Risk of Atrial Fibrillation, Ischemic Stroke and Cognitive Impairment : Study of a Population Cohort ≥65 Years of Age

To evaluate a model for calculating the risk of AF and its relationship with the incidence of ischemic stroke and prevalence of cognitive decline. It was a multicenter, observational, retrospective, community-based study of a cohort of general population ≥6ct 35 years, between 01/01/2016 and 31/12/2018. Setting: Primary Care. Participants: 46,706 people ≥65 years with an active medical history in any of the primary care teams of the territory, information accessible through shared history and without previous known AF. Interventions: The model to stratify the risk of AF (PI) has been previously published and included the variables sex, age, mean heart rate, mean weight and CHA2DS2VASc score. Main measurements: For each risk group, the incidence density/1000 person/years of AF and stroke, number of cases required to detect a new AF, the prevalence of cognitive decline, Kendall correlation, and ROC curve were calculated. The prognostic index was obtained in 37,731 cases (80.8%) from lowest (Q1) to highest risk (Q4). A total of 1244 new AFs and 234 stroke episodes were diagnosed. Q3-4 included 53.8% of all AF and 69.5% of strokes in men; 84.2% of all AF and 85.4% of strokes in women; and 77.4% of cases of cognitive impairment. There was a significant linear correlation between the risk-AF score and the Rankin score (p < 0.001), the Pfeiffer score (p < 0.001), but not NIHSS score (p 0.150). The overall NNS was 1/19. Risk stratification allows identifying high-risk individuals in whom to intervene on modifiable risk factors, prioritizing the diagnosis of AF and investigating cognitive statu

Blood-biomarkers and devices for atrial fibrillation screening : Lessons learned from the AFRICAT (Atrial Fibrillation Research In CATalonia) study

AFRICAT is a prospective cohort study intending to develop an atrial fibrillation (AF) screening program through the combination of blood markers, rhythm detection devices, and long-term monitoring in our community. In particular, we aimed to validate the use of NT-proBNP, and identify new blood biomarkers associated with AF. Also, we aimed to compare AF detection using various wearables and long-term Holter monitoring. 359 subjects aged 65-75 years with hypertension and diabetes were included in two phases: Phase I (n = 100) and Phase II (n = 259). AF diagnosis was performed by baseline 12-lead ECG, 4 weeks of Holter monitoring (Nuubo TM), and/or medical history. An aptamer array including 1310 proteins was measured in the blood of 26 patients. Candidates were selected according to p-value, logFC and biological function to be tested in verification and validation phases. Several screening devices were tested and compared: AliveCor, Watch BP, MyDiagnostick and Fibricheck. AF was present in 34 subjects (9.47%). The aptamer array revealed 41 proteins with differential expression in AF individuals. TIMP-2 and ST-2 were the most promising candidates in the verification analysis, but none of them was further validated. NT-proBNP (log-transformed) (OR = 1.934; p<0.001) was the only independent biomarker to detect AF in the whole cohort. Compared to an ECG, WatchBP had the highest sensitivity (84.6%) and AUC (0.895 [0.780-1]), while MyDiagnostick showed the highest specificity (97.10%). The inclusion and monitoring of a cohort of primary care patients for AF detection, together with the testing of biomarkers and screening devices provided useful lessons about AF screening in our community. An AF screening strategy using rhythm detection devices and short monitoring periods among high-risk patients with high NT-proBNP levels could be feasible

Top table of the differential expressed proteins between AF and no AF

S1 Table: Top table of the differential expressed proteins between AF and no AF. Results from the discovery study.Results from the discovery study. Proteins selected to be verified in the whole Phase 1 are highlighted in grey. Proteins in bold but not highlighted were already tested in the whole phase 1 as part of a previous published work.Peer reviewe

Incidence and Risk Assessment for Atrial Fibrillation at 5 Years: Hypertensive Diabetic Cohort

(1) Background: The link between diabetes and hypertension is mutual and reciprocal, increasing the risks for the development of atrial fibrillation (AF). The main objective was to develop a prediction model for AF in a population with both diabetes and hypertension at five years of follow-up. (2) Methods: A multicenter and community-based cohort study was undertaken of 8237 hypertensive diabetic patients without AF between 1 January 2103 and 31 December 2017. Multivariate Cox proportional-hazards regression models were used to identify predictors AF and to stratify risk scores by quartiles. (3) Results: AF incidence was 10.5/1000 people/years (95% confidence interval (CI) 9.5–11.5), higher in men. The independent prognostic factors identified: age (hazard ratio (HR) 1.07 95% CI 1.05–1.09, p &lt; 0.001), weight (HR 1.03 95% CI 1.02–1.04, p &lt; 0.001), CHA2DS2VASc score (HR 1.57 95% CI 1.16–2.13, p = 0.003) and female gender (HR 0.55 95% CI 0.37–0.82, p = 0.004). Q4 (highest-risk group for AF) had the highest AF incidence, stroke and mortality, and the smallest number needed to screen to detect one case of AF. (4) Conclusions: Risk-based screening for AF should be used in high cardiovascular risk patients as the hypertensive diabetics, for treatment of modifiable cardiovascular risk, and monitoring AF detection

Results from the Registry of Atrial Fibrillation (AFABE): Gap between Undiagnosed and Registered Atrial Fibrillation in Adults—Ineffectiveness of Oral Anticoagulation Treatment with VKA

Objective. This study aimed to examine the effectiveness of the use of oral anticoagulation (OAC) medication, recommended by national guidelines for stroke prevention but reportedly underused in AF patients with moderate to high stroke risk. Method. A multicentre and cross-sectional study of undiagnosed AF among out-of-hospital patients over 60 years old was carried out, visiting 3,638 patients at primary health centres or at home for AF diagnosis using the IDC-10 classification. The main outcome measures were CHA2DS2VASC, HAS-BLED scores, cardiovascular comorbidity, pharmacological information, TTR, and SAMe-TT2R2 scores. Results. The main findings were undiagnosed AF in 26.44% of cases; 31.04% registered with AF but not using OAC despite 95.6% having a CHA2DS2VASC≥2 score; a risk of bleeding in important subgroups using OAC without indication (37.50% CHA2DS2VASC<2 score); the use of OAC with TTR < 60% (33.1%), of whom 47.6% had a HAS-BLED score ≥3. Thus, 35.4% of the expected AF prevalence achieved an optimal time in the therapeutic range. Conclusions. The expected AF prevalence was 10.9% (n 5267), but the registered prevalence was 7.5% (n 3638). Only 35.04% (CI = 95%, 33.7–36.3) of AF patients treated with vitamin K antagonists (VKAs) achieve the goal of TTR > 60%

Boxplot distribution of the 3 proteins selected for validation (NT-proBNP, ST-2 and TIMP-2) according to the methodology used for AF diagnosis

Peer reviewe

All patient data and biomarker measurements

Peer reviewe

Blood-biomarkers and devices for atrial fibrillation screening: Lessons learned from the AFRICAT (Atrial Fibrillation Research In CATalonia) study.

AFRICAT is a prospective cohort study intending to develop an atrial fibrillation (AF) screening program through the combination of blood markers, rhythm detection devices, and long-term monitoring in our community. In particular, we aimed to validate the use of NT-proBNP, and identify new blood biomarkers associated with AF. Also, we aimed to compare AF detection using various wearables and long-term Holter monitoring. 359 subjects aged 65-75 years with hypertension and diabetes were included in two phases: Phase I (n = 100) and Phase II (n = 259). AF diagnosis was performed by baseline 12-lead ECG, 4 weeks of Holter monitoring (NuuboTM), and/or medical history. An aptamer array including 1310 proteins was measured in the blood of 26 patients. Candidates were selected according to p-value, logFC and biological function to be tested in verification and validation phases. Several screening devices were tested and compared: AliveCor, Watch BP, MyDiagnostick and Fibricheck. AF was present in 34 subjects (9.47%). The aptamer array revealed 41 proteins with differential expression in AF individuals. TIMP-2 and ST-2 were the most promising candidates in the verification analysis, but none of them was further validated. NT-proBNP (log-transformed) (OR = 1.934; p The inclusion and monitoring of a cohort of primary care patients for AF detection, together with the testing of biomarkers and screening devices provided useful lessons about AF screening in our community. An AF screening strategy using rhythm detection devices and short monitoring periods among high-risk patients with high NT-proBNP levels could be feasible