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

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Date
2016-12
Authors
Crowley, Anna Lisa
Yow, Eric
Barnhart, Huiman X
Daubert, Melissa A
Bigelow, Robert
Sullivan, Daniel C
Pencina, Michael
Douglas, Pamela S
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Abstract
<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.
Type
Journal article
Subject
Image Enhancement
Echocardiography
Sensitivity and Specificity
Reproducibility of Results
Evidence-Based Medicine
Biomedical Research
Quality Assurance, Health Care
Practice Guidelines as Topic
Data Accuracy
Permalink
https://hdl.handle.net/10161/22519
Published Version (Please cite this version)
10.1016/j.echo.2016.08.006
Publication Info
Crowley, Anna Lisa; Yow, Eric; Barnhart, Huiman X; Daubert, Melissa A; Bigelow, Robert; Sullivan, Daniel C; ... Douglas, Pamela S (2016). Critical Review of Current Approaches for Echocardiographic Reproducibility and Reliability Assessment in Clinical Research. Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography, 29(12). pp. 1144-1154.e7. 10.1016/j.echo.2016.08.006. Retrieved from https://hdl.handle.net/10161/22519.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Barnhart

Huiman Xie Barnhart

Professor of Biostatistics & Bioinformatics
My research interests include both statistical methodology and disease-specific clinical research biostatistics. My statistical research areas include methods for assessing reliability/agreement between methods or raters, evaluating performance of new medical diagnostic tests, missing data, correlated categorical data and methods for clinical trials. My collaborative research include the following clinical areas: cardiovascular imaging, radiology imaging, cardiovascular disease, renal disea
Chamis

Anna Lisa Chamis

Associate Professor of Medicine
Daubert

Melissa Anne Daubert

Associate Professor of Medicine
Douglas

Pamela Susan Douglas

Ursula Geller Distinguished Professor of Research in Cardiovascular Diseases
Pamela S Douglas MD is the Ursula Geller Professor of Research in Cardiovascular Diseases in the Department of Medicine at Duke University and Director of the Multimodality Imaging Program at Duke Clinical Research Institute. During her 30+ years of experience she has led several landmark multicenter government studies and pivotal industry clinical trials along with outcomes research studies.  She is renowned for her scientific and policy work in improving the quality and appropriateness
Pencina

Michael J Pencina

Professor of Biostatistics & Bioinformatics
Michael J. Pencina, PhD Chief Data Scientist, Duke Health Vice Dean for Data Science Director, Duke AI Health Professor, Biostatistics & Bioinformatics Duke University School of Medicine Michael J. Pencina, PhD, is Duke Health's chief data scientist and serves as vice dean for data science, director of Duke AI Health, and professor of biostatistics and bioinformatics at the Duke University School of Medicine. His work bridges the fiel
Sullivan

Daniel Carl Sullivan

Professor Emeritus of Radiology
Research interests are in oncologic imaging, especially the clinical evaluation and validation of imaging biomarkers for therapeutic response assessment.
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