全血细胞计数炎症衍生指标可预测 2 型糖尿病代谢综合征。

Complete blood count inflammation derived indexes as predictors of metabolic syndrome in type 2 diabetes mellitus.

机构信息

Department of Pathophysiology, Faculty of Medicine, University of Sarajevo, Sarajevo, Bosnia and Herzegovina.

General Hospital "Prim. Dr. Abdulah Nakas", Sarajevo, Bosnia and Herzegovina.

出版信息

Technol Health Care. 2024;32(4):2321-2330. doi: 10.3233/THC-231101.

DOI:10.3233/THC-231101

PMID:38251075

Abstract

BACKGROUND

Metabolic syndrome (MetS) is a group of comorbidities related to regulating hyperglycemia and acute cardiovascular incidents and complications. With the increasing prevalence in individuals with type 2 diabetes mellitus (T2DM), MetS represents an increasing public health problem and clinical challenge, and early diagnosis is necessary to avoid the accelerated development of diabetic complications.

OBJECTIVE

To investigate the role of Complete Blood Count-derived Inflammation Indexes (CBCIIs) in predicting MetS in T2DM individuals.

METHODS

The study was designed as a two-year prospective study and included 80 T2DM individuals divided into MetS and non-MetS groups based on MetS development over two years. The sera samples were analyzed for complete blood count parameters and C-reactive protein (CRP). Based on the laboratory test results, 13 CBCIIs were calculated and analyzed. The receiver operating characteristic (ROC) curve and their corresponding areas under the curve (AUC) were used to determine prognostic accuracy.

RESULTS

There were significant differences between T2DM participants with Mets and those without MetS concerning Neutrophil to Platelet Ratio (NPR) values (p< 0.001), Neutrophil to Lymphocyte and Platelet Ratio (NLPR) (p< 0.001), Platelet to Lymphocyte Ratio (PLR) (p< 0.001), Lymphocyte to C-reactive protein Ratio (LCR) (p< 0.001), C-reactive protein to Lymphocyte Ratio (CRP/Ly) (p< 0.001), Systemic immune inflammation index (SII) (< 0.001), and Aggregate Index of Systemic Inflammation (AISI) (p= 0.005). The results of ROC curve analysis have shown that the LCR (AUC of 0.907), CRP/Ly (AUC of 0.907) can serve as excellent predictors, but NPR (AUC of 0.734), NLRP (AUC of 0.755), PLR (AUC of 0.823), SII (AUC of 0.745), and AISI (AUC of 0.688) as good predictors of MetS in T2 DM individuals.

CONCLUSION

This study confirms the reliability of the CBCIIs as novel, simple, low cost and valuable predictors of MetS developing in T2DM.

摘要

背景

代谢综合征（MetS）是一组与调节高血糖和急性心血管事件及并发症相关的共病。随着 2 型糖尿病（T2DM）患者患病率的增加，MetS 成为日益严重的公共卫生问题和临床挑战，早期诊断对于避免糖尿病并发症的加速发展至关重要。

目的

探讨全血细胞计数衍生炎症指数（CBCIIs）在预测 T2DM 患者代谢综合征（MetS）中的作用。

方法

该研究设计为一项为期两年的前瞻性研究，共纳入 80 例 T2DM 患者，根据两年内 MetS 的发展情况分为 MetS 组和非 MetS 组。分析血清样本的全血细胞计数参数和 C 反应蛋白（CRP）。基于实验室检测结果，计算并分析了 13 个 CBCII。采用受试者工作特征（ROC）曲线及其相应的曲线下面积（AUC）来确定预测的准确性。

结果

与非 MetS 组相比，患有 Mets 的 T2DM 参与者的中性粒细胞与血小板比值（NPR）值（p<0.001）、中性粒细胞与淋巴细胞和血小板比值（NLPR）（p<0.001）、血小板与淋巴细胞比值（PLR）（p<0.001）、淋巴细胞与 CRP 比值（LCR）（p<0.001）、CRP 与淋巴细胞比值（CRP/Ly）（p<0.001）、全身免疫炎症指数（SII）（<0.001）和全身炎症综合指数（AISI）（p=0.005）存在显著差异。ROC 曲线分析结果表明，LCR（AUC 为 0.907）和 CRP/Ly（AUC 为 0.907）可作为优秀的预测指标，但 NPR（AUC 为 0.734）、NLPR（AUC 为 0.755）、PLR（AUC 为 0.823）、SII（AUC 为 0.745）和 AISI（AUC 为 0.688）也可作为 T2DM 患者 MetS 的良好预测指标。