ArticleJournal of human hypertension2017
Incidence of atrial fibrillation and its risk prediction model based on a prospective urban Han Chinese cohort.
Article in Journal of human hypertension, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.
- The association of coagulation and atrial fibrillation: a systematic review and meta-analysis.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023Pooled it
- Utility of risk prediction models to detect atrial fibrillation in screened participants.European journal of preventive cardiology · 2021Pooled it
- Precise risk-prediction model including arterial stiffness for new-onset atrial fibrillation using machine learning techniques.Journal of clinical hypertension (Greenwich, Conn.) · 2024Article
- CHARGE-AF: A Useful Score For Atrial Fibrillation Prediction?Current cardiology reviews · 2023Article
- Predicting Silent Atrial Fibrillation in the Elderly: A Report from the NOMED-AF Cross-Sectional Study.Journal of clinical medicine · 2021Article
- Atrial fibrillation in low- and middle-income countries: a narrative review.European heart journal supplements : journal of the European Society of Cardiology · 2020Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prediction models of atrial fibrillation (AF) have been developed; however, there was no AF prediction model validated in Chinese population. Therefore, we aimed to investigate the incidence of AF in urban Han Chinese health check-up population, as well as to develop AF prediction models using behavioral, anthropometric, biochemical, electrocardiogram (ECG) markers, as well as visit-to-visit variability (VVV) in blood pressures available in the routine health check-up. A total of 33 186 participants aged 45-85 years and free of AF at baseline were included in this cohort, to follow up for incident AF with an annually routine health check-up. Cox regression models were used to develop AF prediction model and 10-fold cross-validation was used to test the discriminatory accuracy of prediction model. We developed three prediction models, with age, sex, history of coronary heart disease (CHD), hypertension as predictors for simple model, with left high-amplitude waves, premature beats added for ECG model, and with age, sex, history of CHD and VVV in systolic and diabolic blood pressures as predictors for VVV model, to estimate risk of incident AF. The calibration of our models ranged from 1.001 to 1.004 (P for Hosmer Lemeshow test >0.05). The area under receiver operator characteristics curve were 78%, 80% and 82%, respectively, for predicting risk of AF. In conclusion, we have identified predictors of incident AF and developed prediction models for AF with variables readily available in routine health check-up.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.