scholarly journals Septal flash as a predictor of cardiac resynchronization therapy response: A systematic review and meta-analysis

2021 ◽  
Author(s):  
Sadie Bennett ◽  
Jacopoa Tafuro ◽  
Simon Duckett ◽  
Grant Heatlie ◽  
Ashish Patwala ◽  
...  
Keyword(s):  
Systematic Review ◽  
Cardiac Resynchronization Therapy ◽  
Meta Analysis ◽  
Therapy Response ◽  
Symptomatic Improvement ◽  
Left Ventricular ◽  
Cardiac Resynchronization ◽  
Resynchronization Therapy ◽  
Septal Flash ◽  
Crt Response

Background: Cardiac resynchronization therapy (CRT) in heart failure patients has been shown to improve patient outcomes in some but not all patients. A few studies have identified that septal flash on imaging is associated with response to CRT but there has yet to be systematic review to evaluate consistency of the finding across the literature. Methods: A search of MEDLINE and EMBASE was conducted to identify studies which evaluate septal flash and its association with CRT response. Studies that met the inclusion criteria were statistically pooled with random-effects meta-analysis and heterogeneity was assessed using the I statistic. Results: A total of nine studies were included with 2,307 participants (mean age 76 years, 67% male). Septal flash on imaging before CRT implantation was seen in 53% of patients and the proportion of CRT responders from the included studies varied from 52% to 77%. In patients who were CRT responders, septal flash was seen in 40% of patients compared to 10% in those deemed to be CRT non-responders. Meta-analysis of the eight studies suggests that the presence of septal flash at pre-implant was associated with an increased likelihood of CRT response (RR 2.55 95%CI 2.04-3.19, p<0.001, I2=51%). Septal flash was also reported to be associated with left ventricular reverse remodelling but the association with survival and symptomatic improvement was less clear. Conclusions: Septal flash is a well-defined and distinctive contraction pattern which is consistently associated with CRT response and should be evaluated when assessing for appropriateness of CRT device.

scholarly journals Importance of systematic right ventricular assessment in cardiac resynchronization therapy candidates: a machine-learning approach

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
E Galli ◽  
V Le Rolle ◽  
OA Smiseth ◽  
J Duchenne ◽  
JM Aalen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Failure ◽  
Cardiac Resynchronization Therapy ◽  
Right Ventricular ◽  
Systolic Heart Failure ◽  
Left Ventricular ◽  
Supervised Machine Learning ◽  
Cardiac Resynchronization ◽  
Resynchronization Therapy ◽  
Crt Response

Abstract Funding Acknowledgements Type of funding sources: None. Background Despite having all a systolic heart failure and broad QRS, patients proposed for cardiac resynchronization therapy (CRT) are highly heterogeneous and it remains extremely complicated to predict the impact of the device on left ventricular (LV) function and outcomes. Objectives We sought to evaluate the relative impact of clinical, electrocardiographic, and echocardiographic data on the left ventricular (LV) remodeling and prognosis of CRT-candidates by the application of machine learning (ML) approaches. Methods 193 patients with systolic heart failure undergoing CRT according to current recommendations were prospectively included in this multicentre study. We used a combination of the Boruta algorithm and random forest methods to identify features predicting both CRT volumetric response and prognosis (Figure 1). The model performance was tested by the area under the receiver operating curve (AUC). We also applied the K-medoid method to identify clusters of phenotypically-similar patients. Results From 28 clinical, electrocardiographic, and echocardiographic-derived variables, 16 features were predictive of CRT-response; 11 features were predictive of prognosis. Among the predictors of CRT-response, 7 variables (44%) pertained to right ventricular (RV) size or function. Tricuspid annular plane systolic excursion was the main feature associated with prognosis. The selected features were associated with a very good prediction of both CRT response (AUC 0.81, 95% CI: 0.74-0.87) and outcomes (AUC 0.84, 95% CI: 0.75-0.93) (Figure 1, Supervised Machine Learning Panel). An unsupervised ML approach allowed the identifications of two phenogroups of patients who differed significantly in clinical and parameters, biventricular size and RV function. The two phenogroups had significant different prognosis (HR 4.70, 95% CI: 2.1-10.0, p &lt; 0.0001; log –rank p &lt; 0.0001; Figure 1, Unsupervised Machine Learning Panel). Conclusions Machine learning can reliably identify clinical and echocardiographic features associated with CRT-response and prognosis. The evaluation of both RV-size and function parameters has pivotal importance for the risk stratification of CRT-candidates and should be systematically assessed in patients undergoing CRT. Abstract Figure 1

scholarly journals The use of mechanical dyssynchrony for predicting response to cardiac resynchronization therapy in patients with non-ischemic cardiomyopathy

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
V Saushkin ◽  
YV Varlamova ◽  
AI Mishkina ◽  
DI Lebedev ◽  
SV Popov ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Myocardial Perfusion ◽  
Cardiac Resynchronization Therapy ◽  
Ischemic Cardiomyopathy ◽  
Gated Spect ◽  
Mechanical Dyssynchrony ◽  
Left Ventricular ◽  
Cardiac Resynchronization ◽  
Resynchronization Therapy ◽  
Crt Response

Abstract Funding Acknowledgements Type of funding sources: None. Aim/Introduction: Assessment of mechanical dyssynchrony by myocardial perfusion gated-SPECT in patients with non-ischemic cardiomyopathy for predict response to cardiac resynchronization therapy (CRT). Materials and Methods  We examined 32 patients with non-ischemic cardiomyopathy before and six months after CRT.  Left ventricular mechanical dyssynchrony and contractility were assessed for all patients by myocardial perfusion gated-SPECT. The phase standard deviation (PSD), histogram bandwidth (HBW), phase histogram skewness (S) and phase histogram kurtosis (K) were used as an indicator of mechanical dyssynchrony for the both ventricles.  Results  Mechanical dyssynchrony of both ventricles before CRT was increased in all patients. Median value PSD 53°(41-61°), HBW 176°(136-202°), S 1,62(1,21-1,89), K 2,81(1,21-3,49). Six months after CRT 22(68%) respondents were identified. We divided the patients into two groups (responders and non-responders) and compared phase parameters. It was found that the PSD (44°(35-54°)) and HBW (158°(118-179°) in the responders were significantly lower than in the non-responders (PSD (68°(58-72°); HBW (205°(199-249°)). The value of phase histogram skewness and kurtosis in responders were significantly higher (Responders: S 1,77(1,62-2,02); K 3,03(2,60-3,58). Non-responders: S 1,21(0,93-1,31); K 1,21(0,19-1,46)).  We found that all four indicators of mechanical dyssynchrony can predict CRT response according to the results of univariate logistic regression analysis. Moreover, It was found that only phase histogram kurtosis (OR = 1.196, 95% CI 1.04-1.37) is an independent predictor of CRT response according to multivariate logistic regression. Conclusion  Radionuclide assessment of mechanical dyssynchrony may be the optimal diagnostic method for selecting patients with non-ischemic cardiomyopathy on CRT.

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