Evaluation of sirtuin 1 as a predictor of cardiovascular outcomes in diabetic patients with limb-threatening ischemia

Chronic limb-threatening ischemia (CLTI) significantly increases the risk of major adverse limb events (MALE) and major adverse cardiac events (MACE) after lower extremity revascularization (LER). This study aims to identify novel biomarkers that help to further reduce the risk of postoperative cardiovascular complications. In this prospective, nonrandomized, observational study, baseline serum levels of sirtuin 1 (SIRT1) were assessed in 147 diabetic patients scheduled for LER due to CLTI, and participants were followed for the occurrence of MALE and MACE over 12 months. Fifty-three patients experienced MALE, and 33 experienced MACE within the follow-up period. Lower baseline SIRT1 levels were significantly associated with an increased risk of MALE and MACE, independent of other risk factors. The ROC curve analysis identified a SIRT1 cutoff of 3.79 ng/mL for predicting the risk of MALE. Moreover, incorporating SIRT1 into predictive models significantly enhanced the accuracy of predicting adverse outcomes. Results suggest serum SIRT1 is a potential independent marker for predicting MALE and MACE in diabetic patients with CLTI undergoing LER. Further research is needed to clarify the mechanistic pathways in which SIRT1 may influence cardiovascular outcomes, and the role of this novel biomarker in the management of PAD and CLTI among patients with diabetes.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-11-06
DOI
https://doi.org/10.1038/s41598-024-78576-z
Citations
5
Primary Topic
Cardiac Imaging and Diagnostics
Type
article
Field-Weighted Citation Impact
2.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of sirtuin 1 as a predictor of cardiovascular outcomes in diabetic patients with limb-threatening ischemia

Michele Santoro, Flavia Angelini, Andrea Flex, Antonio Gasbarrini et al.
5 citations
Scientific Reports
Cardiac Imaging and Diagnostics
2.02
article

Evaluation of sirtuin 1 as a predictor of cardiovascular outcomes in diabetic patients with limb-threatening ischemia

Michele Santoro, Flavia Angelini, Andrea Flex, Antonio Gasbarrini, Luis H. Eraso, Roberto Iezzi, Maria Margherita Rando, Paul DiMuzio, Maria Anna Nicolazzi, Dario Pitocco, Massimo Massetti, Federico Biscetti, Enrica Rossini
article en
5 citations

Abstract

Chronic limb-threatening ischemia (CLTI) significantly increases the risk of major adverse limb events (MALE) and major adverse cardiac events (MACE) after lower extremity revascularization (LER). This study aims to identify novel biomarkers that help to further reduce the risk of postoperative cardiovascular complications. In this prospective, nonrandomized, observational study, baseline serum levels of sirtuin 1 (SIRT1) were assessed in 147 diabetic patients scheduled for LER due to CLTI, and participants were followed for the occurrence of MALE and MACE over 12 months. Fifty-three patients experienced MALE, and 33 experienced MACE within the follow-up period. Lower baseline SIRT1 levels were significantly associated with an increased risk of MALE and MACE, independent of other risk factors. The ROC curve analysis identified a SIRT1 cutoff of 3.79 ng/mL for predicting the risk of MALE. Moreover, incorporating SIRT1 into predictive models significantly enhanced the accuracy of predicting adverse outcomes. Results suggest serum SIRT1 is a potential independent marker for predicting MALE and MACE in diabetic patients with CLTI undergoing LER. Further research is needed to clarify the mechanistic pathways in which SIRT1 may influence cardiovascular outcomes, and the role of this novel biomarker in the management of PAD and CLTI among patients with diabetes.

Scientific ReportsVol. 14(1)
Università Cattolica del Sacro Cuore (IT), Thomas Jefferson University (US), Agostino Gemelli University Polyclinic (IT)
Ministero della Salute
Openalex Percentile: Top 13%
Cardiac Imaging and Diagnostics
2.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.