التفاصيل البيبلوغرافية
| العنوان: |
A novel prognostic tool to predict mortality in patients with atrial fibrillation: The BASIC-AF risk scoreKey messages |
| المؤلفون: |
Athanasios Samaras, Anastasios Kartas, Evangelos Akrivos, George Fotos, George Dividis, Dimitra Vasdeki, Eleni Vrana, Georgios Rampidis, Haralambos Karvounis, George Giannakoulas, Apostolos Tzikas |
| المصدر: |
Hellenic Journal of Cardiology, Vol 62, Iss 5, Pp 339-348 (2021) |
| بيانات النشر: |
Elsevier, 2021. |
| سنة النشر: |
2021 |
| المجموعة: |
LCC:Diseases of the circulatory (Cardiovascular) system |
| مصطلحات موضوعية: |
atrial fibrillation, mortality, risk score, left atrial volume, biomarkers, machine learning, Diseases of the circulatory (Cardiovascular) system, RC666-701 |
| الوصف: |
Background: This study sought to develop and validate a risk score to predict mortality in patients with atrial fibrillation (AF) after a hospitalization for cardiac reasons. Methods: The new risk score was derived from a prospective cohort of hospitalized patients with concurrent AF. The outcome measures were all-cause and cardiovascular mortality. Random forest was used for variable selection. A risk points model with predictor variables was developed by weighted Cox regression coefficients and was internally validated by bootstrapping. Results: In total, 1130 patients with AF were included. During a median follow-up of 2 years, 346 (30.6%) patients died and 250 patients had a cardiovascular cause of death. N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin-T were the most important predictors of mortality, followed by indexed left atrial volume, history and type of heart failure, age, history of diabetes mellitus, and intraventricular conduction delay, all forming the BASIC-AF risk score (Biomarkers, Age, ultraSound, Intraventricular conduction delay, and Clinical history). The score had good discrimination for all-cause (c-index = 0.85 and 95% CI 0.82–0.88) and cardiovascular death (c-index = 0.84 and 95% CI 0.81-0.87). The predicted probability of mortality varied more than 50-fold across deciles and adjusted well to observed mortality rates. A decision curve analysis revealed a significant net benefit of using the BASIC-AF risk score to predict the risk of death, when compared with other existing risk schemes. Conclusions: We developed and internally validated a well-performing novel risk score for predicting death in patients with AF. The BASIC-AF risk score included routinely assessed parameters, selected through machine-learning algorithms, and may assist in tailored risk stratification and management of these patients. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
1109-9666 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S1109966621000075; https://doaj.org/toc/1109-9666 |
| DOI: |
10.1016/j.hjc.2021.01.007 |
| URL الوصول: |
https://doaj.org/article/996d0cf7a666423db5f8a6ab205255f5 |
| رقم الانضمام: |
edsdoj.996d0cf7a666423db5f8a6ab205255f5 |
| قاعدة البيانات: |
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