Closing the Last Mile Gap in Access to Multimodality Imaging in Rural Settings: Design of the Imaging Core of the Risk Underlying Rural Areas Longitudinal Study.

Achieving optimal cardiovascular health in rural populations can be challenging for several reasons including decreased access to care with limited availability of imaging modalities, specialist physicians, and other important health care team members. Therefore, innovative solutions are needed to optimize health care and address cardiovascular health disparities in rural areas. Mobile examination units can bring imaging technology to underserved or remote communities with limited access to health care services. Mobile examination units can be equipped with a wide array of assessment tools and multiple imaging modalities such as computed tomography scanning and echocardiography. The detailed structural assessment of cardiovascular and lung pathology, as well as the detection of extracardiac pathology afforded by computed tomography imaging combined with the functional and hemodynamic assessments acquired by echocardiography, yield deep phenotyping of heart and lung disease for populations historically underrepresented in epidemiological studies. Moreover, by bringing the mobile examination unit to local communities, innovative approaches are now possible including engagement with local professionals to perform these imaging assessments, thereby augmenting local expertise and experience. However, several challenges exist before mobile examination unit-based examinations can be effectively integrated into the rural health care setting including standardizing acquisition protocols, maintaining consistent image quality, and addressing ethical and privacy considerations. Herein, we discuss the potential importance of cardiac multimodality imaging to improve cardiovascular health in rural regions, outline the emerging experience in this field, highlight important current challenges, and offer solutions based on our experience in the RURAL (Risk Underlying Rural Areas Longitudinal) cohort study.

Critical Review of Current Approaches for Echocardiographic Reproducibility and Reliability Assessment in Clinical Research.

BACKGROUND: There is no broadly accepted standard method for assessing the quality of echocardiographic measurements in clinical research reports, despite the recognized importance of this information in assessing the quality of study results. METHODS: Twenty unique clinical studies were identified reporting echocardiographic data quality for determinations of left ventricular (LV) volumes (n = 13), ejection fraction (n = 12), mass (n = 9), outflow tract diameter (n = 3), and mitral Doppler peak early velocity (n = 4). To better understand the range of possible estimates of data quality and to compare their utility, reported reproducibility measures were tabulated, and de novo estimates were then calculated for missing measures, including intraclass correlation coefficient (ICC), 95% limits of agreement, coefficient of variation (CV), coverage probability, and total deviation index, for each variable for each study. RESULTS: The studies varied in approaches to reproducibility testing, sample size, and metrics assessed and values reported. Reported metrics included mean difference and its SD (n = 7 studies), ICC (n = 5), CV (n = 4), and Bland-Altman limits of agreement (n = 4). Once de novo estimates of all missing indices were determined, reasonable reproducibility targets for each were identified as those achieved by the majority of studies. These included, for LV end-diastolic volume, ICC > 0.95, CV < 7%, and coverage probability > 0.93 within 30 mL; for LV ejection fraction, ICC > 0.85, CV < 8%, and coverage probability > 0.85 within 10%; and for LV mass, ICC > 0.85, CV < 10%, and coverage probability > 0.60 within 20 g. CONCLUSIONS: Assessment of data quality in echocardiographic clinical research is infrequent, and methods vary substantially. A first step to standardizing echocardiographic quality reporting is to standardize assessments and reporting metrics. Potential benefits include clearer communication of data quality and the identification of achievable targets to benchmark quality improvement initiatives.

Sex Differences in Demographics, Risk Factors, Presentation, and Noninvasive Testing in Stable Outpatients With Suspected Coronary Artery Disease: Insights From the PROMISE Trial.

OBJECTIVES: The aim of this study was to determine whether presentation, risk assessment, testing choices, and results differ by sex in stable symptomatic outpatients with suspected coronary artery disease (CAD). BACKGROUND: Although established CAD presentations differ by sex, little is known about stable, suspected CAD. METHODS: The characteristics of 10,003 men and women in the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial were compared using chi-square and Wilcoxon rank-sum tests. Sex differences in test selection and predictors of test positivity were examined using logistic regression. RESULTS: Women were older (62.4 years of age vs. 59.0 years of age) and were more likely to be hypertensive (66.6% vs. 63.2%), dyslipidemic (68.9% vs. 66.3%), and to have a family history of premature CAD (34.6% vs. 29.3) (all p values <0.005). Women were less likely to smoke (45.6% vs. 57.0%; p < 0.001), although their prevalence of diabetes was similar to that in men (21.8% vs. 21.0%; p = 0.30). Chest pain was the primary symptom in 73.2% of women versus 72.3% of men (p = 0.30), and was characterized as "crushing/pressure/squeezing/tightness" in 52.5% of women versus 46.2% of men (p < 0.001). Compared with men, all risk scores characterized women as being at lower risk, and providers were more likely to characterize women as having a low (<30%) pre-test probability of CAD (40.7% vs. 34.1%; p < 0.001). Compared with men, women were more often referred to imaging tests (adjusted odds ratio: 1.21; 95% confidence interval: 1.01 to 1.44) than nonimaging tests. Women were less likely to have a positive test (9.7% vs. 15.1%; p < 0.001). Although univariate predictors of test positivity were similar, in multivariable models, age, body mass index, and Framingham risk score were predictive of a positive test in women, whereas Framingham and Diamond and Forrester risk scores were predictive in men. CONCLUSIONS: Patient sex influences the entire diagnostic pathway for possible CAD, from baseline risk factors and presentation to noninvasive test outcomes. These differences highlight the need for sex-specific approaches for the evaluation of CAD.