Association Between Rheumatoid Arthritis and the Risk of Incident Degenerative Valvular Heart Disease: Evidence From a Prospective Cohort Study.

BackgroundValvular heart disease (VHD) is a leading cause of cardiovascular morbidity and mortality that poses a substantial health care and economic burden on health care systems. Administrative diagnostic codes for ascertaining VHD diagnosis are incomplete.ObjectiveThis study aimed to develop a natural language processing (NLP) algorithm to identify patients with aortic, mitral, tricuspid, and pulmonic valve stenosis and regurgitation from transthoracic echocardiography (TTE) reports within a large integrated health care system.MethodsWe used reports from echocardiograms performed in the Kaiser Permanente Southern California (KPSC) health care system between January 1, 2011, and December 31, 2022. Related terms/phrases of aortic, mitral, tricuspid, and pulmonic stenosis and regurgitation and their severities were compiled from the literature and enriched with input from clinicians. An NLP algorithm was iteratively developed and fine-trained via multiple rounds of chart review, followed by adjudication. The developed algorithm was applied to 200 annotated echocardiography reports to assess its performance and then the study echocardiography reports.ResultsA total of 1,225,270 TTE reports were extracted from KPSC electronic health records during the study period. In these reports, valve lesions identified included 111,300 (9.08%) aortic stenosis, 20,246 (1.65%) mitral stenosis, 397 (0.03%) tricuspid stenosis, 2585 (0.21%) pulmonic stenosis, 345,115 (28.17%) aortic regurgitation, 802,103 (65.46%) mitral regurgitation, 903,965 (73.78%) tricuspid regurgitation, and 286,903 (23.42%) pulmonic regurgitation. Among the valves, 50,507 (4.12%), 22,656 (1.85%), 1685 (0.14%), and 1767 (0.14%) were identified as prosthetic aortic valves, mitral valves, tricuspid valves, and pulmonic valves, respectively. Mild and moderate were the most common severity levels of heart valve stenosis, while trace and mild were the most common severity levels of regurgitation. Males had a higher frequency of aortic stenosis and all 4 valvular regurgitations, while females had more mitral, tricuspid, and pulmonic stenosis. Non-Hispanic Whites had the highest frequency of all 4 valvular stenosis and regurgitations. The distribution of valvular stenosis and regurgitation severity was similar across race/ethnicity groups. Frequencies of aortic stenosis, mitral stenosis, and regurgitation of all 4 heart valves increased with age. In TTE reports with stenosis detected, younger patients were more likely to have mild aortic stenosis, while older patients were more likely to have severe aortic stenosis. However, mitral stenosis was opposite (milder in older patients and more severe in younger patients). In TTE reports with regurgitation detected, younger patients had a higher frequency of severe/very severe aortic regurgitation. In comparison, older patients had higher frequencies of mild aortic regurgitation and severe mitral/tricuspid regurgitation. Validation of the NLP algorithm against the 200 annotated TTE reports showed excellent precision, recall, and F1-scores.ConclusionsThe proposed computerized algorithm could effectively identify heart valve stenosis and regurgitation, as well as the severity of valvular involvement, with significant implications for pharmacoepidemiological studies and outcomes research.

Recommendations for Evaluation of Prosthetic Valves With Echocardiography and Doppler Ultrasound: A Report From the American Society of Echocardiography's Guidelines and Standards Committee and the Task Force on Prosthetic Valves, Developed in Conjunction With the American College of Cardiology Cardiovascular Imaging Committee, Cardiac Imaging Committee of the American Heart Association, the European Association of Echocardiography, a registered branch of the

Asthma has been associated with the development and progression of various cardiovascular diseases but its relationship with degenerative valvular heart disease (VHD) remains unclear. This study investigated the association between asthma and incident degenerative VHD, including aortic stenosis (AS), aortic regurgitation (AR), mitral regurgitation (MR) and pulmonary regurgitation (PR). We analysed 483 735 participants from the UK Biobank (median age 56.5 years; 45.2% male) who were free of VHD at baseline. Asthma status was self-reported at recruitment. Incident VHD was ascertained through hospital admission and mortality records using International Classification of Diseases, Tenth Revision codes. Cox proportional hazards models were used to estimate HRs and 95% CIs for each VHD subtype, adjusting for demographic, lifestyle and clinical covariates. Sensitivity analyses accounted for asthma medications, duration of asthma and competing risks. Over a median follow-up of 13.8 years, 5388 participants developed AS, 2650 AR, 6088 MR and 821 PR. Asthma was associated with increased risk of AS (HR 1.31; 95% CI 1.21 to 1.41), AR (HR 1.24; 95% CI 1.11 to 1.39), MR (HR 1.19; 95% CI 1.10 to 1.28) and PR (HR 1.34; 95% CI 1.10 to 1.62). The association with AR was attenuated after adjusting for asthma medications (HR 1.12; 95% CI 0.97 to 1.30). Results were robust across multiple sensitivity analyses, including adjustment for asthma duration and exclusion of participants with pre-existing cardiovascular disease. Asthma is independently associated with a modestly increased risk of several degenerative VHDs, particularly aortic and mitral valve diseases. These findings suggest a potential shared inflammatory pathway and highlight the need for heightened cardiovascular surveillance in individuals with asthma.

Morphologic features of the normal and abnormal mitral valve

Valvular heart disease (VHD) is a common clinical condition in geriatric-related cardiovascular diseases that is connected to heart dysfunction. Atrial fibrillation (AF) is the most frequent arrhythmia. Considering these two common clinical conditions, so far no sufficient data on the relationship between degenerative VHD and non-valvular atrial fibrillation (NVAF). We aimed to explore the relationship between valvular structure and biochemistry of nonvalvular AF and degenerative valvular heart disease in the elderly. In our study, 234 VHD patients who were diagnosis evaluated by transthoracic echocardiography were enrolled in this retrospective study from January 2015 and December 2018. Significant valvular diseases were defined according to ACC/AHA Classification as any moderate or severe mitral regurgitation (MR), aortic regurgitation (AR), tricuspid stenosis, regurgitation, or aortic stenosis (AS). Data on relevant laboratory indicators were also collected. A total of 234 patients with degenerative VHD were enrolled, of whom 81 had NVAF and 153 had sinus rhythm. Gender, smoking history, and some comorbidities, such as coronary artery disease, diabetes, and renal dysfunction, did not differ significantly between the two groups, but there were significant differences in age and hypertension {79 [74-83] vs. 70 [65-79] years} After propensity-score matching (PSM), we identified 68 VHD patients with NVAF and 68 VHD patients without NVAF. The NVAF + VHD had higher low-density lipoprotein (LDL) cholesterol (2.94±0.84 vs. 2.26±1.33 mmol/L, P=0.001), lower high-density lipoprotein (HDL) cholesterol [1.03 (0.89-1.34) vs. 1.56 (0.99-2.71) mmol/L, P<0.001], and higher uric acid (UA) (438.18±145.83 vs. 376.67±148.03 µmol/L, P=0.02) than the VHD group. The ejection fraction (EF) of the NVAF + VHD group was lower than that of the VHD group {63 [51-68] vs. 66 [62-69], P=0.013}. In addition, the left atrial size, MR, and calcification of the NVAF + VHD group were higher than those of the VHD group. Pronounced MR, valve calcification and hyperlipidemia were more likely in VHD patients with NVAF. These structures and biomarkers changes maybe important clinical parameters for disease prevention and management, which indicate early drug intervention to AF and hyperlipidemia is necessary.

Background Association of cardiac amyloidosis (CA) with aortic stenosis (AS) is well known. There is limited data on the association of CA with other valvular heart diseases like aortic regurgitation (AR), mitral stenosis (MS), mitral regurgitation (MR), tricuspid stenosis (TS), tricuspid regurgitation (TR), pulmonary stenosis (PS) and regurgitation (PR). Purpose To assess the associations between valvular heart diseases and cardiac amyloidosis. Methods This is a retrospective observational study from hospitalizations between January 1, 2016, and December 31, 2019, using the National Inpatient Sample (NIS), the largest all-payer public database of hospital care data in the United States. We looked into associations between valvular heart diseases (VHD) and CA. Results From 2016 to 2019, a total of 4999 patients with a history of CA, 16,711 MS, 361,864 MR, 380,072 AS, 89,452 AR, 194 TS, 104,151 TR, 853 PS, 13,277 PR were identified. Compared to those without any history of CA, those with a history of CA had significantly higher associations with MR (6.4% vs 1.3%, p&amp;lt;0.001), AS (3.6% vs 1.3%, p&amp;lt;0.001), AR (1% vs 0.3%, p&amp;lt;0.001), TS (0.02% vs 0, p&amp;lt;0.033), TR (2.7% vs 0.4%, p&amp;lt;0.001), PR (0.4% vs 0.1%, p&amp;lt;0.001). Mean age of patients with history of CA in MS (73.7 years), MR (75.2 years), AS (81.4 years), AR (77.1 years), TS (82 years), TR (77.3 years), PR (78.1 years). Compared to males, females had higher incidence of MS (0.1% vs 0.03%, p&amp;lt;0.001) and lower incidence of AS (1.2% vs 1.6%, p&amp;lt;0.001) and AR (0.3% vs 0.4%, p&amp;lt;0.001). Conclusion There was a significantly higher association between CA and MR, AS, TR. Comparatively, patients with CA and MS were younger than those with other VHD. Funding Acknowledgement Type of funding sources: None.

Background: Despite the increasing prevalence of degenerative valvular heart disease (VHD), recommended preventive interventions are notably lacking. The cardiovascular-kidney-metabolic (CKM) health approach advocates for multidisciplinary early-stage disease prevention. We aimed to explore sex differences in CKM risk factors associated with VHD. Methods: Using data from UK Biobank, participants without a history of VHD or heart failure at baseline were included. We assessed the sex differences in hazard ratios (HRs) and population-attributable risk (PAR) for incident aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR) associated with five CKM risk factors: hypertension, diabetes, obesity, high lipoprotein(a), and chronic kidney disease (CKD). Results: Among 463,496 participants (54.4% women), AS, AR, and MR cases were observed at incidence of 1.05 and 0.52, 0.37 and 0.22, 1.04 and 0.70 events per 1000 person-years for men and women, respectively. Hypertension consistently accounted for the largest attributable risk factor for incident VHD in both sexes, with PARs of 29.96% and 26.61% for AS, 23.51% and 16.02% for AR, and 17.56% and 13.09% for MR in women and men, respectively. Compared to men, obesity, CKD, and hypertension were associated with higher risks of AS, AR, and MR in women (women-to-men ratios of HRs: 1.11[1.09–1.36], 1.62[1.01–2.63], and 1.27[1.09–1.49], respectively). Conclusions: This study offers comprehensive insights into the profiles of CKM risk factors for degenerative VHD among middle-aged individuals. Tailoring the prioritization of risk factors based on gender has the potential to improve the precision and effectiveness of VHD prevention strategies.

2020 ACC/AHA Guideline for the Management of Patients With Valvular Heart Disease: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

The cardiovascular-kidney-metabolic (CKM) health approach emphasizes the importance of multidisciplinary early-stage disease prevention. This study aimed to explore sex differences in CKM risk factors associated with common degenerative valvular heart disease (VHD). A total of 436,184 participants (54.4% women; mean age, 58 years) free of VHD or heart failure at baseline and with complete information about CKM risk factors were included from the UK Biobank cohort. We assessed sex differences in hazard ratios (HRs) and population-attributable risk (PAR) for incident VHD and VHD-related interventions or mortality, focusing on five CKM risk factors: hypertension, diabetes, obesity, hypertriglyceridemia, and chronic kidney disease (CKD). At baseline, 81.06% of participants had one or more CKM risk factors: 75.61% had hypertension, 4.80% had diabetes, 24.14% had obesity, 22.26% had hypertriglyceridemia, and 2.32% had CKD. Over a median follow-up period of 13.80 years, incidences of aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR) were 11.18 and 5.42, 3.64 and 2.19, and 10.39 and 6.94 events per 10,000 person-years for men and women, respectively. Hypertension was consistently the largest attributable risk factor for incident VHD in both sexes, with PARs of 29.07% and 25.17% for AS, 24.21% and 16.51% for AR, and 19.55% and 13.01% for MR in women and men, respectively. Compared to men, women had higher risks of AS with obesity (HR: 1.17 [1.04-1.32]), AR with CKD (1.59 [1.01-2.49]), and MR with either hypertension (1.25 [1.07-1.47]) or hypertriglyceridemia (1.22 [1.07-1.39]). Tailoring the prioritization of CKM risk factors based on gender has the potential to enhance the effectiveness of VHD prevention strategies.

There are no effective medications to prevent the onset of degenerative valvular heart disease (VHD). Sweetened beverage consumption may contribute to the development of VHD by affecting metabolic disorders, systemic inflammation, and calcification processes. This study aimed to prospectively assess the association between sweetened beverage consumption and the risk of degenerative VHD. This prospective study included 167,801 participants from the UK Biobank who completed at least one dietary questionnaire. During a median follow-up of 14.53 years, 1,464 cases of aortic valve stenosis (AS) events, 584 cases of aortic valve regurgitation (AR) events, and 1,744 cases of mitral valve regurgitation (MR) events were recorded. Compared with non-consumers, participants consuming more than one drink per day of artificially sweetened beverages (ASBs) had a higher risk of AS (HR: 1.36, 95% CI: 1.10-1.68), AR (HR: 1.42, 95% CI: 1.02-2.00), MR (HR: 1.35, 95% CI: 1.10-1.64). Similarly, the consumption of more than one drink of sugar-sweetened beverages (SSBs) was associated with an increased incidence of MR (HR: 1.47, 95% CI: 1.22-1.77). In contrast, no significant association was observed between the consumption of natural juices (NJs) and VHD risk. Results for VHD-related interventions, deaths, or cardiovascular events were largely consistent. Substituting SSBs or ASBs per day with NJs was associated with a reduced risk of MR (HR: 0.83, 95% CI: 0.72-0.94) events or AS (HR: 0.81, 95% CI: 0.69-0.94) events, respectively. Lower consumption of SSBs or ASBs may reduce the risk of degenerative VHD and VHD-related events.

Physical activity has proven effective in preventing atherosclerotic cardiovascular disease, but its role in preventing degenerative valvular heart disease (VHD) remains uncertain. This study aimed to explore the dose-response association between moderate to vigorous physical activity (MVPA) volume and the risk of degenerative VHD among middle-aged adults. A full week of accelerometer-derived MVPA data from 87 248 UK Biobank participants (median age 63.3, female: 56.9%) between 2013 and 2015 were used for primary analysis. Questionnaire-derived MVPA data from 361 681 UK Biobank participants (median age 57.7, female: 52.7%) between 2006 and 2010 were used for secondary analysis. The primary outcome was the diagnosis of incident degenerative VHD, including aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR). The secondary outcome was VHD-related intervention or mortality. In the accelerometer-derived MVPA cohort, 555 incident AS, 201 incident AR, and 655 incident MR occurred during a median follow-up of 8.11 years. Increased MVPA volume showed a steady decline in AS risk and subsequent AS-related intervention or mortality risk, levelling off beyond approximately 300 min/week. In contrast, its association with AR or MR incidence was less apparent. The adjusted rates of AS incidence (95% confidence interval) across MVPA quartiles (Q1-Q4) were 11.60 (10.20, 13.20), 7.82 (6.63, 9.23), 5.74 (4.67, 7.08), and 5.91 (4.73, 7.39) per 10 000 person-years. The corresponding adjusted rates of AS-related intervention or mortality were 4.37 (3.52, 5.43), 2.81 (2.13, 3.71), 1.93 (1.36, 2.75), and 2.14 (1.50, 3.06) per 10 000 person-years, respectively. Aortic valve stenosis risk reduction was also observed with questionnaire-based MVPA data [adjusted absolute difference Q4 vs. Q1: AS incidence, -1.41 (-.67, -2.14) per 10 000 person-years; AS-related intervention or mortality, -.38 (-.04, -.88) per 10 000 person-years]. The beneficial association remained consistent in high-risk populations for AS, including patients with hypertension, obesity, dyslipidaemia, and chronic kidney disease. Higher MVPA volume was associated with a lower risk of developing AS and subsequent AS-related intervention or mortality. Future research needs to validate these findings in diverse populations with longer durations and repeated periods of activity monitoring.

The following are highlights from the new series, Circulation: Cardiovascular Quality and Outcomes Topic Reviews. This series will summarize the most important manuscripts, as selected by the Editor, which have been published in the Circulation portfolio. The objective of this new series is to provide our readership with a timely, comprehensive selection of important papers that are relevant to the quality and outcomes as well as general cardiology audience. The studies included in this article represent the most significant research in the area of valvular heart disease. ( Circ Cardiovasc Quality and Outcomes . 2012;5:-e103.) In recent years, no field of clinical cardiology has experienced a great influx of transformational therapeutic options as has the area of valvular heart disease. Treatment of severe aortic stenosis (AS) has been revolutionized by transcatheter aortic valve replacement (TAVR), which has been shown to improve life expectancy and functional outcomes in patients with inoperable AS1,2 and to have short-term outcomes comparable to surgical aortic valve replacement (AVR) in patients at high perioperative risk.3,4 Analogously, mitral valve disease has been amenable to percutaneous valve replacement,5,6 as well as clipping procedures7 that can substantively reduce severe mitral regurgitation (MR) and improve functional outcomes. Even right-sided heart disease involving valves in pulmonary8,9 and tricuspid10 positions has been treated successfully with endovascular techniques. Yet, even with this growing focus on percutaneous valvular interventions, open surgical techniques remain the dominant treatment strategies and standard of care for most advanced lesions. Surgical valve repair and replacement account for 10% to 20% of all cardiac surgical procedures,11–13 approximately two thirds of which are for AS.11–13 For patients undergoing surgery, there remains considerable debate about risk stratification,14 intraoperative technique,15 and postoperative …

Background Cardiac auscultation, an essential bedside diagnostic tool, often identifies significant valvular heart disease through murmurs. However, its accuracy is contingent upon the clinician's expertise, leading to a growing dependence on expensive imaging techniques. This study aimed to develop and validate a machine learning model for detecting valvular heart disease from cardiac auscultation. Methods The digital cardiac auscultation and associated echocardiograms were prospectively collected from three sites between May 1, 2022, and Dec 31, 2022. We trained, validated, and externally tested a machine learning based model to classify aortic stenosis, mitral stenosis, aortic regurgitation, mitral regurgitation, tricuspid regurgitation, oveall valvular heart disease from cardiac auscultation, age, sex, and comorbidity. We condcted training, and internal testing using datasets for eXtreme Gradient Boosting (XGBoost) machine learning model from hospital one and hospital two. The dataset from hospital three was employed for external testing. We evaluated the area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), accuracy, sensitivity, specificity. Result We selected the cardiac auscultation and echocardiograms of a total of 4,321 patients, excluding those without valvular heart disease information, congenital heart disease, a history of valvular operation, and cardiac auscultation could not be interpreted. The diagnostic performance of heart murmurs for valvular heart disease across the three datasets generally demonstrated high sensitivity and PPV. Specifically, the sensitivity for aortic stenosis was 89.1%, mitral stenosis 88.8%, aortic regurgitation 88.5%, mitral regurgitation 89.8%, tricuspid regurgitation 90.1%, and for any valvular heart disease, it was 95.0%. However, the NPV was consistently lower, with values of 16.4%, 14.2%, 12.2%, 23.1%, 26.2%, and 65.3% for the respective conditions. In XGBoost machine learning model, the AUROC values for internal testing (N=1,403), along with their 95% confidence intervals, were as follows: aortic stenosis (0.93, 0.88–0.97), mitral stenosis (0.91, 0.81–0.97), aortic regurgitation (0.84, 0.79–0.90), mitral regurgitation (0.94, 0.90–0.98), tricuspid regurgitation (0.81, 0.75–0.87), and overall valvular heart disease (0.86, 0.82–0.89). For external testing (N=814), the AUROC values were: aortic stenosis (0.90, 0.83–0.96), mitral stenosis (0.88, 0.79–0.95), aortic regurgitation (0.94, 0.93–0.96), mitral regurgitation (0.93, 0.92–0.95), tricuspid regurgitation (0.89, 0.87–0.91), and overall valvular heart disease (0.92, 0.90–0.94). Conclusion The machine learning based model can accurately classify valvular heart diseases using information from digital cardiac auscultation.Figure 1.Study FlowFigure 2.AUC curve

Background AI has been used in studies to predict the severity of aortic stenosis (AS) from electrocardiography (ECG), but the application of AI to predict the severity of aortic regurgitation (AR), mitral regurgitation (MR) and tricuspid regurgitation (TR) has not been widely explored. This study aimed to determine whether deep learning can predict the severity of valvular heart disease (AS, AR, MR and TR) assessed by echocardiography using ECG data. Methods and Results We analyzed data from 31,787 adult patients who underwent ECG and echocardiography within three days of each other between 2014 and 2019 at two hospitals. Valvular heart diseases, including AS, AR, MR, and TR, were classified into categories; normal, mild, moderate, and severe; according to guidelines. ECGs, along with patient age, gender, height, and weight, were inputs to a LightGBM machine learning model. The model was trained on 80.6% of the data, with the remaining 19.4% used for validation. The sensitivity for predicting moderate or severe valvular heart disease was 85% for AS, 88% for AR, 85% for MR, and 85% for TR. The negative predictive values for AS, AR, MR, and TR were all 100%. Prediction accuracies for the severity of each disease were AS at 0.857, AR at 0.871, MR at 0.855, and TR at 0.890. Predictions based on AS diagnostic parameters; mean pressure gradient, valve area, and maximum blood flow velocity also showed favorable accuracies at 0.891, 0.821, and 0.877, respectively. Conclusion Integrating AI with standard clinical parameters, including ECG data, height, and weight, showed potential in accurately predicting the severity of various valvular heart diseases. Further researches across diverse populations and settings are necessary to validate the approach's effectiveness and explore its impact on patient care.

Hypothesis: This study aimed to examine the impact of moderate-to-vigorous intensity physical activity (MVPA) on the prevention of left-sided degenerative valvular heart disease (VHD) among middle-aged adults. Methods: In the UK biobank study, data from wrist-worn accelerometer and physical activity questionnaires were utilized to assess the role of MVPA volume on the incidence of aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR). The primary cohort involved 90,865 participants ( median 8.1-year follow-up period) without prevalent VHD and heart failure, who wore accelerometers for one week. The validation cohort included 397,335 participants (median 13.8-year follow-up period) who completed physical activity questionnaires. MVPA volume was categorized according to the American Heart Association’s recommendation. Results: Accelerometer-measured MVPA showed a curvilinear relationship with reduced AS risk, with the risk reduction plateauing above 300 min/week. Compared to no MVPA, those engaging in 150-299 minutes of MVPA per week showed the most significant risk reduction [1-149 min/week: adjusted hazard ratio (HR), 0.79 (0.58, 1.08); 150-299 min/week: HR, 0.52 (0.36, 0.75); ≥300 min/week: HR, 0.57 (0.39, 0.83)]. Similar results were found when repeating the above analyses in self-reported MVPA cohort, with a relatively smaller reduction in HR ratio [150-299 min/week: HR, 0.81 (0.73, 0.91)]. No significant association was found between the MVPA volume and the risk of AR and MR in both cohorts. Conclusions: Meeting current MVPA recommendations (150-300 min/week) was associated with the lowest AS risk. Targeting adherence to accelerometer-measured MVPA thresholds may enhance AS risk reduction. Additionally, MVPA showed limited effectiveness in preventing valvular regurgitation, indicating distinct mechanisms between stenotic lesions and regurgitation lesions in degenerative VHD.