Predictive potential of biomarkers and risk scores for major adverse cardiac events in elderly patients undergoing major elective 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
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

1053-1062

Informations de copyright

© 2021 The Author(s). Published by IMR Press.

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Auteurs

Velimir S Perić (VS)

Clinic of Cardiovascular Surgery, Clinical Center Nis, 18000 Nis, Serbia.

Mladjan D Golubović (MD)

Clinic of Cardiovascular Surgery, Clinical Center Nis, 18000 Nis, Serbia.
Medical School of Nis, University of Nis, 18000 Nis, Serbia.

Milan V Lazarević (MV)

Clinic of Cardiovascular Surgery, Clinical Center Nis, 18000 Nis, Serbia.
Medical School of Nis, University of Nis, 18000 Nis, Serbia.

Tomislav L Kostić (TL)

Medical School of Nis, University of Nis, 18000 Nis, Serbia.
Clinic for Cardiology, Clinical Center Nis, 18000 Nis, Serbia.

Dragana S Stokanović (DS)

Medical School of Nis, University of Nis, 18000 Nis, Serbia.

Miodrag N Đorđević (MN)

Medical School of Nis, University of Nis, 18000 Nis, Serbia.
Clinic for Endocrine Surgery, Clinical Center Nis, 18000 Nis, Serbia.

Vesna G Marjanović (VG)

Medical School of Nis, University of Nis, 18000 Nis, Serbia.
Clinic for Anesthesiology and Intensive Therapy, Clinical Center Nis, 18000 Nis, Serbia.

Marija D Stošić (MD)

Clinic for Anesthesiology and Intensive Therapy, Clinical Center Nis, 18000 Nis, Serbia.

Dragan J Milić (DJ)

Clinic of Cardiovascular Surgery, Clinical Center Nis, 18000 Nis, Serbia.
Medical School of Nis, University of Nis, 18000 Nis, Serbia.

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