Predictor Of Cardiovascular Mortality Research Articles

Progression of valve heart disease in a cohort of patients undergoing renal replacement therapy.

Cardiovascular disease is an important cause of death among patients with chronic kidney disease (CKD). Valve calcification is a predictor of cardiovascular mortality and coronary artery disease. To assess heart valve disease frequency, associated factors, and progression in CKD patients. We conducted a retrospective study on 291 CKD patients at Hospital das Clínicas de Pernambuco. Inclusion criteria were age ≥ 18 with CKD and valve disease, while those on conservative management or with missing data were excluded. Clinical and laboratory variables were compared, and patients were categorized by dialysis duration (<5 years; 5-10 years; >10 years). Statistical tests, including chi-square, Fisher's exact, ANOVA, and Kruskal-Wallis, were employed as needed. Simple and multivariate binary regression models were used to analyze valve disease associations with dialysis duration. Significance was defined as p < 0.05. Mitral valve disease was present in 82.5% (240) of patients, followed by aortic valve disease (65.6%; 86). Over time, 106 (36.4%) patients developed valve disease. No significant association was found between aortic, pulmonary, mitral, or tricuspid valve disease and dialysis duration. Secondary hyperparathyroidism was the sole statistically significant factor for mitral valve disease in the regression model (OR 2.59 [95% CI: 1.09-6.18]; p = 0.031). CKD patients on renal replacement therapy exhibit a high frequency of valve disease, particularly mitral and aortic valve disease. However, no link was established between dialysis duration and valve disease occurrence or progression.

#2099 Long term outcomes in chronic kidney disease patients with heart failure with preserved ejection fraction

Abstract Background and Aims Heart failure (HF) is frequent in chronic kidney disease (CKD) and leads to high morbidity and mortality in this patient category. The aim of our study is to assess the clinical and biological profile, and outcomes in CKD patients with preserved left ventricular ejection fraction (LVEF). Method We prospectively enrolled CKD patients (pts) in pre-dialysis, stratified in two groups by the presence of heart failure symptoms: pts with NYHA class 1-2 (asymptomatic HF) versus pts with NYHA class 3-4 (symptomatic HF). Demographics, clinical history, co-morbidities, physical exam, ambulatory blood pressure monitoring, extensive blood chemistry, systemic inflammation and mineral bone disease parameters were recorded. Cardiac structure and systolic and diastolic function were assessed by echocardiography. Carotid Doppler ultrasound assessed intima media thickness (IMT). Al patients were followed until death of loss from records; patients with less than 6 months of surveillance were excluded. Primary endpoint was all-cause mortality. Secondary endpoints were cardiovascular mortality, a composite cardiac endpoint composite cardiac endpoint comprising coronary heart disease, heart failure hospitalization and new-onset arrhythmia, and reaching the end stage of renal disease (ESRD). Results We included 76 CKD patients (2 pts CKD stage 1, 9 pts CKD stage 2, 19 pts CKD stage 3a, 28 pts CKD stage 3b, 18 pts CKD stage 4) with LVEF ≥ 50%. Mean age 64.7 ± 11.4 years (yrs), men = 56 (73.7%). Mean follow up period was 86 ± 46.4 months (range 6-156 months). Patients with symptomatic HF (54 pts, 71.1%) were older (68 ± 9 vs 56 ± 12 yrs), hypertensive (98.1% vs 86.4%, p &amp;lt; 0.05), more frequent coronary artery disease (66.7% vs 27.3%, p &amp;lt; 0.05), had worse baseline biological profile: lower eGFR (36.9 ± 12.9 vs 55.5 ± 22.7 ml/min/1.73 m2, p &amp;lt; 0.05), lower serum albumin (4.1 ± 0.5 vs 4.4 ± 0.4 g/dl, p &amp;lt; 0.05), as well as higher levels of osteoprotegerin and fetuin A (p &amp;lt; 0.05). Also, symptomatic HF pts had more severe endothelial disease (higher IMT 0.81 ± 0.14 vs 0.63 ± 0.11 mm, p &amp;lt; 0.05), more severe subclinical LV dysfunction revealed by less negative global longitudinal strain GLS (−16.7 ± 2.66 vs −19.2 ± 2.95, p &amp;lt; 0.05) and higher ratio of mitral velocity to early diastolic velocity of the mitral annulus E/E` (12.64 ± 3.63 vs 9.68 ± 2.73, p &amp;lt; 0.05), as well as higher LV mass index (121.5 ± 31 vs 104.9 ± 22.7 g/m2, p &amp;lt; 0.05) and higher left atrial volume index LAVI (42.8 ± 16.8 vs 31.8 ± 11.3 ml/m2, p &amp;lt; 0.05) All-cause mortality was 17.1% (13 events), while cardiovascular mortality was 6.6% (5 events). All deaths were recorded in the symptomatic HF group. Also, a higher percent of pts from symptomatic HF group reached the composite cardiac endpoint (44.4% vs 22.7%) and ESRD (33.3% vs 18.2%) compared to asymptomatic HF group. Kaplan-Meier survival analysis showed significantly higher all-cause mortality (log rang = 0.008) and lower ESRD-free survival (log rank= 0.045) in symptomatic HF group. All-cause mortality was significantly correlated with NYHA class (p &amp;lt; 0.0001), etiology of CKD (p = 0.038), eGFR (p &amp;lt; 0.0001), proteinuria (p = 0.001), intact PTH (p = 0.008), osteocalcin (p = 0.012), osteopontin (p = 0.029), FGF23 (p = 0.044), IL6 (p = 0.037), GLS (p = 0.023), E/E` (p = 0.009). Cardiovascular mortality was significantly correlated with NYHA class (p = 0.019), etiology of CKD (p = 0.008), eGFR (p = 0.011), proteinuria (p = 0.001), intact PTH (p = 0.008), osteocalcin (p = 0.011), osteopontin (p = 0.006), FGF23 (p = 0.006). Cox regression analysis identified NYHA class (p = 0.004), FGF23 (p = 0.009) and IL6 (p = 0.025) as predictors for all-cause mortality, while E/E` (p = 0.032) and intact PTH (p-0.042) were predictors for cardiovascular mortality. Conclusion In our study, CKD pts with symptomatic HF carry a significant burden of morbidity and mortality, even in the case of preserved LV ejection fraction. This emphasizes the need for more comprehensive regular assessments of subclinical cardiac dysfunction in CKD pts. This approach might support targeted interventions, better symptom control, and improved long term outcomes.

Artificial Intelligence-Derived Risk Prediction: A Novel Risk Calculator Using Office and Ambulatory Blood Pressure.

Quantification of total cardiovascular risk is essential for individualizing hypertension treatment. This study aimed to develop and validate a novel, machine-learning-derived model to predict cardiovascular mortality risk using office blood pressure (OBP) and ambulatory blood pressure (ABP). The performance of the novel risk score was compared with existing risk scores, and the possibility of predicting ABP phenotypes utilizing clinical variables was assessed. Using data from 59 124 patients enrolled in the Spanish ABP Monitoring registry, machine-learning approaches (logistic regression, gradient-boosted decision trees, and deep neural networks) and stepwise forward feature selection were used. For the prediction of cardiovascular mortality, deep neural networks yielded the highest clinical performance. The novel mortality prediction models using OBP and ABP outperformed other risk scores. The area under the curve achieved by the novel approach, already when using OBP variables, was significantly higher when compared with the area under the curve of the Framingham risk score, Systemic Coronary Risk Estimation 2, and Atherosclerotic Cardiovascular Disease score. However, the prediction of cardiovascular mortality with ABP instead of OBP data significantly increased the area under the curve (0.870 versus 0.865; P=3.61×10-28), accuracy, and specificity, respectively. The prediction of ABP phenotypes (ie, white-coat, ambulatory, and masked hypertension) using clinical characteristics was limited. The receiver operating characteristic curves for cardiovascular mortality using ABP and OBP with deep neural network models outperformed all other risk metrics, indicating the potential for improving current risk scores by applying state-of-the-art machine learning approaches. The prediction of cardiovascular mortality using ABP data led to a significant increase in area under the curve and performance metrics.

Gender differences in the relationship between serum uric acid and the long-term prognosis in heart failure: a nationwide study

BackgroundSerum uric acid (SUA) is an important pathogenetic and prognostic factor for heart failure (HF). Gender differences are apparent in HF. Furthermore, gender differences also exist in the association between SUA and prognosis in various cardiovascular diseases. However, the gender difference for SUA in the prediction of long-term prognosis in HF is still ambiguous.MethodsA total of 1593 HF patients (897 men, 696 women) from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 cycle were enrolled in our final analysis. Participants were categorized according to gender-specific SUA tertile. We assessed the association between SUA and long-term prognosis of HF patients, defined as all-cause mortality and cardiovascular mortality, in different genders via Kaplan–Meier curve analysis, Cox proportional hazard model, and Fine-Gray competing risk model. The restricted cubic spline (RCS) was performed to investigate the dose-response relationship between SUA and outcomes.ResultsGender differences exist in demographic characteristics, clinical parameters, laboratory tests, and medication of HF patients. After a median follow-up of 127 months (95% CI 120–134 months), there were 853 all-cause deaths (493 events in men, 360 events in women) and 361 cardiovascular deaths (206 events in men, 155 events in women). Kaplan-Meier analysis showed that SUA had gender difference in the prediction of cardiovascular mortality (Log-rank p < 0.001, for male, Log-rank p = 0.150, for female), but not in all-cause mortality. Multivariate Cox regression analysis revealed that elevated SUA levels were associated with higher all-cause mortality and cardiovascular mortality in men (HR 1.11, 95% CI 1.05-1.18, p < 0.001, for all-cause death; HR 1.18, 95% CI 1.09-1.28, p < 0.001, for cardiovascular death), but not in women (HR 1.05, 95% CI 0.98-1.12, p = 0.186, for all-cause death; HR 1.01, 95% CI 0.91-1.12, p = 0.902, for cardiovascular death). Even using non-cardiovascular death as a competitive risk, adjusted Fine-Gray model also illustrated that SUA was an independent predictor of cardiovascular death in men (SHR 1.17, 95% CI 1.08-1.27, p < 0.001), but not in women (SHR 0.98, 95% CI 0.87 − 1.10, p = 0.690).ConclusionsGender differences in the association between SUA and long-term prognosis of HF existed. SUA was an independent prognostic predictor for long-term outcomes of HF in men, but not in women.

Serum Uric Acid/Serum Creatinine Ratio and Cardiovascular Mortality in Diabetic Individuals-The Uric Acid Right for Heart Health (URRAH) Project.

Several studies have detected a direct association between serum uric acid (SUA) and cardiovascular (CV) risk. In consideration that SUA largely depends on kidney function, some studies explored the role of the serum creatinine (sCr)-normalized SUA (SUA/sCr) ratio in different settings. Previously, the URRAH (URic acid Right for heArt Health) Study has identified a cut-off value of this index to predict CV mortality at 5.35 Units. Therefore, given that no SUA/sCr ratio threshold for CV risk has been identified for patients with diabetes, we aimed to assess the relationship between this index and CV mortality and to validate this threshold in the URRAH subpopulation with diabetes; the URRAH participants with diabetes were studied (n = 2230). The risk of CV mortality was evaluated by the Kaplan-Meier estimator and Cox multivariate analysis. During a median follow-up of 9.2 years, 380 CV deaths occurred. A non-linear inverse association between baseline SUA/sCr ratio and risk of CV mortality was detected. In the whole sample, SUA/sCr ratio > 5.35 Units was not a significant predictor of CV mortality in diabetic patients. However, after stratification by kidney function, values > 5.35 Units were associated with a significantly higher mortality rate only in normal kidney function, while, in participants with overt kidney dysfunction, values of SUA/sCr ratio > 7.50 Units were associated with higher CV mortality. The SUA/sCr ratio threshold, previously proposed by the URRAH Study Group, is predictive of an increased risk of CV mortality in people with diabetes and preserved kidney function. While, in consideration of the strong association among kidney function, SUA, and CV mortality, a different cut-point was detected for diabetics with impaired kidney function. These data highlight the different predictive roles of SUA (and its interaction with kidney function) in CV risk, pointing out the difference in metabolic- and kidney-dependent SUA levels also in diabetic individuals.

Metabolic syndrome and hyperuricemia: features of patient management (clinical case)

Metabolic syndrome (MS) is a group of interrelated metabolic disorders such as high blood pressure, central obesity, insulin resistance (IR), dyslipidemia. The main mechanisms that indicate a metabolic disorder and contribute to its development are IR and a large amount of circulating free fatty acids. In turn, tissue IR is often combined with other abnormalities including disorders of uric acid metabolism, changes in the hemostasis system, endothelial dysfunction, increased levels of C-reactive protein. At the same time, metabo­lic disorders are a risk factor for hyperuricemia. MS occurs in 25–60 to 90 % of all gout patients. About 50 % of patients with hyperuricemia have symptoms of MS. Hyperuricemia as a component of MS is a predictor of cardiovascular mortality, development of diabetes mellitus, hypertension and nephrolithiasis. Hyperuricemia is closely related to diabetes, obesity, coronary heart disease, hypertension. On the example of a clinical case, the main components of MS are considered, as well as the issue of the relationship between hyperuricemia, gout and the components of MS. The main idea behind the creation of the MS concept is to select a population of patients at a high cardiovascular risk in whom preventive measures such as lifestyle modification and the use of adequate drugs can significantly affect the main health indicators. The goal of managing patients with MS is to minimize cardiovascular risk and mortality as much as possible. Accordingly, the therapeutic strategy should include optimal ways to modify the lifestyle; lowering blood pressure to the target level and treating comorbid conditions; reducing low-density lipoprotein cholesterol according to the risk profile: &gt; 50 %, and &lt; 70 mg/dL (1.4 mmol/L) in patients at a very high cardiovascular risk; &gt; 50 %, and &lt; 100 mg/dL (1.8 mmol/l) in high-risk patients; reducing fasting serum glucose &lt; 126 mg/dl (7 mmol/l) or glycated hemoglobin &lt; 7 % (53 mmol/mol); maintaining uric acid level &lt; 6.5 mg/dL (0.387 mmol/L), in patients with gout — below 6 mg/dL (0.357 mmol/L). Thus, according to the results of the research, a causal relationship was found between insulin resistance and serum uric acid levels in patients with metabolic syndrome. The strategy for managing patients with metabolic syndrome should include screening and correction of hypertension, carbohydrate purine metabolism, dyslipidemia, and prevention of cardiovascular events.

Canonical Correlation for the Analysis of Lifestyle Behaviors versus Cardiovascular Risk Factors and the Prediction of Cardiovascular Mortality: A Population Study

Objectives: To assess the overall association of lifestyle behaviors with multiple cardiovascular risk factors and mortality. Material and Methods: In the Italian Rural Areas of the Seven Countries Study, involving 1712 middle-aged men (40–59 years) enrolled in 1960, smoking habits, physical activity, dietary habits, marital status, and socioeconomic status (SES) were studied as possible determinants of 15 measurable risk factors (body mass index, tricipital and subscapular skinfold, arm circumference, systolic and diastolic blood pressure, heart rate, double product (systolic blood pressure × heart rate), vital capacity, forced expiratory volume, serum cholesterol, urine protein, urine glucose, corneal arcus and xanthelasma) using canonical correlation (CC). Results: The first CC had a value of 0.54 (R2 0.29, p &lt; 0.0001). The role of marital status was marginal; that of a high SES was contrary to expectations. The strongest behaviors based on standardized CC coefficients were dietary habits and physical activity. The risk factors mostly associated with overall lifestyle behaviors were some anthropometric and cardiovascular measurements. The mean levels of risk factors distributed in tertile classes of the CC variate score of lifestyle behaviors were largely associated in a coherent and graded way with the expected relationship of behaviors versus risk factors. In a large series of Cox models, the CC variate scores were significantly associated with 50-year coronary heart disease (CHD) mortality and much less with stroke and other heart diseases of uncertain etiology. Conclusions: Lifestyle behaviors correlate well with cardiovascular risk factors associated with CHD mortality, and CC is a useful method of analysis to detect long-term impacting characteristics.

Left ventricular global work index and prediction of cardiovascular mortality after transcatheter aortic valve implantation

IntroductionEchocardiography is used for assessment of patients after transcatheter aortic valve implantation (TAVI). Global work index (GWI) integrates LV deformation throughout the cardiac cycle and LV afterload and may be advantageous for long-term follow-up. MethodsWe analysed 144 patients with severe aortic stenosis who underwent TAVI and echocardiography within two weeks afterwards. GE EchoPAC v2.6 was applied for determining LV ejection fraction, global longitudinal strain (GLS), stroke work (SW), cardiac power output (CPO), and GWI. The endpoint was cardiovascular mortality. ResultsDuring median follow-up of 625 [IQR: 511–770] days, 20 (14%) patients died. Clinical baseline characteristics were comparable between non-survivors and survivors. GWI (p = 0.003) and LVEF (p = 0.039) were lower in non-survivors, while GLS, SW, and CPO were not different. In Kaplan-Meier analysis patients with GWI ≤1234 mmHg% exhibited a lower survival probability (P = 0.006). In univariable Cox regression, a significant mortality association was identified for GWI (P = 0.004), weaker for LVEF (P = 0.014), but not for the other parameters. In multivariable Cox regression, GWI independently improved an LV systolic function model including LVEF and GLS. Similarly, GWI but not LVEF independently improved outcome association of different clinical models. ConclusionsGWI was lower in non-survivors than survivors, differentiated non-survivors from survivors, was associated with mortality independent of clinical or LV parameters, and improved the fitness of clinical or LV prediction models. In contrast, GLS, SW, and CPO did not show any of these properties. GWI provides added value for follow-up after TAVI possibly by integrating LV deformation throughout the cardiac cycle.

Association of left atrial strain with long-term cardiovascular mortality in hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is a relatively common genetic cardiac disease affecting 1 in 200 people. Although sudden cardiac death (SCD) is considered the most devastating event in patients with HCM, cardiovascular death (CVD) is the leading cause of death in this population. Little is known about the predictors of cardiovascular mortality. Purpose The aim of this study was to investigate prognostic implication of left atrial (LA) strain on long-term cardiovascular mortality in patients with HCM. Methods Peak longitudinal LA strain was measured on echocardiography at initial evaluation using vendor-independent speckle-tracking software. Among a prospective cohort of 865 HCM patients collected at two large tertiary centers, 697 with adequate echocardiographic images to measure biplane LA strain were included in the analysis. The primary endpoint was CVD during 10 years after initial evaluation. Results The median age was 56.0 years and 74.6% were male. Among the 697 patients, 25 died due to cardiovascular cause for 10 years. Among clinical and echocardiographic variables, older age, female sex, previous myocardial infarction, previous stroke, higher SCD risk score by European Society of Cariology, presence of SCD risk factors by American College of Cardiology, obstructive HCM, larger LA diameter, and lower LA strain were associated with CVD. LA strain had the highest predictive power for CVD occurrence, with a c-statistic of 0.79 (Figure 1). In multivariable Cox analysis, LA strain remains an independent predictor of CVD (hazard ratio [HR] 0.88, 95% confidence interval [CI] 0.82–0.94). Patients with LA strain &amp;lt;19.4% (the lowest quartile), compared with those with LAS ≥19.4%, had a significantly higher risk of CVD (19.5% vs. 2.1%, HR 7.31, 95% CI 3.15–16.95), as well as death by any cause, SCD, and a composite of CVD, heart failure admission, and stroke (Figure 2). Conclusions In patients with HCM, LA strain is an independent predictor of long-term CVD.

Non-invasive pressure-volume loops from cardiovascular magnetic resonance predict cardiovascular mortality in heart failure with reduced ejection fraction

Abstract Background Heart failure with reduced ejection fraction (HFrEF) is characterized by impaired ventricular energetics secondary to ventricular remodeling. Left ventricular pressure-volume (PV) loop analysis (Figure 1) can now be performed noninvasively using cardiovascular magnetic resonance (CMR) imaging, enabling study of cardiac thermodynamic efficiency without the risk and cost associated with invasive measurements (1–3). Here we investigated whether noninvasive PV loops from CMR can predict cardiovascular death in HFrEF patients. Methods We analyzed 135 datasets (age 60±12 years, 79% male) from HFrEF patients (LVEF≤40%) who underwent clinical CMR examination at our center between 2004-2013. Pressure-volume loop parameters were computed from manually segmented CMR data and same-day brachial blood pressure (Segment 4.0 R11026, Medviso, Lund, Sweden). The primary endpoint was cardiovascular mortality extracted from national registries with a 5-year follow-up. Parameters of interest were selected from univariate Cox regression, and associations with clinical outcome evaluated using multivariate Cox regression. Survival was visualized using Kaplan-Meier analysis. Statistical analysis was performed in R 4.0.3 (R Core Team). Results A total of 19 deaths from cardiovascular causes occurred during follow-up. Univariate Cox regression found stroke work (SW, joule), ventricular efficiency (VE, %), external power (J/s), contractility (mmHg/ml), and energy per ejected volume (mJ/ml) computed from PV loops associated with the primary endpoint alongside age, LVEF, and NT-proBNP level. In multivariate Cox regression adjusted for age, ventricular efficiency remained significant (HR 0.86, p&amp;lt;0.001), while EF did not (p = 0.077). Event-free survival is shown in Figure 2. Conclusion Ventricular efficiency derived from non-invasive pressure-volume loop analysis from standard CMR scans, may outperform LV EF as a predictor of cardiovascular mortality in HFrEF. Figures: Figure 1. Example of left ventricular pressure-volume (PV) loop. The area enclosed by the loop is the stroke work (SW). The area bounded by the PV loop and the end-systolic pressure-volume relationship (ESPVR) is the potential energy (PE). Ventricular efficiency (VE) is calculated as SW/(PE+SW). Figure 2. Kaplan-Meier plots of survival by tertiles of stroke work and ventricular efficiency.Figure 1Figure 2

Abstract 12323: Cardiovascular Mortality Prediction Depends on the Time Point of Blood Pressure Measurement Rather Than on the Use of European versus US Blood Pressure Categorizations

Introduction: Blood pressure (BP) is a predictor of cardiovascular risk but it changes during lifetime. Hypothesis: We hypothesize that there are differences in the value of systolic and diastolic blood pressure (BP) at different stages of life for predicting cardiovascular mortality risk, an issue which was addressed in this observation study (OS). Methods: At the baseline of the OS, BP was measured in 1497 cardiovascular disease patients at a median age of 65 years, and their outcome was recorded over 21 years. Fifteen years prior to the OS, the identical patients had participated in a health survey (HS) comprising BP measurement. The value of earlier (HS) vs. recent (OS) BP measurements for risk prediction was addressed using both guideline-defined BP categorizations from Europe (ESC/ESH) and the US (ACC/AHA). Results: BP at HS was a significantly better predictor of cardiovascular mortality than BP at OS (NRIESC/ESH=0.29, p&lt;0.001; NRIACC/AHA=0.30, p&lt;0.001). Each 10mm Hg increase was significantly positively associated with cardiovascular mortality for both systolic and diastolic blood pressure (HR=1.17 [1.11-1.23] and 1.20 [1.09-1.32], respectively) when measured at HS. In contrast, regarding systolic BP recorded at OS, the significant association with cardiovascular mortality (HR=1.04 [0.98-1.10]) was abrogated, and with diastolic BP the association has reversed (HR=0.82 [0.74-0.92]. In contrast, ESC/ESH and ACC/AHA BP categorizations were comparably valuable predicting cardiovascular mortality (NRIHS=0.04, p=0.563; NRIOS=0.02, p=0.817). Conclusions: Irrespective of categorization differences between European and US BP guidelines, earlier-in-life BP readings are valuable risk predictors for cardiovascular mortality and they outperform BP readings done at a more advanced age.

Abstract 12178: Association Between QT Prolongation and Cardiovascular Mortality in Cancer Patients

Introduction: The QT interval (QT) is a safeguard criterion to avoid detrimental arrhythmias. Cancer patients are vulnerable to QT prolongation. However, its prognostic impact on cardiovascular (CV) mortality in cancer patients is not clear. Research questions: Which is the best QTc formula to predict CV mortality in cancer patients? Whether a QT interval would be a suitable predictor for CV mortality in cancer patients? Methods: This retrospective observational cohort included adult cancer patients who had an electrocardiogram (ECG) performed in a tertiary hospital in Taiwan. The first performed ECGs after cancer diagnosis (n=59,568) were analyzed. The corrected QT intervals by Bazett (QTcB), Fridericia (QTcFri), and Framingham (QTcFra) formulae were used to predict the 90-day and one-year CV mortality according to the Taiwan death registry. Results: The AUC of QTcB (0.70) for predicting CV mortality at 90 days was better than QTcFri and QTcFra (0.63 and 0.50). The AUC of QTcB (0.68) for predicting CV mortality at one year was also better than QTcFri and QTcFra (0.65 and 0.56).Using the restricted cubic spline regression model adjusted by age and comorbidities, QTcB increased a significant but trivial risk of CV mortality at 90 days (hazard ratio, 1.007, P= 0.02) and one year (1.006, P &lt;0.01). Compared to those with QTcB &lt;500ms, the patients with QTcB ≥500ms were older, had more comorbidities, and higher CV (1.74%), cancer (24.5%), and all-cause mortalities (32.5%) within one year. The incidence of sudden death and ventricular arrhythmias was only 0.2%. After adjusting for comorbidities, QTcB was neither associated with 90-day nor one-year CV mortality. Conclusions: Rather than a long QT interval per se, comorbidities contributed to CV mortality and irreversible outcome in cancer patients.

Abstract 13430: Cardiovascular Magnetic Resonance Imaging for Comprehensive Risk Assessment in Patients With Aortic Stenosis

Introduction: Precise risk assessment is essential for accurate management of patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). This study aimed to assess the prognostic implications of cardiovascular magnetic resonance (CMR)-derived imaging biomarkers in a large cohort of AS patients. Methods: 145 patients with severe AS underwent CMR imaging before TAVR. Image analyses included myocardial volumes, CMR-feature-tracking derived left and right atrial (LA &amp; RA) as well as left and right ventricular (LV &amp; RV) strain, myocardial T1 mapping as well as late gadolinium enhancement analyses. Cardiovascular (CV) mortality was defined as primary clinical endpoint. Results: Patients with CV death during follow-up had significantly enlarged RV enddiastolic volumes (82.9ml/ml 2 [70.8-96.0] vs. 62.8ml/ml 2 [54.7-76.0], p&lt;0.001) and impaired strain values of all cardiac chambers compared to patients that survived (LV GLS: -18.1% [-13.1- -20.4] vs. -22.5% [-16.1- -27.3], p=0.019; RV GLS: -22.9% [-18.6 - -25.4] vs. -27.9% [-22.9- -32.0], p=0.002; LA Es: 9.5% [7.2 - 15.4] vs. 14.3% [9.0-18.1], p=0.036; RA Es: 12.4% [6.8-14.4] vs. 16.2% [11.2-22.1], p&lt;0.001). RA reservoir strain independently predicted CV mortality after adjusting for other CMR imaging biomarkers and clinical parameters of heart failure. Within patients with high ECV values especially RA strain further identified AS patients at high-risk for CV mortality (p=0.001 on log-rank testing). Conclusion: Comprehensive CMR-imaging allows accurate outcome assessment and additional identification of high-risk groups in AS patients. Especially RA strain emerged as independent predictor for cardiovascular mortality and might serve for future optimized patient management.

Relation between impaired coronary microvascular circulation and plasma atherogenic index in patients with ankylosing spondylitis

Aim: The coronary flow reserve (CFR) is a sign of endothelial dysfunction and early-stage coronary artery disease (CAD). Plasma atherogenic index (PAI) is related to subclinical CAD and may be used as a predictor of cardiovascular mortality. Our aim is to determine CFR and PAI in patients with AS and to investigate whether PAI can be used in the detection of early stage CAD.&#x0D; Methods: The study population comprised 48 patients, who were diagnosed with AS based on modified New York criteria and 35 healthy volunteers. PAI values were calculated with the formula log 10 triglyceride (TG) / high-density lipoprotein (HDL).&#x0D; Results: No difference was detected between the two groups for the demographic variables, including age, sex and BMI. The comparison of the groups for PAI and CFR demonstrated that PAI levels were observed to be significantly higher and CFR levels were observed to be significantly lower in the AS patients (p=0.01, p

Door to Balloon Time of Non-ST Elevation Myocardial Infarction May be Reconsidered According to Systemic Immune-Inflammation Index.

Aim Early diagnosis and treatment is very important in acute coronary syndromes (ACS). Previous studies showed that not all non-ST elevation myocardial infarction (NSTEMI) patients should be considered and treated in the same way. The systemic immune-inflammation index (SII), which is an easily accessible, rapidly computed, and cost-effective parameter, was evaluated in this study to determine the optimal intervention time for NSTEMI.Material and methods 469 patients diagnosed with ACS were included to the study. STEMI and NSTEMI patients were compared according to their SII. Univariate and binary logistic regression analysis were performed to determine which parameters have a significant effect on the discrimination of types of myocardial infarction.Results The mean age of the patients was 61.43±11.52 yrs, and 348 (74.2 %) were male. NSTEMI patients with an SII value higher than 768×109 / l may be assumed to be STEMI (p&lt;0.001). Univariate analysis and binary logistic regression showed that only SII and hypertension had statistically impact on differentiation of STEMI and NSTEMI. In addition, SII value of 1105×109 / l was the cut-off point for discrimination of cardiovascular survival (p&lt;0.001, AUC =0.741). This study was performed to find out which NSTEMI patients should be treated percutaneously immediately after first medical contact according to SII. It was found that, SII value of higher than 768×109 / l is related with STEMI.Conclusion In conclusion, NSTEMI patients with a SII value higher than 768×109 / l may be considered as STEMI and treated with in 120 min after first contact. In addition, SII was found to be a cardiovascular mortality predictor after myocardial infarction, and this may be used for identifying high-risk patients after percutaneous coronary intervention.

Remnant cholesterol predicts cardiovascular mortality beyond low-density lipoprotein cholesterol in patients with peritoneal dialysis

Patients undergoing peritoneal dialysis (PD) are prone to dyslipidemia. However, studies concerning remnant cholesterol (RC) in such patients are limited. We aimed to investigate the association between RC and cardiovascular (CV) mortality in patients on PD. Patients who initiated PD at our center (2006-2018) were retrospectively enrolled. Adjusted Cox models were used to evaluate the independent association between baseline RC levels and CV mortality. We classified patients into 4 concordant/discordant categories according to their baseline lipid profiles. Cox models were then used to determine the association between different low-density lipoprotein cholesterol (LDL-C) and RC levels and CV mortality risk. The study enrolled 2333 individuals, with a mean RC of 33.4mg/dl. RC levels were positively associated with CV mortality risk independent of LDL-C in patients on PD (hazard ratio [HR]: 1.05; 95% confidence interval [CI]: 1. 00-1.10). In the concordant/discordant categories, patients with high LDL-C and RC levels had a higher CV mortality risk (HR: 1.52; 95% CI: 1.01-2.28) than those with low LDL-C and RC levels in the entire cohort. Moreover, in older patients, a higher RC level increased CV mortality risk regardless of the LDL-C level (HR: 2.41, 95% CI: 1.22-4.74; HR: 2.15, 95% CI: 1.12-4.14). RC levels are elevated in patients on PD and can predict CV mortality beyond LDL-C levels. RC levels should be considered alongside LDL-C levels when assessing prognostic lipid levels in these patients. More attention should be given to RC than to LDL-C in older patients undergoing PD.

A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study

In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respiratory causes were identified whereby the CNN model was used to capture imaging features in the CT scans and the RNN model was used to investigate time series and thus global information. To account for heterogeneity in patients' follow-up times, two different variants of LSTM models were evaluated, each incorporating different strategies to address irregularities in follow-up time. The models were trained on subjects who underwent cardiovascular and respiratory deaths and a control cohort matched to participant age, gender, and smoking history. The combined model can achieve an AUC of 0.76 which outperforms humans at cardiovascular mortality prediction. The corresponding F1 and Matthews Correlation Coefficient are 0.63 and 0.42 respectively. The generalisability of the model is further validated on an ‘external’ cohort. The same models were applied to survival analysis with the Cox Proportional Hazard model. It was demonstrated that incorporating the follow-up history can lead to improvement in survival prediction. The Cox neural network can achieve an IPCW C-index of 0.75 on the internal dataset and 0.69 on an external dataset. Delineating subjects at increased risk of cardiorespiratory mortality can alert clinicians to request further more detailed functional or imaging studies to improve the assessment of cardiorespiratory disease burden. Such strategies may uncover unsuspected and under-recognised pathologies thereby potentially reducing patient morbidity.

Machine Learning for Risk Factor Identification and Cardiovascular Mortality Prediction Among Patients with Osteoporosis.

Risk prediction tools are increasingly popular aids in clinical decision-making. However, the underlying models are often trained on data from general patient cohorts and may not be representative of and suitable for use with targeted patient groups in actual clinical practice, such as in the case of osteoporosis patients who may be at elevated risk of mortality. We developed and internally validated a cardiovascular mortality risk prediction model tailored to individuals with osteoporosis using a range of machine learning models. We compared the performance of machine learning models with existing expert-based models with respect to data-driven risk factor identification, discrimination, and calibration. The proposed models were found to outperform existing cardiovascular mortality risk prediction tools for the osteoporosis population. External validation of the model is recommended.Clinical Relevance- This study presents the performance of machine learning models for cardiovascular death prediction among osteoporotic patients as well as the risk factors identified by the models to be important predictors.

Cardiovascular mortality in patients with advanced chronic kidney disease with and without diabetes: a nationwide cohort study

BackgroundCardiovascular mortality and the impact of cardiac risk factors in advanced chronic kidney disease (CKD) remain poorly investigated. We examined the risk of cardiovascular mortality in patients with advanced CKD with and without diabetes as well as the impact of albuminuria, plasma hemoglobin, and plasma low-density lipoprotein (LDL) cholesterol levels.MethodsIn a Danish nationwide registry-based cohort study, we identified persons aged ≥ 18 years with an estimated glomerular filtration rate < 30 mL/min/1.73m2 between 2002 and 2018. Patients with advanced CKD were age- and sex-matched with four individuals from the general Danish population. Cause-specific Cox regression models were used to estimate the 1-year risk of cardiovascular mortality standardized to the distribution of risk factors in the cohort.ResultsWe included 138,583 patients with advanced CKD of whom 32,698 had diabetes. The standardized 1-year risk of cardiovascular mortality was 9.8% (95% CI 9.6–10.0) and 7.4% (95% CI 7.3–7.5) for patients with and without diabetes, respectively, versus 3.1% (95% CI 3.1–3.1) in the matched cohort. 1-year cardiovascular mortality risks were 1.1- to 2.8-fold higher for patients with diabetes compared with those without diabetes across the range of advanced CKD stages and age groups. Albuminuria and anemia were associated with increased cardiovascular mortality risk regardless of diabetes status. LDL-cholesterol was inversely associated with cardiovascular mortality risk in patients without diabetes, while there was no clear association in patients with diabetes.ConclusionsDiabetes, albuminuria, and anemia remained important risk factors of cardiovascular mortality whereas our data suggest a limitation of LDL-cholesterol as a predictor of cardiovascular mortality in advanced CKD.

Chronic Electronic Cigarette Users Exhibit Reduced Cardiorespiratory Fitness and Associated Increased Cardiovascular Disease Risk

BACKGROUND: Electronic cigarettes (e-cigs) are popular tobacco products that are currently advertised as a safer alternative to traditional cigarettes. Preliminary data, primarily from animal studies, suggests that e-cigs are associated with an increased cardiovascular disease (CVD) risk. Cardiorespiratory fitness is a marker of cardiovascular (CV) health and a predictor of CV mortality, which is diminished in traditional tobacco users. However, the effect of chronic e-cigs usage on cardiorespiratory fitness and associated CVD risk in otherwise healthy individuals without established CVD or CVD risk factor, is currently unknown. PURPOSE: The purpose of this study was to investigate the impact of chronic e-cig use on cardiorespiratory fitness and CVD risk in healthy young adults. METHODS: Ten chronic e-cig users (ECU, 4 males and 6 females; age: 24±3 yr; e-cigs usage 3±1.5 yr.) and ten demographical matched, never users (NU, 4 males and 6 females; age: 22.7±2 yr.) participated in this study. Cardiorespiratory fitness was measured by peak oxygen consumption (VO2peak) via a respiratory gas exchange analyzer during a cardiopulmonary exercise test. CVD risk was calculated using Framingham’s 30-year CVD risk score accounting for 8 risk factors (age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein, presence of diabetes mellitus, hypertension treatment, and smoking status). RESULTS: Chronic e-cig users exhibited significantly lower VO2peak (ECU vs. NU; 30.9±4.9 vs. 37.8±6.4 ml/kg/min; p=0.015) and percent predicted (ECU vs. NU; 85.9±16 vs. 105.4±14 % predicted; p=0.001) when compared to never users. Framingham’s 30-year CVD risk score was significantly higher in ECU than in NU (7.7± 4.8, vs. 2.7±0.8 %; p=0.017). Furthermore, an inverse association was identified between VO2peak and 30-year CVD risk ( r=-0.720; p= 0.030). CONCLUSIONS: For the first time, we have identified significantly reduced cardiorespiratory fitness, a marker of CV health and mortality risk, in chronic e-cig users when compared to never users. In addition, chronic e-cig users exhibit higher CVD risk scores. Results from our study imply a negative effect of chronic e-cig use on CV health in otherwise young, apparently healthy adults. Future studies are warranted to investigate the long-term effects of e-cig use on CV health. Supported in part by a Rapid Response Project NIDA/FDA (PRM). Supported in part by a Rapid Response Project NIDA/FDA (PRM). This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.