Oscillometry in Asthma: Respiratory Modeling and Analysis in Occupational and Work-Exacerbated Phenotypes

被引:0
作者
Pinto, Monique da Silva [1 ,2 ]
Ribeiro, Caroline de Oliveira [1 ,2 ]
de Sa, Paula Morisco [3 ]
Castro, Hermano Albuquerque [4 ]
Bartholo, Thiago Prudente [5 ]
Lopes, Agnaldo Jose [5 ]
Melo, Pedro Lopes [1 ,2 ,6 ]
机构
[1] Univ Estado Rio De Janeiro, Inst Biol, Biomed Instrumentat Lab, Rio De Janeiro, Brazil
[2] Univ Estado Rio De Janeiro, Fac Engn, Rio De Janeiro, Brazil
[3] Univ Brazilian Air Force, Postgrad Program Operat Human Performance, Rio De Janeiro, Brazil
[4] Fundacao Oswaldo Cruz, Natl Sch Publ Hlth, Rio De Janeiro, Brazil
[5] Univ Estado Rio De Janeiro, Pedro Ernesto Univ Hosp, Pulm Funct Lab, Rio De Janeiro, Brazil
[6] Univ Estado Rio De Janeiro, Lab Clin & Expt Res Vasc Biol, Rio De Janeiro, Brazil
关键词
occupational asthma; work-exacerbated asthma; pulmonary function; forced oscillations; respiratory modeling; fractional order modeling; FORCED OSCILLATION TECHNIQUE; AIRWAY-OBSTRUCTION; INCREASING DEGREES; MECHANICS; SYSTEM; STANDARDIZATION; SPIROMETRY; REACTANCE; DIAGNOSIS; ACCURACY;
D O I
10.2147/JAA.S473639
中图分类号
R392 [医学免疫学];
学科分类号
100102 ;
摘要
Background: Asthma onset or worsening of the disease in adulthood may be associated with occupational asthma (OA) or workexacerbated asthma (WEA). Oscillometry and respiratory modeling offer insight into the pathophysiology and contribute to the early diagnosis of respiratory abnormalities. Purpose: This study aims to compare the changes due to OA and WEA and evaluate the diagnostic accuracy of this method. Patients and Methods: Ninety-nine volunteers were evaluated: 33 in the control group, 33 in the OA group, and 33 in the WEA group. The area under the receiver operator characteristic curve (AUC) was used to describe diagnostic accuracy. Results: Oscillometric analysis showed increased resistance at 4 hz (R4, p<0.001), 20 hz (R20, p<0.05), R4-R20 (p<0.0001), and respiratory work (p<0.001). Similar analysis showed reductions in dynamic compliance (p<0.001) and ventilation homogeneity, as evaluated by resonance frequency (Fr, p<0.0001) and reactance area (p<0.0001). Respiratory modeling showed increased peripheral resistance (p<0.0001), hysteresivity (p<0.0001), and damping (p<0.0001). No significant changes were observed comparing OA with WEA in any parameter. For OA, the diagnostic accuracy analyses showed Fr as the most accurate among oscillometric parameters (AUC=0.938), while the most accurate from respiratory modeling was hysteresivity (AUC=0.991). A similar analysis for WEA also showed that Fr was the most accurate among traditional parameters (AUC=0.972), and hysteresivity was the most accurate from modeling (AUC=0.987). The evaluation of differential diagnosis showed low accuracy. Conclusion: Oscillometry and modeling have advanced our understanding of respiratory abnormalities in OA and WEA. Furthermore, our study presents evidence suggesting that these models could aid in the early diagnosis of these diseases. Respiratory oscillometry examinations necessitate only tidal breathing and are straightforward to conduct. Collectively, these practical considerations, coupled with the findings of our study, indicate that respiratory oscillometry in conjunction with respiratory modeling, may enhance lung function assessments in OA and WEA.
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页码:983 / 1000
页数:18
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