Prediction of Abnormal Functional Performance in Chronic Obstructive Pulmonary Disease Using Respiratory Models: A Pilot Study.

IF 3.1 3区 医学 Q2 RESPIRATORY SYSTEM
Caroline Oliveira Ribeiro, Agnaldo José Lopes, Pedro Lopes de Melo
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Abstract

Introduction: The contribution of respiratory models to understanding and predicting functional capacity abnormalities in chronic obstructive pulmonary disease (COPD) has not yet been investigated.

Purpose: The aims of this study were: (1) To investigate the associations between the extended Resistance-Inertance-Compliance (eRIC) and the fractional-order (FrOr) models with changes in Glittre-ADL and handgrip tests and; (2) To evaluate the accuracy of these models in predicting abnormal functional capacity in COPD.

Patients and methods: The study was carried out in a group of 40 adults with COPD and a control group of 40 healthy individuals, both evaluated by respiratory oscillometry, spirometry, Glittre-ADL test and handgrip test. eRIC and fractional order models were also used to quantify biomechanical changes and obtain physiological information. The ability of model parameters to predict abnormal functional performance was evaluated by investigating the area under the receiver operating characteristic curve (AUC).

Results: Inverse relationships were observed between central airway resistance from the eRIC model and the handgrip test (p<0.005), while respiratory compliance (C) was directly related with handgrip strength test and inversely associated with the Glittre-ADL test time (p<0.05). The FrOr model showed direct associations among respiratory damping (G) and elastance with the Glittre-ADL test (p<0.02), while significant inverse relationships were observed with the handgrip test (p<0.05). Modeling parameters (peripheral resistance, total resistance and hysteresivity) achieved high prediction accuracy (AUC>0.90) in predicting non-normal functional capacity in COPD assessed by the Glittre-ADL test. Considering abnormal changes evaluated by the handgrip test as a reference, C (AUC=0.810) and G (AUC=0.786) obtained the highest predictive accuracies.

Conclusion: Parameters obtained from the eRIC and the fractional order models are associated with non-normal exercise performance in COPD and may help predict poor functional performance in these patients.

使用呼吸模型预测慢性阻塞性肺疾病的异常功能表现:一项初步研究。
呼吸模型对理解和预测慢性阻塞性肺疾病(COPD)功能异常的贡献尚未得到研究。目的:本研究的目的是:(1)探讨扩展阻力-惯性-依从性(eRIC)和分数阶(FrOr)模型与glitre - adl和握感测试变化的关系;(2)评价这些模型预测COPD患者功能容量异常的准确性。患者和方法:该研究在40名成人COPD患者和40名健康个体的对照组中进行,均通过呼吸振荡测定法、肺活量测定法、glitre - adl试验和握力试验进行评估。eRIC和分数阶模型也被用于量化生物力学变化和获得生理信息。模型参数预测异常功能性能的能力通过调查接收器工作特征曲线(AUC)下的面积来评估。结果:在预测glitre - adl试验评估的COPD非正常功能容量时,eRIC模型的中心气道阻力与握力试验呈负相关(p0.90)。以握感试验评价的异常变化为参照,C (AUC=0.810)和G (AUC=0.786)的预测准确率最高。结论:从eRIC和分数阶模型中获得的参数与COPD患者的异常运动表现有关,并可能有助于预测这些患者的功能表现不佳。
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来源期刊
CiteScore
4.80
自引率
10.70%
发文量
372
审稿时长
16 weeks
期刊介绍: An international, peer-reviewed journal of therapeutics and pharmacology focusing on concise rapid reporting of clinical studies and reviews in COPD. Special focus will be given to the pathophysiological processes underlying the disease, intervention programs, patient focused education, and self management protocols. This journal is directed at specialists and healthcare professionals
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