In:
Perfusion, SAGE Publications, Vol. 38, No. 4 ( 2023-05), p. 843-852
Kurzfassung:
The recurrence rate of ischemic symptoms after coronary artery bypass grafting (CABG) is increasing in recent years. How to prevent and treat saphenous vein graft disease (SVGD [symptomatic ⩾50% stenosis in at least one Saphenous vein graft]) has been a clinical challenge to date. Different pathogenesis may exist in SVGD of different periods. There are currently few available scores for estimating the risk of SVGD after one year post CABG. Objective: We sought to develop and validate a simple predictive clinical risk score for SVGD with recurring ischemia after one year post CABG. Methods and Results: This was a cross-sectional study and the results were validated using bootstrap resampling on a separate cohort. A nomogram and risk scoring system were developed based on retrospective data from a training cohort of 606 consecutive patients with recurring ischemia 〉 1 year after CABG. Logistic regression model was used to find the predictive factors and to build a nomogram. To assess the generalization, models were validated using bootstrap resampling and an external cross-sectional study of 187 consecutive patients in four other hospitals. In multivariable analysis of the primary cohort, native lesion vessel number, SVG age, recurring ischemia type, very low-density lipoprotein level, and left ventricular end-diastolic diameter were independent predictors. A summary risk score was derived from nomogram, with a cut-off value of 15. In internal and external validation, the C-index was 0.86 and 0.82, indicating good discrimination. The calibration curve for probability of SVGD showed optimal agreement between actual observations and risk score prediction. Conclusion: A simple-to-use risk scoring system based on five easily variables was developed and validated to predict the risk of SVGD among patients who recurring ischemia after one year post CABG. This score may be useful for providing patients with individualized estimates of SVGD risk.
Materialart:
Online-Ressource
ISSN:
0267-6591
,
1477-111X
DOI:
10.1177/02676591221090588
Sprache:
Englisch
Verlag:
SAGE Publications
Publikationsdatum:
2023
ZDB Id:
2029611-3
