Electrocardiogram Signal Classification in the Diagnosis of Heart Disease Based on RBF Neural Network.

Heart disease is a common disease affecting human health. Electrocardiogram (ECG) classification is the most effective and direct method to detect heart disease, which is helpful to the diagnosis of most heart disease symptoms. At present, most ECG diagnosis depends on the personal judgment of medical staff, which leads to heavy burden and low efficiency of medical staff. Automatic ECG analysis technology will help the work of relevant medical staff. In this paper, we use the MIT-BIH ECG database to extract the QRS features of ECG signals by using the Pan-Tompkins algorithm. After extraction of the samples, K-means clustering is used to screen the samples, and then, RBF neural network is used to analyze the ECG information. The classifier trains the electrical signal features, and the classification accuracy of the final classification model can reach 98.9%. Our experiments show that this method can effectively detect the abnormality of ECG signal and implement it for the diagnosis of heart disease.

The importance of ventilatory thresholds to define aerobic exercise intensity in cardiac patients and healthy subjects.

BACKGROUND: Although structured exercise training is strongly recommended in cardiac patients, uncertainties exist about the methods for determining exercise intensity (EI) and their correspondence with effective EI obtained by ventilatory thresholds. We aimed to determine the first (VT1 ) and second ventilatory thresholds (VT2 ) in cardiac patients, sedentary subjects, and athletes comparing VT1 and VT2 with EI defined by recommendations. METHODS: We prospectively enrolled 350 subjects (mean age: 50.7±12.9 years; 167 cardiac patients, 150 healthy sedentary subjects, and 33 competitive endurance athletes). Each subject underwent ECG, echocardiography, and cardiopulmonary exercise testing. The percentages of peak VO2 , peak heart rate (HR), and HR reserve were obtained at VT1 and VT2 and compared with the EI definition proposed by the recommendations. RESULTS: VO2 at VT1 corresponded to high rather than moderate EI in 67.1% and 79.6% of cardiac patients, applying the definition of moderate exercise by the previous recommendations and the 2020 guidelines, respectively. Most cardiac patients had VO2  values at VT2 corresponding to very-high rather than high EI (59.9% and 50.3%, by previous recommendations and 2020 guidelines, respectively). A better correspondence between ventilatory thresholds and recommended EI domains was observed in healthy subjects and athletes (90% and 93.9%, respectively). CONCLUSIONS: EI definition based on percentages of peak HR and peak VO2  may misclassify the effective EI, and the discrepancy between the individually determined and the recommended EI is particularly relevant in cardiac patients. A ventilatory threshold-based rather than a range-based approach is advisable to define an appropriate level of EI.

Feature Selection and Classification of Clinical Datasets Using Bioinspired Algorithms and Super Learner.

A computer-aided diagnosis (CAD) system that employs a super learner to diagnose the presence or absence of a disease has been developed. Each clinical dataset is preprocessed and split into training set (60%) and testing set (40%). A wrapper approach that uses three bioinspired algorithms, namely, cat swarm optimization (CSO), krill herd (KH) ,and bacterial foraging optimization (BFO) with the classification accuracy of support vector machine (SVM) as the fitness function has been used for feature selection. The selected features of each bioinspired algorithm are stored in three separate databases. The features selected by each bioinspired algorithm are used to train three back propagation neural networks (BPNN) independently using the conjugate gradient algorithm (CGA). Classifier testing is performed by using the testing set on each trained classifier, and the diagnostic results obtained are used to evaluate the performance of each classifier. The classification results obtained for each instance of the testing set of the three classifiers and the class label associated with each instance of the testing set will be the candidate instances for training and testing the super learner. The training set comprises of 80% of the instances, and the testing set comprises of 20% of the instances. Experimentation has been carried out using seven clinical datasets from the University of California Irvine (UCI) machine learning repository. The super learner has achieved a classification accuracy of 96.83% for Wisconsin diagnostic breast cancer dataset (WDBC), 86.36% for Statlog heart disease dataset (SHD), 94.74% for hepatocellular carcinoma dataset (HCC), 90.48% for hepatitis dataset (HD), 81.82% for vertebral column dataset (VCD), 84% for Cleveland heart disease dataset (CHD), and 70% for Indian liver patient dataset (ILP).

Outcome of aortic stenosis according to invasive cardiac damage staging after transcatheter aortic valve replacement.

BACKGROUND: In recent studies, a 5-stage cardiac damage classification in severe aortic stenosis (AS) based on echocardiographic parameters has shown to provide predictive value regarding clinical outcome. The objective of this study was to investigate the prognostic impact of a cardiac damage classification based on invasive hemodynamics in patients with AS undergoing transcatheter aortic valve replacement (TAVR). METHODS: A total of 1400 patients with symptomatic AS and full invasive hemodynamic assessment before TAVR were included. Patients were categorized according to their cardiac damage stage into five groups that are defined as: stage 0, no cardiac damage; stage 1, left ventricular damage; stage 2, left atrial and/or mitral valve damage; stage 3, pulmonary vasculature and/or tricuspid valve damage; stage 4, right ventricular damage. RESULTS: 9.9% patients were classified as stage 0, 23.6% as stage 1, the majority of patients as stage 2 (33.5%), 23.1% as stage 3 and 10% as stage 4. One- and 4-year mortality were 10.1%/29.5% in stage 0, 16.1%/60.6% in stage 1, 17.3%/39.4% in stage 2, 22%/54.6% in stage 3, 27.1%/62.2% in stage 4 (p = 0.001/p < 0.001). The extent of cardiac damage was independently associated with increased mortality after TAVR (HR 1.16 per each increment in stage, 95% confidence interval 1.03-1.18; p = 0.018). CONCLUSIONS: Cardiac damage staging in severe AS patients based on invasive hemodynamics appears to show strong association between the extent of cardiac damage and post-TAVR mortality. This staging classification provides predictive value and may improve risk stratification, therapy management and decision-making in patients with AS. Invasive Staging Classification of Cardiac Damage in Severe Symptomatic Aortic Stenosis has an Impact on Outcome after TAVR. (Top) Invasive staging criteria for cardiac damage in five stages using left ventricular end-diastolic pressure (LVEDP) for stage 1 (red), post-capillary wedge pressure (PCWP) for stage 2 (green), systolic pulmonary artery pressure (SPAP) for stage 3 (purple) and right atrial pressure (RAP) for stage 4 (yellow). The cake chart shows the distribution of the different stage in the whole cohort. (Bottom) Survival Analyses According to Stage of Cardiac Damage after Transcatheter Aortic Valve Replacement using Invasive Criteria. Kaplan-Meier plots comparing overall (left) and cardiovascular (right) 4-year survival showing with the more advancing stage a higher mortality rate.

Essential roles of the dystrophin-glycoprotein complex in different cardiac pathologies.

The dystrophin-glycoprotein complex (DGC), situated at the sarcolemma dynamically remodels during cardiac disease. This review examines DGC remodeling as a common denominator in diseases affecting heart function and health. Dystrophin and the DGC serve as broad cytoskeletal integrators that are critical for maintaining stability of muscle membranes. The presence of pathogenic variants in genes encoding proteins of the DGC can cause absence of the protein and/or alterations in other complex members leading to muscular dystrophies. Targeted studies have allowed the individual functions of affected proteins to be defined. The DGC has demonstrated its dynamic function, remodeling under a number of conditions that stress the heart. Beyond genetic causes, pathogenic processes also impinge on the DGC, causing alterations in the abundance of dystrophin and associated proteins during cardiac insult such as ischemia-reperfusion injury, mechanical unloading, and myocarditis. When considering new therapeutic strategies, it is important to assess DGC remodeling as a common factor in various heart diseases. The DGC connects the internal F-actin-based cytoskeleton to laminin-211 of the extracellular space, playing an important role in the transmission of mechanical force to the extracellular matrix. The essential functions of dystrophin and the DGC have been long recognized. DGC based therapeutic approaches have been primarily focused on muscular dystrophies, however it may be a beneficial target in a number of disorders that affect the heart. This review provides an account of what we now know, and discusses how this knowledge can benefit persistent health conditions in the clinic.

Long-Term Outcomes Among a Nationwide Cohort of Patients Using an Implantable Cardioverter-Defibrillator: UMBRELLA Study Final Results.

Background Large-scale studies describing modern populations using an implantable cardioverter-defibrillator (ICD) are lacking. We aimed to analyze the incidence of arrhythmia, device interventions, and mortality in a broad spectrum of real-world ICD patients with different heart disorders. Methods and Results The UMBRELLA study is a prospective, multicenter, nationwide study of contemporary patients using an ICD followed up by remote monitoring, with a blinded review of arrhythmic episodes. From November 2005 to November 2017, 4296 patients were followed up. After 46.6±27.3 months, 16 067 episodes of sustained ventricular arrhythmia occurred in 1344 patients (31.3%). Appropriate ICD therapy occurred in 27.3% of study population. Patients with ischemic cardiomyopathy (hazard ratio [HR], 1.51; 95% CI, 1.29-1.78), dilated cardiomyopathy (HR, 1.28; 95% CI, 1.07-1.53), and valvular heart disease (HR, 1.94; 95% CI, 1.43-2.62) exhibited a higher risk of appropriate ICD therapies, whereas patients with hypertrophic cardiomyopathy (HR, 0.72; 95% CI, 0.54-0.96) and Brugada syndrome (HR, 0.25; 95% CI, 0.14-0.45) showed a lower risk. All-cause death was 13.4% at follow-up. Ischemic cardiomyopathy (HR, 3.09; 95% CI, 2.58-5.90), dilated cardiomyopathy (HR, 3.33; 95% CI, 2.18-5.10), and valvular heart disease (HR, 3.97; 95% CI, 2.25-6.99) had the worst prognoses. Delayed high-rate detection was enabled in 39.7% of patients, and single-zone programming occurred in 52.6% of primary prevention patients. Both parameters correlated with lower risk of first appropriate ICD therapy, with no excess risk of mortality. The rate of inappropriate shocks at follow-up was low (6%) and did not differ among type of ICD but was lower in SmartShock-capable devices. Conclusions Irrespective of the cause, contemporary ICD patients with heart failure-related disorders had a similar risk of ICD life-saving interventions and death. Current ICD programming recommendations still need to be implemented. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NTC01561144.

Heterogeneous trends in burden of heart disease mortality by subtypes in the United States, 1999-2018: observational analysis of vital statistics.

OBJECTIVE: To describe trends in the burden of mortality due to subtypes of heart disease from 1999 to 2018 to inform targeted prevention strategies and reduce disparities. DESIGN: Serial cross sectional analysis of cause specific heart disease mortality rates using national death certificate data in the overall population as well as stratified by race-sex, age, and geography. SETTING: United States, 1999-2018. PARTICIPANTS: 12.9 million decedents from total heart disease (49% women, 12% black, and 19% <65 years old). MAIN OUTCOME MEASURES: Age adjusted mortality rates (AAMR) and years of potential life lost (YPLL) for each heart disease subtype, and respective mean annual percentage change. RESULTS: Deaths from total heart disease fell from 752 192 to 596 577 between 1999 and 2011, and then increased to 655 381 in 2018. From 1999 to 2018, the proportion of total deaths from heart disease attributed to ischemic heart disease decreased from 73% to 56%, while the proportion attributed to heart failure increased from 8% to 13% and the proportion attributed to hypertensive heart disease increased from 4% to 9%. Among heart disease subtypes, AAMR was consistently highest for ischemic heart disease in all subgroups (race-sex, age, and region). After 2011, AAMR for heart failure and hypertensive heart disease increased at a faster rate than for other subtypes. The fastest increases in heart failure mortality were in black men (mean annual percentage change 4.9%, 95% confidence interval 4.0% to 5.8%), whereas the fastest increases in hypertensive heart disease occurred in white men (6.3%, 4.9% to 9.4%). The burden of years of potential life lost was greatest from ischemic heart disease, but black-white disparities were driven by heart failure and hypertensive heart disease. Deaths from heart disease in 2018 resulted in approximately 3.8 million potential years of life lost. CONCLUSIONS: Trends in AAMR and years of potential life lost for ischemic heart disease have decelerated since 2011. For almost all other subtypes of heart disease, AAMR and years of potential life lost became stagnant or increased. Heart failure and hypertensive heart disease account for the greatest increases in premature deaths and the largest black-white disparities and have offset declines in ischemic heart disease. Early and targeted primary and secondary prevention and control of risk factors for heart disease, with a focus on groups at high risk, are needed to avoid these suboptimal trends beginning earlier in life.

Evaluation of mode of birth in pregnant women with heart disease.

OBJECTIVE: Maternal heart disease (HD) complicates 1-4 % of pregnancies and is associated with adverse maternal and fetal outcomes. Although vaginal birth is generally recommended in the guidelines, cesarean section (CS) rates in women with HD are often high. Aim of the present study was to evaluate mode of birth and pregnancy outcomes in women with HD in a tertiary care hospital in the Netherlands. STUDY DESIGN: The study population consisted of 128 consecutive pregnancies in 99 women with HD, managed by a pregnancy heart team between 2012-2017 and ending in births after 24 weeks' gestation. Pregnancy risk was assessed per modified World Health Organization class. Mode of birth (planned and performed) and maternal and fetal complications (cardiovascular events, postpartum hemorrhage, prematurity, small for gestational age and death) were assessed for each pregnancy. RESULTS: Pregnancy risk was classified as modified World Health Organization class I in 23 %, class II in 50 %, class III in 21 % and class IV in 6% of pregnancies. Planned mode of birth was vaginal in 114 pregnancies (89 %) and CS in 14 (11 %; nine for obstetric and five for cardiac indication). An unplanned CS was performed in 18 pregnancies (16 %; 16 for obstetric and two for cardiac indications). Overall mode of birth was vaginal in 75 % and CS in 25 %. Twelve cardiovascular events occurred in eight pregnancies (6 %), postpartum hemorrhage in nine (7 %) and small for gestational age in 14 (11 %). No maternal or fetal deaths occurred. CONCLUSIONS: Findings of this study indicate that - given that pregnancies are managed and mode of birth is meticulously planned by a multidisciplinary pregnancy heart team - vaginal birth is a suitable option for women with HD.

Major cardiac events for adult survivors of childhood cancer diagnosed between 1970 and 1999: report from the Childhood Cancer Survivor Study cohort.

OBJECTIVE: To investigate the impact of modifications to contemporary cancer protocols, which minimize exposures to cardiotoxic treatments and preserve long term health, on serious cardiac outcomes among adult survivors of childhood cancer. DESIGN: Retrospective cohort study. SETTING: 27 institutions participating in the Childhood Cancer Survivor Study. PARTICIPANTS: 23 462 five year survivors (6193 (26.4%) treated in the 1970s, 9363 (39.9%) treated in the 1980s, and 7906 (33.6%) treated in the 1990s) of leukemia, brain cancer, Hodgkin lymphoma, non-Hodgkin lymphoma, renal tumors, neuroblastoma, soft tissue sarcomas, and bone sarcomas diagnosed prior to age 21 years between 1 January 1970 and 31 December 1999. Median age at diagnosis was 6.1 years (range 0-20.9) and 27.7 years (8.2-58.3) at last follow-up. A comparison group of 5057 siblings of cancer survivors were also included. MAIN OUTCOME MEASURES: Cumulative incidence and 95% confidence intervals of reported heart failure, coronary artery disease, valvular heart disease, pericardial disease, and arrhythmias by treatment decade. Events were graded according to the National Cancer Institute's Common Terminology Criteria for Adverse Events. Multivariable subdistribution hazard models were used to estimate hazard ratios by decade, and mediation analysis examined risks with and without exposure to cardiotoxic treatments. RESULTS: The 20 year cumulative incidence of heart failure (0.69% for those treated in the 1970s, 0.74% for those treated in the 1980s, 0.54% for those treated in the 1990s) and coronary artery disease (0.38%, 0.24%, 0.19%, respectively), decreased in more recent eras (P<0.01), though not for valvular disease (0.06%, 0.06%, 0.05%), pericardial disease (0.04%, 0.02%, 0.03%), or arrhythmias (0.08%, 0.09%, 0.13%). Compared with survivors with a diagnosis in the 1970s, the risk of heart failure, coronary artery disease, and valvular heart disease decreased in the 1980s and 1990s but only significantly for coronary artery disease (hazard ratio 0.65, 95% confidence interval 0.45 to 0.92 and 0.53, 0.36 to 0.77, respectively). The overall risk of coronary artery disease was attenuated by adjustment for cardiac radiation (0.90, 0.78 to 1.05), particularly among survivors of Hodgkin lymphoma (unadjusted for radiation: 0.77, 0.66 to 0.89; adjusted for radiation: 0.87, 0.69 to 1.10). CONCLUSIONS: Historical reductions in exposure to cardiac radiation have been associated with a reduced risk of coronary artery disease among adult survivors of childhood cancer. Additional follow-up is needed to investigate risk reductions for other cardiac outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT01120353.

Role of electrolyte concentrations and renin-angiotensin-aldosterone activation in the staging of canine heart disease.

BACKGROUND: Refractory congestive heart failure (CHF) and associated diuretic resistance are not well defined. OBJECTIVES: To characterize renal function, electrolyte concentrations, indices of diuretic efficacy, and renin-angiotensin-aldosterone system (RAAS) activation in dogs with naturally occurring heart disease (HD) in American College of Veterinary Internal Medicine stages B1, B2, C, and D and to determine their usefulness in defining HD stages. ANIMALS: Group 1:149 dogs with HD stages B1, B2, C, and D. Group 2:22 dogs with HD stages C and D. METHODS: Group 1: Renal parameters, serum and urine electrolyte and diuretic concentrations, and urine aldosterone concentrations were measured. Medication dosages and measured variables were compared among stages. Correlation of furosemide dosages to serum concentrations was explored. Group 2: Angiotensin-converting enzyme activity and RAAS components were measured and compared among CHF stages. RESULTS: Serum chloride concentration was the best differentiator of HD stage. Furosemide PO dosages (≤6 mg/kg/day) were weakly correlated with serum furosemide concentrations, whereas higher dosages were not significantly correlated. Angiotensin-converting enzyme inhibitor dosage and RAAS inhibition were greater in stage D, compared to stage C dogs. CONCLUSIONS AND CLINICAL IMPORTANCE: Hypochloremia is a useful marker for stage D HD in dogs. Poor furosemide dosage correlation to serum concentration may indicate variable and poor absorption, especially at higher dosages, advanced disease, or both. A small number of stage D dogs met proposed criteria for diuretic resistance. Greater RAAS inhibition in stage D versus stage C indicates effectiveness of RAAS-suppressive treatments in this group of dogs with refractory CHF.

Prevalence, predictors and outcomes of potential drug-drug interactions in left ventricular failure: considerable factors for quality use of medicines

Hospitalized patients with left ventricular failure (LVF) are at high risk for potential drug-drug interactions (pDDIs) and its related adverse effects owing to multiple risk factors such as old age, comorbidities and polypharmacy. This cross-sectional study conducted in two tertiary care hospitals aim to identify frequency, levels and predictors of pDDIs in LVF patients. Data about patients' demographic, hospital stay, medication therapy, sign/symptoms and laboratory test results were collected for 385 patients with LVF. Micromedex Drug-Reax® was used to screen patients' medication profiles for pDDIs. Overall prevalence and severity-wise prevalence of pDDIs were identified. Chi-square test was performed for comparative analysis of various variables. Logistic regression was applied to determine the odds-ratios (OR) for predictors of pDDIs. The prevalence of pDDIs was 96.4% (n=371). Overall 335 drug-interacting pairs were detected, which were presented in a total of 2870 pDDIs. Majority of pDDIs were of major- (48.9%) and moderate-severity (47.5%). Logistic regression analysis shows significant association of >6 all types of pDDIs with >12 drugs as compared with <8 drugs (OR=16.5; p=<0.001). Likewise, there was a significant association of >4 major-pDDIs with men as compared with female (OR=1.9; p=0.007) and >12 drugs as compared with <8 drugs (OR=10.9; p=<0.001). Hypotension (n=57), impaired renal function (23) and increased blood pressure (22) were the most frequent adverse outcomes associated with pDDIs. This study shows high prevalence of pDDIs in LVF patients. Majority of pDDIs were of major- and moderate-severity. Male patients and those prescribed greater number of medicines were more exposed to major-pDDIs

Radiation-induced heart disease: a review of classification, mechanism and prevention.

With the increasing incidence of thoracic tumors, radiation therapy (RT) has become an important component of comprehensive treatment. RT improves survival in many cancers, but it involves some inevitable complications. Radiation-induced heart disease (RIHD) is one of the most serious complications. RIHD comprises a spectrum of heart disease including cardiomyopathy, pericarditis, coronary artery disease, valvular heart disease and conduction system abnormalities. There are numerous clinical manifestations of RIHD, such as chest pain, palpitation, and dyspnea, even without obvious symptoms. Based on previous studies, the pathogenesis of RIHD is related to the production and effects of various cytokines caused by endothelial injury, inflammatory response, and oxidative stress (OS). Therefore, it is of great importance for clinicians to identify the mechanism and propose interventions for the prevention of RIHD.

Neural-network classification of cardiac disease from 31P cardiovascular magnetic resonance spectroscopy measures of creatine kinase energy metabolism.

BACKGROUND: The heart's energy demand per gram of tissue is the body's highest and creatine kinase (CK) metabolism, its primary energy reserve, is compromised in common heart diseases. Here, neural-network analysis is used to test whether noninvasive phosphorus (31P) cardiovascular magnetic resonance spectroscopy (CMRS) measurements of cardiac adenosine triphosphate (ATP) energy, phosphocreatine (PCr), the first-order CK reaction rate kf, and the rate of ATP synthesis through CK (CK flux), can predict specific human heart disease and clinical severity. METHODS: The data comprised the extant 178 complete sets of PCr and ATP concentrations, kf, and CK flux data from human CMRS studies performed on clinical 1.5 and 3 Tesla scanners. Healthy subjects and patients with nonischemic cardiomyopathy, dilated (DCM) or hypertrophic disease, New York Heart Association (NYHA) class I-IV heart failure (HF), or with anterior myocardial infarction are included. Three-layer neural-networks were created to classify disease and to differentiate DCM, hypertrophy and clinical NYHA class in HF patients using leave-one-out training. Network performance was assessed using 'confusion matrices' and 'area-under-the-curve' (AUC) analyses of 'receiver operating curves'. Possible methodological bias and network imbalance were tested by segregating 1.5 and 3 Tesla data, and by data augmentation by random interpolation of nearest neighbors, respectively. RESULTS: The network differentiated healthy, HF and non-HF cardiac disease with an overall accuracy of 84% and AUC > 90% for each category using the four CK metabolic parameters, alone. HF patients with DCM, hypertrophy, and different NYHA severity were differentiated with ~ 80% overall accuracy independent of CMRS methodology. CONCLUSIONS: While sample-size was limited in some sub-classes, a neural network classifier applied to noninvasive cardiac 31P CMRS data, could serve as a metabolic biomarker for common disease types and HF severity with clinically-relevant accuracy. Moreover, the network's ability to individually classify disease and HF severity using CK metabolism alone, implies an intimate relationship between CK metabolism and disease, with subtle underlying phenotypic differences that enable their differentiation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00181259.

Staging Cardiac Damage in Patients With Asymptomatic Aortic Valve Stenosis.

BACKGROUND: The optimal timing of intervention in patients with asymptomatic severe aortic stenosis (AS) remains controversial. OBJECTIVES: This multicenter study sought to test and validate the prognostic value of the staging of cardiac damage in patients with asymptomatic moderate to severe AS. METHODS: This study retrospectively analyzed the clinical, Doppler echocardiographic, and outcome data that were prospectively collected in 735 asymptomatic patients (71 ± 14 years of age; 60% men) with at least moderate AS (aortic valve area <1.5 cm2) and preserved left ventricular ejection fraction (≥50%) followed in the heart valve clinics of 4 high-volume centers. Patients were classified according to the following staging classification: no cardiac damage associated with the valve stenosis (Stage 0), left ventricular damage (Stage 1), left atrial or mitral valve damage (Stage 2), pulmonary vasculature or tricuspid valve damage (Stage 3), or right ventricular damage or subclinical heart failure (Stage 4). The primary endpoint was all-cause mortality. RESULTS: At baseline, 89 (12%) patients were classified in Stage 0, 200 (27%) in Stage 1, 341 (46%) in Stage 2, and 105 (14%) in Stage 3 or 4. Median follow-up was 2.6 years (interquartile range: 1.1 to 5.2 years). There was a stepwise increase in mortality rates according to staging: 13% in Stage 0, 25% in Stage 1, 44% in Stage 2, and 58% in Stages 3 to 4 (p < 0.0001). The staging was significantly associated with excess mortality in multivariable analysis adjusted for aortic valve replacement as a time-dependent variable (hazard ratio: 1.31 per each increase in stage; 95% CI: 1.06 to 1.61; p = 0.01), and showed incremental value to several clinical variables (net reclassification index = 0.34; p = 0.003). CONCLUSIONS: The new staging system characterizing the extra-aortic valve cardiac damage provides incremental prognostic value in patients with asymptomatic moderate to severe AS. This staging classification may be helpful to identify asymptomatic AS patients who may benefit from elective aortic valve replacement.

Staging Cardiac Damage in Patients With Symptomatic Aortic Valve Stenosis.

BACKGROUND: In severe aortic stenosis (AS), patients often show extra-aortic valvular injury. Recently, a new staging system for severe AS has been proposed on the basis of the extent of cardiac damage. OBJECTIVES: The present study evaluated the prevalence and prognostic impact of these different stages of cardiac damage in a large, real-world, multicenter cohort of symptomatic severe AS patients. METHODS: From the ongoing registries from 2 academic institutions, a total of 1,189 symptomatic severe AS patients were selected and retrospectively analyzed. According to the extent of cardiac damage on echocardiography, patients were classified as Stage 0 (no cardiac damage), Stage 1 (left ventricular damage), Stage 2 (mitral valve or left atrial damage), Stage 3 (tricuspid valve or pulmonary artery vasculature damage), or Stage 4 (right ventricular damage). Patients were followed for all-cause mortality and combined endpoint (all-cause mortality, stroke, and cardiac-related hospitalization). RESULTS: On the basis of the proposed classification, 8% of patients were classified as Stage 0, 24% as Stage 1, 49% as Stage 2, 7% as Stage 3, and 12% as Stage 4. On multivariable analysis, cardiac damage was independently associated with all-cause mortality and combined outcome, although this was mainly determined by Stages 3 and 4. CONCLUSIONS: In this large multicenter cohort of symptomatic severe AS patients, stage of cardiac injury as classified by a novel staging system was independently associated with all-cause mortality and combined endpoint, although this seemed to be predominantly driven by tricuspid valve or pulmonary artery vasculature damage (Stage 3) and right ventricular dysfunction (Stage 4).