Key result
The SHFM-D risk model was superior to FADES and MADIT for predicting non-benefit of prophylactic ICD treatment, with a C-statistic of 0.75 vs 0.66 and 0.69 (all P<0.001).
Why the study?
Does the SHFM-D risk model improve prediction of non-benefit of prophylactic ICD treatment compared to FADES and MADIT models in patients receiving prophylactic ICDs?
Population
1,969 patients receiving a prophylactic implantable cardioverter-defibrillator at a single center, mean age…
Comparison
Risk stratification using the SHFM-D risk model vs Risk stratification using the FADES and MADIT…
Design
Cohort
Follow-up
median 4.5 ± 3.9 years
Authors
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SHFM-D may aid identification of ICD non-benefit; hypothesis-generating and requires prospective validation before practice change.
Cohort (n=1,969)
No
Does the SHFM-D risk model improve prediction of non-benefit of prophylactic ICD treatment compared to FADES and MADIT models in patients receiving prophylactic ICDs?
Effect estimate: C-statistic 0.75 (SHFM-D), 0.69 (MADIT), 0.66 (FADES)
p-value: p=<0.001
The SHFM-D risk model provides superior predictive and discriminatory value compared to FADES and MADIT for identifying patients who will not benefit from prophylactic ICD implantation.
Heijden et al. (2017) conducted a cohort in Prophylactic implantable cardioverter-defibrillator (ICD) treatment (n=1,969). SHFM-D risk model vs. FADES and MADIT risk models was evaluated on Non-benefit of ICD treatment, defined as mortality without prior ventricular arrhythmias requiring ICD intervention (C-statistic 0.75 (SHFM-D), 0.69 (MADIT), 0.66 (FADES), p=<0.001). The SHFM-D risk model was superior to FADES and MADIT for predicting non-benefit of prophylactic ICD treatment, with a C-statistic of 0.75 vs 0.66 and 0.69 (all P<0.001).
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