Clinical phenotypes predict exacerbations of COPD: the TIE cohort study

IF 3.5 3区医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

Respiratory medicine Pub Date : 2025-05-26 DOI:10.1016/j.rmed.2025.108182

Jens Ellingsen , Christer Janson , Kristina Bröms , Amir Farkhooy , Maria Hårdstedt , Marieann Högman , Karin Lisspers , Andreas Palm , Björn Ställberg , Andrei Malinovschi

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引用次数: 0

Abstract

Background

In 2017, Burgel and colleagues developed an algorithm to identify clinical phenotypes that predict mortality in COPD. Our study aimed to 1) investigate whether the phenotypes can predict acute exacerbations of COPD (AECOPD) and 2) validate their ability to predict mortality.

Methods

The Tools Identifying Exacerbations (TIE) cohort study recruited participants with spirometry-verified COPD from primary and secondary care in three Swedish regions. Participants were allocated to phenotypes 1–5 using the previously developed algorithm containing comorbidities (heart failure, coronary artery disease, hypertension, and/or diabetes), dyspnoea, age, forced expiratory volume in 1 s (FEV₁), and body mass index (BMI). Data on AECOPDs and deaths during the three-year follow-up were collected from medical records and analysed with Cox proportional hazards regressions. Harrel's C-index was used to assess the models' discriminative ability.

Results

Among the 566 participants, 59 % were female, and the mean ± SD FEV₁ was 57 ± 18 % of predicted. The hazard ratios (HRs) [95 % CI] for time to AECOPD were 3.04 [1.93–4.79], 2.38 [1.54–3.66], and 3.52 [1.73–7.15] in phenotypes 1, 2, and 4 compared with 5 (C-index = 0.61). When AECOPD history was used to predict future AECOPD the C-index was 0.65.

The HRs [95 % CI] for mortality were 8.24 [1.93–35.3], 6.26 [1.40–28.0], and 16.7 [3.25–86.3] in phenotypes 1, 3, and 4 compared to 5 (C-index = 0.68). For AECOPD history, the C-index was 0.55.

Conclusion

Clinical COPD phenotypes based on comorbidities, dyspnoea, age, FEV₁, and BMI predict AECOPDs but do not perform better than AECOPD history. However, they perform better than AECOPD history in predicting mortality.

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临床表型预测COPD恶化：TIE队列研究

2017年，Burgel及其同事开发了一种算法来识别预测COPD死亡率的临床表型。我们的研究旨在1)研究表型是否可以预测COPD急性加重（AECOPD）， 2)验证其预测死亡率的能力。方法：工具识别加重（TIE）队列研究从瑞典三个地区的初级和二级医疗机构招募了经肺活量测定证实的COPD患者。使用先前开发的包含合并症（心力衰竭、冠状动脉疾病、高血压和/或糖尿病）、呼吸困难、年龄、1秒内用力呼气量（FEV1）和体重指数（BMI）的算法将参与者分配到1 - 5型。从医疗记录中收集了三年随访期间aecopd和死亡的数据，并使用Cox比例风险回归分析。采用Harrel’sc指数评价模型的判别能力。结果566名参与者中，59%为女性，平均±SD FEV1为预测的57±18%。表型1、2、4与表型5的发病时间风险比（hr） [95% CI]分别为3.04[1.93 ~ 4.79]、2.38[1.54 ~ 3.66]、3.52 [1.73 ~ 7.15]（C-index = 0.61）。当使用AECOPD病史预测未来AECOPD时，c指数为0.65。表型1、3、4与表型5的死亡率hr [95% CI]分别为8.24[1.93-35.3]、6.26[1.40-28.0]和16.7 [3.25-86.3]（c指数= 0.68）。对于AECOPD病史，c指数为0.55。结论基于合并症、呼吸困难、年龄、FEV1和BMI的临床COPD表型预测AECOPD，但并不优于AECOPD病史。然而，它们在预测死亡率方面优于AECOPD病史。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Respiratory medicine 医学-呼吸系统

CiteScore

7.50

自引率

0.00%

发文量

199

审稿时长

38 days

期刊介绍： Respiratory Medicine is an internationally-renowned journal devoted to the rapid publication of clinically-relevant respiratory medicine research. It combines cutting-edge original research with state-of-the-art reviews dealing with all aspects of respiratory diseases and therapeutic interventions. Topics include adult and paediatric medicine, epidemiology, immunology and cell biology, physiology, occupational disorders, and the role of allergens and pollutants. Respiratory Medicine is increasingly the journal of choice for publication of phased trial work, commenting on effectiveness, dosage and methods of action.