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Updated: Jan 23, 2026

A Zebrafish Model of Diabetes Mellitus and Metabolic Memory
Published on: February 28, 2013
Performance of a clinical/proteomic panel to predict obstructive peripheral artery disease in patients with and
Cian P McCarthy1, Shreya Shrestha1, Nasrien Ibrahim2
1Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.
Background:
Patients with diabetes mellitus (DM) are at substantial risk of developing peripheral artery disease (PAD). We recently developed a clinical/proteomic panel to predict obstructive PAD. In this study, we compare the accuracy of this panel for the diagnosis of PAD in patients with and without DM.
Methods And Results:
The HART PAD panel consists of one clinical variable (history of hypertension) and concentrations of six biomarkers (midkine, kidney injury molecule-1, interleukin-23, follicle-stimulating hormone, angiopoietin-1 and eotaxin-1). In a prospective cohort of 354 patients undergoing peripheral and/or coronary angiography, performance of this diagnostic panel to detect ≥50% stenosis in at least one peripheral vessel was assessed in patients with (n=94) and without DM (n=260). The model had an area under the receiver operating characteristic curve (AUC) of 0.85 for obstructive PAD. At optimal cut-off, the model had 84% sensitivity, 75% specificity, positive predictive value (PPV) of 84% and negative predictive value (NPV) of 75% for detection of PAD among patients with DM, similar as in those without DM. In those with DM, partitioning the model into five levels resulted in a PPV of 95% and NPV of 100% in the highest and lowest levels, respectively. Abnormal scores were associated with a shorter time to revascularisation during 4.3 years of follow-up.
Conclusion:
A clinical/biomarker model can predict with high accuracy the presence of PAD among patients with DM.
Trial Registration Number:
NCT00842868.
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