bluuebunny/crossref_metadata_2025_split huggingface dataset:
Longitudinal associations between accelerometry-assessed sleep clusters and obesity in adolescence and young adulthood: the German GINIplus and LISA birth cohorts study
Authors: Wang M , Flexeder C , Harris C , Kress S , Schikowski T , Peters A , Standl M 
Published: October 2024

Abstract

Background
Some studies have identified diverse sleep patterns in adolescents and adults by considering multidimensional objective sleep parameters. However, whether sleep patterns are consistent from adolescence to young adulthood and their long-term associations with obesity remain unknown.

Purpose
This study aimed to investigate the longitudinal associations of objectively measured and clustering-identified sleep patterns with body mass index (BMI) and overweight/obesity in adolescence and young adulthood, and to test whether these associations change over time or are modified by genetic risk.

Methods
A total of 1973 participants wearing 7-day accelerometers in either 15-year (n=1347, aged 14.3-16.4 years) and/or 20-year (n=1262, aged 19.5-22.4 years) follow-ups of German GINIplus and LISA birth cohorts were included. Sleep clusters were identified by K-means cluster analysis on 12 accelerometry-assessed sleep characteristics at each follow-up. BMI and overweight/obesity were measured by physical exams or self-/parent-reported questionnaires. Multivariable linear and logistic regression models with generalized estimating equations were tested. The interaction effects with time of follow-ups and polygenic risk scores (PRS, n=1087) for BMI were further examined.

Results
Although sleep characteristics changed from adolescence to young adulthood, such as shorter total sleep time (mean 7.2 to 6.6 hours), the consistent five sleep clusters were classified in both periods: good sleep, delayed sleep phase, sleep irregularity and variability, fragmented sleep, and prolonged sleep latency. Compared to the "good sleep" cluster, the "prolonged sleep latency" cluster showed significant associations with higher BMI (β=0.56, 95% confidence interval (CI) = [0.06, 1.05]) and increased odds of overweight/obesity (odds ratio (OR)=1.55, 95%CI= [1.02, 2.34]). PRS was associated with higher BMI (β=0.65, 95%CI= [0.39, 0.91]) and overweight/obesity (OR=1.52, 95%CI= [1.15, 2.00]), with no significant gene-sleep cluster interaction effect. Only among males, the interaction effects with time of follow-ups on overweight/obesity were observed in the "delayed sleep phase", "sleep irregularity and variability", and "fragmented sleep" clusters (p-interaction &lt;0.05), showing more harmful effects with increasing age.

Conclusions
Five sleep patterns were identified consistently across adolescence and young adulthood, and the "prolonged sleep latency" pattern was associated with higher BMI and overweight/obesity, independent of genetic risk. For young adult males, "delayed sleep phase", "sleep irregularity and variability" and "fragmented sleep" patterns seemed to have more unfavorable impacts on overweight/obesity.
Association of COVID-19 and influenza vaccinations and cardiovascular drugs with hospitalisation and mortality in COVID-19 and Long COVID: 2-year follow-up of 17 million individuals in England
Authors: Dashtban A , Mizani M , Rafferty S , Pasea L , Tomlinson C , Mu Y , Islam N , Warren-Gash C , Denaxas S , Petersen S , Sudlow C , Khunti K , Banerjee A 
Published: October 2024

Abstract

Introduction
For COVID-19 and Long COVID, determining the highest-risk subgroups, particularly in the context of compound pressures such as influenza and cardiovascular disease (CVD), may identify effective interventions to prevent adverse health outcomes, and inform public health and policy decisions.

Methods
Using national, linked electronic health records for England (NHS England Secure Data Environment: via CVD-COVID-UK/COVID-IMPACT Consortium), we studied individuals with COVID-19 and Long COVID from January 2020 to February 2023. We compared all-cause hospitalisation and mortality in unmatched and matched cohort analyses, by prior CVD, high CVD risk (by QRISK2), COVID-19 and influenza vaccination status, and prescription of CVD preventive therapies. We investigated potential impact of targeted vaccination and CVD prevention strategies on mortality and hospitalisations by calculating population preventable fractions.

Results
We identified 17,373,850 individuals with COVID-19 [54.4% female; mean age 38.8 years; COVID-19 vaccination ≥2 doses:50.0%, influenza vaccination (≥1 dose):27.8%; mean follow-up 1.28 years] and 301,115 with Long Covid [61.8% female; mean age 46.0 years; COVID-19 vaccination ≥2 doses:66.4%, influenza vaccination:33.1%; mean follow-up 1.1 years]. Hospitalisation and mortality rates were 15.3% and 2.0% in COVID-19 (Long COVID rate 1.3%) and 16.8% and 1.4% in Long COVID, respectively. Adjusted risk of mortality and hospitalisation were reduced with COVID-19 vaccination ≥2 doses (COVID-19:HR 0.36, 95% CI 0.34-0.38 and 0.69, 0.68-0.69; Long COVID:0.44, 0.42-0.47 and 0.90, 0.89-0.91). With influenza vaccination, mortality was reduced, but not hospitalisation (COVID-19: 0.86, 0.85-0.86 and HR 1.01, 1.01-1.01, and Long COVID: 0.72, 0.67-0.76, and 1.05, 1.03-1.07), with greatest effect in those with prior CVD and high CVD risk. Mortality and hospitalisation were also reduced by CVD prevention in those with CVD, e.g. anticoagulants- COVID-19: 0.69, 0.69-0.70 and 0.92, 0.91-0.93; Long Covid: 0.59, 0.54-0.64, and 0.88, 0.84-0.92. COVID-19 vaccination, influenza vaccination and CVD drugs (Anticoagulants) averted 101117 of 193598, 2138 of 4017 and 16573 of 36847 preventable deaths among individuals after COVID-19, and 875 of 1189, 65 of 127 and 507 of 1007 preventable deaths among those with Long COVID, particularly in people with CVD.

Conclusions
Prior CVD and high CVD risk are associated with increased hospitalisation and mortality risk in people with COVID-19 and Long COVID. Targeted improvement in COVID-19 vaccination and CVD prevention, especially in those with CVD are priority interventions in pandemics to avoid excess hospitalisation and mortality.Baseline Characteristics and OutcomesHospitalisation/mortality by COVID vaccn
Genetic predisposition of metabolic syndrome independent of weight in premature atherosclerosis
Authors: Singh S , Crooijmans J , Baars D P , Zwinderman A H , Pinto-Sietsma S J 
Published: October 2024

Abstract

Background
Family history is a significant predictor of premature atherosclerotic cardiovascular events, which suggest that a genetic susceptibility underlies the development of premature atherosclerosis. Rather than the influence of single classic risk factors, such as hypertension, diabetes and dyslipidemia, these risk factors could be part of an underlying genetic insulin resistance or metabolic syndrome

Methods
Data on patients and their first degree family members visiting premature atherosclerosis clinic in a university medical centre, from 2007 until 2023 was analyzed. We divided them in controls (CACs=0 and Age &gt;40 years), subclinical ASCVD (sASCVD) (CAC score ≥80th percentile) and premature ASCVD (PAS). We used principal component analysis (PCA) for clustering the predictor variables and generalized linear mixed model (GLMM) to analyze the mutual relationship between different clusters. The model performance was further validated in predicting the premature ASCVD.

Result
There were 1551 individuals divided across control (n=438), sASCVD (n=309) and PAS (804). We found 12 variables univariate significantly related to sASCVD. Using a principal component analysis (PCA) approach, these variables were loaded across 4 clusters which were defined as 1. Metabolic (elevated glucose or diabetes, elevated blood pressure or Hypertension, elevated Triglycerides, elevated waist circumference and elevated LDL-C); 2. Liver (elevated ALAT, elevated GGT, elevated triglycerides, decreased thrombocytes) 3. Inflammatory (decreased HDL-C, elevated Triglycerides and elevated leucocyte count) and 4. Lipid (elevated Lp(a) and elevated LDL-C). After mutual correction and model building, the metabolic (OR; 95% CI) (1.82; 1.48-2.27) and Liver clusters (1.20; 1.00-1.45) were only found to be significantly associated with risk of sASCVD. However, we did not find any association of inflammatory (1.19; 0.98-1.44) and lipid cluster (1.19; 0.99-1.41) with risk of sASCVD. Besides, association of these clusters with risk of sASCVD significantly varies among families suggested from variance of intercept when family was kept as a random effect in GLMM model and no interaction was noticed with BMI. We checked the performance of this model on premature atherosclerosis cohort and found model had a good discriminatory (AUC, 0.762; 0.735-0.790; P=0.001) ability for predicting PAS [Figure 1].

Conclusion
In conclusion, our findings are suggestive of a significant association between metabolic syndrome factors and an increased risk of sASCVD in individuals with family history of premature atherosclerosis, regardless of weight. This association suggests the potential genetic predisposition towards premature atherosclerosis driving the observed metabolic parameters clustering in these individuals. Besides, the model demonstrated robust discriminatory power to predict premature atherosclerosis.ROC curve for premature atherosclerosis
Comparison of the predicting value for incident cardiovascular events by vascular age based on brachial-ankle pulse wave velocity or carotid-femoral pulse wave velocity
Authors: Dong D T , Fan F F , Chen C H , Dong D Z , Yang Y L , Luo L Y , Qiu Q Z , Fang F R , Zheng Z Q , Zhang Z X , Zhang Z Y 
Published: October 2024

Abstract

Background
There is a good correlation between brachial-ankle pulse wave velocity（baPWV）and carotid-femoral pulse wave velocity (cfPWV). Whether baPWV has the same predictability for cardiovascular risk as cfPWV in calculating vascular age remains to be clarified.

Purpose
This study examines which vascular age calculated by baPWV or cfPWV has a stronger association with the risk of cardiovascular events.

Methods
This prospective cohort study included 5725 participants from a community atherosclerosis cohort in Beijing, China. Vascular age was the predicted age in a multivariable regression model, including classical cardiovascular risk factors (sex, systolic and diastolic blood pressure, glycemia, triglyceride, low density lipoprotein cholesterol, waist, body mass index, heart rate, smoking) and treatment (anti-hypertensive agents, hypoglycemic agents, lipid-lowering agents) and pulse wave velocity. Residuals between chronological age and vascular age were defined as ∆-age, and the 10th and 90th percentiles of ∆-age were used as cutoffs to define supernormal vascular aging, normal vascular aging, and early vascular aging, respectively. The major adverse cardiovascular event was a composite of myocardial infarction, stroke, and cardiovascular death. The study used Cox proportional hazards regression to examine the association between vascular age and major adverse cardiovascular events.

Results
During the median 3-year follow-up period, 172 endpoint events were observed. After adjusting for age and sex, ∆-age as a continuous variable calculated by baPWV was significantly and increasingly associated with cardiovascular events (every 1-year increase led to a rise of 1.04% [95% confidence interval [CI]: 1.00%-1.08%; p=0.03] in cardiovascular events risk). After adjusting for age, sex, smoking, body mass index, hypertension, diabetes, dyslipidemia, anti-hypertensive agents, lipid-lowering agents, hypoglycemic agents, family history of atherosclerotic cardiovascular disease, and estimated glomerular filtration rate, early vascular aging group calculated by baPWV had an increased risk of cardiovascular events (hazard ratio: 1.76; 95% CI: 1.19-2.62 p=0.005), compared with the normal vascular aging group. In contrast, no significant results were observed in vascular age calculated by cfPWV.

Conclusion(s)
Vascular age calculated by baPWV has a stronger predictive ability for cardiovascular events than that calculated by cfPWV in the Chinese population. Considering baPWV is a simple and convenient method, it is recommended for vascular age calculation.
Cardiovascular disease risk in people with diabetes in the era of universal diabetes screening
Authors: Liang J , Jackson R , Wells S , Poppe K 
Published: October 2024

Abstract

Background/Introduction
Traditionally, most people with diabetes have been considered at high cardiovascular disease (CVD) risk and CVD preventive treatment has been recommended for almost all patients after diagnosis. However, guidelines are increasingly recommending a more stratified approach to preventive treatment informed by predicted CVD risk. In the early 2000’s, New Zealand initiated the world-first national diabetes screening programme, as a component of a national CVD risk assessment programme, and by 2016, approximately 90% of eligible New Zealand adults had been screened. We hypothesised that in the era of universal diabetes screening, many recently diagnosed patients will be at low CVD risk and that contemporary CVD risk prediction equations would be required to accurately assess their risk.

Purpose
We aimed to develop sex-specific 5-year CVD risk prediction models in people with diabetes in New Zealand using a contemporary natural-population based cohort, and to characterise the distribution of CVD risk.

Methods
De-identified individual-level linkage of multiple health administrative datasets was undertaken to establish a cohort of almost all adults with diabetes in the northern region of New Zealand (one-third of the national population), without CVD or heart failure, and aged 30–74 years on January 1, 2014, with follow-up linkage to hospitalisations and mortality until December 31, 2018. Sex-specific models were developed to estimate the 5-year risk of CVD hospitalisation or death, with 15 pre-defined predictors, including sociodemographic variables, diabetes-related and renal function measures.

Results
64,645 participants (median age: 57 years [IQR: 49–65]) were included in the final cohort, of whom 4,992 had first CVD events during 301,272 person-years follow-up. Models calibrated well in both women and men (Figure 1). Overall, increasing age; high deprivation level; smoking-related hospitalisations or use of smoking cessation medications; history of atrial fibrillation; high levels of haemoglobin A1c, total cholesterol to HDL cholesterol ratio, and albumin-to-creatinine ratio; use of blood pressure-lowering medications and insulin were associated with elevated CVD risk. Median 5-year CVD risks were 4.9% (IQR: 2.9%–8.1%) in women and 7.7% (4.8%–12.0%) in men. There was a wide range of predicted 5-year CVD risk, with 51% of women and 27% of men having a predicted risk below 5%, and 6% of women and 16% of men having a risk of 15% or above (Figure 2).

Conclusions
This study demonstrated marked heterogeneity in predicted CVD risk in people with diabetes in an era of universal diabetes screening. As diabetes screening is increasingly undertaken as part of a routine CVD risk assessment, these findings will have important clinical implications for accurately targeting new but expensive CVD preventive medications to the highest risk patients.
Prediction of 10-year risk for recurrent atherosclerotic cardiovascular events in a secondary prevention population: Insights from CHART-2 and Suita studies in the Japanese population
Authors: Oyama K , Kokubo Y , Nochioka K , Hamaya R , Shiroto T , Takahashi J , Miyamoto Y , Shimokawa H , Yasuda S 
Published: October 2024

Abstract

Background
Despite the European Society of Cardiology (ESC) guidelines advocating risk prediction models for secondary prevention in established atherosclerotic cardiovascular disease (ASCVD) patients, such models for Japanese individuals remain limited, owing to their comparatively lower ASCVD risk than Western populations. Given this gap, there is a need to develop tailored risk assessment tools for Japanese ASCVD patients to optimize secondary prevention strategies.

Purpose
Leveraging data from two large-scale, long-term cardiovascular cohorts in Japan, our aim was to develop and externally validate a 10-year risk model predicting recurrent cardiovascular events among patients with established ASCVD.

Methods
The CHART-2 and Suita studies, large-scale prospective observational multicenter cohort studies in Japan, served as the primary data sources for this investigation. From the CHART-2 study, which comprised 3,560 patients with a history of coronary artery disease or ischemic stroke, we derived our risk model. External validation was conducted using data from the Suita study, which included 445 patients with similar ASCVD backgrounds. The primary outcome of interest was a composite endpoint encompassing cardiovascular death, myocardial infarction, or stroke. Variable selection was performed based on clinically relevant factors previously employed in established risk scores (SMART, REACH, and TRS 2°P risk scores). Logistic regression was utilized for model development, and the predictive performance was assessed using the C-index.

Results
Over a median follow-up of 10.1 years, the derivation cohort experienced 756 cardiovascular events. Patients in the derivation cohort had an average age of 68.9 ± 10.6 years, with 91% and 24% having a history of coronary artery disease and ischemic stroke, respectively. Using logistic regression, the multivariate model revealed a higher recurrent risk associated with several factors including age, smoking status, systolic blood pressure, diabetes, renal function, number of ASCVD events, atrial fibrillation, lipid levels, left ventricular systolic dysfunction, and statin use. A simple risk score based on these predictors demonstrated a &gt;5-fold gradient of 10-year recurrent risk with a C-index of 0.65 (95% CI 0.63-0.68, Figure). The prediction model was externally validated in the Suita study wit 245 cardiovascular events and a median follow-up of 10.4 years, showing good discriminative ability with a C-index of 0.64 (95% CI 0.60–0.68).

Conclusion
Our newly developed prediction model offers a valuable tool for identifying individuals at heightened risk of recurrent cardiovascular events over a 10-year period, thereby facilitating more targeted and effective secondary prevention strategies tailored to the unique characteristics of Japanese ASCVD patients.
Impact of measured or calculated small dense LDL cholesterol compared with apolipoprotein B or non-HDL cholesterol for long-term secondary prevention in patients with stable coronary artery disease
Authors: Koba S , Satoh N , Ito Y , Yokota Y , Tsunoda F , Sakai K , Nakamura Y , Shoji M , Hirano T , Shinke T 
Published: October 2024

Abstract

Background
This study was aimed to investigate whether directly measured small dense low-density lipoprotein cholesterol (D-sdLDL-C) can predict long-term coronary artery disease (CAD) events compared with LDL-C, non–high-density lipoprotein cholesterol (non-HDL-C), apolipoprotein B (apoB), and estimated sdLDL-C (E-sdLDL-C) determined by Sampson’s equation in patients with stable CAD.

Methods
D-sdLDL-C measured at Showa University, and E-sdLDL-C were evaluated in 790 male and 244 female patients with stable CAD. CAD events defined as sudden cardiac death, onset of acute coronary syndrome, and/or need for coronary revascularization were monitored for 12 years. Cut-points of D-sdLDL-C, E-sdLDL-C, LDL-C, non-HDL-C, and apoB were determined by receiver operating characteristic curves.

Results
CAD events were observed in 238 male and 67 female patients. The Kaplan–Meier event-free survival curves showed that patients with D-sdLDL-C ≥32.1 mg/dL had an increased risk for CAD events (chi-square from log-rank test = 7.23), whereas risk in patients with E-sdLDL-C ≥36.2 mg/dL was not. In the group with high D-sdLDL-C, the multivariable-adjusted hazard ratio (HR) was 1.47, 95% confidence interval (CI) 1.15-1.89, and it remained significant after adjustment for LDL-C, non-HDL-C, or apoB. These results remained significant in the patients treated with statin. HRs for high LDL-C, non-HDL-C, or apoB were not statistically significant after adjustment for high D-sdLDL-C. The high D-sdLDL-C enhanced risk of high LDL-C, non-HDL-C, and apoB (HR 1.73, 95%CI 1.27-2.37). Conclusions: High D-sdLDL-C can predict long-term recurrence of CAD in stable CAD patients independently of apoB and non-HDL-C by distinguishing the patients at high risk. D-sdLDL-C is an independent risk-enhancer for secondary CAD prevention whereas E-sdLDL-C is not.Figure
Association of serum testosterone levels with left atrial size, function, and risk of atrial fibrillation in adult men: observational and mendelian randomization analyses
Authors: Cho S H , Yang P S , Jang E S , Kim D H , Yu H T , Kim T H , Uhm J S , Pak H N , Lee M H , Joung B Y 
Published: October 2024

Abstract

Background
Numerous studies have investigated the association between serum testosterone levels, testosterone replacement therapy (TRT), and cardiovascular risk. However, research examining the relationship between testosterone levels and atrial fibrillation (AF) risk remains limited. We comprehensively analyzed the association between total testosterone (TT) levels, intermediary phenotypes such as left atrium (LA) size and function, and the risk of AF in middle-aged and older men.

Methods
We utilized data from the UK Biobank, a population-based prospective cohort, focusing on 179,988 White men who had complete serum TT level data and no AF history. Observational associations between TT levels and LA imaging traits, as well as AF risk, were estimated using multivariable regression and time-dependent Cox regression models, treating TT levels as a time-varying variable. Genetic associations were examined by Mendelian randomization (MR), using both UK Biobank and external large consortia genome-wide association study data.

Results
During the median follow-up of 11.8 years (IQR 10.9–12.5), we observed 13,847 incident AF cases (7.7%). Participants with normal TT levels (≥ 300 ng/dL) showed a 15% reduced risk of AF (HR of 0.85 [95% CI, 0.82–0.89]) compared to those with low TT (&lt; 300 ng/dL). Interestingly, participants undergoing TRT experienced a 51% higher risk of AF (1.51 [1.09–2.07]). Furthermore, each 1-standard deviation increase in TT levels was associated with a reduced AF risk (OR of 0.91 [0.89–0.93]) and an improved LA emptying fraction (1.29 [1.06–1.58]). Applying age-specific cutoff values for low TT levels highlighted a more pronounced AF risk reduction in participants with normal TT. MR analyses supported these observations, suggesting potential causal relationships between TT levels and both LA function and AF risk.

Conclusions
Our findings suggest that low TT levels are associated with reduced LA function and increased risk of AF, both observationally and genetically, indicating that serum TT could serve as a surrogate marker or even a potential causal mediator in the development of AF.Abstract tableAbstract figure