Increased left atrial size is associated with higher atrial fibrillation recurrence in patients treated with antiarrhythmic medications

The relationship between serum potassium levels and cardiac arrhythmias in left ventricular assist device (LVAD) recipients: a comprehensive analysis and prognostic evaluation

BACKGROUND

This study aimed to comprehensively analyze the relationship between serum potassium (K+) levels and the risk of de novo cardiac arrhythmias in left ventricular assist device (LVAD) recipients.

METHODS

We performed a retrospective study using the INTERMACS registry. Data was collected on adult patients with available K+ measurements taken 1-month post-LVAD implantation. K+ levels were the main exposure of interest and were analyzed as a continuous and categorical variable (quartiles of baseline K+ distribution). The main outcome of interest was the occurrence of de novo arrhythmia events, either sustained (ventricular [VA] or supraventricular arrhythmia [SVA]) or not sustained (atrial fibrillation/flutter [AF]). All-cause mortality was evaluated as the secondary outcome. Multivariable adjusted time-dependent Cox regression models and natural splines were used to describe the relationship between the exposure and outcomes of interest.

RESULTS

10,570 patients met our inclusion criteria. A significant and consistent relationship was observed between the lowest quartile of longitudinal K+ and the risk of arrhythmic events (HR 1.28, 95% CI 1.08, 1.53, p = 0.005) as well as in the highest K+ quartile (HR 1.24, 95% CI 1.02, 1.49, p = 0.027). A similar relationship was confirmed in the stratified analysis of arrhythmia types for SVAs and AF. The data were reflected in a U shaped relationship. Similarly, the highest and lowest quartiles of longitudinal K+ were independently associated with a significant increase in the HR of death, which was reflected by a U shaped relationship.

CONCLUSIONS

Our study reveals a significant U shaped relationship between low and high K + levels and cardiac arrhythmias in LVAD patients, particularly SVAs and AF. Both high and low K + levels negatively impacted patient survival.

Qualitative Evaluation of an Artificial Intelligence–Based Clinical Decision Support System to Guide Rhythm Management of Atrial Fibrillation: Survey Study

Background

Despite the numerous studies evaluating various rhythm control strategies for atrial fibrillation (AF), determination of the optimal strategy in a single patient is often based on trial and error, with no one-size-fits-all approach based on international guidelines/recommendations. The decision, therefore, remains personal and lends itself well to help from a clinical decision support system, specifically one guided by artificial intelligence (AI). QRhythm utilizes a 2-stage machine learning (ML) model to identify the optimal rhythm management strategy in a given patient based on a set of clinical factors, in which the model first uses supervised learning to predict the actions of an expert clinician and identifies the best strategy through reinforcement learning to obtain the best clinical outcome—a composite of symptomatic recurrence, hospitalization, and stroke.

Objective

We qualitatively evaluated a novel, AI-based, clinical decision support system (CDSS) for AF rhythm management, called QRhythm, which uses both supervised and reinforcement learning to recommend either a rate control or one of 3 types of rhythm control strategies—external cardioversion, antiarrhythmic medication, or ablation—based on individual patient characteristics.

Methods

Thirty-three clinicians, including cardiology attendings and fellows and internal medicine attendings and residents, performed an assessment of QRhythm, followed by a survey to assess relative comfort with automated CDSS in rhythm management and to examine areas for future development.

Results

The 33 providers were surveyed with training levels ranging from resident to fellow to attending. Of the characteristics of the app surveyed, safety was most important to providers, with an average importance rating of 4.7 out of 5 (SD 0.72). This priority was followed by clinical integrity (a desire for the advice provided to make clinical sense; importance rating 4.5, SD 0.9), backward interpretability (transparency in the population used to create the algorithm; importance rating 4.3, SD 0.65), transparency of the algorithm (reasoning underlying the decisions made; importance rating 4.3, SD 0.88), and provider autonomy (the ability to challenge the decisions made by the model; importance rating 3.85, SD 0.83). Providers who used the app ranked the integrity of recommendations as their highest concern with ongoing clinical use of the model, followed by efficacy of the application and patient data security. Trust in the app varied; 1 (17%) provider responded that they somewhat disagreed with the statement, “I trust the recommendations provided by the QRhythm app,” 2 (33%) providers responded with neutrality to the statement, and 3 (50%) somewhat agreed with the statement.

Conclusions

Safety of ML applications was the highest priority of the providers surveyed, and trust of such models remains varied. Widespread clinical acceptance of ML in health care is dependent on how much providers trust the algorithms. Building this trust involves ensuring transparency and interpretability of the model.

Predicting Values of Neutrophil-to-Lymphocyte Ratio (NLR), High-Sensitivity C-Reactive Protein (hs-CRP), and Left Atrial Diameter (LAD) in Patients with Nonvalvular Atrial Fibrillation Recurrence After Radiofrequency Ablation

BACKGROUND The purpose of this study was to evaluate the predictive values of lipid level, inflammatory biomarkers, and echocardiographic parameters in late NVAF (nonvalvular atrial fibrillation) recurrence after RFA (radiofrequency ablation). MATERIAL AND METHODS This retrospective single-center study enrolled 263 patients with paroxysmal or persistent NVAF who underwent initial RFA from Jan 2017 to Jan 2019. The patients were divided into a Recurrent group (n=70) and a Nonrecurrent group (n=193). Univariate and multivariate logistic regression analyses were used for evaluating the predictive factors of late NVAF recurrence. Receiver operating characteristic (ROC) curves were constructed to assess the predictive performance and the optimum cut-off level of variables. RESULTS Late NVAF recurrence occurred in 70 patients (26.6%) after initial RFA within 12-month follow-up. Patients in the Recurrent group had significant higher NLR (neutrophil-to-lymphocyte ratio), hs-CRP (high-sensitivity C-reactive protein), LVEDD (left ventricular end-diastolic dimension), LVESD (left ventricular end-systolic dimension), and LAD (left atrial diameter) than those in the Nonrecurrent group (P<0.05). In multivariate analysis, increased NLR (HR=1.438, 95% CI: 1.036-1.995, P<0.05), hs-CRP (HR=1.137, 95% CI: 1.029-1.257, P<0.05) and LAD (HR=1.089, 95% CI: 1.036-1.146, P<0.05) were independent predictors of NVAF recurrence. The area under the curve (AUC) of NLR and hs-CRP was 0.603 (95% CI 0.525-0.681) and 0.584 (95% CI 0.501-0.666), respectively. The combination of NLR, hs-CRP, and LAD revealed an AUC of 0.684 (95% CI 0.611-0.757), with cut-off values of 2.33, 2.025 ng/L, and 44.5 mm, respectively. CONCLUSIONS The combination of preoperative NLR, hs-CRP, and LAD can predict late NVAF recurrence.

Serum relaxin level predicts recurrence of atrial fibrillation after radiofrequency catheter ablation

Relaxin, an emerging biomarker in heart failure, is involved in fibrosis and inflammation. The value of relaxin in predicting recurrence of atrial fibrillation (AF) after radiofrequency catheter ablation (RFCA) is unknown and the subject of this study. We prospectively enrolled 248 consecutive patients with AF (paroxysmal in 127 and persistent in 121) who underwent RFCA at our center after measurement of circulating levels of relaxin by ELISA. Kaplan-Meier analysis with log-rank test and multivariate analysis were used to assess the association between pre-RFCA relaxin levels and post-RFCA AF recurrence at 18 months follow-up. At mean 16.3 ± 3.8 months post-RFCA, 195 (78.6%) patients maintained sinus rhythm, and their pre-RFCA relaxin level was lower than that in patients with AF recurrence (P < 0.001). From lowest to highest pre-RFCA relaxin level tertiles (T1; 82.10-< 234.36; T2; 234.36-< 342.26; and T3; 342.26-740.63 ng/L), AF recurrence rate increased significantly (8.5%, 20.5% and 34.9%, respectively; Kaplan-Meier analysis with log-rank test, χ² = 18.44, P < 0.001). Using a cutoff of 285.4 ng/L, pre-RFCA relaxin level predicted AF recurrence during follow-up with sensitivity of 77.4% and specificity of 55.9% (area under the receiver operating characteristic curve = 0.71). On multivariate Cox proportional hazard model, relaxin level by tertile (T2, hazard ratio 2.678; 95% confidence interval 1.110-6.460; P = 0.028, and T3, hazard ratio 4.745; 95% confidence interval 2.075-10.854; P < 0.001, respectively compared with the T1) was the independent factor predicting recurrence. Elevated pre-RFCA relaxin level is associated with post-RFCA AF recurrence. A simple measurement of relaxin level therefore might help identify patients at high risk of AF recurrence after RFCA.Clinical Trial Registration chictr.org.cn identifier: ChiCTR-OOC-15006130.

Increased left atrial size is associated with higher atrial fibrillation recurrence in patients treated with antiarrhythmic medications

BACKGROUND

Atrial fibrillation (AF) is highly prevalent, and antiarrhythmic therapy is often used to help with rhythm control. Some common echocardiographic parameters may be useful in predicting AF recurrence among these patients. The purpose of this study was to evaluate the association between 3 common echocardiographic parameters (left atrial [LA] size, left ventricular ejection fraction [LVEF], and mitral regurgitation [MR]) and AF recurrence among patients treated with antiarrhythmic medications.

HYPOTHESIS

We hypothesized that LA size, LVEF, and severity of MR are predictors of AF recurrence in this population.

METHODS

A real-world cohort of AF patients who had transthoracic echocardiograms was analyzed. Data on LA size, LVEF, and MR were collected retrospectively from echocardiography reports. Patients were followed from the time of the echocardiogram until first recurrence of AF.

RESULTS

A total of 2522 patients had echocardiography reports available for review. LA size showed the strongest prognostic relationship with AF recurrence; neither LVEF nor MR was significantly associated with AF recurrence. These results persisted after adjusting for age, sex, race, tobacco use, alcohol use, drug use, body mass index, and Charlson Comorbidity Index in a multivariable model.

CONCLUSIONS

In a cohort of patients treated with antiarrhythmic medications that had transthoracic echocardiogram data, LA size was a significant predictor of AF recurrence. The clinical utility of this finding would be strengthened by replication in a multicenter setting.