You are currently on the new version of our website. Access the old version .
MDPIMDPI
Search all articles
JCMJournal of Clinical Medicine
Download PDF
  • Article
  • Open Access

21 November 2025

Trends in Aortic Stenosis Mortality Among Older Adults in the United States from 1999 to 2020

,
,
,
,
,
,
,
,
and
1
Department of Medicine, Khyber Medical College, Peshawar 25120, Pakistan
2
Department of Cardiovascular Medicine, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR 97239, USA
3
Department of Internal Medicine, Hackensack University Medical Center, Hackensack, NJ 07601, USA
4
Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD 57107, USA
J. Clin. Med.2025, 14(23), 8276;https://doi.org/10.3390/jcm14238276
This article belongs to the Special Issue Clinical Updates on Valvular Heart Diseases: A New Era in Personalized Treatment
Version Notes
Order Reprints

Abstract

Background: Aortic stenosis (AS) represents a prevalent valvular condition in older adults, associated with significant morbidity and mortality. The objective of the study was to examine trends in mortality related to AS in the United States (U.S.). Methods: The U.S. CDC WONDER dataset was analyzed, extracting age-adjusted mortality rates (AAMR) per 100,000 and calculating annual percentage change (APC) through Joinpoint regression. The results were stratified to identify temporal, sex-specific, racial/ethnic, and regional differences. Results: From 1999 to 2020, 267,515 deaths among older adults (>65 years old) were attributed to AS, with the AAMR declining from 28.00 to 23.69. Males had a higher AAMR (30.35) compared to females (27.42), though more deaths occurred in females (164,104 vs. 103,411). Non-Hispanic (NH) Whites exhibited the greatest AAMR (31.61), trailed by NH American Indian/Alaska Native individuals (16.62), whereas NH Asians/Pacific Islanders had the least (11.50). Significant state-wise variations were noted, with AAMRs ranging from 60.55 in Oregon to 17.23 in Mississippi, and 19 states depicting a concerning rise over the study duration. Regionally, the Northeast (32.09) had the highest AAMRs, while the South (23.06) had the lowest. Micropolitan (32.28) and noncore (28.43) areas reported higher AAMRs compared to large central metropolitan areas (24.32). Conclusions: While there is a trend towards decreased mortality due to AS in the U.S., significant disparities based on race, sex, and region persist and may be worsening. The underlying causes of these discrepancies require further investigation, and targeted strategies must be developed to address them effectively.

1. Introduction

Aortic stenosis (AS) represents the most prevalent valvular disease, affecting 2–5% adults above 65 years of age. Studies in those aged 75 and older have reported that approximately 12.4% are affected by AS, with severe disease occurring in 3.4% [1]. The prevalence of AS shows a clear age-related increase, affecting about 0.2% of individuals in their 50s, roughly 1% in their 60s, nearly 4% in their 70s, and approaching 10% in those in their 80s [2].
AS can be caused by congenital, degenerative, and rheumatic processes, leading to progressive valvular fibrosis and calcification. This leads to a gradual obstruction of the aortic orifice, resulting in left ventricular pressure overload and the eventual onset of symptoms. Without aortic valve replacement (AVR), the prognosis is fatal within 2 to 3 years [3].
In recent decades, transcatheter aortic valve replacement (TAVR) has shown promise for patients who are poor candidates for surgical valve replacement [4]. The number of patients receiving surgical or transcatheter treatment is rising annually, with improving outcomes.
However, the temporal, sex-based, racial, and geographic variations of AS-related mortality trends in the U.S. remain uncertain. We hypothesize that outcomes have improved over time with advancements in management, leading to lower mortality rates.

2. Methodology

This study drew upon publicly available data from the Centers for Disease Control and Prevention’s Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database, which compiles mortality information derived from death certificates across all fifty states and the District of Columbia.

3. Study Setting and Population

We carried out a retrospective study using mortality records obtained from the CDC WONDER database, specifically drawing from the Multiple Cause of Death Public Use dataset. This dataset encompasses mortality and population counts for all U.S. counties, alongside various socio-demographic parameters, including race/ethnicity and place of death [5]. Data were extracted on 2 May 2024. Our analysis centered on the trends in mortalities among older adults (>65 years old) from 1999 to 2020, where AS was implicated as the underlying cause of death using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision codes (ICD-10), I06.0, I06.2, I35.0, I35.2. The same have been used in previous studies analyzing various aspects of AS [6,7,8]. As the analysis relied on anonymized data from a publicly accessible database, ethical approval was not applicable. The data were reported in compliance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines [9] (Supplementary Table S1).
We extracted data regarding year, population, demographics, states, urban–rural classification, and regions to analyze the temporal trends in AS mortality across various socio-demographic parameters. Demographic variables included sex, race/ethnicity, place of death, and age. Racial/ethnic groups were categorized as Hispanic or Latino, Non-Hispanic (NH) White, NH American Indian or Alaska Native, NH Black or African American, and NH Asian or Pacific Islander. These classifications rely on information recorded in death certificates, as reported by the funeral director either through information provided by the next of kin or self-reported based on observation, and have been used in the previous analyses of the WONDER dataset [10]. The location of death was categorized as home, hospice, nursing or long-term care facility, or medical facility, with the latter further classified as inpatient, outpatient, or emergency department, dead on arrival, or unknown. Urban–rural differences were assessed using the National Center for Health Statistics framework, which distinguishes metropolitan from nonmetropolitan regions. Metropolitan regions were further classified as large (populations over 1 million), medium (250,000–999,999), or small (below 250,000). Nonmetropolitan areas encompassed micropolitan regions (urban clusters with 10,000–49,999 residents) and noncore counties, which are rural areas not classified as part of a metropolitan or micropolitan area [11]. Regional designations followed the U.S. Census Bureau’s definitions of Northeast, Midwest, South, and West [11].

4. Statistical Analysis

Our analysis examined the trends in AS mortality from 1999 to 2020, stratified across various demographic, regional, and geographic factors. Crude mortality rates per 100,000 individuals were extracted, and age-adjusted mortality rates (AAMRs) per 100,000 individuals were calculated using the year 2000 U.S. population as the reference standard for adjustment [12]. Data points with fewer than 20 mortality events were regarded as unreliable and not included in the analysis. Annual percent changes (APCs) in AAMRs, along with their corresponding 95% confidence intervals (CIs), were calculated using the Joinpoint Regression Program version 5.4.0 to assess temporal changes in AAMRs. This method entails fitting log-linear regression models to detect significant changes in AAMR over time and has been previously used to analyze trends in mortality attributable to various diseases [13,14]. Subsequently, the weighted averages of the APCs were also calculated, the average annual percent change (AAPC) with their 95% confidence intervals, which provides a summary of the mortality trends over the complete duration of the study. All APCs/AAPCs were estimated based on AAMR (standardized to the 2000 US standard population). For subgroup analyses (sex, race/ethnicity, state, region, and urban–rural categories), AAMRs were calculated separately for each subgroup, and APCs/AAPCs were then computed independently for each stratum. Annual percent changes (APCs) were classified as rising or declining based on whether they showed a statistically significant difference from zero trend, as determined by a two-tailed t-test with a significance threshold of p < 0.05. To ensure that the COVID-19 pandemic did not distort long-term trends, a sensitivity analysis was performed by excluding data from 2020, confirming the robustness of the overall findings.

5. Results

A total of 267,515 deaths were recorded amongst older adults from 1999–2020, in which AS was implicated as the underlying cause of death. Profound sex-based and ethnic disparities were evident: 61.3% of the deaths occurred in females, and 91.7% occurred in the NH White population, followed by 3.6% amongst NH Black or African Americans (Table 1). Racial/ethnic data were available for 99.84% of the recorded deaths. The overall AAMR for the entire study duration was 28.62 (95% CI: 28.51 to 28.73). Location of death information was available for 99.8% mortalities, with the largest proportion of deaths (39.31%) occurring in medical inpatient care facilities, followed by decedents’ homes (25.78%) and nursing home/long-term care facilities (21.90%) (Figure 1) (Supplementary Table S2).
Table 1. AS deaths, stratified by sex and race, in the United States, 1999 to 2020.
Figure 1. National trends in overall and sex-specific age-adjusted mortality rates due to AS in the United States from 1999 to 2020; * denotes years in which the annual percentage change (APC) differed significantly from 0 at α = 0.05.

8. Discussion

This analysis spanning two decades of mortality data revealed several compelling insights. Overall, mortality rates from AS remained relatively stable with a slight increase from 1999 to 2014, after which they declined. The initial rise in mortality may be a result of improved disease detection, potentially driven by increased echocardiography utilization and evolving diagnostic coding practices [15]. Our findings are in line with data from 2008 to 2017, looking at patients above the age of 45 who had AS listed as an underlying cause of death [8].
TAVR was first approved in 2011 for patients with severe AS with prohibitive operative risk. In 2012, its use was expanded to high-surgical-risk patients and, in 2015, to “valve-in-valve” procedures [16]. In 2016, it was approved for use in intermediate-risk patients, and after the PARTNER-3 trial in 2019, the indication was expanded to include low-risk patients [17]. The expanding use of TAVR, with its demonstrated improvements in mortality, stroke, duration of hospitalization, and 30-day readmission compared to surgical AVR, correlates with the decreasing mortality from AS in 2015–2020 [18].
The link between TAVR practice developments and AS mortality trends cannot be assumed to be causal. TAVR uptake may indicate other aspects of high-value care that could improve mortality. Additionally, TAVR and surgical AVR rates are inconsistently collected from various sources, and other factors influence AS mortality, such as surgical AVR experience, AS diagnosis frequency, and the prevalence and management of risk factors (e.g., chronic renal disease, hypercholesterolemia, diabetes, smoking). These risk factors significantly overlap with those for atherosclerotic cardiovascular disease, and care has continued to improve for these conditions in the past few years. Moreover, the management of comorbidities among patients undergoing TAVR has been continuously improving, with broader adoption of contemporary preventive therapies such as SGLT2 inhibitors, which may have contributed to the observed mortality decline [19,20].
Despite the overall improvement in AAMR, the data does show some concerning trends. While males had a higher AAMR compared to females, the total deaths in females were more than in males. The literature shows that women are diagnosed with AS in later stages, are more symptomatic on diagnosis, have fewer comorbidities, and are managed conservatively for longer compared to men, despite having higher left atrial volumes and pulmonary pressures [21]. Though women have a longer average life expectancy compared to men, women with severe AS have a higher mortality rate than men of the same age [21]. Data show female sex is associated with improved survival at 1 year after TAVR [22]. Addressing sex disparities in the treatment and outcomes of severe AS is crucial to ensuring equitable care.
Mortality due to AS remained largely unchanged among NH American Indian/Alaskan, Hispanic/Latino, NH Black/African American, and NH Pacific islanders, in contrast to the decline observed in NH white patients. This is evidenced by the steep decline in AAMR noted in NH Whites (APC: −4.36, 95% CI: −6.67 to −2.91) from 2015–2020. This is in comparison to the APC for other racial and ethnic groups.
It is likely that the incidence of AS is underreported in the non-white cohort. Racial disparities in this cohort have been extensively reported in the literature. A racial and ethnic gap between TAVR utilization rates has already been documented [23]. The underlying causes of racial and ethnic disparities in TAVR utilization remain incompletely understood and are likely multifactorial. Potential contributors include physician decision-making and implicit bias, variations in patient preferences and health literacy, differences in access to subspecialty care, and the broader influence of structural inequities within the healthcare system [24]. Moreover, disparities have been observed in diagnostic coding practices for AS, with Non-Hispanic Black and Non-Hispanic Asian patients being less likely than their Non-Hispanic White counterparts to receive an ICD code confirming AS after initial transthoracic echocardiography. This distinction is critical, as the presence of a diagnostic code often determines eligibility for further evaluation and intervention, including TAVR [25]. Additional research is warranted to better delineate the factors underlying these racial differences in diagnosis, treatment, and outcomes.
Our analysis uncovered profound regional and geographic variations in AS mortality trends. Most states had an initial rise in AAMRs until 2013–2015, followed by a decline until 2020, culminating in an overall decline in AAMRs across the study period. However, 19 states deviated from this trend, recording increases in AAMR over the course of the study. These states were mostly located in the Midwest and Northeast regions, with South Dakota and Maine experiencing the highest increases in AAMRs.
Although the precise reasons behind these divergent trends remain unclear, they are likely influenced by a multitude of factors. Certain states, including Maine, Vermont, Iowa, New Hampshire, and Oregon, have comparatively older populations and higher proportions of White populations, which may partly contribute to increased incidence and mortality in these regions. Additionally, the harsh winter climates in some northern and midwestern states may exacerbate cardiovascular conditions, potentially contributing to increased mortality rates [26]. Furthermore, states with higher percentages of rural populations often lack robust healthcare infrastructures and have higher uninsured rates, creating barriers to timely and specialized care. Lifestyle factors such as the high prevalence of obesity, hypertension, and smoking—particularly pervasive in some Midwestern and Southern states—also elevate the risk of developing AS, contributing to higher incidence in some states [27,28].
Among the four U.S. Census regions, the Northeast and West exhibited the highest overall AAMRs, both around 32.09, while the South had the lowest at 23.06. The AAMR generally declined across all regions during the study period, except for the Midwest, which saw a slight increase. Urban–rural trends showed that micropolitan areas had notably higher AAMRs (32.28) compared to large central metropolitan areas (24.32). Both micropolitan and small metropolitan areas experienced an initial increase in AAMR until 2015, followed by a significant decline. In contrast, noncore (non-metropolitan) areas showed a continuous rise in AAMR from 1999 to 2020. Socioeconomic factors, including higher income, better education, and broader insurance coverage, are more prevalent in regions like the Northeast, contributing to lower AS mortality rates. Lifestyle and health behaviors, such as higher prevalence of chronic diseases and smoking, further impact AS outcomes, especially in rural and certain Midwest and Southern states. Variations in healthcare policies, with some regions adopting advanced treatments like TAVR more rapidly, also influence mortality rates.

9. Limitations

Our study utilized data from the CDC WONDER database and identified deaths that listed AS as the primary or underlying cause of death using ICD-10 codes. However, reliance on administrative coding introduces the potential for misclassification bias, as inaccuracies in death certification or coding practices may lead to underreporting or overestimation of AS-related mortality. Additionally, the database lacks detailed clinical information, including laboratory parameters, imaging findings, treatment modalities such as TAVR or surgical valve replacement, and medication use. It also does not include socioeconomic variables, comorbidity burden, or access-to-care indicators, all of which may substantially affect mortality outcomes and contribute to observed demographic or regional disparities. These limitations may, therefore, influence the precision of our findings and should be considered when interpreting the results.

10. Conclusions

Our study highlights persistent disparities in AS-related mortality across demographic and geographic groups. Mortality rates have declined in recent years, potentially reflecting advances in diagnostic practices and broader adoption of TAVR. Notably, however, sex-, race-, and region-based differences remain evident and may be widening over time. Further research is needed to elucidate the drivers of these disparities and to develop targeted interventions that ensure more equitable access to diagnosis and treatment.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm14238276/s1, Figure S1: Trends in age-adjusted mortality rates (AAMR) due to aortic stenosis in the United States from 1999 to 2020, with Joinpoint regression identifying significant shifts in temporal trends. * indicates a statistically significant annual percent change (APC) at α = 0.05; Figure S2: Sensitivity analysis of age-adjusted mortality rates (AAMR) due to aortic stenosis from 1999 to 2019, excluding the year 2020 to minimize potential confounding effects of the COVID-19 pandemic. Joinpoint regression was used to detect significant changes in trend; * indicates a statistically significant APC at α = 0.05; Table S1: STROBE Statement; Table S2: AS related mortality stratified by place of death in the United States from 1999 to 2020; Table S3: Annual percent change (APC) of AS-associated age-adjusted mortality rates per 100,000 in the United States, 1999 to 2020; Table S4: Overall and sex-stratified AS-associated age-adjusted mortality rates per 100,000 in the United States, 1999 to 2020; Table S5: Racial trends in AS-associated age-adjusted mortality rates per 100,000, in the United States, 1999 to 2020; Table S6: AS-associated age-adjusted mortality rates per 100,000, stratified by State in the United States, 1999 to 2020; Table S7: AS-associated age-adjusted mortality rates per 100,000, stratified by Census Region in the United States, 1999 to 2020; Table S8: AS-associated age-adjusted mortality rates per 100,000, stratified by urban–rural status in the United States, 1999 to 2020.

Author Contributions

M.A. and S.Z. contributed equally to the conception, study design, data analysis, and drafting of the manuscript. M.S. and D.S. assisted with data collection, data curation, and preliminary analyses. E.S. and H.R. supported statistical analysis, literature review, and critical revision of the manuscript. M.R. contributed to the interpretation of results and manuscript editing. C.B. and M.V.-A. provided clinical expertise, critical review, and substantial revisions. R.K. supervised the study and provided senior guidance. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study as the study relied on de-identified publicly available data and did not involve humans directly.

Data Availability Statement

All data supporting the findings of this study are included within the manuscript and its accompanying Supplementary File. The dataset is publicly accessible through the CDC WONDER Multiple Cause of Death database at: https://wonder.cdc.gov/mcd.html (accessed on 10 November 2025).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Osnabrugge, R.L.; Mylotte, D.; Head, S.J.; Van Mieghem, N.M.; Nkomo, V.T.; LeReun, C.M.; Bogers, A.J.; Piazza, N.; Kappetein, A.P. Aortic stenosis in the elderly: Disease prevalence and number of candidates for transcatheter aortic valve replacement: A meta-analysis and modeling study. J. Am. Coll. Cardiol. 2013, 62, 1002–1012. [Google Scholar] [CrossRef]
  2. Eveborn, G.W.; Schirmer, H.; Heggelund, G.; Lunde, P.; Rasmussen, K. The evolving epidemiology of valvular aortic stenosis. The Tromsø Study. Heart 2013, 99, 396–400. [Google Scholar] [CrossRef] [PubMed]
  3. Carabello, B.A. Introduction to Aortic Stenosis. Circ. Res. 2013, 113, 179–185. [Google Scholar] [CrossRef] [PubMed]
  4. Wu, C.; Vasseur, B.; Maisel, W. The March of Transcatheter Aortic Valve Replacement Therapy-US Food and Drug Administration Perspectives on Device Approval for Patients at Low Surgical Risk. JAMA Cardiol. 2020, 5, 5–6. [Google Scholar] [CrossRef]
  5. Centers for Disease Control and Prevention; National Center for Health Statistics. About Multiple Cause of Death, 1999–2020. Available online: http://wonder.cdc.gov/mcd-icd10.html (accessed on 2 May 2024).
  6. Hughes, Z.H.; Hammond, M.M.; Lewis-Thames, M.; Sweis, R.; Shah, N.S.; Khan, S.S. Rural-Urban Trends for Aortic Stenosis Mortality in the United States, 2008 to 2019. JACC Adv. 2023, 2, 100617. [Google Scholar] [CrossRef]
  7. Tung, M.; Nah, G.; Tang, J.; Marcus, G.; Delling, F.N. Valvular disease burden in the modern era of percutaneous and surgical interventions: The UK Biobank. Open Heart 2022, 9, e002039. [Google Scholar] [CrossRef]
  8. Bevan, G.H.; Zidar, D.A.; Josephson, R.A.; Al-Kindi, S.G. Mortality Due to Aortic Stenosis in the United States, 2008–2017. JAMA 2019, 321, 2236–2238. [Google Scholar] [CrossRef]
  9. von Elm, E.; Altman, D.G.; Egger, M.; Pocock, S.J.; Gøtzsche, P.C.; Vandenbroucke, J.P. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. BMJ 2007, 335, 806–808. [Google Scholar] [CrossRef] [PubMed]
  10. CDC Wonder. Mortality Data—About Multiple Cause of Death. [Internet]. Available online: https://wonder.cdc.gov/wonder/help/mcd.html (accessed on 31 May 2024).
  11. Ingram, D.D.; Franco, S.J. 2013 NCHS Urban-Rural Classification Scheme for Counties; US Department of Health and Human Services: Washington, DC, USA, 2014; pp. 1–73. [Google Scholar] [PubMed]
  12. Anderson, R.N.; Rosenberg, H.M. Age standardization of death rates: Implementation of the year 2000 standard. Natl. Vital Stat. Rep. 1998, 47, 1–17. [Google Scholar]
  13. Joinpoint Regression Program; Version 5.0.2; Statistical Methodology and Applications Branch, Surveillance Research Program, National Cancer Institute: Bethesda, MD, USA, 2023. Available online: https://surveillance.cancer.gov/joinpoint/ (accessed on 20 April 2024).
  14. Siddiqi, T.J.; Khan Minhas, A.M.; Greene, S.J.; Van Spall, H.G.C.; Khan, S.S.; Pandey, A.; Mentz, R.J.; Fonarow, G.C.; Butler, J.; Khan, M.S. Trends in Heart Failure-Related Mortality Among Older Adults in the United States from 1999–2019. JACC Heart Fail. 2022, 10, 851–859. [Google Scholar] [CrossRef]
  15. Matteucci, A.; Bonanni, M.; Versaci, F.; Frati, G.; Peruzzi, M.; Sangiorgi, G.; Biondi-Zoccai, G.; Massaro, G. Cardiovascular medicine: A year in review. Minerva Cardiol. Angiol. 2022, 70, 40–55. [Google Scholar] [CrossRef]
  16. Mahmaljy, H.; Tawney, A.; Young, M. Transcatheter Aortic Valve Replacement. In StatPearls; StatPearls Publishing LLC.: Treasure Island, FL, USA, 2024. [Google Scholar]
  17. Mack, M.J.; Leon, M.B.; Thourani, V.H.; Makkar, R.; Kodali, S.K.; Russo, M.; Kapadia, S.R.; Malaisrie, S.C.; Cohen, D.J.; Pibarot, P.; et al. Transcatheter Aortic-Valve Replacement with a Balloon-Expandable Valve in Low-Risk Patients. N. Engl. J. Med. 2019, 380, 1695–1705. [Google Scholar] [CrossRef]
  18. Carroll, J.D.; Mack, M.J.; Vemulapalli, S.; Herrmann, H.C.; Gleason, T.G.; Hanzel, G.; Deeb, G.M.; Thourani, V.H.; Cohen, D.J.; Desai, N.; et al. STS-ACC TVT Registry of Transcatheter Aortic Valve Replacement. JACC 2020, 76, 2492–2516. [Google Scholar] [CrossRef]
  19. Playford, D.; Schwarz, N.; Chowdhury, E.; Williamson, A.; Duong, M.; Kearney, L.; Stewart, S.; Strange, G. Comorbidities and Symptom Status in Moderate and Severe Aortic Stenosis: A Multicenter Clinical Cohort Study. JACC Adv. 2023, 2, 100356. [Google Scholar] [CrossRef]
  20. Matteucci, A.; Pandozi, C.; Bonanni, M.; Mariani, M.V.; Sgarra, L.; Nesti, L.; Pierucci, N.; La Fazia, V.M.; Lavalle, C.; Nardi, F.; et al. Impact of empagliflozin and dapagliflozin on sudden cardiac death: A systematic review and meta-analysis of adjudicated randomized evidence. Heart Rhythm. 2025, in press. [CrossRef]
  21. Tribouilloy, C.; Bohbot, Y.; Rusinaru, D.; Belkhir, K.; Diouf, M.; Altes, A.; Delpierre, Q.; Serbout, S.; Kubala, M.; Levy, F.; et al. Excess Mortality and Undertreatment of Women with Severe Aortic Stenosis. J. Am. Heart Assoc. 2021, 10, e018816. [Google Scholar] [CrossRef]
  22. Gaglia, M.A., Jr.; Lipinski, M.J.; Torguson, R.; Gai, J.; Ben-Dor, I.; Bernardo, N.L.; Satler, L.F.; Pichard, A.D.; Waksman, R. Comparison in Men Versus Women of Co-morbidities, Complications, and Outcomes After Transcatheter Aortic Valve Implantation for Severe Aortic Stenosis. Am. J. Cardiol. 2016, 118, 1692–1697. [Google Scholar] [CrossRef] [PubMed]
  23. Antia, A.; Pius, R.; Ndukauba, C.; Zarauz, V.R.; Olafiranye, O. Temporal trends in the utilization and outcome of transcatheter aortic valve replacement across racial and ethnic groups. A Nationwide analysis. Int. J. Cardiol. 2024, 399, 131669. [Google Scholar] [CrossRef] [PubMed]
  24. Minha, S.; Barbash, I.M.; Magalhaes, M.A.; Ben-Dor, I.; Okubagzi, P.G.; Pendyala, L.K.; Satler, L.F.; Pichard, A.D.; Torguson, R.; Waksman, R. Outcome comparison of African-American and Caucasian patients with severe aortic stenosis subjected to transcatheter aortic valve replacement: A single-center experience. Catheter. Cardiovasc. Interv. 2015, 85, 640–647. [Google Scholar] [CrossRef] [PubMed]
  25. Crousillat, D.R.; Amponsah, D.K.; Camacho, A.; Kandanelly, R.R.; Bapat, D.; Chen, C.; Selberg, A.; Shaqdan, A.; Tanguturi, V.K.; Picard, M.H.; et al. Racial and Ethnic Differences in the Clinical Diagnosis of Aortic Stenosis. J. Am. Heart Assoc. 2022, 11, e025692. [Google Scholar] [CrossRef] [PubMed]
  26. Fares, A. Winter cardiovascular diseases phenomenon. N. Am. J. Med. Sci. 2013, 5, 266–279. [Google Scholar] [CrossRef] [PubMed]
  27. Eveborn, G.W.; Schirmer, H.; Lunde, P.; Heggelund, G.; Hansen, J.B.; Rasmussen, K. Assessment of risk factors for developing incident aortic stenosis: The Tromsø Study. Eur. J. Epidemiol. 2014, 29, 567–575. [Google Scholar] [CrossRef]
  28. Holford, T.R.; McKay, L.; Jeon, J.; Tam, J.; Cao, P.; Fleischer, N.L.; Levy, D.T.; Meza, R. Smoking Histories by State in the U.S. Am. J. Prev. Med. 2023, 64, S42–S52. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Article Metrics

Citations

Article Access Statistics

Journal Statistics
Multiple requests from the same IP address are counted as one view.
Download PDF
Multicenter Evaluation of Different Anti-Xa Assays and Diluted Russell’s Viper Venom Time in Ex Vivo Plasma Samples from Patients Treated with Rivaroxaban or Apixaban
Previous
Early Outcomes of Lecanemab for Alzheimer’s Disease in the Veterans Health Administration
Next