| 厉晨.慢性阻塞性肺疾病患者并发呼吸衰竭的影响因素及血清CC16、CyPA对呼吸衰竭的预测价值[J].浙江中西医结合杂志,2026,36(7): |
| 慢性阻塞性肺疾病患者并发呼吸衰竭的影响因素及血清CC16、CyPA对呼吸衰竭的预测价值 |
| Influencing factors of respiratory failure in patients with chronic obstructive pulmonary disease and predictive value of serum CC16 and CyPA for respiratory failure |
| 投稿时间：2025-03-07 修订日期：2026-06-11 |
| DOI： |
| 中文关键词: 慢性阻塞性肺疾病 呼吸衰竭 影响因素 血清克拉细胞分泌蛋白 亲环素A |
| 英文关键词: |
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| 中文摘要: |
| 目的：分析慢性阻塞性肺疾病患者并发呼吸衰竭的影响因素及血清CC16、CyPA对呼吸衰竭的预测价值。方法：选取我院收治的84例慢性阻塞性肺疾病并发呼吸衰竭患者,作为病例组,另选取同期68例慢性阻塞性肺疾病患者,作为对照组,所选取年限为2021年1月-2023年12月,整理两组患者临床资料,并利用多因素Logistics分析影响慢性阻塞性肺疾病患者并发呼吸衰竭的风险因素,对比两组患者CC16、HSP27、MVV、KL-6、PaCO2、PEF、pH值、FVC、PaO2、CyPA、FEV1、SaO2水平；利用ROC曲线分析CC16、CyPA对呼吸衰竭的预测价值。结果：与对照组相比,病例组PaCO2、CC16、pH值、CyPA、HSP27、SaO2、FVC水平升高,MVV、KL-6、FEV1、PaO2、PEF水平下降,差异具有统计学意义(P<0.05)。颈围、心血管疾病、肾脏疾病、病史时间、革兰阴性菌感染、GOLD分级D级、夜间憋醒、呼吸困难、咳嗽、低蛋白血症、咳痰属于影响并发呼吸衰竭的风险因素；ROC曲线显示：CC16：AUC值为0.599、敏感度60.71%、特异度75.00%、准确度67.11%、95%CI为0.508~0.691；CyPA：AUC值为0.604、敏感度77.38%、特异度66.18%、准确度69.74%、95%CI为0.513~0.694；两项联合：AUC值为0.932、敏感度94.05%、特异度61.76%、准确度91.45%、95%CI为0.885~0.979,说明CC16、CyPA可作为呼吸衰竭的预测指标,且两项联合检测准确度及敏感度较高。结论：颈围、疾病史、疾病时间、革兰阴性菌感染、GOLD分级D级及临床症状均为并发呼吸衰竭的影响因素,且经ROC曲线显示,联合检测价值优于单项指标。 |
| 英文摘要: |
| Objective: To analyze the influencing factors of respiratory failure in patients with chronic obstructive pulmonary disease and the predictive value of serum CC16 and CyPA for respiratory failure. Methods: 84 cases were selected from our hospital Chronic obstructive pulmonary disease patients with respiratory failure, As a case group, Another 68 patients with chronic obstructive pulmonary disease were selected during the same period. As a control group, The clinical data of the two groups were sorted out. And multi-factor Logistics was used to analyze the risk factors affecting respiratory failure in patients with chronic obstructive pulmonary disease. The levels of CC16, HSP27, MVV, KL-6, PaCO2, PEF, pH, FVC, PaO2, CyPA, FEV1 and SaO2 were compared between the two groups. ROC curve was used to analyze the predictive value of CC16 and CyPA in respiratory failure. Results: Compared with the control group, The levels of PaCO2, CC16, pH, CyPA, HSP27, SaO2 and FVC were increased in the case group. MVV, KL-6, FEV1, PaO2, PEF levels decreased, The difference was statistically significant (P<0.05). Neck circumference, cardiovascular disease, kidney disease, medical history, gram-negative bacterial infection, GOLD grade D, awake at night, dyspnea, cough, hypoproteinemia and expectoration were risk factors for respiratory failure. ROC curve showed that CC16: AUC value was 0.599, sensitivity was 60.71%, specificity was 75.00%, accuracy was 67.11%, 95%CI was 0.508~0.691. CyPA: AUC value was 0.604, sensitivity 77.38%, specificity 66.18%, accuracy 69.74%, 95%CI 0.513-0.694. Combined, AUC value was 0.932, sensitivity 94.05%, specificity 61.76%, accuracy 91.45%, 95%CI 0.885~0.979. These results indicate that CC16 and CyPA can be used as predictors of respiratory failure, and the combined detection of CC16 and CYPA has high accuracy and sensitivity. Conclusion: Neck circumference, history of disease, duration of disease, gram-negative bacterial infection, GOLD grade D and clinical symptoms are all factors affecting respiratory failure. And as shown by ROC curve, The combined detection value is better than the single index. |
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