Atrial fibrillation detection in primary care during blood pressure measurements and using a smartphone cardiac monitor

Atrial Fibrillation Screening During Routine Automated Office, Home, and Ambulatory Blood Pressure Measurement: A Diagnostic Test Accuracy Systematic Review and Meta-Analysis

BACKGROUND

Atrial fibrillation (AF) is often asymptomatic and undiagnosed. As AF and hypertension often coexist, opportunistic AF detection during routine automated blood pressure (BP) measurement appears to be an attractive screening method.

METHODS

A systematic literature search was conducted to identify studies assessing the diagnostic test accuracy of office, home, or 24-hour ambulatory BP measuring devices with AF detection algorithms versus reference electrocardiography. Analyses were performed per participant (AF status based on several BP readings; most office/home devices) or per reading (AF status based on individual readings; all ambulatory devices). A meta-analysis stratified by device type (office/home/ambulatory) was conducted to calculate pooled measures of diagnostic accuracy. Sensitivity/meta-regression analyses were also performed.

RESULTS

Among 3096 records initially retrieved, 23 diagnostic test accuracy studies were included. Data derived from 11 093 individuals (weighted age 69 years, males 56%, hypertensives 79%, diabetics 24%, and AF prevalence 17%) indicated a pooled sensitivity 0.97 (95% CI, 0.92-0.99), specificity 0.93 (95% CI, 0.90-0.95), and accuracy 0.93 (95% CI, 0.89-0.95), with generally consistent results using office, home, or ambulatory BP devices (slightly lower specificity with the latter). The positive and negative predictive values were 0.70 (95% CI, 0.60-0.80) and 0.99 (95% CI, 0.98-1.00), respectively. Sensitivity analyses indicated lower specificity in studies implementing reading versus participant analyses. Most studies presented a low risk of bias and minor applicability concerns.

CONCLUSIONS

There is considerable and consistent evidence suggesting high diagnostic accuracy of AF detection algorithms implemented in automated BP monitors during routine BP measurements in and out of the office. AF diagnosis requires verification (electrocardiography) before treatment is administered.

Identifying metabolic syndrome in migrant Asian Indian adults with anthropometric and visceral fat action points

BACKGROUND

Metabolic syndrome (MetS) is a clustering of metabolic risk factors, including large waist circumference (WC). Other anthropometric parameters and visceral fat mass (VFM) predicted from these may improve MetS detection. Our aim was to assess the ability of such parameters to predict this clustering in a cross-sectional, diagnostic study.

METHOD

Participants were 82 males and 86 females, aged 20-74 years, of Asian Indian ethnicity. VFM was estimated by dual-energy X-ray absorptiometry (DXA) through identification of abdominal subcutaneous fat layer boundaries. Non-anthropometric metabolic risk factors (triglycerides, HDL cholesterol, blood pressure and glucose) were defined using MetS criteria. We estimated the ability of anthropometry and VFM to detect ≥ 2 of these factors by receiver operating characteristic (ROC) and precision-recall curves.

RESULTS

Two or more non-anthropometric metabolic risk factors were present in 45 (55%) males and 29 (34%) females. The area under the ROC curve (AUC) to predict ≥ 2 of these factors using WC was 0.67 (95% confidence interval: 0.55-0.79) in males and 0.65 (0.53-0.77) in females. Optimal WC cut-points were 92 cm for males (63% accuracy) and 79 cm for females (53% accuracy). VFM, DXA-measured sagittal diameter and suprailiac skinfold thickness yielded higher AUC point estimates (by up to 0.06), especially in females where these measures improved accuracy to 69%, 69% and 65%, respectively. Pairwise combinations that included WC further improved accuracy.

CONCLUSION

Our findings indicate that cut-points for readily obtained measures other than WC, or in combination with WC, may provide improved detection of MetS risk factor clusters.