Background Cardiac resynchronization therapy(CRT)is a highly effective treatment in patients with a class I recommendation.However,a small proportion of the strictly selected patients still fail to respond.This study ...Background Cardiac resynchronization therapy(CRT)is a highly effective treatment in patients with a class I recommendation.However,a small proportion of the strictly selected patients still fail to respond.This study was designed to identify predictors of non-response in patients with class I indications for CRT and determine the non-response probability of the patients.Methods A total of 296 consecutive patients with a class I recommendation received CRT from January 2009 to January 2017 were retrospectively analyzed.Multivariate logistic regression analysis was performed to identify predictors for non-response(defined as cardiac death,heart transplantation,or HF hospitalization during 1-year follow-up).Results Among 296 patients,30(10.1%)met non-response.Multivariate analysis demonstrated that non-response to CRT was associated with a fragmented QRS(odd ratio(OR)=2.86,95%CI:1.14–7.12;P=0.025)and left ventricular end-diastolic dimension(LVEDD)≥77 mm(OR=3.02,95%CI:1.17–7.82;P=0.022).Patients with both of the predictors had a non-response probability of 46.2%(95%CI:19.1%–73.3%).Conclusion In patients with left bundle branch block and wider QRS duration,the proportion of non-response to CRT is not low in real world.The presence of the dilated LVEDD or fragmented QRS is a strong predictor of non-response to CRT.The probability of non-response in the patients with the two predictors was 46.2%.展开更多
Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping pr...Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping procedures such as cluster analysis, including stronger theoretical underpinnings, more clearly defined measures of model fit, and the ability to conduct confirmatory analyses. In addition, it is possible to ascertain whether an LCA solution is equally applicable to multiple known groups, using invariance assessment techniques. This study compared the effectiveness of multiple statistics for detecting group LCA invariance, including a chi-square difference test, a bootstrap likelihood ratio test, and several information indices. Results of the simulation study found that the bootstrap likelihood ratio test was the optimal invariance assessment statistic. In addition to the simulation, LCA group invariance assessment was demonstrated in an application with the Youth Risk Behavior Survey (YRBS). Implications of the simulation results for practice are discussed.展开更多
基金financially supported by the National Natural Science Foundation of China(81570370)CAMS Innovation Fund for Medical Sciences(2017-I2M-1-009)
文摘Background Cardiac resynchronization therapy(CRT)is a highly effective treatment in patients with a class I recommendation.However,a small proportion of the strictly selected patients still fail to respond.This study was designed to identify predictors of non-response in patients with class I indications for CRT and determine the non-response probability of the patients.Methods A total of 296 consecutive patients with a class I recommendation received CRT from January 2009 to January 2017 were retrospectively analyzed.Multivariate logistic regression analysis was performed to identify predictors for non-response(defined as cardiac death,heart transplantation,or HF hospitalization during 1-year follow-up).Results Among 296 patients,30(10.1%)met non-response.Multivariate analysis demonstrated that non-response to CRT was associated with a fragmented QRS(odd ratio(OR)=2.86,95%CI:1.14–7.12;P=0.025)and left ventricular end-diastolic dimension(LVEDD)≥77 mm(OR=3.02,95%CI:1.17–7.82;P=0.022).Patients with both of the predictors had a non-response probability of 46.2%(95%CI:19.1%–73.3%).Conclusion In patients with left bundle branch block and wider QRS duration,the proportion of non-response to CRT is not low in real world.The presence of the dilated LVEDD or fragmented QRS is a strong predictor of non-response to CRT.The probability of non-response in the patients with the two predictors was 46.2%.
文摘Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping procedures such as cluster analysis, including stronger theoretical underpinnings, more clearly defined measures of model fit, and the ability to conduct confirmatory analyses. In addition, it is possible to ascertain whether an LCA solution is equally applicable to multiple known groups, using invariance assessment techniques. This study compared the effectiveness of multiple statistics for detecting group LCA invariance, including a chi-square difference test, a bootstrap likelihood ratio test, and several information indices. Results of the simulation study found that the bootstrap likelihood ratio test was the optimal invariance assessment statistic. In addition to the simulation, LCA group invariance assessment was demonstrated in an application with the Youth Risk Behavior Survey (YRBS). Implications of the simulation results for practice are discussed.
