and demonstrated reliability in the joint distributions. We propose that this method could be used to develop datasets that can be made publicly available while considerably lowering the risk of breaching patient confidentiality.

Prior Beta-Blocker Therapy for Hypertension and Sex-Based Differences in Heart Failure Among Patients With Incident Coronary Heart Disease.

The usefulness of ß-blockers has been questioned for patients who have hypertension without a prior manifestation of coronary heart disease or heart failure. In addition, sex-based differences in the efficacy of ß-blockers for prevention of heart failure during acute myocardial ischemia have never been evaluated. We explored whether the effect of ß-blocker therapy varied according to the sex among patients with hypertension who have no prior history of cardiovascular disease. Data were drawn from the ISACS (International Survey of Acute Coronary Syndromes)-Archives. The study population consisted of 13 764 patients presenting with acute coronary syndromes. There were 2590 patients in whom hypertension was treated previously with ß-blocker (954 women and 1636 men). Primary outcome measure was the incidence of heart failure according to Killip class classification. Subsidiary analyses were conducted to estimate the association between heart failure and all-cause mortality at 30 days. Outcome rates were assessed using the inverse probability of treatment weighting and logistic regression models. Estimates were compared by test of interaction on the log scale. Among patients taking ß-blockers before admission, there was an absolute difference of 4.6% between women and men in the rate of heart failure (Killip ≥2) at hospital presentation (21.3% versus 16.7%; relative risk ratio, 1.35 [95% CI, 1.10-1.65]). On the opposite, the rate of heart failure was approximately similar among women and men who did not receive ß-blockers (17.2% versus 16.1%; relative risk ratio, 1.09 [95% CI, 0.97-1.21]). The test of interaction identified a significant (P=0.034) association between sex and ß-blocker therapy. Heart failure was predictive of mortality at 30-day either in women (odds ratio, 7.54 [95% CI, 5.78-9.83]) or men (odds ratio, 9.62 [95% CI, 7.67-12.07]). In conclusion, ß-blockers use may be an acute precipitant of heart failure in new-onset coronary heart disease among women, but not men. Heart failure increases the risk of death. Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT04008173.

Aspirin for primary prevention of ST segment elevation myocardial infarction in persons with diabetes and multiple risk factors.

BACKGROUND: Controversy exists as to whether low-dose aspirin use may give benefit in primary prevention of cardiovascular (CV) events. We hypothesized that the benefits of aspirin are underevaluated. METHODS: We investigated 12,123 Caucasian patients presenting to hospital with acute coronary syndromes as first manifestation of CV disease from 2010 to 2019 in the ISACS-TC multicenter registry (ClinicalTrials.gov, NCT01218776). Individual risk of ST segment elevation myocardial infarction (STEMI) and its association with 30-day mortality was quantified using inverse probability of treatment weighting models matching for concomitant medications. Estimates were compared by test of interaction on the log scale. FINDINGS: The risk of STEMI was lower in the aspirin users (absolute reduction: 6·8%; OR: 0·73; 95%CI: 0·65-0·82) regardless of sex (p for interaction=0·1962) or age (p for interaction=0·1209). Benefits of aspirin were seen in patients with hypertension, hypercholesterolemia, and in smokers. In contrast, aspirin failed to demonstrate a significant risk reduction in STEMI among diabetic patients (OR:1·10;95%CI:0·89-1·35) with a significant interaction (p: <0·0001) when compared with controls (OR:0·64,95%CI:0·56-0·73). Stratification of diabetes in risk categories revealed benefits (p interaction=0·0864) only in patients with concomitant hypertension and hypercholesterolemia (OR:0·87, 95% CI:0·65-1·15), but not in smokers. STEMI was strongly related to 30-day mortality (OR:1·93; 95%CI:1·59-2·35). INTERPRETATION: Low-dose aspirin reduces the risk of STEMI as initial manifestation of CV disease with potential benefit in mortality. Patients with diabetes derive substantial benefit from aspirin only in the presence of multiple risk factors. In the era of precision medicine, a more tailored strategy is required. FUNDING: None.

Sex Differences in Modifiable Risk Factors and Severity of Coronary Artery Disease.

Background It is still unknown whether traditional risk factors may have a sex-specific impact on coronary artery disease (CAD) burden. Methods and Results We identified 14 793 patients who underwent coronary angiography for acute coronary syndromes in the ISACS-TC (International Survey of Acute Coronary Syndromes in Transitional Countries; Clini​calTr​ials.gov, NCT01218776) registry from 2010 to 2019. The main outcome measure was the association between traditional risk factors and severity of CAD and its relationship with 30-day mortality. Relative risk (RR) ratios and 95% CIs were calculated from the ratio of the absolute risks of women versus men using inverse probability of weighting. Estimates were compared by test of interaction on the log scale. Severity of CAD was categorized as obstructive (≥50% stenosis) versus nonobstructive CAD. The RR ratio for obstructive CAD in women versus men among people without diabetes mellitus was 0.49 (95% CI, 0.41-0.60) and among those with diabetes mellitus was 0.89 (95% CI, 0.62-1.29), with an interaction by diabetes mellitus status of P =0.002. Exposure to smoking shifted the RR ratios from 0.50 (95% CI, 0.41-0.61) in nonsmokers to 0.75 (95% CI, 0.54-1.03) in current smokers, with an interaction by smoking status of P=0.018. There were no significant sex-related interactions with hypercholesterolemia and hypertension. Women with obstructive CAD had higher 30-day mortality rates than men (RR, 1.75; 95% CI, 1.48-2.07). No sex differences in mortality were observed in patients with nonobstructive CAD. Conclusions Obstructive CAD in women signifies a higher risk for mortality compared with men. Current smoking and diabetes mellitus disproportionally increase the risk of obstructive CAD in women. Achieving the goal of improving cardiovascular health in women still requires intensive efforts toward further implementation of lifestyle and treatment interventions. Registration URL: https://www.clini​caltr​ials.gov; Unique identifier: NCT01218776.