Prediction of incident atrial fibrillation in community-based electronic health records: a systematic review with meta-analysis.

OBJECTIVE: Atrial fibrillation (AF) is common and is associated with an increased risk of stroke. We aimed to systematically review and meta-analyse multivariable prediction models derived and/or validated in electronic health records (EHRs) and/or administrative claims databases for the prediction of incident AF in the community. METHODS: Ovid Medline and Ovid Embase were searched for records from inception to 23 March 2021. Measures of discrimination were extracted and pooled by Bayesian meta-analysis, with heterogeneity assessed through a 95% prediction interval (PI). Risk of bias was assessed using Prediction model Risk Of Bias ASsessment Tool and certainty in effect estimates by Grading of Recommendations, Assessment, Development and Evaluation. RESULTS: Eleven studies met inclusion criteria, describing nine prediction models, with four eligible for meta-analysis including 9 289 959 patients. The CHADS (Congestive heart failure, Hypertension, Age>75, Diabetes mellitus, prior Stroke or transient ischemic attack) (summary c-statistic 0.674; 95% CI 0.610 to 0.732; 95% PI 0.526-0.815), CHA2DS2-VASc (Congestive heart failure, Hypertension, Age>75 (2 points), Stroke/transient ischemic attack/thromboembolism (2 points), Vascular disease, Age 65-74, Sex category) (summary c-statistic 0.679; 95% CI 0.620 to 0.736; 95% PI 0.531-0.811) and HATCH (Hypertension, Age, stroke or Transient ischemic attack, Chronic obstructive pulmonary disease, Heart failure) (summary c-statistic 0.669; 95% CI 0.600 to 0.732; 95% PI 0.513-0.803) models resulted in a c-statistic with a statistically significant 95% PI and moderate discriminative performance. No model met eligibility for inclusion in meta-analysis if studies at high risk of bias were excluded and certainty of effect estimates was 'low'. Models derived by machine learning demonstrated strong discriminative performance, but lacked rigorous external validation. CONCLUSIONS: Models externally validated for prediction of incident AF in community-based EHR demonstrate moderate predictive ability and high risk of bias. Novel methods may provide stronger discriminative performance. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021245093.

Prescription of oral anticoagulants and antiplatelets for stroke prophylaxis in atrial fibrillation: nationwide time series ecological analysis.

AIMS: To investigate trends in the prescription of oral anticoagulants (OACs) and antiplatelet agents for atrial fibrillation (AF). METHODS AND RESULTS: Prescription data for 450 518 patients with AF from 3352 General Practices in England, was obtained from the GRASP-AF registry, 2009-2018. Annualized temporal trends for OAC and antiplatelet prescription were reported according to eligibility based on stroke risk (CHADS2 or CHA2DS2-VASc scores ≥1 or >2, respectively). From 2009 to 2018, the prevalence of AF increased from 1.6% [95% confidence interval (CI) 1.5-1.7%] to 2.4% (2.3-2.5%), and for those with AF the proportion prescribed OAC increased from 47.6% to 75.0% (P-trend < 0.001; relative risk 1.57, 95% CI 1.55-1.60) and for antiplatelet decreased from 37.4% to 9.2% (P-trend < 0.001). In early-years (2009-2013), eligible patients aged ≥80 years were less likely to be prescribed OAC than patients aged <80 years [odds ratio (OR) 0.55, 95% CI 0.51-0.59 for CHADS2≥1 in 2009] (all P-trends < 0.001). This 'OAC prescription gap' reduced over the study period (OR 0.93, 0.90-0.96 in 2018). Whilst the prescription of direct oral anticoagulant (DOAC) as a proportion of all OAC increased from 0.1% (95% CI 0.0-0.2%) in 2011 to 58.8% (58.4-59.2%) in 2018, it was inversely associated with patient age (P-trend < 0.001) and their risk of stroke. CONCLUSION: Between 2009 and 2018, in England, the use of OAC for stroke prophylaxis in AF increased, with DOAC accounting for over half of OAC uptake in 2018. Despite a reduction in the OAC-prescription gap, a new paradox exists relating to DOAC prescription for the elderly and those at higher risk of stroke.

Distribution of hemoglobinopathy disorders in Saudi Arabia based on data from the premarital screening and genetic counseling program, 2011-2015.

The prevalence rates of ß-thalassemia (ß-thal) and Sickle Cell Disease (SCD) in Saudi Arabia are considered one of the highest compared to surrounding countries in the Middle East (0.05% and 4.50%, respectively). In this study, Secondary data analysis was obtained from the premarital screening and genetic counseling program (PMSGC), and included 12,30,582 individuals from February 2011 to December 2015. Prevalence rates (per 1000 population) for ß-thal and SCD were calculated for carrier status, disease status and their combination. During the 5-year study period, the overall prevalence rate per 1000 population for ß-thal was 13.6 (12.9 for the trait and 0.7 for the disease). The prevalence rate for SCD was 49.6 (45.8 for the trait and 3.8 for the disease). Rates for ß-thal were found to decrease from 24.2 in 2011, to 12 in 2015. However, SCD rates remained rather constant and ranged from 42.3 in 2011 to 49.8 in 2015. The highest rate for both ß-thal and SCD was observed in the Eastern and Southern regions. This result reflects major accomplishment of the PMSGC. This study recommends further improvement in preventive measures in high-risk regions, and enhanced community awareness to provide the highest rate reduction for these disorders.