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Background Atrial fibrillation (AF) remain a prevalent undiagnosed condition frequently encountered in primary care. Objective We aimed to find the parameters that optimize the diagnostic accuracy of pulse palpation to detect AF. We also aimed to create a simple algorithm for selecting which individuals would benefit from pulse palpation and, if positive, receive an ECG to detect AF. Methods Nurses from four Cardiology outpatient clinics palpated 7,844 pulses according to a randomized list of arterial territories and durations of measure and immediately followed by a 12-lead ECG, which we used as the reference standard. We calculated the sensitivity and specificity of the palpation parameters. We also assessed whether diagnostic accuracy depended on the nurse’s experience or on a list of clinical factors of the patients. With this information, we estimated the positive predictive values and false omission rates according to very few clinical factors readily available in primary care (age, sex, and diagnosis of heart failure) and used them to create the algorithm. Results The parameters associated with the highest diagnostic accuracy were palpation of the radial artery and classifying as irregular those palpations in which the nurse was uncertain about pulse regularity or unable to palpate pulse (sensitivity = 79%; specificity = 86%). Specificity decreased with age. Neither the nurse’s experience nor any investigated clinical factor influenced diagnostic accuracy. We provide the algorithm to select the ≥40 years old individuals that would benefit from a pulse palpation screening: a) do nothing in <60 years old individuals without heart failure; b) do ECG in ≥70 years old individuals with heart failure; c) do radial pulse palpation in the remaining individuals and do ECG if the pulse is irregular or you are uncertain about its regularity or unable to palpate it. Conclusions Opportunistic screening for AF using optimal pulse palpation in candidate individuals according to a simple algorithm may have high effectiveness in detecting AF in primary care.

Funding Acknowledgements Type of funding sources: None. INTRODUCTION  Left ventricular noncompaction (LVNC) is a poorly defined entity with heterogeneous prognosis. LV ejection fraction (LVEF) is one of the main predictors of major adverse cardiovascular events (MACE). However, outcomes of LVNC patients with preserved LVEF (pEF) remain uncertain. PURPOSE  The aim of our study was to determine the incidence and predictors of MACE in LVNC patients with pEF as well as to assess the evolution of LVEF throughout follow-up.  METHODS  We conducted a retrospective, longitudinal, multicentre cohort study. Consecutive patients with transthoracic echocardiography (TTE) and/or cardiac magnetic resonance (CMR) diagnostic criteria for LVNC and initially pEF (LVEF≥50%) were recruited. MACE were defined as a composite of heart failure (HF), ventricular arrhythmias (VA), systemic embolisms (SE) and/or all-cause mortality. Progressive systolic dysfunction was defined as an LVEF &lt; 50% at last TTE and/or an absolute ≥10-point decrease in LVEF from first to last TTE. Lower limit of LVEF CMR values were considered 50-57% according to current recommendations. Cox-regression analysis was used for MACE and logistic regression was used for progressive systolic dysfunction (only first and last TTE were available). RESULTS  A total of 305 patients from 12 centres were included from 2000 to 2018. Age was 38 ± 19 years and 165 (54%) were men. LVEF was 62 ± 8% and 8% had late gadolinium enhancement (LGE). During a median follow-up of 4.7 (IQR 2.1-7.4) years, MACE occurred in 40 (13%) patients with an incidence rate of 2.73 (95% CI 2.00-3.72) events per 100 person-years: 8 HF, 27 VA, 3 SE and 5 deaths. LVEF by CMR (HR 0.95, 95% CI 0.91-0.99, p = 0.0048) and hypertension (HR 2.30, 95% CI 1.08-4.89, p = 0.031) were the only variables independently associated with the endpoint. Patients with lower limit LVEF values showed an increased risk of MACE (Figure 1). LGE was not associated. Sixty-one (21%) patients experienced progressive systolic dysfunction: 31 (11%) had an LVEF &lt; 50% and 48 (17%) an absolute ≥10-point decrease in LVEF at last follow-up. On multivariate analysis, LVEF by CMR was the only independent predictor (OR 0.93, 95% CI 0.89-0.98, p = 0.008). Patients with lower limit LVEF values had an increased risk (Figure 2). In this subgroup, LGE was also associated with the endpoint (HR 10.69, 95% CI 1.97-58.13, p = 0.006). CONCLUSIONS  Patients with left ventricular noncompaction and preserved ejection fraction carry a moderate risk of major adverse cardiovascular events and progressive systolic dysfunction. LVEF remains the main predictor of outcomes in this subgroup. Patients with lower limit LVEF values are at increased risk, probably suggesting subclinical systolic dysfunction. Therefore, they should be carefully monitored. Abstract Figure. Kaplan Meier cuves for MACE  Abstract Figure. Risk of progressive systolic dysfunction

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