One-year mortality after implantable defibrillator implantation: do risk stratification models help improving clinical practice?
| Autor: | Daniele Giacopelli, Alessio Gargaro, Giampiero Maglia, Francesco Solimene, Antonio Curnis, Saverio Iacopino, Carlo Pignalberi, Ennio Pisano, Antonio Rapacciuolo, Gaetano Senatore, Stefano Pedretti, Paolo Della Bella, Davide Saporito, Giuseppe Bottaro, Patrizia Bertocchi, Gabriele Zanotto, Matteo Santamaria, Antonio Russo, Daniela Orsida, Antonio D'Onofrio, Valeria Calvi, Michele Manzo, Massimo Giammaria, Vincenzo Ezio Santobuono, Massimiliano Marini, Mauro Biffi, Fabio Quartieri, Giovanni B. Forleo, Fabrizio Caravati, Caterina Bisceglia |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
medicine.medical_specialty medicine.medical_treatment Cardiac resynchronization therapy Implantable defibrillator Risk Assessment Risk Factors Physiology (medical) Implantable cardioverter defibrillator Medicine Humans Cardiac Resynchronization Therapy Devices Mortality Risk stratification Heart Failure business.industry Mortality rate Hazard ratio Implantable cardioverter-defibrillator Confidence interval Defibrillators Implantable Treatment Outcome Quartile Emergency medicine Cohort Female Cardiology and Cardiovascular Medicine business |
| Popis: | Purpose The purpose of this study was to assess the available mortality risk stratification models for implantable cardioverter defibrillator (ICD) and cardiac resynchronization therapy defibrillator (CRT-D) patients. Methods We conducted a review of mortality risk stratification models and tested their ability to improve prediction of 1-year survival after implant in a database of patients who received a remotely controlled ICD/CRT-D device during routine care and included in the independent Home Monitoring Expert Alliance registry. Results We identified ten predicting models published in peer-reviewed journals between 2000 and 2021 (Parkash, PACE, MADIT, aCCI, CHA2DS2-VASc quartiles, CIDS, FADES, Sjoblom, AAACC, and MADIT-ICD non-arrhythmic mortality score) that could be tested in our database as based on common demographic, clinical, echocardiographic, electrocardiographic, and laboratory variables. Our cohort included 1,911 patients with left ventricular dysfunction (median age 71, 18.3% female) from sites not using any risk stratification score for systematic patient screening. Patients received an ICD (53.8%) or CRT-D (46.2%) between 2011 and 2017, after standard physician evaluation. There were 56 deaths within 1-year post-implant, with an all-cause mortality rate of 2.9% (95% confidence interval [CI], 2.3-3.8%). Four predicting models (Parkash, MADIT, AAACC, and MADIT-ICD non-arrhythmic mortality score) were significantly associated with increased risk of 1-year mortality with hazard ratios ranging from 3.75 (CI, 1.31-10.7) to 6.53 (CI 1.52-28.0, p ≤ 0.014 for all four). Positive predictive values of 1-year mortality were below 25% for all models. Conclusion In our analysis, the models we tested conferred modest incremental predicting power to ordinary screening methods. |
| Databáze: | OpenAIRE |
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