Yao, Xiaoxi

Catheter ablation has brought major advances in the management of patients with atrial fibrillation (AF). As evidenced by multiple randomized trials, AF catheter ablation can reduce the risk of recurrent AF and improve quality of life. In some studies, AF ablation significantly reduced cardiovascular hospitalizations. Despite the existing data on AF catheter ablation, numerous knowledge gaps remain concerning this intervention. This report is based on a recent virtual workshop convened by the National Heart, Lung, and Blood Institute to identify key research opportunities in AF ablation. We outline knowledge gaps related to emerging technologies, the relationship between cardiac structure and function and the success of AF ablation in patient subgroups in whom clinical benefit from ablation varies, and potential platforms to advance clinical research in this area. This report also considers the potential value and challenges of a sham ablation randomized trial. Prioritized research opportunities are identified and highlighted to empower relevant stakeholders to collaborate in designing and conducting effective, cost-efficient, and transformative research to optimize the use and outcomes of AF ablation.

Background The American College of Cardiology and American Heart Association periodically revise clinical practice guidelines. We evaluated changes in the evidence underlying guidelines published over a 10‐year period. Methods and Results Thirty‐five American College of Cardiology/American Heart Association guidelines were divided into 2 time periods: 2008 to 2012 and 2013 to 2017. Guidelines were categorized into the following topic areas: arrhythmias, prevention, acute and stable ischemia, heart failure, valvular heart disease, and vascular medicine. Changes in recommendations were assessed for each topic area. American College of Cardiology/American Heart Association designated class of recommendation as level I, II , or III (I represented “strongly recommended”) and levels of evidence ( LOE ) as A, C, or C (A represented “highest quality”). The median number of recommendations per each topic area was 281 (198–536, interquartile range) in 2008 to 2012 versus 247 (190–451.3, interquartile range) in 2013 to 2017. The median proportion of class of recommendation I was 49.3% and 44.4% in the 2 time periods, 38.0% and 44.5% for class of recommendation II , and 12.5% and 11.2% for class of recommendation III . Median proportions for LOE A were 15.7% and 14.1%, 41.0% and 52.8% for LOE B, and 46.9% and 32.5% for LOE C. The decrease in the proportion of LOE C was highest in heart failure (24.8%), valvular heart disease (22.3%), and arrhythmia (19.2%). An increase in the proportion of LOE B was observed for these same areas: 31.8%, 23.8%, and 19.2%, respectively. Conclusions There has been a decrease in American College of Cardiology/American Heart Association guidelines recommendations, driven by removal of recommendations based on lower quality of evidence, although there was no corresponding increase in the highest quality of evidence.

Abstract Rationale Since their approval, there has been no real-world or randomized trial evidence evaluating the effect of the antifibrotic medications pirfenidone and nintedanib on clinically important outcomes such as mortality and hospitalizations. Objectives To evaluate the clinical effectiveness of the antifibrotic medications pirfenidone and nintedanib in patients with idiopathic pulmonary fibrosis. Methods Using a large U.S. insurance database, we identified 8,098 patients with idiopathic pulmonary fibrosis between October 1, 2014 and March 1, 2018. A one-to-one propensity score–matched cohort was created to compare patients treated with antifibrotic medications (n = 1,255) with those not on treatment (n = 1,255). The primary outcome was all-cause mortality. The secondary outcome was acute hospitalizations. Subgroup analyses were performed to evaluate mortality differences by drug. Measurements and Main Results The use of antifibrotic medications was associated with a decreased risk of all-cause mortality (hazard ratio [HR], 0.77; 95% confidence interval [CI], 0.62–0.98; P value = 0.034). However, this association was present only through the first 2 years of treatment. There was also a decrease in acute hospitalizations in the treated cohort (HR, 0.70; 95% CI, 0.61–0.80; P value <0.001). There was no significant difference in all-cause mortality between patients receiving pirfenidone and those on nintedanib (HR, 1.14; 95% CI, 0.79–1.65; P = 0.471). Conclusions Among patients with idiopathic pulmonary fibrosis, antifibrotic agents may be associated with a lower risk of all-cause mortality and hospitalization compared with no treatment. Future research should test the hypothesis that these treatments reduce early, but not long-term, mortality as demonstrated in our study.

Background: Stroke prevention using warfarin is challenging in AF patients with CKD, due to high bleeding risk and difficulties in the INR control. NOACs provide alternative options, but all have greater degrees of renal clearance. This study aimed to compare the outcomes of apixaban, dabigatran, rivaroxaban, and warfarin across the range of kidney function in patients with AF. Methods: Using a US administrative database including private insurance or Medicare Advantage patients with linked claims and laboratory data, we identified 34,569 new users of oral anticoagulants with AF and eGFR ≥15 between 10/1/2010-11/29/2017. Stabilized IPTW balanced four treatment groups on 66 baseline characteristics. The primary outcomes included stroke, major bleeding, and mortality. Weighted Cox proportional hazards models compared treatments in the overall population and in each eGFR subgroup, with mortality as a competing risk for stroke and major bleeding. Results: The proportion of patients using warfarin increased as the kidney function declined - 26.5%, 30.4%, 34.6%, 40.5%, and 55.0% of patients were prescribed warfarin in eGFR ≥90, 60-90, 45-60, 30-45, 15-30 groups, respectively. In comparison to warfarin, apixaban was associated with a lower risk of stroke, major bleeding, and mortality; dabigatran was associated with a similar risk of stroke, and a lower risk of major bleeding and mortality; rivaroxaban was associated with a lower risk of stroke, major bleeding, and mortality (Figure). When comparing one NOAC to another NOAC, apixaban and dabigatran were associated with a lower risk of major bleeding than rivaroxaban (HR 0.61 [0.51-0.73], p<0.001 for apixaban versus rivaroxaban; HR 0.67 [0.50-0.90], p=0.007 for dabigatran versus rivaroxaban); dabigatran was associated with a higher risk of stroke than apixaban (HR 1.65 [1.11-2.46], p=0.01); there was no difference in mortality. There was no significant interaction between treatment and eGFR categories for any outcome, but the number of patients with low eGFR was small. Conclusions: In practice, relative to warfarin, NOACs are progressively less commonly used with increasing degree of renal dysfunction. However, each NOAC was consistently associated with at least equivalent effectiveness and safety compared with warfarin across the range of kidney function.

AbstractObjectivesWe sought to validate a deep learning algorithm designed to predict an ejection fraction (EF) less than or equal to 35% based on the 12‐lead electrocardiogram (ECG) in a large prospective cohort.BackgroundPatients undergoing routine ECG may have undetected left ventricular (LV) dysfunction that warrants further echocardiographic assessment. However, identification of these patients can be challenging.MethodsWe applied the algorithm to all ECGs interpreted by the Mayo Clinic ECG laboratory in September 2018. The performance of the algorithm was tested among patients with recent echocardiographic assessments of LV function. We also applied the algorithm in patients with no recent echocardiographic assessments of LV function to determine the rate of new “positive screens.”ResultsAmong 16 056 adult patients who underwent routine ECG, 8600 (age 67.1 ± 15.2 years, 45.6% male), had a transthoracic echocardiogram (TTE) and 3874 patients had a TTE and ECG less than 1 month apart. Among these patients, the algorithm was able to detect an EF less than or equal to 35% with 86.8% specificity, 82.5% sensitivity, and 86.5% accuracy, (area under the curve, 0.918). Among 474 “false‐positives screens,” 189 (39.8%) had an EF of 36% to 50%. Among patients with no prior TTE, the algorithm identified 3.5% of the patients with suspected EF less than or equal to 35%. Exploratory analysis suggests false positives could be reduced by assessing NT‐pro‐BNP after the initial “positive screen.”ConclusionsA deep learning algorithm detected depressed LV function with good accuracy in routine practice. Further studies are needed to validate the algorithm in patients with no prior echocardiogram and to assess the impact on echocardiography utilization, cost, and clinical outcomes.