Predictive potential of biomarkers and risk scores for major adverse cardiac events in elderly patients undergoing major elective vascular surgery.
Biomarker
Elderly
MACE
Risk score
Vascular surgery
Journal
Reviews in cardiovascular medicine
ISSN: 1530-6550
Titre abrégé: Rev Cardiovasc Med
Pays: Singapore
ID NLM: 100960007
Informations de publication
Date de publication:
24 Sep 2021
24 Sep 2021
Historique:
received:
14
07
2021
revised:
05
08
2021
accepted:
27
08
2021
entrez:
26
9
2021
pubmed:
27
9
2021
medline:
29
10
2021
Statut:
ppublish
Résumé
Elderly patients scheduled for major elective vascular surgery are at high risk for a major adverse cardiac events (MACE). The objectives of the study were: (1) To determine the individual discriminatory ability of four risk prediction models and four biomarkers in predicting MACEs in elderly patients undergoing major elective vascular surgery; (2) to find a prognostic model with the best characteristics; (3) to examine the significance of all preoperative parameters; and (4) to determine optimal cut-off values for biomarkers with best predictor capabilities. We enrolled 144 geriatric patients, aged 69.97 ± 3.73 years, with a 2:1 male to female ratio. Essential inclusion criteria were open major vascular surgery and age >65 years. The primary outcome was the appearance of MACEs within 6 months. These were noted in 33 (22.9%) patients. The most frequent cardiac event was decompensated heart failure, which occurred in 22 patients (15.3%). New onset atrial fibrillation was registered in 13 patients (9%), and both myocardial infarction and ventricular arrhythmias occurred in eight patients each (5.5%). Excellent discriminatory ability (AUC >0.8) was observed for all biomarker combinations that included the N-terminal fragment of pro-B-type natriuretic peptide (NT-proBNP). The most predictive two-variable combination was the Geriatric-Sensitive Cardiac Risk Index (GSCRI) + NT-proBNP (AUC of 0.830 with a 95% confidence interval). Female gender, previous coronary artery disease, and NT-proBNP were three independent predictors in a multivariate model of binary logistic regression. The Cox regression multivariate model identified high-sensitivity C-reactive protein and NT-proBNP as the only two independent predictors.
Identifiants
pubmed: 34565107
pii: 1632453112033-527738844
doi: 10.31083/j.rcm2203115
doi:
Substances chimiques
Biomarkers
0
Peptide Fragments
0
Natriuretic Peptide, Brain
114471-18-0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1053-1062Informations de copyright
© 2021 The Author(s). Published by IMR Press.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.