Zhang Dandan, Zhao Lianbo, Wang Zheng, Zhai Ming, Chen Yan, Fang Caoyang
Department of Respiratory and Critical Care Medicine, Mengcheng First People's Hospital, Mengcheng, Anhui Province, China.
Department of Cardiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, Anhui Province, China.
Medicine (Baltimore). 2025 Sep 5;104(36):e42754. doi: 10.1097/MD.0000000000042754.
The C-reactive protein-triglyceride-glucose index (CTI) is becoming a new indicator for the comprehensive evaluation of inflammation and insulin resistance severity. This study aimed to analyze the correlation between CTI and the risk of acute exacerbation in chronic obstructive pulmonary disease (COPD), as well as its influencing factors, and construct and validate a risk prediction nomogram. We selected 447 COPD patients who visited the First People's Hospital of Mengcheng County from January 2020 to May 2024, among whom 266 were acute exacerbation patients. They were randomly divided into a training set and a validation set in a 7:3 ratio. Clinical data were collected, and multiple logistic regression was used to explore the risk factors for acute exacerbation in COPD patients. Based on the results of the multiple logistic regression, a risk prediction nomogram was constructed. Internal validation of the nomogram was performed using receiver operating characteristic curve analysis to assess discrimination, Hosmer-Lemeshow test and calibration curve analysis to assess calibration, and decision curve analysis to evaluate the clinical usefulness of the nomogram. The results of multiple logistic regression analysis showed that smoking, hypertension, red blood cells, and CTI were risk factors for acute exacerbation of COPD (P < .05). A risk prediction nomogram for acute exacerbation of COPD was constructed based on the results of multiple logistic regression analysis. The receiver operating characteristic curve analysis showed that the area under the curve of the nomogram for predicting acute exacerbation of COPD was 0.985 (95% CI: 0.976-0.994); the results of Hosmer-Lemeshow test and calibration curve analysis indicated that the nomogram had a good fit in the modeling group (χ2 = 12.95, P = .1136). The decision curve analysis results showed that the net clinical benefit of the nomogram was > 0 when the threshold probability was > .05 in the modeling group. The nomogram model for predicting the risk of acute exacerbation in COPD patients based on CTI has good consistency, calibration, clinical applicability, and discriminability. The nomogram prediction model constructed by these factors can identify COPD patients with acute exacerbation early, which is helpful for early intervention and improvement of patient prognosis.
C反应蛋白-甘油三酯-葡萄糖指数（CTI）正成为综合评估炎症和胰岛素抵抗严重程度的新指标。本研究旨在分析CTI与慢性阻塞性肺疾病（COPD）急性加重风险之间的相关性及其影响因素，并构建和验证风险预测列线图。我们选取了2020年1月至2024年5月期间在蒙城县第一人民医院就诊的447例COPD患者，其中266例为急性加重患者。将他们按7:3的比例随机分为训练集和验证集。收集临床数据，采用多因素logistic回归分析探讨COPD患者急性加重的危险因素。基于多因素logistic回归分析结果构建风险预测列线图。采用受试者工作特征曲线分析进行列线图的内部验证，以评估区分度，采用Hosmer-Lemeshow检验和校准曲线分析评估校准度，采用决策曲线分析评估列线图的临床实用性。多因素logistic回归分析结果显示，吸烟、高血压、红细胞和CTI是COPD急性加重的危险因素（P<0.05）。基于多因素logistic回归分析结果构建了COPD急性加重的风险预测列线图。受试者工作特征曲线分析显示，预测COPD急性加重的列线图曲线下面积为0.985（95%CI：0.976-0.994）；Hosmer-Lemeshow检验和校准曲线分析结果表明，列线图在建模组中拟合良好（χ2=12.95，P=0.1136）。决策曲线分析结果显示，在建模组中，当阈值概率>0.05时，列线图的净临床获益>0。基于CTI预测COPD患者急性加重风险的列线图模型具有良好的一致性、校准度、临床适用性和区分度。由这些因素构建的列线图预测模型可早期识别急性加重的COPD患者，有助于早期干预和改善患者预后。
