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Background Paroxysmal atrial fibrillation (PAF) is associated with cardioembolic risk, however events may occur during sinus rhythm (SR). 4D-flow cardiac magnetic resonance (CMR) imaging allows visualisation of left atrial blood flow, to determine the residence time distribution (RTD), an assessment of atrial transit time. Objective To determine if atrial transit time is prolonged in PAF patients during SR, consistent with underlying atrial stasis. Method 91 participants with PAF and 18 healthy volunteers underwent 4D flow analysis in SR. Velocity fields were produced RTDs, calculated by seeding virtual ‘particles’ at the right upper pulmonary vein and counting them exiting the mitral valve. An exponential decay curve quantified residence time of particles in the left atrium, and atrial stasis was expressed as the derived constant (RTDTC) based on heartbeats. The RTDTC was evaluated within the PAF group, and compared to healthy volunteers. Results Patients with PAF (n = 91) had higher RTDTC compared with gender-matched controls (n = 18) consistent with greater atrial stasis (1.68 ± 0.46 beats vs 1.51 ± 0.20 beats; p = .005). PAF patients with greater thromboembolic risk had greater atrial stasis (median RTDTC of 1.72 beats in CHA₂DS₂-VASc≥2 vs 1.52 beats in CHA₂DS₂-VASc Conclusions Atrial stasis quantified by 4D flow is greater in PAF, correlating with higher CHA₂DS₂-VASc scores. Female gender and systolic dysfunction are associated with atrial stasis. RTD offers an insight into atrial flow that may be developed to provide a personalised assessment of thromboembolic risk.

Paroxysmal atrial fibrillation (PAF) is associated with cardioembolic risk, however events may occur during sinus rhythm (SR). 4D-flow cardiac magnetic resonance (CMR) imaging allows visualisation of left atrial blood flow, to determine the residence time distribution (RTD), an assessment of atrial transit time.To determine if atrial transit time is prolonged in PAF patients during SR, consistent with underlying atrial stasis.91 participants with PAF and 18 healthy volunteers underwent 4D flow analysis in SR. Velocity fields were produced RTDs, calculated by seeding virtual 'particles' at the right upper pulmonary vein and counting them exiting the mitral valve. An exponential decay curve quantified residence time of particles in the left atrium, and atrial stasis was expressed as the derived constant (RTDPatients with PAF (n = 91) had higher RTDAtrial stasis quantified by 4D flow is greater in PAF, correlating with higher CHA₂DS₂-VASc scores. Female gender and systolic dysfunction are associated with atrial stasis. RTD offers an insight into atrial flow that may be developed to provide a personalised assessment of thromboembolic risk.

Cognitive impairment is highly prevalent in heart failure (HF), and may be associated with short-term readmission. This study investigated the role of cognition, incremental to other clinical and non-clinical factors, independent of depression and anxiety, in predicting 30-day readmission or death in HF.This study followed 565 patients from an Australia-wide HF longitudinal study. Cognitive function (MoCA score) together with standard clinical and non-clinical factors, mental health and 2D echocardiograms were collected before hospital discharge. The study outcomes were death and readmission within 30days of discharge. Logistic regression, Harrell's C-statistic, integrated discrimination improvement (IDI) and net reclassification index were used for analysis.Among 565 patients, 255 (45%) had at least mild cognitive impairment (MoCA≤22). Death (n=43, 8%) and readmission (n=122, 21%) within 30days of discharge were more likely to occur among patients with mild cognitive impairment (OR=2.00, p=0.001). MoCA score was also negatively associated with 30-day readmission or death (OR=0.91, p0.001) independent of other risk factors. Adding MoCA score to an existing prediction model of 30-day readmission significantly improved discrimination (C-statistic=0.715 vs. 0.617, IDI estimate 0.077, p0.001). From prediction models developed from our study, adding MoCA score (C-statistic=0.83) provided incremental value to that of standard clinical and non-clinical factors (C-statistic=0.76) and echocardiogram parameters (C-statistic=0.81) in predicting 30-day readmission or death. Reclassification analysis suggests that addition of MoCA score improved classification for a net of 12% of patients with 30-day readmission or death and of 6% of patients without (p=0.002).Mild cognitive impairment predicts short-term outcomes in HF, independent of clinical and non-clinical factors.