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正常肺功能人群中最大呼气中期流量受损患者的定量胸部 CT 结构特征。

Structural features on quantitative chest computed tomography of patients with maximal mid-expiratory flow impairment in a normal lung function population.

机构信息

Department of Radiology, Huadong Hospital Affiliated With Fudan University, No. 221 West Yanan Road, Shanghai, 200040, China.

Department of Respiratory Medicine, Huadong Hospital Affiliated With Fudan University, No. 221 West Yanan Road, Shanghai, 200040, China.

出版信息

BMC Pulm Med. 2023 Mar 15;23(1):86. doi: 10.1186/s12890-023-02380-0.

Abstract

BACKGROUND

Maximal mid-expiratory flow (MMEF) is an earlier predictor of chronic obstructive pulmonary disease (COPD) development than forced expiratory volume in 1 s (FEV). Changes of lung structure in patients with MMEF impairment only is still not clear. Therefore, this study aimed to investigate the structural features of patients with decreased MMEF by quantitative computed tomography (QCT) and develop a predictive model for predicting patients with reduced MMEF in normal lung function population.

METHODS

In this study, 131 patients with normal spirometry results and available volumetric chest CT images were enrolled and divided into the reduced MMEF group (FEV/forced expiratory vital capacity (FEV/FVC) > 0.7, FEV% predictive values (FEV%pred) > 80%, MMEF%pred < 80%, n = 52) and the normal MMEF group (FEV/FVC > 0.7, FEV%pred > 80%, MMEF%pred ≥ 80%, n = 79). The emphysema, small airway disease and medium-size airway parameters were measured by a commercial software. The differences were investigated in clinical features, spirometrical parameters and QCT parameters between the two groups. A nomogram model was constructed based on the results of the multivariable logistic regression model. Spearman's correlation coefficients were calculated between QCT measurements and spirometrical parameters.

RESULTS

There were more males in reduced MMEF group than normal group (P < 0.05). Lung parenchyma parameter (PRM) and airway-related parameters (functional small airway disease (PRM), luminal area of fifth- and sixth- generation airway (LA, LA) were significantly different between the reduced MMEF group and the normal group (20.2 ± 17.4 vs 9.4 ± 6.7, 3.4 ± 3.5 vs 1.9 ± 2.0, 12.2 ± 2.5 vs 13.7 ± 3.4, 7.7 ± 2.4 vs 8.9 ± 2.8, respectively, all P < 0.01). After multivariable logistical regression, only sex (odds ratio [OR]: 2.777; 95% confidence interval [CI]:1.123-3.867), PRM (OR:1.102, 95%CI:1.045-1.162) and LA (OR:0.650, 95%CI:0.528-0.799) had significant differences between the two groups (P < 0.05) and a model incorporating with the three indicators was constructed (area under curve, 0.836). Correlation analysis showed MMEF%pred had mild to moderate correlation with airway-related measurements.

CONCLUSION

In normal lung function population, patients with reduced MMEF have potential medium-size and small airway changes, and MMEF%pred is significantly associated with airway-related CT parameters. The nomogram incorporating with sex, PRM and LA has good predictive value and offers more objective evidences in a group with reduced MMEF.

摘要

背景

最大呼气中期流量(MMEF)是预测慢性阻塞性肺疾病(COPD)发展的早期指标,比 1 秒用力呼气量(FEV 1 )更早。仅 MMEF 受损患者的肺结构变化尚不清楚。因此,本研究旨在通过定量计算机断层扫描(QCT)研究 MMEF 降低患者的结构特征,并建立预测正常肺功能人群中 MMEF 降低患者的预测模型。

方法

本研究纳入了 131 例肺功能正常且有容积性胸部 CT 图像的患者,并分为 MMEF 降低组(FEV/用力肺活量(FEV/FVC)>0.7,FEV%预计值(FEV%pred)>80%,MMEF%预计值(MMEF%pred)<80%,n=52)和 MMEF 正常组(FEV/FVC>0.7,FEV%pred>80%,MMEF%pred≥80%,n=79)。使用商业软件测量肺气肿、小气道疾病和中气道参数。比较两组间的临床特征、肺功能参数和 QCT 参数。根据多变量逻辑回归模型的结果构建列线图模型。计算 QCT 测量值与肺功能参数之间的斯皮尔曼相关系数。

结果

与 MMEF 正常组相比,MMEF 降低组中男性比例更高(P<0.05)。两组间肺实质参数(PRM)和气道相关参数(功能性小气道疾病(PRM)、第 5 代和第 6 代气道的管腔面积(LA、LA)存在显著差异(20.2±17.4 vs 9.4±6.7,3.4±3.5 vs 1.9±2.0,12.2±2.5 vs 13.7±3.4,7.7±2.4 vs 8.9±2.8,均 P<0.01)。经过多变量逻辑回归,只有性别(比值比[OR]:2.777;95%置信区间[CI]:1.123-3.867)、PRM(OR:1.102,95%CI:1.045-1.162)和 LA(OR:0.650,95%CI:0.528-0.799)在两组间有显著差异(P<0.05),并构建了一个包含这三个指标的模型(曲线下面积,0.836)。相关性分析显示 MMEF%pred 与气道相关测量值呈轻度至中度相关。

结论

在肺功能正常的人群中,MMEF 降低的患者可能存在潜在的中气道和小气道改变,MMEF%pred 与气道相关 CT 参数显著相关。该列线图模型纳入了性别、PRM 和 LA,具有良好的预测价值,为 MMEF 降低的患者提供了更客观的证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/658a/10015933/d0261f2c732f/12890_2023_2380_Fig1_HTML.jpg

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