Dataset Information

Triage tests for identifying atrial fibrillation in primary care: a diagnostic accuracy study comparing single-lead ECG and modified BP monitors.

ABSTRACT: New electronic devices offer an opportunity within routine primary care settings for improving the detection of atrial fibrillation (AF), which is a common cardiac arrhythmia and a modifiable risk factor for stroke. We aimed to assess the performance of a modified blood pressure (BP) monitor and two single-lead ECG devices, as diagnostic triage tests for the detection of AF.6 General Practices in the UK.1000 ambulatory patients aged 75 years and over.Comparative diagnostic accuracy of modified BP monitor and single-lead ECG devices, compared to reference standard of 12-lead ECG, independently interpreted by cardiologists.A total of 79 participants (7.9%) had AF diagnosed by 12-lead ECG. All three devices had a high sensitivity (93.9-98.7%) and are useful for ruling out AF. WatchBP is a better triage test than Omron autoanalysis because it is more specific-89.7% (95% CI 87.5% to 91.6%) compared to 78.3% (95% CI 73.0% to 82.9%), respectively. This would translate into a lower follow-on ECG rate of 17% to rule in/rule out AF compared to 29.7% with the Omron text message in the study population. The overall specificity of single-lead ECGs analysed by a cardiologist was 94.6% for Omron and 90.1% for Merlin.WatchBP performs better as a triage test for identifying AF in primary care than the single-lead ECG monitors as it does not require expertise for interpretation and its diagnostic performance is comparable to single-lead ECG analysis by cardiologists. It could be used opportunistically to screen elderly patients for undiagnosed AF at regular intervals and/or during BP measurement.

SUBMITTER: Kearley K

PROVIDER: S-EPMC4025411 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Triage tests for identifying atrial fibrillation in primary care: a diagnostic accuracy study comparing single-lead ECG and modified BP monitors.

Kearley Karen K Selwood Mary M Van den Bruel Ann A Thompson Matthew M Mant David D Hobbs Fd Richard FR Fitzmaurice David D Heneghan Carl C

BMJ open 20140502 5

<h4>Objective</h4>New electronic devices offer an opportunity within routine primary care settings for improving the detection of atrial fibrillation (AF), which is a common cardiac arrhythmia and a modifiable risk factor for stroke. We aimed to assess the performance of a modified blood pressure (BP) monitor and two single-lead ECG devices, as diagnostic triage tests for the detection of AF.<h4>Setting</h4>6 General Practices in the UK.<h4>Participants</h4>1000 ambulatory patients aged 75 years ...[more]

PMID: 24793250

Similar Datasets

Project description:BackgroundAtrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. If new-onset AF could be predicted, targeted screening could be used to find it early. We hypothesized that a deep neural network could predict new-onset AF from the resting 12-lead ECG and that this prediction may help identify those at risk of AF-related stroke.MethodsWe used 1.6 M resting 12-lead digital ECG traces from 430 000 patients collected from 1984 to 2019. Deep neural networks were trained to predict new-onset AF (within 1 year) in patients without a history of AF. Performance was evaluated using areas under the receiver operating characteristic curve and precision-recall curve. We performed an incidence-free survival analysis for a period of 30 years following the ECG stratified by model predictions. To simulate real-world deployment, we trained a separate model using all ECGs before 2010 and evaluated model performance on a test set of ECGs from 2010 through 2014 that were linked to our stroke registry. We identified the patients at risk for AF-related stroke among those predicted to be high risk for AF by the model at different prediction thresholds.ResultsThe area under the receiver operating characteristic curve and area under the precision-recall curve were 0.85 and 0.22, respectively, for predicting new-onset AF within 1 year of an ECG. The hazard ratio for the predicted high- versus low-risk groups over a 30-year span was 7.2 (95% CI, 6.9-7.6). In a simulated deployment scenario, the model predicted new-onset AF at 1 year with a sensitivity of 69% and specificity of 81%. The number needed to screen to find 1 new case of AF was 9. This model predicted patients at high risk for new-onset AF in 62% of all patients who experienced an AF-related stroke within 3 years of the index ECG.ConclusionsDeep learning can predict new-onset AF from the 12-lead ECG in patients with no previous history of AF. This prediction may help identify patients at risk for AF-related strokes.

Project description:The inverse problem of electrocardiography is usually analyzed during stationary rhythms. However, the performance of the regularization methods under fibrillatory conditions has not been fully studied. In this work, we assessed different regularization techniques during atrial fibrillation (AF) for estimating four target parameters, namely, epicardial potentials, dominant frequency (DF), phase maps, and singularity point (SP) location. We use a realistic mathematical model of atria and torso anatomy with three different electrical activity patterns (i.e., sinus rhythm, simple AF, and complex AF). Body surface potentials (BSP) were simulated using Boundary Element Method and corrupted with white Gaussian noise of different powers. Noisy BSPs were used to obtain the epicardial potentials on the atrial surface, using 14 different regularization techniques. DF, phase maps, and SP location were computed from estimated epicardial potentials. Inverse solutions were evaluated using a set of performance metrics adapted to each clinical target. For the case of SP location, an assessment methodology based on the spatial mass function of the SP location, and four spatial error metrics was proposed. The role of the regularization parameter for Tikhonov-based methods, and the effect of noise level and imperfections in the knowledge of the transfer matrix were also addressed. Results showed that the Bayes maximum-a-posteriori method clearly outperforms the rest of the techniques but requires a priori information about the epicardial potentials. Among the purely non-invasive techniques, Tikhonov-based methods performed as well as more complex techniques in realistic fibrillatory conditions, with a slight gain between 0.02 and 0.2 in terms of the correlation coefficient. Also, the use of a constant regularization parameter may be advisable since the performance was similar to that obtained with a variable parameter (indeed there was no difference for the zero-order Tikhonov method in complex fibrillatory conditions). Regarding the different targets, DF and SP location estimation were more robust with respect to pattern complexity and noise, and most algorithms provided a reasonable estimation of these parameters, even when the epicardial potentials estimation was inaccurate. Finally, the proposed evaluation procedure and metrics represent a suitable framework for techniques benchmarking and provide useful insights for the clinical practice.

Project description:BackgroundDetection of undiagnosed or undertreated ("actionable") atrial fibrillation could increase the use of appropriate oral anticoagulant therapy and reduce the risk of stroke. We sought to compare newer screening technologies with a pulse-check for the detection of atrial fibrillation and to determine whether the detection of actionable atrial fibrillation increases the use of oral anticoagulant agents.MethodsThis prospective multicentre cohort study involved 22 primary care clinics. We recruited participants aged 65 years and older who were attending routine appointments. Each participant underwent 3 methods of screening: a 30-second radial pulse-check; single-lead electrocardiogram; and screening by blood pressure machine with atrial fibrillation detection algorithms. Participants who received a positive result on 1 or more test underwent 12-lead electrocardiogram with or withour 24-hour Holter. Screening tests were compared using the McNemar test. Participants with confirmed atrial fibrillation received follow-up at 90 days.ResultsThe mean age of participants was 73.7 (± 6.9) years, and 53.4% of participants were female. Of 2171 patients, we had data from all 3 screening tests for 2054 patients. Both single-lead electrocardiogram and the blood pressure device showed superior specificity compared with pulse-check (p < 0.001 for each). Fifty-six patients (2.7%) had confirmed atrial fibrillation: 12 patients had newly detected atrial fibrillation (none of the patients were using anticoagulation agents), and 44 patients had previously diagnosed atrial fibrillation (42 patients were receiving anticoagulant therapy, 2 were not). Thus, 14 patients had actionable atrial fibrillation (0.7%). By 90 days, 77% of patients with actionable atrial fibrillation had started anticoagulant therapy.InterpretationNewer screening technologies showed superior specificity compared with a pulse-check. Screening detected undiagnosed or undertreated atrial fibrillation in 0.7% of participants, and 77% started appropriate anticoagulant therapy.Trial registrationClinicalTrials.gov, no. NCT02262351.

Dataset Information

Triage tests for identifying atrial fibrillation in primary care: a diagnostic accuracy study comparing single-lead ECG and modified BP monitors.

Publications

Triage tests for identifying atrial fibrillation in primary care: a diagnostic accuracy study comparing single-lead ECG and modified BP monitors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets