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Nomogram predicting death and heart transplantation before appropriate ICD shock in dilated cardiomyopathy
AIMS: This study aimed to develop and validate a competing risk nomogram for predicting all‐cause mortality and heart transplantation (HT) before first appropriate shock in non‐ischaemic dilated cardiomyopathy (DCM) patients receiving implantable cardioverter‐defibrillators (ICD). METHODS AND RESULT...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934923/ https://www.ncbi.nlm.nih.gov/pubmed/35064655 http://dx.doi.org/10.1002/ehf2.13808 |
Sumario: | AIMS: This study aimed to develop and validate a competing risk nomogram for predicting all‐cause mortality and heart transplantation (HT) before first appropriate shock in non‐ischaemic dilated cardiomyopathy (DCM) patients receiving implantable cardioverter‐defibrillators (ICD). METHODS AND RESULTS: A total of 218 consecutive DCM patients implanted with ICD between 2010 and 2019 at our institution were retrospectively enrolled. Cox proportional hazards model was primarily built to identify variables associated with death and HT. Then, a Fine–Gray model, accounting for the appropriate shock as a competing risk, was constructed using these selected variables along with implantation indication (primary vs. secondary). Finally, a nomogram based on the Fine–Gray model was established to predict 1‐, 3‐, and 5‐year probabilities of all‐cause mortality and HT before first appropriate shock. The area under the receiver operating characteristic (ROC) curve (AUC), Harrell's C‐index, and calibration curves were used to evaluate and internally validate the performance of this model. The decision curve analysis was applied to assess its clinical utility. The 1‐, 3‐, and 5‐year cumulative incidence of all‐cause mortality and HT without former appropriate shock were 5.3% [95% confidence interval (CI) 2.9–9.9%], 16.6% (95% CI 11–25.0%), and 25.3% (95% CI 17.2–37.1%), respectively. Five variables including implantation indication, left ventricular end‐diastolic diameter, N‐terminal pro‐brain natriuretic peptide, angiotensin‐converting enzyme inhibitor/angiotensin receptor blocker, and amiodarone treatment were independently associated with it (all P < 0.05) and were used for constructing the nomogram. The 1‐, 3‐, and 5‐year AUC of the nomogram were 0.83 (95% CI 0.73–0.94, P < 0.001), 0.84 (95% CI 0.75–0.93, P < 0.001), and 0.85 (95% CI 0.77–0.94, P < 0.001), respectively. The Harrell's C‐index was 0.788 (95% CI 0.697–0.877, P < 0.001; 0.762 for the optimism‐corrected C‐index), showing the good discriminative ability of the model. The calibration was acceptable (optimism‐corrected slope 0.896). Decision curve analysis identified our model was clinically useful within the entire range of potential treatment thresholds for ICD implantation. Three risk groups stratified by scores were significantly different between cumulative incidence curves (P < 0.001). The identified high‐risk group composed 17.9% of our population and did not derive long‐term benefit from ICD. CONCLUSIONS: The proposed nomogram is a simple, useful risk stratification tool for selecting potential ICD recipients in DCM patients. It might facilitate the shared decision‐making between patients and clinicians. |
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