Key result
AF screening participation yields no difference in new AF detection compared to non-participation.
Why the study?
The success of screening programs depends on participation, and non-participants usually have a higher risk of disease; therefore, predicting participation and estimating the potential yield of screening-detected disease in non-participants was needed.
What factors predict participation in an atrial fibrillation screening program, and what is the estimated yield of screening-detected disease among non-participants?
Observational (n=6,868)
What factors predict participation in an atrial fibrillation screening program, and what is the estimated yield of screening-detected disease among non-participants?
Answers are grounded in this paper and cite their sources.
Low income is a strong predictor of non-participation in atrial fibrillation screening, and despite higher stroke risk scores among non-participants, the estimated yield of new atrial fibrillation is similar to that of participants.
BACKGROUND: The success of any screening program is dependent on participation. The characteristics of participants vs. non-participants have been studied and non-participants usually have a higher risk of disease. The potential yield of screening-detected disease in non-participants could be of interest to several screening programs. AIMS: This is a sub-study to STROKESTOP II, a Swedish atrial fibrillation screening study. The aim was to study factors predicting participation and to estimate the potential yield of screening-detected disease in non-participants. METHODS: Individual, anonymized data for participants and non-participants with respect to socioeconomic factors, medical history and drugs dispensed were obtained from Swedish registries. A random forest model was trained to predict propensity scores for participation. The propensity scores were used to estimate potential screening-detected disease among non-participants. The strongest factor predicting non-attendance was low income. The weighted estimates suggested that the yield of new atrial fibrillation was 2.4% in non-participants compared to 2.3% in the participants, which was not significant. Low income was the strongest factor for predicting non-attendance and should be a focus area when planning future screening scenarios.
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Gudmundsdottir et al. (2022) conducted an observational in Atrial fibrillation (n=6,868). Non-participation in screening vs. Participation in screening was evaluated on Yield of new atrial fibrillation (p=not significant). Non-participation in an atrial fibrillation screening program yielded an estimated 2.4% of new atrial fibrillation compared to 2.3% in participants, which was not significantly different.
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