糖尿病足患者伤口预后与血清IL-6、ICAM-1、sST2的相关性及Nomogram模型的建立

Yali Zhou, Wenhu Zhou, Yu Guo, Changping Hu
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引用次数: 0

摘要

糖尿病足(DF)是糖尿病最严重的慢性并发症之一。本研究探讨了2019年1月至2024年1月210例DF患者血清白细胞介素-6 (IL-6)、细胞间粘附分子-1 (ICAM-1)和可溶性抑制致瘤性2 (sST2)与伤口预后的关系。210例DF患者根据预后分为预后良好组(n = 147)和预后不良组(n = 63)。比较分析发现,预后不良组患者血清IL-6、ICAM-1、sST2水平均显著高于预后良好组(P < 0.05)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Correlation of Wound Prognosis with serum IL-6, ICAM-1 and sST2 in Patients with Diabetic Foot and Construction of a Nomogram Model.

Diabetes foot (DF) is one of the most serious chronic complications of diabetes. This study explored the relationship between serum interleukin-6 (IL-6), intercellular adhesion molecule-1 (ICAM-1) and soluble suppression of tumorigenicity 2 (sST2) and wound prognosis in 210 DF patients between January 2019 and January 2024. 210 DF patients were divided into the good prognosis (n = 147) and poor prognosis (n = 63) group according to the prognosis. Comparative analysis revealed that levels of serum IL-6, ICAM-1 and sST2 in the poor prognosis group were all higher than those in the good prognosis group significantly (P < .05). Multivariate logistic regression identified these 3 biomarkers as independent risk factors for poor wound healing (P < .05). Positive correlations between serum IL-6 (r = 0.269), ICAM-1 (r = 0.302), sST2 (r = 0.289) levels and poor prognosis were confirmed through Pearson's correlation analysis. A prediction model was established to analyse their predictive value. The training and validation sets ROC curves had AUCs of 0.79 (0.71-0.87) and 0.75 (0.59-0.91) respectively. Calibration curves were plotted to evaluate the consistency of the model, and the results showed that the predictive value of the nomogram model was similar to that of the actual one. Decision curves were plotted, which showed that the nomogram had higher positive net benefit in the range of 20% to 60%. This study suggest that serum IL-6, ICAM-1, and sST2 levels may serve as valuable prognostic indicators for wound healing progression in DF patients, with combined biomarker assessment showing potential clinical utility for outcome prediction. The total sample size (n = 210), with validation set (n = 63) of this study are relatively limited and the representativeness is restricted, which may affect the universality of the research conclusions.

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