Identifying People at High Risk for Severe Aortic Stenosis: Aortic Valve Calcium Versus Lipoprotein(a) and Low-Density Lipoprotein Cholesterol.

BACKGROUND: Aortic valve calcification (AVC), Lp(a) [lipoprotein(a)], and low-density lipoprotein cholesterol (LDL-C) are associated with severe aortic stenosis (AS). We aimed to determine which of these risk factors were most strongly associated with the risk of incident severe AS. METHODS: A total of 6792 participants from the MESA study (Multi-Ethnic Study of Atherosclerosis) had computed tomography-quantified AVC, Lp(a), and LDL-C values at MESA visit 1 (2000-2002). We calculated the absolute event rate of incident adjudicated severe AS per 1000 person-years and performed multivariable adjusted Cox proportional hazards regression. RESULTS: The mean age was 62 years old, and 47% were women. Over a median 16.7-year follow-up, the rate of incident severe AS increased exponentially with higher AVC, regardless of Lp(a) or LDL-C values. Participants with AVC=0 had a very low rate of severe AS even with elevated Lp(a) ≥50 mg/dL (<0.1/1000 person-years) or LDL-C ≥130 mg/dL (0.1/1000 person-years). AVC >0 was strongly associated with severe AS when Lp(a) <50 mg/dL hazard ratio (HR) of 33.8 (95% CI, 16.4-70.0) or ≥50 mg/dL HR of 61.5 (95% CI, 7.7-494.2) and when LDL-C <130 mg/dL HR of 31.1 (95% CI, 14.4-67.1) or ≥130 mg/dL HR of 50.2 (95% CI, 13.2-191.9). CONCLUSIONS: AVC better identifies people at high risk for severe AS compared with Lp(a) or LDL-C, and people with AVC=0 have a very low long-term rate of severe AS regardless of Lp(a) or LDL-C level. These results suggest AVC should be the preferred prognostic risk marker to identify patients at high risk for severe AS, which may help inform participant selection for future trials testing novel strategies to prevent severe AS.

Association of aortic valve calcium with dementia and stroke: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND AND AIMS: Calcific aortic valve disease is associated with increased thrombin formation, platelet activation, decreased fibrinolysis, and subclinical brain infarcts. We examined the long-term association of aortic valve calcification (AVC) with newly diagnosed dementia and incident stroke in the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS: AVC was measured using non-contrast cardiac CT at Visit 1. We examined AVC as a continuous (log-transformed) and categorical variable (0, 1-99, 100-299, ≥300). Newly diagnosed dementia was adjudicated using International Classification of Disease codes. Stroke was adjudicated from medical records. We calculated absolute event rates (per 1000 person-years) and multivariable adjusted Cox proportional hazards ratios (HR). RESULTS: Overall, 6812 participants had AVC quantified with a mean age of 62.1 years old, 52.9 % were women, and the median 10-year estimated atherosclerotic cardiovascular disease (ASCVD) risk was 13.5 %. Participants with AVC >0 were older and less likely to be women compared to those with AVC=0. Over a median 16-year follow-up, there were 535 cases of dementia and 376 cases of stroke. The absolute risk of newly diagnosed dementia increased in a stepwise pattern with higher AVC scores, and stroke increased in a logarithmic pattern. In multivariable analyses, AVC was significantly associated with newly diagnosed dementia as a log-transformed continuous variable (HR 1.09; 95 % CI 1.04-1.14) and persons with AVC ≥300 had nearly a two-fold higher risk (HR 1.77; 95 % CI 1.14-2.76) compared to those with AVC=0. AVC was associated with an increased risk of stroke after adjustment for age, sex, and race/ethnicity, but not after adjustment for ASCVD risk factors. CONCLUSIONS: After multivariable adjustment, AVC >0 was significantly associated with an increased risk of newly diagnosed dementia, but not incident stroke. This suggests that AVC may be an important risk factor for the long-term risk of dementia beyond traditional ASCVD risk factors.

Prevalence of Aortic Valve Calcium and the Long-Term Risk of Incident Severe Aortic Stenosis.

BACKGROUND: Aortic valve calcification (AVC) is a principal mechanism underlying aortic stenosis (AS). OBJECTIVES: This study sought to determine the prevalence of AVC and its association with the long-term risk for severe AS. METHODS: Noncontrast cardiac computed tomography was performed among 6,814 participants free of known cardiovascular disease at MESA (Multi-Ethnic Study of Atherosclerosis) visit 1. AVC was quantified using the Agatston method, and normative age-, sex-, and race/ethnicity-specific AVC percentiles were derived. The adjudication of severe AS was performed via chart review of all hospital visits and supplemented with visit 6 echocardiographic data. The association between AVC and long-term incident severe AS was evaluated using multivariable Cox HRs. RESULTS: AVC was present in 913 participants (13.4%). The probability of AVC >0 and AVC scores increased with age and were generally highest among men and White participants. In general, the probability of AVC >0 among women was equivalent to men of the same race/ethnicity who were approximately 10 years younger. Incident adjudicated severe AS occurred in 84 participants over a median follow-up of 16.7 years. Higher AVC scores were exponentially associated with the absolute risk and relative risk of severe AS with adjusted HRs of 12.9 (95% CI: 5.6-29.7), 76.4 (95% CI: 34.3-170.2), and 380.9 (95% CI: 169.7-855.0) for AVC groups 1 to 99, 100 to 299, and ≥300 compared with AVC = 0. CONCLUSIONS: The probability of AVC >0 varied significantly by age, sex, and race/ethnicity. The risk of severe AS was exponentially higher with higher AVC scores, whereas AVC = 0 was associated with an extremely low long-term risk of severe AS. The measurement of AVC provides clinically relevant information to assess an individual's long-term risk for severe AS.

Use of Actigraphy (Wearable Digital Sensors to Monitor Activity) in Heart Failure Randomized Clinical Trials: A Scoping Review.

BACKGROUND: Actigraphy-based measurements of physiologic parameters may enable design of patient-centric heart failure (HF) clinical trials. Recently, the Heart Failure Collaboratory focused on recommendations for meaningful change and use of actigraphy as an end point in HF clinical trials. We aimed to evaluate randomized controlled trials (RCTs) that have quantified the impact of HF interventions using actigraphy. METHODS: Using a scoping review strategy, we evaluated the use of actigraphy in HF RCTs. Studies were identified through electronic searches of Embase, OVID Medline, PubMed, and Cochrane Review. Data on trial characteristics and results were collected. RESULTS: We identified 11 RCTs with a total of 1,455 participants. The risk of bias across the included trials was high overall. All trials had the primary outcomes reflecting measures of either physical activity (n = 8), sleep (n = 2), or both (n = 1). Five trials evaluated response to pharmacologic therapies compared with placebo, 3 evaluated physical activity interventions, 2 evaluated group or cognitive therapy, and 1 evaluated sleep-ventilation strategy. Sample sizes ranged from 30 to 619 participants. There was significant heterogeneity relating to device type, body placement site, and handling of missing actigraphy data. Duration of monitoring ranged from 48 hours to 12 weeks. None of the studies evaluating pharmacologic therapies (n = 5) demonstrated a significant improvement of actigraphy-based primary end point measurements. CONCLUSIONS: There is significant heterogeneity in the use, methodology, and results of actigraphy-based HF RCTs. Our results highlight the need to develop, standardize, and validate actigraphy-specific outcomes for use in HF clinical trials.

Risk Reclassification With Coronary Computed Tomography Angiography-Visualized Nonobstructive Coronary Artery Disease According to 2018 American College of Cardiology/American Heart Association Cholesterol Guidelines (from the Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes : An International Multicenter Registry [CONFIRM]).

The 2018 American College of Cardiology (ACC)/American Heart Association (AHA) cholesterol management guideline recommends risk enhancers in the borderline-risk and statin recommended/intermediate-risk groups. We determined the risk reclassification by the presence and severity of coronary computed tomography angiography (CCTA)-visualized coronary artery disease (CAD) according to statin eligibility groups. Of 35,281 individuals who underwent CCTA, 1,303 asymptomatic patients (age 59, 65% male) were identified. Patients were categorized as low risk, borderline risk, statin recommended/intermediate risk or statin recommended/high risk according to the guideline. CCTA-visualized CAD was categorized as no CAD, nonobstructive, or obstructive. Major adverse cardiovascular events (MACE) were defined as a composite outcome of all-cause mortality, nonfatal myocardial infarction, and late coronary revascularization (>90 days). We tested a reclassification wherein no CAD reclassifies downward, and the presence of any CAD reclassifies upward. During a median follow-up of 2.9 years, 93 MACE events (7.1%) were observed. Among the borderline-risk and statin-recommended/intermediate-risk groups eligible for risk enhancers, the presence or absence of any CCTA-visualized CAD led to a net increase of 2.3% of cases and 22.4% of controls correctly classified (net reclassification index [NRI] 0.27, 95% CI 0.13 to 0.41, p = 0.0002). The NRI was not significant among low- or statin-recommended/high-risk patients (all p >0.05). The presence or absence of CCTA-visualized CAD, including both obstructive and nonobstructive CAD, significantly improves reclassification in patients eligible for risk enhancers in 2018 ACC/AHA guidelines. Patients in low- and high-risk groups derive no significant improvement in risk reclassification from CCTA.

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging.

Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models. We highlight several domains of ML application such as echocardiography, electrocardiography, and recently developed non-invasive imaging modalities such as coronary artery calcium scoring and coronary computed tomography angiography. We conclude by reviewing the limitations associated with contemporary application of ML algorithms within the cardiovascular disease field.

Association between epicardial fat volume and fractional flow reserve: An analysis of the determination of fractional flow reserve (DeFACTO) study.

BACKGROUND: This study examines the relationship between epicardial fat volume (EFV) and lesion-specific ischemia by fractional flow reserve (FFR). METHODS: In a study of 173 patients (63.0 ±â€¯8.3 years) undergoing FFR, EFV was determined using cardiac computed tomography. Relationships between EFV and FFR were assessed using multivariable linear and logistic regression. RESULTS: Using multivariable linear and logistic regression, no association between EFV and FFR was observed (ß [SE] = -0.001 [0.003], P = 0.6, OR [95% CI]: 1.02 [0.94-1.11], P = 0.64, respectively). CONCLUSION: In patients with suspected or known coronary artery disease undergoing invasive angiography, EFV was not associated with FFR.

The Impact of Age on Long-Term Quality of Life After Endonasal Endoscopic Resection of Skull Base Meningiomas.

BACKGROUND: Midline ventral skull base meningiomas may be amenable to an endonasal endoscopic approach, which has theoretical advantages and may help preserve quality of life (QOL) when compared with transcranial approaches. OBJECTIVE: To investigate the effect of age on QOL following endonasal endoscopic surgery, given the documented impact of age on QOL outcomes following transcranial resection of midline ventral skull base meningiomas. METHODS: We reviewed a prospectively acquired database of endonasal endoscopic surgery for meningiomas. Inclusion criteria included patients who had completed long-term postoperative (≥6 months follow-up) QOL questionnaires (Anterior Skull Base Questionnaire [ASBQ] and Sino-Nasal Outcome Test [SNOT-22]). Postoperative QOL scores were also compared with preoperative QOL in a patient subset. RESULTS: Long-term QOL data were available in 34 patients. Average postoperative ASBQ and SNOT-22 scores were 3.39 and 23.0, respectively. Better QOL was statistically associated with age <55 (P = .02). In a subset of patients, preoperative and postoperative ASBQ and SNOT-22 scores were compared. Only SNOT-22 scores significantly increased from 15.9 + 20.8 to 25.9 + 19.5 (P = .04). CONCLUSION: We report the first study specifically evaluating long-term QOL after endonasal endoscopic resection of skull base meningiomas. QOL was decreased postoperatively in patients aged ≥55. ABBREVIATIONS: ASBQ, Anterior Skull Base QuestionnaireGTR, gross total resectionQOL, quality of lifeSNOT-22, 22-item Sino-Nasal Outcome Test.