RESUMO
In 2019 the European Society of Cardiology (ESC) lowered the target values for low-density lipoprotein cholesterol (LDL-C) from <1.8 mmol/L to <1.4 mmol/L for secondary prevention of cardiovascular disease (CVD). The aim of this study was to determine the clinical impact of the 2019 ESC/EAS dyslipidaemia guidelines on lipid-lowering therapies and achievement rates of LDL-C targets in a contemporary cohort of CAD patients participating in an ambulatory cardiac rehabilitation (CR) program.We conducted a retrospective analysis of prospectively collected data from the Swiss Secondary Prevention Registry (SwissPR) in patients with Coronary Artery Disease (CAD), who completed the ambulatory cardiovascular rehabilitation program (CR) of the University Hospital Basel, Switzerland from January 2017 to April 2021. To evaluate the impact of the guideline publication, the cohort was split into a pre-Guideline 2019 group (A) and a post-Guideline 2019 group (B). In total 1320 patients were screened leaving 875 patients for analysis. At discharge, more patients in group B were on maximal statin doses (20% vs. 9%, p < 0.0001) and on combination therapy with ezetimibe (51% vs. 17%, p < 0.0001) than in group A, which resulted in 53% of patients reaching the LDL-C target of <1.4 mmol/L in group B. Regression analysis revealed that dyslipidaemia and positive smoking history represent independent predictors for intensified lipid-lowering medication, whereas absolving CR after publication of the 2019 guidelines was the only significant predictor for reduced LDL-C at CR discharge. We found a significant difference in prescription rates of lipid-lowering medication, especially combination therapies and statin doses, after publication of the 2019 ESC/EAS dyslipidaemia guidelines resulting in an achievement rate of >50% of the LDL-C target <1.4 mmol/L in CAD patients participating in ambulatory CR.
RESUMO
OBJECTIVES: The WATCH AF (SmartWATCHes for Detection of Atrial Fibrillation) trial compared the diagnostic accuracy to detect atrial fibrillation (AF) by a smartwatch-based algorithm using photoplethysmographic (PPG) signals with cardiologists' diagnosis by electrocardiography (ECG). BACKGROUND: Timely detection of AF is crucial for stroke prevention. METHODS: In this prospective, 2-center, case-control trial, a PPG pulse wave recording using a commercially available smartwatch was obtained along with Internet-enabled mobile ECG in 672 hospitalized subjects. PPG recordings were analyzed by a novel automated algorithm. Cardiologists' diagnoses were available for 650 subjects, although 142 (21.8%) datasets were not suitable for PPG analysis, among them 101 (15.1%) that were also not interpretable by the automated Internet-enabled mobile ECG algorithm, resulting in a sample size of 508 subjects (mean age 76.4 years, 225 women, 237 with AF) for the main analyses. RESULTS: For the PPG algorithm, we found a sensitivity of 93.7% (95% confidence interval [CI]: 89.8% to 96.4%), a specificity of 98.2% (95% CI: 95.8% to 99.4%), and 96.1% accuracy (95% CI: 94.0% to 97.5%) to detect AF. CONCLUSIONS: The results of the WATCH AF trial suggest that detection of AF using a commercially available smartwatch is in principle feasible, with very high diagnostic accuracy. Applicability of the tested algorithm is currently limited by a high dropout rate as a result of insufficient signal quality. Thus, achieving sufficient signal quality remains challenging, but real-time signal quality checks are expected to improve signal quality. Whether smartwatches may be useful complementary tools for convenient long-term AF screening in selected at-risk patients must be evaluated in larger population-based samples. (SmartWATCHes for Detection of Atrial Fibrillation [WATCH AF]:; NCT02956343).