主管单位:中华人民共和国
国家卫生健康委员会
主办单位:中国医师协会
总编辑:杨秋
编辑部主任:吴翔宇
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英文作者:Jia Xiuzhen Wang Jialie
单位:内蒙古自治区人民医院呼吸与危重症医学科,呼和浩特010010
英文单位:Department of Respiratory and Critical Care Medicine Inner Mongolia Autonomous Region People′s Hospital Hohhot 010010 China
关键词:肺间质纤维化;肺气肿;老年;临床特征;风险预测评估模型;影响因素
英文关键词:Pulmonaryinterstitialfibrosis;Emphysema;Oldage;Clinicalcharacteristics;Riskpredictionandevaluationmodel;Influencingfactors
目的 探讨肺间质纤维化合并肺气肿综合征(CPFE)老年患者的各类指标变化情况,分析该种疾病的相关影响因素,利用数据构建列线图预测模型并实施验证。方法 收集2018年1月至2023年1月在内蒙古自治区人民医院接受治疗的120例CPFE(CPFE组)和120例单纯肺气肿(单纯肺气肿组)老年患者的临床资料行回顾性分析。采用单因素分析方法分析老年CPFE患者的临床特征,采用多因素分析方法分析CPFE的影响因素。构建老年患者CPFE的列线图预测模型并分析其预测效能。利用受试者工作特征(ROC)曲线对相关指标预测CPFE的价值进行评估。结果 CPFE组吸烟指数、反流性食管炎比例、白蛋白、红细胞体积分布宽度、一氧化碳弥散量占预计值百分比(DLCO%)高于/大于单纯肺气肿组,肺总量占预计值百分比(TLC%)低于单纯肺气肿组,差异均有统计学意义(均P<0.05)。Logistic多因素回归分析结果显示,吸烟指数、反流性食管炎、白蛋白、红细胞体积分布宽度、TLC%、DLCO%是老年CPFE患者的独立影响因素(均P<0.05)。依据多因素分析所筛选出来的变量构建列线图风险模型,一致性指数为0.756,校准曲线平均绝对误差为0.019。ROC曲线分析结果显示,上述多因素分析所得独立影响因素以及回归模型P值预测概率预测老年患者CPFE的曲线下面积分别为0.713、0.600、0.739、0.674、0.702、0.729和0.893。结论 与单纯肺气肿的患者相比,CPFE老年患者的部分临床指标会出现明显的变化,利用这些指标构建的预测模型能够较好地预测老年患者发生CPFE。
Objective To investigate the changes of various indicators in elderly patients with pulmonary interstitial fibrosis combined with emphysema syndrome(CPFE), analyze the related influencing factors of the disease, and use the data to construct a nomogram prediction model and implement verification. Methods The clinical data of 120 elderly patients with CPFE (CPFE group) and 120 elderly patients with simple emphysema (simple emphysema group) who were treated in Inner Mongolia Autonomous Region People′s Hospital from January 2018 to January 2023 were retrospectively analyzed. Univariate analysis was used to analyze the clinical characteristics of elderly CPFE patients, and multivariate analysis was used to analyze the influencing factors of CPFE. A nomogram prediction model for CPFE in elderly patients was constructed and its predictive efficiency was analyzed. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of relevant indicators for CPFE. Results The smoking index, proportion of reflux esophagitis, albumin, red blood cell volume distribution width, and percentage of carbon monoxide diffusion to predicted value (DLCO%) in the CPFE group were higher/greater than those in the simple emphysema group, while the percentage of total lung volume to predicted value (TLC%) was lower than that in the simple emphysema group(all P<0.05). The results of Logistic multiple regression analysis showed that smoking index, reflux esophagitis, albumin, red blood cell volume distribution width, TLC%, and DLCO% were independent influencing factors for CPFE in elderly patients(all P<0.05). A nomogram was constructed based on the variables selected by multivariate analysis. The concordance index was 0.756, and the mean absolute error of the calibration curve was 0.019. The ROC curve analysis results showed that the areas under the curve of independent influencing factors obtained from the above multiple factor analysis and the P-value prediction probability of the regression model predicting of CPFE in elderly patients were 0.713, 0.600, 0.739, 0.674, 0.702, 0.729, and 0.893, respectively. Conclusion Compared with patients with simple emphysema, some clinical indicators of elderly patients with CPFE will show significant changes, and the prediction model based on these indicators can better predict the occurrence of CPFE in elderly patients.
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