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Figure.  Sensitivity of Correct Rhythm Identification, by Subgroups of Interest
Sensitivity of Correct Rhythm Identification, by Subgroups of Interest

AAD indicates antiarrhythmic drug; AT/AF, atrial tachycardia/atrial fibrillation; ECG, electrocardiogram; HF, heart failure.

Table.  Baseline Characteristics Overall and Stratified by Rhythm and Identificationa
Baseline Characteristics Overall and Stratified by Rhythm and Identificationa
1.
Dorian  P, Jung  W, Newman  D,  et al.  The impairment of health-related quality of life in patients with intermittent atrial fibrillation: implications for the assessment of investigational therapy.   J Am Coll Cardiol. 2000;36(4):1303-1309. doi:10.1016/S0735-1097(00)00886-XPubMedGoogle ScholarCrossref
2.
Biber  J, Ose  D, Reese  J,  et al.  Patient reported outcomes: experiences with implementation in a university health care setting.   J Patient Rep Outcomes. 2017;2:34. doi:10.1186/s41687-018-0059-0PubMedGoogle ScholarCrossref
3.
Steinberg  BA, Turner  J, Lyons  A,  et al.  Systematic collection of patient-reported outcomes in atrial fibrillation: feasibility and initial results of the Utah mEVAL AF programme.   Europace. 2020;22(3):368-374. doi:10.1093/europace/euz293PubMedGoogle ScholarCrossref
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    Research Letter
    Cardiology
    May 21, 2020

    Accuracy of Patient Identification of Electrocardiogram-Verified Atrial Arrhythmias

    Author Affiliations
    • 1Division of Cardiovascular Medicine, University of Utah Health Sciences Center, University of Utah, Salt Lake City
    • 2Data Science Services, University of Utah Health Sciences Center, Salt Lake City
    • 3Department of Population Health Sciences, University of Utah, Salt Lake City
    JAMA Netw Open. 2020;3(5):e205431. doi:10.1001/jamanetworkopen.2020.5431
    Introduction

    Atrial fibrillation (AF) is the most common arrhythmia in adults, and treatment of AF is often focused on improving symptoms. Patient-reported outcomes can provide standardized, health-related, quality-of-life end points to guide and support clinical decisions. The association of patient symptoms with arrhythmia may be confounded. We sought to understand the accuracy of patients’ identification of their arrhythmia and association with perceived symptom burden. Specifically, the objectives of this cross-sectional study were to describe the sensitivity and specificity of patient self-assessment for atrial arrhythmia compared with 12-lead electrocardiogram (ECG) and to describe the association of patient perception of arrhythmia with symptom burden.

    Methods

    This study was approved by the University of Utah institutional review board. A waiver of consent was granted because the study used anonymous, aggregate data that were collected as part of routine clinical care.

    All patients with AF in our electrophysiology clinic are asked to complete the Toronto Atrial Fibrillation Severity Scale (AFSS) patient-reported outcomes assessment immediately before the clinic visit.1 The details of our system have been described previously.2,3 Among its 4 domains, the AFSS requests that patients identify their current rhythm; it also yields a 35-point symptom score (referred to hereafter as the AFSS symptom score), with higher scores reflecting increasing patient perceived AF symptom burden (range, 0-35 points). We compared single-visit patient self-awareness results with the results of same-day, in-clinic, 12-lead ECG (reference standard) to understand patient accuracy of atrial arrhythmia self-identification. We also assessed perceived vs actual atrial arrhythmia compared with AFSS symptom score.

    Categorical variables are summarized as number (percentage), and continuous variables are summarized as mean (SD). Univariate comparisons were performed with χ2 tests for categorical variables and analysis of variance for continuous variables. Two-sided P < .05 was considered statistically significant. All analyses were performed using R statistical software version 3.5.2 and RStudio version 1.2.1335 (both from R Project for Statistical Computing), with specialty packages. Data analysis was performed from September 2018 to September 2019.

    Results

    From October 2016 to February 2019, 656 patients (mean [SD] age, 66.34 [11.94] y; 255 women [38.9%]) responded to the AFSS question regarding current atrial rhythm and had an interpretable ECG from the same day. Baseline characteristics of these patients, stratified by ECG rhythm and response, are shown in the Table. Most of the patients were white (599 patients [91.3%]), 75.5% (495 patients) had a history of hypertension, and 38.3% (25 patients) were taking a β-blocker. The mean (SD) left ventricular ejection fraction was 59.36 (10.11).

    Among 160 patients in arrhythmia, patients’ own assessment of rhythm was 64% sensitive for detecting it (102 of 160 patients). On the basis of ECG, 496 patients were in sinus rhythm and demonstrated an accuracy of 91% for detecting it (453 correctly indicated no arrhythmia). Overall, 85% of patients responded consistently with their ECG, including patients with normal rhythm and those in atrial arrhythmia (positive predictive value, 70%; negative predictive value, 89%). Sensitivities for rhythm self-identification, by subgroups of interest, are shown in the Figure.

    The mean (SD) overall AFSS symptom score was 8.95 (7.4), with 16% missing. The AFSS symptom score was higher for those who believed they were currently in atrial arrhythmia (mean [SD], 12.70 [8.45] for those who correctly identified AF and 12.23 [8.17] for those in sinus rhythm who incorrectly thought they were in AF) compared with those who did not believe they were in atrial arrhythmia (mean [SD], 8.12 [6.95] for those who correctly identified that they were not in AF and 6.86 [5.47] for those who were in AF but incorrectly thought they were not). In sum, the AFSS symptom score was lowest in the population who were in atrial arrhythmia but were unaware of it.

    Discussion

    Our analysis of patient self-identification of arrhythmia yields several important observations that may affect treatment decisions for patients with AF. First, the sensitivity of patient identification for atrial arrhythmia is low; only two-thirds (64%) of patients in atrial arrhythmia correctly identified it. Second, there are important subgroup differences regarding self-identification of cardiac rhythm; younger patients and those receiving an antiarrhythmic drug appear particularly sensitive to detecting atrial arrhythmia. Finally, AFSS symptom score measuring perceived AF symptoms appears to track more closely with perceived vs actual arrhythmia. There are few data available regarding a patient’s ability to correctly identify symptoms of AF, yet we rely on this information nearly every day for clinical decision-making. Naturally, this analysis is limited by the real-world uncontrolled setting, and we were not present while patients answered patient-reported outcomes questions. Regardless, these findings have important implications for both routine, symptomatic management of AF, as well as clinical trials with symptom-driven outcomes. Our data highlight the limitations of relying solely on patient symptom self-reporting for arrhythmia burden and impact and support the routine use of confirmatory testing to diagnose AF and to evaluate the association of symptoms with arrhythmia.

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    Article Information

    Accepted for Publication: March 17, 2020.

    Published: May 21, 2020. doi:10.1001/jamanetworkopen.2020.5431

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Turner JL et al. JAMA Network Open.

    Corresponding Author: Benjamin A. Steinberg, MD, MHS, Division of Cardiovascular Medicine, University of Utah Health Sciences Center, University of Utah, 30 N 1900 E, Rm 4A100, Salt Lake City, UT 84132 (benjamin.steinberg@hsc.utah.edu).

    Author Contributions: Dr Steinberg had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Turner, Hess, Steinberg.

    Acquisition, analysis, or interpretation of data: Turner, Lyons, Shah, Zenger, Steinberg.

    Drafting of the manuscript: Turner, Steinberg.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Turner, Steinberg.

    Obtained funding: Shah.

    Administrative, technical, or material support: Turner, Zenger, Steinberg.

    Supervision: Hess, Steinberg.

    Conflict of Interest Disclosures: Dr Hess reported receiving personal fees from Astellas Pharmaceuticals outside the submitted work. Dr Steinberg reported receiving grants from American Heart Association and Patient-Centered Outcomes Research and Boston Scientific; grants and personal fees from Janssen; and personal fees from BMS/Pfizer, Biosense-Webster, Bayer, and Merit Medical. No other disclosures were reported.

    Funding/Support: Research reported in this publication was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under Award Number K23HL143156 (to Dr Steinberg).

    Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

    Additional Contributions: T. Jared Bunch, MD (University of Utah Health Sciences Center), James C. Fang, MD (University of Utah Health Sciences Center), Roger A. Freedman, MD (University of Utah Health Sciences Center), Jonathan P. Piccini, MD, MHS (Duke University Medical Center), Ravi Ranjan, MD, PhD (University of Utah Health Sciences Center), John A. Spertus, MD, MPH (Mid America Heart Institute), and Josef Stehlik, MD, MPH (University of Utah Health Sciences Center), critically reviewed the manuscript for intellectual content; none of them was compensated for this contribution.

    References
    1.
    Dorian  P, Jung  W, Newman  D,  et al.  The impairment of health-related quality of life in patients with intermittent atrial fibrillation: implications for the assessment of investigational therapy.   J Am Coll Cardiol. 2000;36(4):1303-1309. doi:10.1016/S0735-1097(00)00886-XPubMedGoogle ScholarCrossref
    2.
    Biber  J, Ose  D, Reese  J,  et al.  Patient reported outcomes: experiences with implementation in a university health care setting.   J Patient Rep Outcomes. 2017;2:34. doi:10.1186/s41687-018-0059-0PubMedGoogle ScholarCrossref
    3.
    Steinberg  BA, Turner  J, Lyons  A,  et al.  Systematic collection of patient-reported outcomes in atrial fibrillation: feasibility and initial results of the Utah mEVAL AF programme.   Europace. 2020;22(3):368-374. doi:10.1093/europace/euz293PubMedGoogle ScholarCrossref
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