Approximately 1/3 of patients with non-ST-segment elevation (NSTE) acute coronary syndromes (ACS) are ≥75 years of age. Risk stratification in these patients is generally difficult because supporting evidence is scarce. The investigators developed and validated a simple risk prediction score for 1-year mortality in patients ≥75 years of age presenting with NSTE ACS. The derivation cohort was the Italian Elderly ACS trial, which included 313 patients with NSTE ACS aged ≥75 years. A logistic regression model was developed to predict 1-year mortality. The validation cohort was a registry cohort of 332 patients with NSTE ACS meeting the same inclusion criteria as for the Italian Elderly ACS trial but excluded from the trial for any reason. The risk score included 5 statistically significant covariates: previous vascular event, hemoglobin level, estimated glomerular filtration rate, ischemic electrocardiographic changes, and elevated troponin level. The model allowed a maximum score of 6. The score demonstrated a good discriminating power (C statistic = 0.739) and calibration, even among subgroups defined by gender and age. When validated in the registry cohort, the scoring system confirmed a strong association with the risk for all-cause death. Moreover, a score ≥3 (the highest baseline risk group) identified a subset of patients with NSTE ACS most likely to benefit from an invasive approach. In conclusion, the risk for 1-year mortality in patients ≥75 years of age with NSTE ACS is substantial and can be predicted through a score that can be easily derived at the bedside at hospital presentation. The score may help in guiding treatment strategy.

A Risk Score for Predicting 1-Year Mortality in Patients >= 75 Years of Age Presenting With Non-ST-Elevation Acute Coronary Syndrome

Angeli F;
2015

Abstract

Approximately 1/3 of patients with non-ST-segment elevation (NSTE) acute coronary syndromes (ACS) are ≥75 years of age. Risk stratification in these patients is generally difficult because supporting evidence is scarce. The investigators developed and validated a simple risk prediction score for 1-year mortality in patients ≥75 years of age presenting with NSTE ACS. The derivation cohort was the Italian Elderly ACS trial, which included 313 patients with NSTE ACS aged ≥75 years. A logistic regression model was developed to predict 1-year mortality. The validation cohort was a registry cohort of 332 patients with NSTE ACS meeting the same inclusion criteria as for the Italian Elderly ACS trial but excluded from the trial for any reason. The risk score included 5 statistically significant covariates: previous vascular event, hemoglobin level, estimated glomerular filtration rate, ischemic electrocardiographic changes, and elevated troponin level. The model allowed a maximum score of 6. The score demonstrated a good discriminating power (C statistic = 0.739) and calibration, even among subgroups defined by gender and age. When validated in the registry cohort, the scoring system confirmed a strong association with the risk for all-cause death. Moreover, a score ≥3 (the highest baseline risk group) identified a subset of patients with NSTE ACS most likely to benefit from an invasive approach. In conclusion, the risk for 1-year mortality in patients ≥75 years of age with NSTE ACS is substantial and can be predicted through a score that can be easily derived at the bedside at hospital presentation. The score may help in guiding treatment strategy.
www.elsevier.com/locate/amjcard
Angeli, F; Cavallini, C; Verdecchia, P; Morici, N; Del Pinto, M; Petronio, As; Antonicelli, R; Murena, E; Bossi, I; De Servi, S; Savonitto, S
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11383/2085075
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 14
social impact