通过前瞻性队列研究中的临床特征对阻塞性肺病进行分类。

Alirio R Bastidas, Lina M Morales-Cely, Maria A Bejarano, Geraldine Ospina, Juan S Afanador, Daniel Botero, Angélica M Giraldo, Eduardo Tuta-Quintero, Luis F Giraldo, Adriana Maldonado-Franco
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摘要

导言:利用临床特征来区分阻塞性肺部疾病的方法尚不明确,支持性研究有限。本研究旨在评估临床问卷中的体征和症状在诊断阻塞性肺部疾病中的有效性:这项前瞻性队列研究纳入了根据肺活量测定诊断为慢性阻塞性肺疾病(COPD)、哮喘或哮喘-COPD 重叠(ACOS)的患者。通过问卷调查收集临床症状,并将其纳入多项式逻辑预测模型,以评估其在诊断阻塞性肺部疾病中的作用:共分析了 1443 名患者:其中 177 人(12.3%)患有慢性阻塞性肺病,135 人(9.4%)患有哮喘,163 人(11.3%)患有 ACOS,968 人(67.1%)无阻塞症状。患者的平均年龄为 64 岁(标清 13.23),其中慢性阻塞性肺病患者的年龄大于哮喘或 ACOS 患者。使用支气管扩张剂后第一秒用力呼气容积/用力肺活量比值分别为:慢性阻塞性肺病 61.1(标清 8.48),哮喘 78.9(标清 6.99),ACOS 57.3(标清 9.48),无阻塞患者 81.7(标清 7.15)。诊断慢性阻塞性肺病的曲线下面积为 0.75,诊断哮喘的曲线下面积为 0.68,诊断 ACOS 的曲线下面积为 0.78(PP 均小于 0.001):临床变量能有效识别阻塞性肺部疾病患者,具有很强的诊断性能和精确性。
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Classification of Obstructive Pulmonary Diseases Through Clinical Characteristics in a Prospective Cohort Study.

Introduction: The use of clinical characteristics to differentiate obstructive lung diseases remains unclear, with limited supporting studies. This study aims to assess the effectiveness of signs and symptoms from clinical questionnaires in diagnosing obstructive lung diseases.

Methods: This prospective cohort study included patients diagnosed with chronic obstructive pulmonary disease (COPD), asthma, or asthma-COPD overlap (ACOS) based on spirometry. Clinical symptoms were gathered using questionnaires and incorporated into a multinomial logistic prediction model to evaluate their role in diagnosing obstructive lung diseases.

Results: A total of 1443 patients were analyzed: 177 (12.3%) with COPD, 135 (9.4%) with asthma, 163 (11.3%) with ACOS, and 968 (67.1%) without obstruction. The average age was 64 years (SD 13.23), with COPD patients being older than those with asthma or ACOS. Forced expiratory volume in the first second of expiration/forced vital capacity ratios after bronchodilator use were 61.1 (SD 8.48) for COPD, 78.9 (SD 6.99) for asthma, 57.3 (SD 9.48) for ACOS, and 81.7 (SD 7.15) for non-obstructed patients. The area under the curve for diagnosing COPD was 0.75, for asthma 0.68, and for ACOS 0.78 (all PP  <  0.001).

Conclusions: Clinical variables can identify patients with obstructive lung diseases effectively, offering strong diagnostic performance and precision.

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