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Detection of Atrial Fibrillation on Stroke Units: Comparison of Manual versus Automatic Analysis of Continuous
Andreas Rogalewski1, Jorge Plümer2, Tobias Feldmann3
1Department of Neurology, Evangelisches Klinikum Bethel, EvKB, Bielefeld, Bielefeld, Germany, andreas.rogalewski@evkb.de.
Insights
Automated atrial fibrillation (AF) detection is specific but less sensitive than manual ECG analysis. Combining both methods is recommended for optimal stroke patient care.
Area of Science:
- Cardiology
- Neurology
- Medical Technology
Background:
- Atrial fibrillation (AF) detection is crucial for stroke patients.
- Manual ECG analysis is the gold standard but resource-intensive.
- Automated RR interval analysis offers a potential simplification.
Purpose of the Study:
- To compare automated vs. manual ECG analysis for AF detection in stroke patients.
- To evaluate specificity, sensitivity, and cost-effectiveness.
- To determine the optimal role of automated AF detection.
Main Methods:
- Prospective study of 216 stroke patients over 7 months.
- Continuous ECG telemetry with both automated and manual blinded analysis.
- Comparison of sensitivity, specificity, time, cost, and cost-effectiveness.
Main Results:
- Automated AF detection showed 94.6% specificity and 78.4% sensitivity.
- Manual analysis detected AF in 6.7% of days, automated in 10.3%.
- Automation reduced human resources but increased costs; AF patients were older with more comorbidities.
Conclusions:
- Automated AF detection is highly specific but has lower sensitivity.
- Automated methods should complement, not replace, manual ECG analysis.
- Combined approach may improve AF detection in stroke units.
Background:
Detection of atrial fibrillation (AF) is one of the primary diagnostic goals for patients on a stroke unit. Physician-based manual analysis of continuous ECG monitoring is regarded as the gold standard for AF detection but requires considerable resources. Recently, automated computer-based analysis of RR intervals was established to simplify AF detection. The present prospective study analyzes both methods head to head regarding AF detection specificity, sensitivity, and overall effectiveness.
Methods:
Consecutive stroke patients without history of AF or proof of AF in the admission ECG were enrolled over the period of 7 months. All patients received continuous ECG telemetry during the complete stay on the stroke unit. All ECGs underwent automated analysis by a commercially available program. Blinded to these results, all ECG tracings were also assessed manually. Sensitivity, specificity, time consumption, costs per day, and cost-effectiveness were compared.
Results:
216 consecutive patients were enrolled (70.7 ± 14.1 years, 56% male) and 555 analysis days compared. AF was detected by manual ECG analysis on 37 days (6.7%) and automatically on 57 days (10.3%). Specificity of the automated algorithm was 94.6% and sensitivity 78.4% (28 [5.0%] false positive and 8 [1.4%] false negative). Patients with AF were older and had more often arterial hypertension, higher NIHSS at admission, more often left atrial dilatation, and a higher CHA2DS2-VASc score. Automation significantly reduced human resources but was more expensive compared to manual analysis alone.
Conclusion:
Automatic AF detection is highly specific, but sensitivity is relatively low. Results of this study suggest that automated computer-based AF detection should be rather complementary to manual ECG analysis than replacing it.
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