[Risk factors for heart failure after right ventricular apical pacing].

OBJECTIVE: To explore the prevalence and risk factors for the onset of heart failure after right ventricular apical pacing. METHODS: The clinical data of 1 343 patients with pacemaker implantation at our hospital from 2003 to 2008 were analyzed retrospectively. And the predictors of heart failure were evaluated by the Cox proportional hazard model and Kaplan-Meier method. RESULTS: During a median follow-up period of 71 (76±24) months, 303 patients (22.6%) developed a new onset of heart failure. Multivariate Cox analysis revealed that ≥65 years old (hazard ratio 2.37), a history of myocardial infarction (hazard ratio 2.16), VVI mode (hazard ratio 2.37), left ventricular ejection fraction (LVEF)<50% (hazard ratio 2.00), atrioventricular block or atrial fibrillation with slow ventricular rate etiologically (hazard ratio 1.43) were independent risk factors for heart failure (P<0.05). And the risks increased by 19.4%, 33.0%, 20.9%, 38.4%, 17.2% or 25.9% at 71 months respectively. CONCLUSION: After right ventricular apical pacing, heart failure is a progressive syndrome correlated with basal cardiac functions, underlying etiologies and age. And right ventricular apical pacing should be avoided in patients with high risk factors.

Comparison of the RF-CL and CACS-CL models to estimate the pretest probability of obstructive coronary artery disease and predict prognosis in patients with stable chest pain and diabetes mellitus.

Background: The most appropriate tool for estimating the pretest probability (PTP) of obstructive coronary artery disease (CAD) in patients with diabetes mellitus (DM) and stable chest pain (SCP) remains unknown. Therefore, we aimed to validate and compare two recent models, namely, the risk factor-weighted clinical likelihood (RF-CL) model and coronary artery calcium score (CACS)-weighted clinical likelihood (CACS-CL) model, in these patient populations. Methods: A total of 1,245 symptomatic patients with DM, who underwent CACS and coronary computed tomographic angiography (CCTA) scan, were identified and followed up. PTP of obstructive CAD for each patient was estimated using the RF-CL model and CACS-CL model, respectively. Area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to assess the performance of models. The associations of major adverse cardiovascular events (MACE) with risk groups were evaluated using Cox proportional hazards regression. Results: Compared with the RF-CL model, the CACS-CL model revealed a larger AUC (0.856 vs. 0.782, p = 0.0016), positive IDI (12%, p < 0.0001) and NRI (34%, p < 0.0001), stronger association to MACE (hazard ratio: 0.26 vs. 0.38) and less discrepancy between observed and predicted probabilities, resulting in a more effective risk assessment to optimize downstream clinical management. Conclusion: Among patients with DM and SCP, the incorporation of CACS into the CACS-CL model resulted in a more accurate estimation for PTP and prediction of MACE. Utilizing the CACS-CL model, instead of the RF-CL model, might have greater potential to avoid unnecessary and omissive cardiovascular imaging testing with minimal cost.