BACKGROUND AND OBJECTIVE:Exacerbation(s) of chronic obstructive pulmonary disease (eCOPD) entail important events describing an acute deterioration of respiratory symptoms. Changes in medication and/or hospitalization are needed to gain control over the event. However, an exacerbation leading to hospitalization is associated with a worse prognosis for the patient. The objective of this study is to explore factors that could predict the probability of an eCOPD-related hospitalization. METHODS:Data from 128 patients with COPD included in a prospective, longitudinal study were used. At baseline, physical, emotional, and social status of the patients were assessed. Moreover, hospital admission during a one year follow-up was captured. Different models were made based on univariate analysis, literature, and practice. These models were combined to come to one final overall prediction model. RESULTS:During follow-up, 31 (24.2%) participants were admitted for eCOPD. The overall model contained six significant variables: currently smoking (OR = 3.93), forced vital capacity (FVC; OR = 0.97), timed-up-and-go time (TUG-time) (OR = 14.16), knowledge (COPD knowledge questionnaire, percentage correctly answered questions (CIROPD%correct)) (<60% (OR = 1.00); 60%-75%: (OR = 0.30); >75%: (OR = 1.94), eCOPD history (OR = 9.98), and care dependency scale (CDS) total score (OR = 1.12). This model was well calibrated (goodness-of-fit test: p = 0.91) and correctly classified 79.7% of the patients. CONCLUSION:A combination of TUG-time, eCOPD-related admission(s) prior to baseline, currently smoking, FVC, CDS total score, and CIROPD%correct allows clinicians to predict the probability of an eCOPD-related hospitalization.

译文

背景与目的:慢性阻塞性肺疾病(eCOPD)的恶化会引起描述呼吸道症状急性恶化的重要事件。需要改变用药和/或住院治疗以控制事件。然而,导致住院的恶化与患者预后较差有关。这项研究的目的是探讨可以预测eCOPD相关住院的可能性的因素。
方法:采用一项前瞻性,纵向研究中的128例COPD患者的数据。在基线时,评估患者的身体,情绪和社会状况。此外,在一年的随访期间还记录了入院情况。基于单变量分析,文献和实践建立了不同的模型。将这些模型组合起来,得出一个最终的整体预测模型。
结果:在随访期间,有31名(24.2%)参与者被录入了eCOPD。总体模型包含六个重要变量:当前吸烟(OR = 3.93),强制肺活量(FVC; OR = 0.97),定时走走时间(TUG时间)(OR = 14.16),知识(COPD知识)问卷,正确回答问题的百分比(CIROPD%正确))(<60%(OR = 1.00); 60%-75%:(OR = 0.30);> 75%:(OR = 1.94),eCOPD历史记录(OR = 9.98) )和护理依赖性量表(CDS)的总评分(OR = 1.12),该模型已经过很好的校准(拟合优度检验:p = 0.91),并正确分类了79.7%的患者。
结论:TUG时间,基线之前的eCOPD相关入院,当前吸烟,FVC,CDS总分和CIROPD%correct的组合使临床医生可以预测eCOPD相关住院的可能性。

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