Patients with atrial fibrillation were identified using three clinical risk factors — sex, age and BMI — and two biomarkers, including elevated brain natriuretic peptide and elevated fibroblast growth factor-23, according to a study published in the European Heart Journal.
“People with atrial fibrillation are much more likely to develop blood clots and suffer from strokes,” Winnie Chua, MD, postdoctoral researcher at the Institute of Cardiovascular Sciences at University of Birmingham in the United Kingdom, said in a press release. “To avoid strokes, it is important for them to take anticoagulant drugs to prevent blood clotting. However, atrial fibrillation is often only diagnosed after a patient has suffered a stroke. Therefore, it is important that patients at risk are screened so that they can begin taking anticoagulants to prevent potentially life-threatening complications.”
Researchers analyzed data from 638 patients (mean age, 70 years; 62% men; 46% AF) who were referred to a hospital for evaluation between September 2015 and August 2016. Patients at this time were either diagnosed with AF or had at least two CHA2DS2-VASc stroke risk factors. Seven-day ambulatory ECG was performed in patients who were not diagnosed with AF to potentially detect silent AF.
Clinical information was obtained through chart review, detailed interview and a review of electronic patient records. All patients underwent transthoracic echocardiography, and blood samples were taken for biomarker quantification. In this study, researchers assessed 40 biomarkers and seven clinical risk factors, including sex, age, hypertension, history of stroke or transient ischemic attack, HF, BMI and kidney function.
The clinical risk factors that were significantly associated with AF were older age (OR = 1.06 per year increase; 95% CI, 1.04-1.1), male sex (OR = 2.022; 95% CI, 1.28-3.56) and higher BMI (OR = 1.06 per BMI unit increase; 95% CI, 1.02-1.12).
The biomarkers linked to AF were elevated brain natriuretic peptide (OR = 1.293 per fold change increase; 95% CI, 1.11-1.63), elevated fibroblast growth factor-23 (OR = 1.667; 95% CI, 1.36-2.34) and reduced tumor necrosis factor-related apoptosis-induced ligand-receptor 2 (OR = 0.242 per fold change increase; 95% CI, 0.14-0.32).
Compared with clinical risk factors alone, adding biomarkers to clinical risk factors improved AF prediction (net reclassification improvement = 0.178; P < .001). During validation, AF was predicted well in logistic regression (area under the receiver-operator curve = 0.684; 95% CI, 0.62-0.75) and machine learning (area under the receiver-operator curve = 0.697; 95% CI, 0.63-0.76).
“Including biomarker measurements in clinical practice could better identify patients with undiagnosed prevalent AF,” Chua and colleagues wrote. “A point-of-care test for [brain natriuretic peptide] and/or [fibroblast growth factor]-23 could allow such screening in many settings, especially in environments without immediate input from medically trained personnel. This can refine ongoing approaches using only age and [brain natriuretic peptide] to select patients for screening.” – by Darlene Dobkowski
Disclosures: Chua reports no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.