Adjustment For Traditional Risk Factors Research Articles

Impaired Balance Predicts Cardiovascular Disease in 70-Year-Old Individuals-An Observational Study From the Healthy Aging Initiative.

Limited research has explored balance problems as a prospective risk factor for cardiovascular disease (CVD). This study aimed to characterize the association between balance measures and the risk of incident CVD in a population of 70-year-olds. From 2012 to 2022 a cohort of 4927 older individuals who were CVD free underwent balance assessments using a balance board. Measurements included lateral and anterior-posterior sway, along with a safety limit of stability in a subcohort (N=2782). Time to first hospitalization for CVD, encompassing stroke, myocardial infarction, or angina pectoris was the primary outcome. Multivariable regression models assessed associations between balance parameters and CVD risk. Over a mean follow-up of 4.9 years, 320 individuals were hospitalized for CVD. In a balance test with eyes open, increased lateral sway at baseline was associated with a higher risk of CVD (hazard ratio [HR], 1.014 [95% CI, 1.004-1.025], P=0.005, per mm increased sway), after adjustment for traditional risk factors for CVD. Similarly, individuals with CVD during follow-up exhibited higher lateral sway with eyes closed at baseline (HR, 1.015 [95% CI, 1.005-1.025], P=0.002, per mm increased sway), after multivariable adjustment. The 4 strongest independent predictors of CVD included lateral sway and were associated with a population attributable fraction of 61% (95% CI, 54-68). In community-dwelling 70-year-olds, impaired lateral balance was an independent predictor of later CVD, after adjustment for traditional risk factors. This may suggest that position balance could be used as an early risk marker for underlying atherosclerotic disease.

Trimethylamine-N-oxide and 5-year mortality: the role of gut microbiota-generated metabolite from the CORE-Thailand cohort

The gut microbiota metabolite trimethylamine-N-oxide (TMAO)—derived from dietary phosphatidylcholine—is mechanistically linked to cardiovascular disease (CVD) and increased cardiovascular risk. This study examined the relationship between fasting plasma TMAO levels and 5-year all-cause mortality in a cohort of patients at high risk of cardiovascular events (CORE-Thailand Registry). Of the 134 patients, 123 (92%) had established cardiovascular disease, and 11 (8%) had multiple risk factors. Fasting plasma TMAO levels were measured using nuclear magnetic resonance spectroscopy. Within this prospective cohort study, the median TMAO was 3.81 μM [interquartile range (IQR) 2.89–5.50 μM], with a mean age of 65 ± 11 years; 61% were men, and 39.6% had type II diabetes. Among 134 patients, 65 (49%) were identified as the high-TMAO group (≥ 3.8 μM), and 69 (51%) were identified as the low-TMAO group (< 3.8 μM). After a median follow-up of 58.8 months, the high-TMAO group was associated with a 2.88-fold increased mortality risk. Following adjustment for traditional risk factors, high-sensitivity cardiac troponin-T, estimated glomerular filtration rate, angiotensin-converting enzyme (ACEI), or angiotensin-receptor blocker (ARB) use, the high-TMAO group remained predictive of 5-year all-cause mortality risk (the high-TMAO vs. the low-TMAO group, adjusted hazard ratio 2.73, 95% CI 1.13–6.54; P = 0.025). Among Thai patients at high risk of cardiovascular events, increased plasma TMAO levels portended greater long-term mortality risk.

Increased risk of kidney failure in patients with genetic kidney disorders.

BACKGROUNDIt is unknown whether the risk of kidney disease progression and failure differs between patients with and without genetic kidney disorders.METHODSThree cohorts were evaluated: the prospective Cure Glomerulonephropathy Network (CureGN) and 2 retrospective cohorts from Columbia University, including 5,727 adults and children with kidney disease from any etiology who underwent whole-genome or exome sequencing. The effects of monogenic kidney disorders and APOL1 kidney-risk genotypes on the risk of kidney failure, estimated glomerular filtration rate (eGFR) decline, and disease remission rates were evaluated along with diagnostic yields and the impact of American College of Medical Genetics secondary findings (ACMG SFs).RESULTSMonogenic kidney disorders were identified in 371 patients (6.5%), high-risk APOL1 genotypes in 318 (5.5%), and ACMG SFs in 100 (5.2%). Family history of kidney disease was the strongest predictor of monogenic disorders. After adjustment for traditional risk factors, monogenic kidney disorders were associated with an increased risk of kidney failure (hazard ratio [HR] = 1.72), higher rate of eGFR decline (-3.06 vs. 0.25 mL/min/1.73 m2/year), and lower risk of complete remission (odds ratioNot achieving CR = 5.25). High-risk APOL1 genotypes were associated with an increased risk of kidney failure (HR = 1.67) and faster eGFR decline (-2.28 vs. 0.25 mL/min/1.73 m2), replicating prior findings. ACMG SFs were not associated with personal or family history of associated diseases, but were predicted to impact care in 70% of cases.CONCLUSIONSMonogenic kidney disorders were associated with an increased risk of kidney failure, faster eGFR decline, and lower rates of complete remission, suggesting opportunities for early identification and intervention based on molecular diagnosis.TRIAL REGISTRATIONNA.FUNDINGNational Institute of Diabetes and Digestive and Kidney Diseases grants U24DK100845 (formerly UM1DK100845), U01DK100846 (formerly UM1DK100846), U01DK100876 (formerly UM1DK100876), U01DK100866 (formerly UM1DK100866), U01DK100867 (formerly UM1DK100867), U24DK100845, DK081943, RC2DK116690, 2U01DK100876, 1R01DK136765, 5R01DK082753, and RC2-DK122397; NephCure Kidney International; Department of Defense Research Awards PR201425, W81XWH-16-1-0451, and W81XWH-22-1-0966; National Center for Advancing Translational Sciences grant UL1TR001873; National Library of Medicine grant R01LM013061; National Human Genome Research Institute grant 2U01HG008680.

AI-based Fully-Automated Stress Left Ventricular Ejection Fraction as a Prognostic Marker in Patients Undergoing Stress-CMR.

To determine in patients undergoing stress CMR whether fully automated stress artificial intelligence (AI)-based left ventricular ejection fraction (LVEFAI) can provide incremental prognostic value to predict death above traditional prognosticators. Between 2016 and 2018, we conducted a longitudinal study that included all consecutive patients referred for vasodilator stress CMR. LVEFAI was assessed using AI-algorithm combines multiple deep learning networks for LV segmentation. The primary outcome was all-cause death assessed using the French National Registry of Death. Cox regression was used to evaluate the association of stress LVEFAI with death after adjustment for traditional risk factors and CMR findings.In 9,712 patients (66±15 years, 67% men), there was an excellent correlation between stress LVEFAI and LVEF measured by expert (LVEFexpert) (r=0.94, p<0.001). Stress LVEFAI was associated with death (median [IQR] follow-up 4.5 [3.7-5.2] years) before and after adjustment for risk factors (adjusted hazard ratio [HR], 0.84 [95% CI, 0.82-0.87] per 5% increment, p<0.001). Stress LVEFAI had similar significant association with death occurrence compared with LVEFexpert. After adjustment, stress LVEFAI value showed the greatest improvement in model discrimination and reclassification over and above traditional risk factors and stress CMR findings (C-statistic improvement: 0.11; NRI=0.250; IDI=0.049, all p<0.001; LR-test p<0.001), with an incremental prognostic value over LVEFAI determined at rest. AI-based fully automated LVEF measured at stress is independently associated with the occurrence of death in patients undergoing stress CMR, with an additional prognostic value above traditional risk factors, inducible ischemia and LGE.

Associations of four surrogate insulin resistance indexes with non-alcoholic steatohepatitis in Chinese patients with obesity: a cross-sectional study.

This study was designed to evaluate the association of four surrogate indexes of IR with NASH in patients with obesity. A total of 270 patients who underwent bariatric surgery, were included in this cross-sectional study. NASH was diagnosed based on liver biopsies. Binary logistics regression analyses were performed to assess the associations of four surrogate indexes of IR (HOMA-IR, Matsuda index, TyG, and TG/HDL-C) with NASH in patients with obesity. The restricted cubic spline was used to assess the dose-response associations of surrogate indexes of IR with NASH after adjusting for confounding factors. NASH was diagnosed in 136 patients, with a prevalence of 50.37%. Compared with tertile 1, the fully adjusted ORs (95% CIs) of NASH for tertile 3 were 2.711(1.113-6.608) and 0.297 (0.152-0.579) for TyG and Matsuda index. Consistently, per SD increment of TyG were still significantly associated with 64% increased risks of NASH, and per SD increment of Matsuda index were still significantly associated with 38% decreased risks of NASH. In contrast, no significant associations were found between HOMA-IR and TG/HDL-C and the risk of NASH in patients with obesity (all P > 0.05). After adjusting covariates in restricted cubic splines, the risk of NASH decreased with the increment of Matsuda Index levels (P-nonlinear = 0.442, P-overall = 0.007) and with the decrement of TyG levels (P-nonlinear = 0.004, P-overall = 0.001). In patients with obesity, TyG and Matsuda index were independently related to the risk of NASH after adjustment for traditional risk factors. In addition, compared with HOMA-IR and TG/HDL-C, the Matsuda index and TyG may be more suitable for NASH prediction in patients with obesity.

Role of ADAR2-mediated innate immune responses in vascular inflammation and atherosclerosis

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Deutsche Forschungsgemeinschaft (DFG) Background Adenosine-to-inosine (A-to-I) RNA editing is an epitranscriptional regulator of RNA metabolism, catalyzed by the adenosine deaminases acting on RNA-1/-2 (ADAR1/2). Whether ADAR2 play a role in atherosclerotic processes remains elusive. Aim We examined the role of ADAR2 in vascular endothelial cell (EC) immunomodulatory responses and its biological relevance in murine and human atherosclerosis. Methods The role of ADAR2 in atherosclerosis was determined in a double ADAR2 and ApoE knockout mice fed with Western diet for 20 weeks. Three mouse genetic models (global and inducible vascular endothelial cell (iEC)-restricted ADAR2 and IL6ST knockout) were used to determine the role of ADAR2 in IL-6-related innate immunity. Expression levels of ADAR2 were measured in peripheral blood mononuclear cells derived from 533 individuals at risk for atherosclerotic vascular disease. Structural vascular measurements were used, including intima-media thickness (IMT), carotid wall maximum thickness (maxWT), and the number of atheromatous plaques by carotid and femoral artery ultrasonography as surrogate markers of subclinical arterial disease. Study participants were followed for major adverse cardiovascular events (MACE). Results Genetic ablation of ADAR2 resulted in a reduction of atherosclerotic plaque burden and necrotic core in the aorta and brachiocephalic trunk as well as reduced leukocyte infiltration in atherosclerotic plaques without affecting cholesterol levels in mice. Blood analysis revealed decreased pro-inflammatory cytokine levels including IL-6 after treatment of ADAR2/APOE KO mice compared to littermate control mice. Intravital imaging of IL-6-inflamed vascular endothelium showed that rolling and adhesion of leukocyte subsets to vascular wall were impaired by 2-fold in ADAR2-/- or iEC-ADAR2-/- KO mice. In vivo and ex vivo histological examination revealed that endothelial ADAR2 controls endothelial vascular adhesion molecule expression induced by gp130 signaling. ADAR2-deficient transcriptome revealed a selective upregulation of a conserved group of miRNAs targeting the IL6ST mRNA. Multilayered rescue studies including miR-inhibitors restored IL6ST levels after ADAR2 deficiency. In humans, increased ADAR2 expression was independently associated with the presence of CAD, higher C-reactive protein and mean carotid IMT after adjustment for traditional risk factors. Increased ADAR2 at baseline was prospectively associated with accelerated progression of subclinical atherosclerosis reflected by the increased number of carotid plaques at follow-up (OR=3.74, P&amp;lt;0.05). Finally, high ADAR2 levels were independently associated with higher MACE incidence across a median follow-up period of 54 months. Conclusion Posttranscriptional control of vascular inflammation by ADAR2 is integral for the development and progression of atherosclerosis in mice and humans. Our findings suggest that ADAR2 may serve as a promising therapeutic target for atherosclerosis.Role of ADAR2 in atherosclerosis

THE UTILITY OF BODY INDICES FOR DIABETES PREDICTION IN PATIENTS WITH FASTING HYPERGLYCEMIA: A 10-YEAR FOLLOW-UP STUDY

Objective: We aimed to compare the new body indices against traditional body mass index in their ability to predict diabetes development in patients with fasting hyperglycemia. Design and method: Baseline examination of population-based cohort was performed 2012-2013 in the framework of epidemiological study ESSE-RF which included questionnaires, anthropometry (weight, height, waist and hip circumference), laboratory tests (fasting glucose, glycated hemoglobin, lipids) and target organ damage assessment. In 2022-2023 patients with fasting hyperglycemia at baseline visit were re-examined to register onset of diabetes mellitus (DM), glucose and glycated hemoglobin levels. Several anthropometric indices were calculated: body mass index (BMI), waist-to-height ratio (WHtR), body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), and lipid accumulation product (LAP). Results: In total 72 participants were re-examined - 35 men and 37 women (mean age 43,6 years and 50,5 years, respectively). New onset of DM was confirmed in 15 patients (20,8%), in 6 men and 9 women. According to multiple regression analysis the most significant predictors of DM development were BRI (p=0,04, beta=-2,2) and WHTR (p=0,04, beta=2,94), but not BMI (p=0,42, beta=-0,22), model (R2 = 0.32; p=0,0014). After adjustment for traditional risk factors (sex, triglycerides, age, insulin, high density lipoproteins, waist circumference, glucose), the most significant diabetes predictors were the WHTR (p=0,01, beta=4,23) and VAI indices (p=0,04, beta=0,732), model (R2 = 0.547; p=1x10-4). We used individual body indices as predictors for the DM and estimated the area under the ROC curve (AUC). The AUC ROC for BRI, WHTR, CVAI and ABSI was greater than for traditional BMI, while for VAI and LAP indices performed worse than BMI (Table 1). Conclusions: New body composition indices involving advanced mathematical framework and including extended set of parameters - BRI, WHTR, CVAI and ABSI, are more reliable diabetes predictors than BMI in patients with fasting hyperglycemia after 10 years of follow-up. This work was supported by the Ministry of Science and Higher Education of the Russian Federation (Agreement # 075-15-2022-301) to A.Konradi.

Discordance Between Very Low-Density Lipoprotein Cholesterol and Low-Density Lipoprotein Cholesterol Increases Cardiovascular Disease Risk in a Geographically Defined Cohort.

Clinical risk scores are used to identify those at high risk of atherosclerotic cardiovascular disease (ASCVD). Despite preventative efforts, residual risk remains for many individuals. Very low-density lipoprotein cholesterol (VLDL-C) and lipid discordance could be contributors to the residual risk of ASCVD. Cardiovascular disease-free residents, aged ≥40 years, living in Olmsted County, Minnesota, were identified through the Rochester Epidemiology Project. Low-density lipoprotein cholesterol (LDL-C) and VLDL-C were estimated from clinically ordered lipid panels using the Sampson equation. Participants were categorized into concordant and discordant lipid pairings based on clinical cut points. Rates of incident ASCVD, including percutaneous coronary intervention, coronary artery bypass grafting, stroke, or myocardial infarction, were calculated during follow-up. The association of LDL-C and VLDL-C with ASCVD was assessed using Cox proportional hazards regression. Interaction between LDL-C and VLDL-C was assessed. The study population (n=39 098) was primarily White race (94%) and female sex (57%), with a mean age of 54 years. VLDL-C (per 10-mg/dL increase) was significantly associated with an increased risk of incident ASCVD (hazard ratio, 1.07 [95% CI, 1.05-1.09]; P<0.001]) after adjustment for traditional risk factors. The interaction between LDL-C and VLDL-C was not statistically significant (P=0.11). Discordant individuals with high VLDL-C and low LDL-C experienced the highest rate of incident ASCVD events, 16.9 per 1000 person-years, during follow-up. VLDL-C and lipid discordance are associated with a greater risk of ASCVD and can be estimated from clinically ordered lipid panels to improve ASCVD risk assessment.

Prognostic significance of preoperative nutritional status for postoperative acute kidney injury in older patients undergoing major abdominal surgery: a retrospective cohort study.

The association between malnutrition and postoperative acute kidney injury (AKI) has not been well studied. In this study, the authors examined the association between preoperative nutritional status and postoperative AKI in older patients who underwent major abdominal surgery, as well as the predictive value of malnutrition for AKI. The authors retrospectively included patients aged 65 or older who underwent major elective abdominal surgery. The nutritional status of the patient was evaluated using three objective nutritional indices, such as the geriatric nutritional risk index (GNRI), the prognostic nutritional index (PNI), and the controlling nutritional status (CONUT). AKI was determined using the KDIGO criteria. The authors performed logistic regression analysis to investigate the association between preoperative nutritional status and postoperative AKI, as well as the predictive value of nutritional scores for postoperative AKI. A total of 2775 patients were included in the study, of which 707 (25.5%), 291 (10.5%), and 517 (18.6%) had moderate to severe malnutrition according to GNRI, PNI, and CONUT calculations. After surgery, 144 (5.2%) patients developed AKI, 86.1% at stage 1, 11.1% at stage 2, and 2.8% at stage 3 as determined by KDIGO criteria. After adjustment for traditional risk factors, worse nutritional scores were associated with a higher AKI risk. In addition to traditional risk factors, these nutritional indices improved the predictive ability of AKI prediction models, as demonstrated by significant improvements in integrated discrimination and net reclassification. Poor preoperative nutritional status, as assessed by GNRI, PNI, and CONUT scores, was associated with an increased risk of postoperative AKI. Incorporating these scores into AKI prediction models improved their performance. These findings emphasize the need for screening surgical patients for malnutrition risk. Further research is needed to determine whether preoperative malnutrition assessment and intervention can reduce postoperative AKI incidence.

Association of circulating fibroblast growth factor 21 levels with all-cause and cardiovascular mortality: The multi-ethnic study of atherosclerosis

BackgroundFibroblast growth factor 21 (FGF21) levels are often elevated in cardiovascular disease (CVD). However, no study has assessed its association with cardiovascular and all-cause mortality in a population free of clinically evident CVD. MethodsA total of 5543 Multi-Ethnic Study of Atherosclerosis (MESA) participants (mean age 62.7 years, 47.5 % male), free of clinically evident CVD at baseline, were studied. From baseline (2000–2002), 1606 deaths (including 387 CVD deaths) were observed over a median follow-up of 17.7 years. Multivariable Cox regression analysis was performed to assess the association of plasma FGF21 levels with mortality. ResultsFGF21 levels at baseline were associated with all-cause mortality, even after adjustment for traditional risk factors, including demographic, socioeconomic and cardiovascular risk factors (adjusted hazard ratio 1.08 [95% confidence interval 1.01, 1.16] per 1 SD increase in ln-transformed levels; 1.27 for the highest vs, lowest quartile). Baseline FGF21 levels were significantly associated with both CVD and non-CVD mortality in unadjusted models. However, the association with non-CVD mortality, but not CVD mortality, remained statistically significant after adjusting for covariates. Similar results were obtained in FGF21 quartile analyses and also when using competing risk regression or matched case-control cohort in sensitivity analyses. ConclusionsIn subjects without clinically-evident CVD at baseline, over 17.7 years follow-up there is a modest association of baseline FGF21 levels with all-cause mortality. The finding that this is driven primarily by a significant association with non-CVD mortality over almost two decades merits further investigation.

Prognostic value of gut microbe-generated metabolite phenylacetylglutamine in patients with heart failure.

Phenylacetylglutamine (PAGln) is a phenylalanine-derived metabolite produced by gut microbiota with mechanistic links to heart failure (HF)-relevant phenotypes. We sought to investigate the prognostic value of PAGln in patients with stable HF. Fasting plasma PAGln levels were measured by stable-isotope-dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) in patients with stable HF from two large cohorts. All-cause mortality was assessed at 5-year follow-up in the Cleveland cohort, and HF, hospitalization, or mortality were assessed at 3-year follow-up in the Berlin cohort. Within the Cleveland cohort, median PAGln levels were 4.2 (interquartile range [IQR] 2.4-6.9) μM. Highest quartile of PAGln was associated with 3.09-fold increased mortality risk compared to lowest quartile. Following adjustments for traditional risk factors, as well as race, estimated glomerular filtration rate, amino-terminal pro-B-type natriuretic peptide, high-sensitivity C-reactive protein, left ventricular ejection fraction, ischaemic aetiology, and HF drug treatment, elevated PAGln levels remained predictive of 5-year mortality in quartile comparisons (adjusted hazard ratio [HR] [95% confidence interval, CI] for Q4 vs Q1: 1.64 [1.07-2.53]). In the Berlin cohort, a similar distribution of PAGln levels was observed (median 3.2 [IQR 2.0-4.8] μM), and PAGln levels were associated with a 1.92-fold increase in 3-year HF hospitalization or all-cause mortality risk (adjusted HR [95% CI] for Q4 vs Q1: 1.92 [1.02-3.61]). Prognostic value of PAGln appears to be independent of trimethylamine N-oxide levels. High levels of PAGln are associated with adverse outcomes independent of traditional cardiac risk factors and cardio-renal risk markers.

Lower serum carotenoid levels are associated with incident cognitive decline independent of traditional risk factors in a prospective study of older men from Northern Ireland

AbstractBackgroundNutritional influences, and antioxidant status in particular, have been implicated in the aetiology of cognitive decline. This study investigated the neuroprotective effects of serum antioxidants in a prospective cohort of older men to identify associations with cognitive outcomes, independent of traditional risk factors.MethodThis cohort study included 873 Northern Irish men nested within PRIME (Prospective Epidemiological Study of Myocardial Infarction) who were followed‐up for at least 15 years. Mini Mental State Examination (MMSE) was carried out at baseline. The Addenbrooke’s Cognitive Examination‐R and MMSE were carried out at follow‐up. A consensus diagnosis of normal cognition for age, mild cognitive impairment (MCI) or dementia was made using accepted clinical criteria. Serum concentrations of retinol, two forms of vitamin E (α‐ and ϒ‐tocopherol) and six carotenoids measured from baseline samples were quantified by high‐performance liquid chromatography and assessed by multiple logistic regression analyses.ResultThe case definition included the 163 men characterised with MCI and 46 men with dementia; 664 participants were considered cognitively normal controls (Table 1). In unadjusted analyses, serum levels of the carotenoids α‐carotene, β‐carotene, lycopene and β‐cryptoxanthin were significantly lower in MCI/dementia cases than controls, in contrast to ϒ‐tocopherol, which was significantly higher (Table 2). Following adjustment for traditional risk factors including height, APOε4 genotype, diastolic blood pressure, smoking status and the presence of (pre)diabetes or depression, the effect size of those carotenoids significant in the unadjusted analysis was attenuated somewhat; only α‐carotene remained significantly associated with MCI/dementia (odds ratio = 0.55; confidence interval: 0.31‐0.99; Table 2).ConclusionOur data implicates lower levels of serum carotenoids as potential early biomarkers of MCI/ dementia before overt manifestation of symptoms, independent of traditional risk factors. These findings are consistent with hypotheses supportive of a neuroprotective role of dietary antioxidants and corroborate previous associations of higher serum carotenoid levels with better cognition in aging subjects. There is emerging evidence that carotenoids, through their potent antioxidant and anti‐inflammatory properties, may positively impact cognitive function. Limiting cognitive decline through lifestyle, exercise, and a higher carotenoid intake, may prove beneficial.

Left atrioventricular coupling index assessed using cardiac CT as a prognostic marker of cardiovascular death

Abstract Background Although the left atrioventricular coupling index (LACI) measured by cardiovascular magnetic resonance (CMR) is a strong predictor of cardiovascular events, the availability to CMR remains limited in clinical routine. Therefore, it would be useful to validate LACI assessment using other imaging methods such as computed tomography (CT). However, the feasibility of LACI measurement using cardiac CT and its prognostic value are not established. Purpose We aimed to investigate the prognostic value of the LACI assessed by cardiac CT, to predict the occurrence of cardiovascular death in consecutive patients without known CVD referred for coronary CT angiography (CCTA). Methods Between 2010 and 2020, we conducted a single-center study with all consecutive patients without known CVD referred for CCTA. LACI was defined as the ratio of LA to LV end-diastolic volumes. The primary outcome was cardiovascular death. Cox regressions were used to evaluate the association of LACI with the primary outcome after adjustment for traditional risk factors and CCTA findings. Results In 1,444 patients (70±12 years, 43% men), 92 (6.4%) patients experienced all-cause death, including 67 (4.3%) patients with cardiovascular death after a median (IQR) follow-up of 6.8 (5.9-9.1) years. After adjustment for risk factors and CCTA findings, LACI was positively associated with the occurrence of cardiovascular death (adjusted hazard ratio [HR], 1.07 [95% CI, 1.05-1.09] per 1% increment, p&amp;lt;0.001), and all-cause death (adjusted HR, 1.05 [95% CI, 1.03-1.07] per 1% increment, p&amp;lt;0.001). After adjustment, a LACI ≥25% showed the best improvement in model discrimination and reclassification above traditional risk factors and CCTA findings (C-statistic improvement: 0.27; NRI=0.826; IDI=0.209, all p&amp;lt;0.001; LR-test p&amp;lt;0.001). Conclusions LACI measured by CCTA is independently associated with cardiovascular death and all-cause death in patients without known CVD referred for CCTA, with an incremental prognostic value over traditional risk factors and CCTA findings.LACI measurement using CCTASurvival curves stratified by LACI value

Ai-based fully automated left atrioventricular coupling index as a prognostic marker in patients undergoing stress-CMR

Abstract Background The left atrioventricular coupling index (LACI) is a strong and independent predictor of heart failure (HF) in individuals without clinical cardiovascular disease. Its prognostic value is not established in patients with cardiovascular disease. Purpose To determine in patients undergoing stress CMR whether fully automated artificial intelligence-based LACI can provide incremental prognostic value to predict HF. Methods Between 2016 and 2018, we conducted a longitudinal study including all consecutive patients with abnormal (inducible ischemia or late gadolinium enhancement (LGE)) vasodilator stress CMR. Control subjects with normal stress CMR were selected using propensity score-matching. LACI was defined as the ratio of LA to LV end-diastolic volumes. The primary outcome included hospitalization for acute HF or cardiovascular death. Cox regression was used to evaluate the association of LACI with the primary outcome after adjustment for traditional risk factors. Results In 2,134 patients [65±12 years, 77% men, 1:1 matched patients (1,067 with normal and 1,067 with abnormal CMR)], LACI was positively associated with the primary outcome (median follow-up 5.2 (4.8-5.5) years) before and after adjustment for risk factors in the overall propensity-matched population (adjusted hazard ratio [HR], 1.18 [95%CI, 1.13-1.24] per 0.1% increment), patients with abnormal (adjusted HR, 1.22 [95%CI, 1.14-1.30] per 0.1% increment), and normal CMR (adjusted HR, 1.12 [95%CI, 1.05-1.20] per 0.1% increment; all p&amp;lt;0.001). After adjustment, a higher LACI of ≥25% showed the greatest improvement in model discrimination and reclassification over and above traditional risk factors and stress CMR findings (C-statistic improvement: 0.16; NRI=0.388; IDI=0.153, all p&amp;lt;0.001; LR-test p&amp;lt;0.001). Conclusion LACI is independently associated with hospitalization for HF and cardiovascular death in patients undergoing stress CMR, with an incremental prognostic value over traditional risk factors including inducible ischemia and LGE.LACI measurement method using CMRKaplan-Meier curves by LACI value

Incremental prognostic value of coronary plaque features on CT angiography in symptomatic patients with obstructive CAD

Abstract Background Several coronary computed tomography angiography (CCTA) studies have shown the strong prognostic value of the coronary artery disease (CAD) burden and the potential interest of the plaque composition analysis. However, the incremental prognostic value of this plaque analysis above the CAD burden in patients with obstructive CAD is not well established. Purpose To assess the incremental prognostic value of the plaque composition analysis using CCTA to predict major adverse cardiovascular events (MACEs) above traditional risk factors and CAD burden in consecutive symptomatic patients with obstructive CAD. Methods In a large multicentric registry, consecutive symptomatic patients without known CAD referred for CCTA were screened between 2008-2020. All patients with obstructive CAD (at least 1 ≥50% stenosis on CCTA) were included. The primary composite outcome was MACE defined by cardiovascular death or nonfatal myocardial infarction. CCTA data were interpreted using multiplanar reconstruction according to the 16-segment coronary artery model. Coronary segments were scored visually for both degree of luminal stenosis and composition of coronary plaque which were classified as noncalcified, mixed, or calcified. To assess the prognostic value of each CCTA findings, different multivariable Cox regression models were used (Model 1: clinical [traditional risk factors]; Model 2: model 1 + CAD burden [number of proximal segments with stenosis ≥50% + number of vessels with obstructive CAD]; Model 3: model 2 + plaques feature [number of segments with noncalcified plaques]). The additional predictive value of each model for predicting MACEs was calculated using C-statistic increment, continuous net reclassification improvement (NRI), and the integrative discrimination index (IDI). Results Of 2,312 patients referred for CCTA, 2,038 (mean age 70±12 years, 46% men) completed follow-up (median 6.7 years; interquartile range: 5.9-9.1 years), and 319 experienced a MACE (14%). After adjustment for traditional risk factors, number of proximal segments with &amp;gt;50% stenosis, number of vessels with obstructive CAD, number of segments with noncalcified were all strongly associated with MACEs (all p&amp;lt;0.001). After adjustment, the addition of the analysis of plaque features (model 3) showed the best improvement in model discrimination and reclassification above a model including traditional risk factors and CAD burden (model 2) (C-statistic improvement=0.03; NRI=45.0%; IDI=9.8%, Chi-2 global=412, all p&amp;lt;0.001; LR-test p&amp;lt;0.001). Conclusions In a large cohort of symptomatic patients with obstructive CAD on CCTA, the analysis of plaque features had an incremental prognostic value to predict MACEs over and above a model combining traditional risk factors and CAD burden.Survival curves for MACEIncremental prognostic value of CCTA

Cardiovascular and inflammatory biomarkers for non-invasive detection of coronary artery obstruction and prediction of long-term survival in patients with suspected chronic coronary syndrome

Abstract Introduction and methods: The knowledge about diagnostic and prognostic value of cardiac and inflammatory biomarkers in patients with chronic coronary syndrome (CCS) is limited. To address this, we analyzed serum levels of selected biomarkers in 2536 patients with suspected CCS (35% female) from the Leipzig LIFE Heart Study who were admitted for coronary angiography. The median follow-up was 10 years. The following biomarkers were considered: high sensitive troponin T (hsTNT), N-terminal pro B-type natriuretic peptide (NT-proBNP), copeptin, high sensitive C-reactive protein (hsCRP) and interleukin-6 (IL-6). Patients were stratified according to the angiographic severity of coronary artery disease (CAD): CAD0 (no sclerosis), CAD1 (non-obstructive, i.e., stenosis &amp;lt; 50%), CAD2 (≥ one stenosis ≥ 50%). Group comparison (GC) included GC1: CAD0 + 1 vs. CAD2, GC2: CAD0 vs. CAD1 + 2. Using age-, sex and symptom-based pre-test probability (PTP) table for obstructive CAD (i.e. CAD 2) which was published in the current CCS guidelines, patients were further classified into the following three categories: PTP &amp;lt; 5% (n=559), PTP 5-15% (n=545) and PTP &amp;gt; 15% (n=1432). Results CAD0, CAD1, CAD2 were apparent in 999, 529, and 1008 patients, respectively. Upon adjustment for traditional risk factors (TRF) the levels of hsTNT, NT-proBNP and IL-6 showed significant difference in GC1 (hsTNT: p=2.0x10-10, NT-proBNP: p=0.049, IL6: p=0.030). In GC2 only elevated hsTNT remained significant (p=1.9x10-7). In the ROC analysis only hsTNT slightly improved the AUC for the GC1-comparison in addition to TRF (0.729 with vs 0.712 witt hsTNT, p=0.013). Within the PTP subcategories the following results were obtained: PTP &amp;lt; 5%: AUC 0.747 with vs 0.730 without hsTNT, p=0.017; PTP 5-15 %: AUC 0.636 with vs 0.670 without hsTNT, p&amp;lt;0.001; PTP &amp;gt; 15%: AUC 0.699 with vs 0.677 without hsTNT, p= 0.024). In PTP 5-15% subgroup TropT cut-off value &amp;lt; 3 pg/mL (N= 119 / 23.4%) showed sensitivity of 89.7% and specificity of 73.1% for CAD2 detection. Ten years survival in groups CAD0, CAD1, CAD2 were 88.3%, 77.3%, 72.4%, respectively. In the multivariate analysis elevated hsTNT, NT-proBNP, copeptin and IL-6 remained significant mortality predictors in CAD2 patients with hazard ratios of similar magnitude (i.e. 1.5, 1.3, 1.4 and 1.3 per unit on the log-scale of the parameters, respectively). hsCRP did not reach significance. In the model stratified into tertiles according to the effects of classical risk factors and the joint biomarker levels for except hsCRP, hazard rates were 3.13 (tertile 2 vs 1) and 11.2 (tertile 3 vs 1). Conclusions In the present study hsTNT substantially improved the detection of obstructive CAD particularly in patients with intermediate PTP 5-15%. Furthermore, the studied biomarkers enable fast and precise non-invasive prediction of mortality risk in patients with suspected CCS, allowing tailored primary and secondary CAD prevention in this high-risk group.

Incremental prognostic value of fully-automatic machine-learning based global circumferential strain during a stress CMR exam

Abstract Background Left ventricular global circumferential strain using cardiovascular magnetic resonance (CMR) is an accurate indicator to predict cardiovascular events. Although several studies have shown the excellent prognostic value of stress CMR, the prognostic value of stress global circumferential strain (sGCS) remains unknown. Purpose To investigate the prognostic value of sGCS for predicting cardiovascular events using a fully automatic machine learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular death or nonfatal myocardial infarction (MI). A fully automatic machine learning algorithm was trained and validated on unseen CMR studies (MAGNETOM Aera and Skyra, Siemens Healthcare, Erlangen, Germany) to assess the sGCS from short-axis cine images at stress. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of sGCS. Results Among 2,906 consecutive patients who underwent stress CMR, the automatic sGCS was successfully computed in 2,859 (98.4%) patients (68% male, mean age 64±12 years). A total of 256 (8.8%) MACEs were observed during a median (IQR) follow-up period of 4.5 (3.7-5.3) years. Using Kaplan-Meier analysis, sGCS and the presence of inducible ischemia were significantly associated with the occurrence of MACE (hazard ratio, HR: 1.12 [95% CI, 1.08-1.17]; and HR: 8.48 [95% CI, 6.05-11.91], both p&amp;lt;0.001; respectively). After adjustment for traditional risk factors, inducible ischemia and late gadolinium enhancement (LGE), sGCS was an independent predictor of a higher incidence of MACE (adjusted HR: 1.12 [95% CI, 1.05-1.20]). Finally, sGCS showed an incremental prognostic value to predict MACE compared to a multivariable model including traditional risk factors, the presence of inducible ischemia and LGE (C-statistic improvement: 0.05, p=0.007; NRI= 0.169; IDI= 0.097; both p&amp;lt;0.001). Conclusions Automatic sGCS has an incremental prognostic value to predict MACE above traditional risk factors, and other stress CMR parameters.Survival curvesIncremental prognostic value

Fully automated assessment of global longitudinal strain by machine learning predicts death in patients undergoing stress CMR

Abstract Background Several studies described the independent prognostic value of left ventricular global longitudinal strain (GLS) using cardiovascular magnetic resonance (CMR) to predict death and cardiovascular events. While routine GLS evaluation is a time consuming and partially operator-dependent process, the potential interest of GLS using a fully automated method has not yet been established. Purpose To assess the feasibility and prognostic value of GLS to predict all-cause death using a fully automated machine-learning algorithm without human correction in consecutive patients referred for stress CMR. Methods Between 2016 and 2018, all consecutive patients referred for stress CMR were included and followed for the occurrence of all-cause death. A fully automated machine learning algorithm was trained and validated on unseen CMR studies (MAGNETOM Aera and Skyra) to assess the GLS from long-axis cine images acquired at rest. The algorithm combines multiple deep learning networks for detection and segmentation with an active contours approach. Cox regressions were performed to determine the prognostic value of GLS. Results In a retrospective study of 9,883 consecutive patients who underwent stress CMR between 2016 and 2018, automated GLS was successfully computed in 9,638 (97.5%) patients (67% male, mean age 66±12 years). A total of 510 (5.3%) deaths were observed during a median follow-up period of 4.5 years (interquartile range: 3.7-5.2). GLS, the presence of inducible ischemia and late gadolinium enhancement (LGE) were significantly associated with the occurrence of death (hazard ratio, HR: 1.22 [95% CI, 1.17-1.26]; HR: 2.23 [95% CI, 1.61-3.10]; and HR: 2.04 [95% CI, 1.41-2.95], respectively, all p&amp;lt;0.001). After adjustment for traditional risk factors, inducible ischemia and LGE, GLS was an independent predictor of a higher incidence of death (adjusted HR: 1.14 [95% CI, 1.08-1.20]). Automated GLS showed an incremental prognostic value to predict death compared to traditional risk factors, inducible ischemia and LGE (C-statistic improvement: 0.05; NRI=0.146; IDI=0.244; all p&amp;lt;0.001). Conclusions Fully automated GLS measured at rest has an incremental prognostic value to predict all-cause death above traditional risk factors, and other stress CMR parameters. This finding suggests that unsupervised GLS measurements are accurate and allow improved risk stratification.

Feature-based clustering of left ventricular strain curve for risk stratification in the general population

Abstract Objective Global left ventricular (LV) strain has been identified as an important predictor of adverse cardiovascular (CV) events. However, currently only the peak strain is used from the LV deformation curve, neglecting the temporal information hidden in all phases of cardiac cycle. Therefore, we employed unsupervised machine learning methods on time-series-derived features from LV strain to identify distinct clinical phenogroups associated with the risk of developing adverse events in the general population. Design and Method We prospectively studied 1185 community-dwelling individuals (mean age, 53.2 years; 51.3% women), in whom we acquired clinical and echocardiographic data including LV strain traces at baseline and collected CV events (n=116) on average 8.7 years later. We utilised Gaussian Mixture Model (GMM) on different features derived from LV strain curve, including slope during systole and early diastole, peak strain, slope during late diastole and the duration and height of diastasis (Figure, left panel). We evaluated the clinical significance of the clusters (k) by comparing the clinical characteristics and CV adverse outcome. Results Based on inertia and BIC scores the optimal number of clusters (k) was 4. The first two clusters had differences in heart rate, but had similar low CV risk profiles. Cluster 4 had the worst CV risk factors combination, and higher prevalence of LV remodelling and diastolic dysfunction (i.e. lowest e’ velocity and highest E/e’) compared to other clusters. Kaplan–Meier showed an increased cumulative incidence risk for all CV events across clusters (Figure, right panel). After adjustment for traditional risk factors, the risk was significantly higher in clusters 3 (HR: 1.28; 95% CI: 1.01-1.61; P=0.038) and 4 (HR: 1.20; 95% CI: 1.02-1.43; P=0.034) compared to the average population, while the risk of adverse events did not reach the significant level in subjects with an abnormal peak LV strain (&amp;lt;17%) (HR 1.12; P=0.66). Conclusion Unsupervised machine learning algorithm employed on features derived from time series LV strain curves identifies clinically meaningful clusters, and provides important prognostic information over the peak LV strain.

Abstract 12316: Metrnl Deficiency Destabilized the Atherosclerotic Plaque and Increased the Risk of Acute Coronary Syndrome

Introduction: Metrnl has been recently identified as a myokine/adipokine that acts as an immune/metabolic regulator. Hypothesis: Metrnl might be exert an important role in acute coronary syndrome. Methods: Circulating Metrnl levels were evaluated in 983 subjects with acute coronary syndrome and healthy controls recruited from Jinan Central Hospital. Apolipoprotein E-deficient mice infected with Metrnl-silencing adenovirus were used for investigating the function of Metrnl in atherosclerotic plaques. The relevant molecular mechanisms were then explored in-vitro in siMetrnl transfected and Metrnl treated HUSMC cells. Results: We found circulating Metrnl levels were significantly decreased in patients with ACS as compared to healthy controls. Metrnl were inversely associated with the incident and recurrent risk of acute coronary syndrome after adjustment for traditional risk factors. Metrnl inhibition in HFD-fed ApoE-/- mice resulted in aggravated atherosclerotic lesions with an SMC-poor/macrophage-rich fibrous cap. Further study demonstrated that Metrnl downregulation increased whereas overexpression prevented SMCs apoptosis and lipid trans-differentiation. KIT/SRC/AKT signaling pathway is involved in the role of Metrnl for the regulation of SMCs fate. Conclusions: Our findings demonstrated that decreased circulating Metrnl levels might be a potential biomarker for identification of patients with increased risk of acute coronary syndrome. Metrnl protected against apoptosis and lipid trans-differentiation in SMCs and stabilized the atherosclerotic plaque, suggesting a potential target for the treatment of atherosclerosis.