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

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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

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Project description:IntroductionPostoperative atrial fibrillation (AF) occurs in 30-40% of patients after cardiac surgery. Identification of recurrent postoperative AF is required to initiate evidence-based management to reduce the risk of subsequent stroke. However, as AF is often asymptomatic, recurrences may not be detected after discharge. This study determines feasibility and impact of a self-surveillance programme to identify recurrence of postoperative AF in the month of posthospital discharge.Methods and analysisThis is a feasibility study, using a cross-sectional study design, of self-screening for AF using a hand-held single-lead iPhone electrocardiograph device (iECG). Participants will be recruited from the cardiothoracic surgery wards of the Royal North Shore Hospital and North Shore Private Hospital, Sydney, Australia. Cardiac surgery patients admitted in sinus rhythm and experiencing a transient episode of postoperative AF will be eligible for recruitment. Participants will be taught to take daily ECG recordings for 1 month posthospital discharge using the iECG and will be provided education regarding AF, including symptoms and health risks. The primary outcome is the feasibility of patient self-monitoring for AF recurrence using an iECG. Secondary outcomes include proportion of patients identified with recurrent AF; estimation of stroke risk and patient knowledge. Process outcomes and qualitative data related to acceptability of patient's use of the iECG and sustainability of the screening programme beyond the trial setting will also be collected.Ethics and disseminationPrimary ethics approval was received on 25 February 2014 from Northern Sydney Local Health District Human Resource Ethics Committee, and on 17 July 2014 from North Shore Private Hospital Ethics Committee. Results will be disseminated via forums including, but not limited to, peer-reviewed publications and presentation at national and international conferences.Trial registration numberACTRN12614000383662.

Project description:Radiofrequency ablation (RFA) using the CARTO 3D mapping system is a common approach for pulmonary vein isolation to treat atrial fibrillation (AF). Linkage between CARTO procedural data and patients' electronical health records (EHR) provides an opportunity to identify the ablation-related parameters that would predict AF recurrence. The objective of this study is to assess the incremental accuracy of RFA procedural data to predict post-ablation AF recurrence using machine learning model. Procedural data generated during RFA procedure were downloaded from CARTONET and linked to deidentified Mercy Health EHR data. Data were divided into train (70%) and test (30%) data for model development and validation. Automate machine learning (AutoML) was used to predict 1 year AF recurrence, defined as a composite of repeat ablation, electrical cardioversion, and AF hospitalization. At first, AutoML model only included Patients' demographic and clinical characteristics. Second, an AutoML model with procedural variables and demographical/clinical variables was developed. Area under receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI) were used to compare model performances using test data. Among 306 patients, 67 (21.9%) patients experienced 1-year AF recurrence. AUROC increased from 0.66 to 0.78 after adding procedural data in the AutoML model based on test data. For patients with AF recurrence, NRI was 32% for model with procedural data. Nine of 10 important predictive features were CARTO procedural data. From CARTO procedural data, patients with lower contact force in right inferior site, long ablation duration, and low number of left inferior and right roof lesions had a higher risk of AF recurrence. Patients with persistent AF were more likely to have AF recurrence. The machine learning model with procedural data better predicted 1-year AF recurrence than the model without procedural data. The model could be used for identification of patients with high risk of AF recurrence post ablation.

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

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