Dataset Information

Application and comparison of the FADES, MADIT, and SHFM-D risk models for risk stratification of prophylactic implantable cardioverter-defibrillator treatment.

ABSTRACT:

Aims

Implantable cardioverter-defibrillator (ICD) treatment is beneficial in selected patients. However, it remains difficult to accurately predict which patients benefit most from ICD implantation. For this purpose, different risk models have been developed. The aim was to validate and compare the FADES, MADIT, and SHFM-D models.

Methods and results

All patients receiving a prophylactic ICD at the Leiden University Medical Center were evaluated. Individual model performance was evaluated by C-statistics. Model performances were compared using net reclassification improvement (NRI) and integrated differentiation improvement (IDI). The primary endpoint was non-benefit of ICD treatment, defined as mortality without prior ventricular arrhythmias requiring ICD intervention. A total of 1969 patients were included (age 63 ± 11 years; 79% male). During a median follow-up of 4.5 ± 3.9 years, 318 (16%) patients died without prior ICD intervention. All three risk models were predictive for event-free mortality (all: P < 0.001). The C-statistics were 0.66, 0.69, and 0.75, respectively, for FADES, MADIT, and SHFM-D (all: P < 0.001). Application of the SHFM-D resulted in an improved IDI of 4% and NRI of 26% compared with MADIT; IDI improved 11% with the use of SHFM-D instead of FADES (all: P < 0.001), but NRI remained unchanged (P = 0.71). Patients in the highest-risk category of the MADIT and SHFM-D models had 1.7 times higher risk to experience ICD non-benefit than receive appropriate ICD interventions [MADIT: mean difference (MD) 20% (95% CI: 7-33%), P = 0.001; SHFM-D: MD 16% (95% CI: 5-27%), P = 0.005]. Patients in the highest-risk category of FADES were as likely to experience ICD intervention as ICD non-benefit [MD 3% (95% CI: -8 to 14%), P = 0.60].

Conclusion

The predictive and discriminatory value of SHFM-D to predict non-benefit of ICD treatment is superior to FADES and MADIT in patients receiving prophylactic ICD treatment.

SUBMITTER: van der Heijden AC

PROVIDER: S-EPMC5841558 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Publications

Application and comparison of the FADES, MADIT, and SHFM-D risk models for risk stratification of prophylactic implantable cardioverter-defibrillator treatment.

van der Heijden Aafke C AC van Rees Johannes B JB Levy Wayne C WC van der Bom Johanna G JG Cannegieter Suzanne C SC de Bie Mihàly K MK van Erven Lieselot L Schalij Martin J MJ Borleffs C Jan Willem CJ

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology 20170101 1

<h4>Aims</h4>Implantable cardioverter-defibrillator (ICD) treatment is beneficial in selected patients. However, it remains difficult to accurately predict which patients benefit most from ICD implantation. For this purpose, different risk models have been developed. The aim was to validate and compare the FADES, MADIT, and SHFM-D models.<h4>Methods and results</h4>All patients receiving a prophylactic ICD at the Leiden University Medical Center were evaluated. Individual model performance was e ...[more]

PMID: 28130376

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Project description:AimsThe benefit of prophylactic implantable cardioverter-defibrillator (ICD) is not uniform due to differences in the risk of life-threatening ventricular tachycardia (VT)/ventricular fibrillation (VF) and non-arrhythmic mortality. We aimed to develop an ICD benefit prediction score that integrates the competing risks.Methods and resultsThe study population comprised all 4531 patients enrolled in the MADIT trials. Best-subsets Fine and Gray regression analysis was used to develop prognostic models for VT (≥200 b.p.m.)/VF vs. non-arrhythmic mortality (defined as death without prior sustained VT/VF). Eight predictors of VT/VF (male, age < 75 years, prior non-sustained VT, heart rate > 75 b.p.m., systolic blood pressure < 140 mmHg, ejection fraction ≤ 25%, myocardial infarction, and atrialarrhythmia) and 7 predictors of non-arrhythmic mortality (age ≥ 75 years, diabetes mellitus, body mass index < 23 kg/m2, ejection fraction ≤ 25%, New York Heart Association ≥II, ICD vs. cardiac resynchronization therapy with defibrillator, and atrial arrhythmia) were identified. The two scores were combined to create three MADIT-ICD benefit groups. In the highest benefit group, the 3-year predicted risk of VT/VF was three-fold higher than the risk of non-arrhythmic mortality (20% vs. 7%, P < 0.001). In the intermediate benefit group, the difference in the corresponding predicted risks was attenuated (15% vs. 9%, P < 0.01). In the lowest benefit group, the 3-year predicted risk of VT/VF was similar to the risk of non-arrhythmic mortality (11% vs. 12%, P = 0.41). A personalized ICD benefit score was developed based on the distribution of the two competing risks scores in the study population (https://is.gd/madit). Internal and external validation confirmed model stability.ConclusionsWe propose the novel MADIT-ICD benefit score that predicts the likelihood of prophylactic ICD benefit through personalized assessment of the risk of VT/VF weighed against the risk of non-arrhythmic mortality.

Project description:Background One third of primary prevention implantable cardioverter-defibrillator patients receive appropriate therapy, but all remain at risk of defibrillator complications. Information on these complications in contemporary cohorts is limited. This study assessed complications and their risk factors after defibrillator implantation in a Dutch nationwide prospective registry cohort and forecasts the potential reduction in complications under distinct scenarios of updated indication criteria. Methods and Results Complications in a prospective multicenter registry cohort of 1442 primary implantable cardioverter-defibrillator implant patients were classified as major or minor. The potential for reducing complications was derived from a newly developed prediction model of appropriate therapy to identify patients with a low probability of benefitting from the implantable cardioverter-defibrillator. During a follow-up of 2.2 years (interquartile range, 2.0-2.6 years), 228 complications occurred in 195 patients (13.6%), with 113 patients (7.8%) experiencing at least one major complication. Most common ones were lead related (n=93) and infection (n=18). Minor complications occurred in 6.8% of patients, with lead-related (n=47) and pocket-related (n=40) complications as the most prevailing ones. A surgical reintervention or additional hospitalization was required in 53% or 61% of complications, respectively. Complications were strongly associated with device type. Application of stricter implant indication results in a comparable proportional reduction of (major) complications. Conclusions One in 13 patients experiences at least one major implantable cardioverter-defibrillator-related complication, and many patients undergo a surgical reintervention. Complications are related to defibrillator implantations, and these should be discussed with the patient. Stricter implant indication criteria and careful selection of device type implanted may have significant clinical and financial benefits.

Project description:Background Current approaches fail to separate patients at high versus low risk for ventricular arrhythmias owing to overreliance on a snapshot left ventricular ejection fraction measure. We used statistical machine learning to identify important cardiac imaging and time-varying risk predictors. Methods and Results Three hundred eighty-two cardiomyopathy patients (left ventricular ejection fraction ≤35%) underwent cardiac magnetic resonance before primary prevention implantable cardioverter defibrillator insertion. The primary end point was appropriate implantable cardioverter defibrillator discharge or sudden death. Patient characteristics; serum biomarkers of inflammation, neurohormonal status, and injury; and cardiac magnetic resonance-measured left ventricle and left atrial indices and myocardial scar burden were assessed at baseline. Time-varying covariates comprised interval heart failure hospitalizations and left ventricular ejection fractions. A random forest statistical method for survival, longitudinal, and multivariable outcomes incorporating baseline and time-varying variables was compared with (1) Seattle Heart Failure model scores and (2) random forest survival and Cox regression models incorporating baseline characteristics with and without imaging variables. Age averaged 57±13 years with 28% women, 66% white, 51% ischemic, and follow-up time of 5.9±2.3 years. The primary end point (n=75) occurred at 3.3±2.4 years. Random forest statistical method for survival, longitudinal, and multivariable outcomes with baseline and time-varying predictors had the highest area under the receiver operating curve, median 0.88 (95% CI, 0.75-0.96). Top predictors comprised heart failure hospitalization, left ventricle scar, left ventricle and left atrial volumes, left atrial function, and interleukin-6 level; heart failure accounted for 67% of the variation explained by the prediction, imaging 27%, and interleukin-6 2%. Serial left ventricular ejection fraction was not a significant predictor. Conclusions Hospitalization for heart failure and baseline cardiac metrics substantially improve ventricular arrhythmic risk prediction.

Dataset Information

Application and comparison of the FADES, MADIT, and SHFM-D risk models for risk stratification of prophylactic implantable cardioverter-defibrillator treatment.

Aims

Methods and results

Conclusion

Publications

Application and comparison of the FADES, MADIT, and SHFM-D risk models for risk stratification of prophylactic implantable cardioverter-defibrillator treatment.

Similar Datasets

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