Early Diagnosis of Respiratory Abnormalities in Asbestos-Exposed Workers by the Forced Oscillation Technique

Respiratory abnormalities in sarcoidosis: physiopathology and early diagnosis using oscillometry combined with respiratory modeling

BACKGROUND

Sarcoidosis is a multisystemic syndrome of uncertain etiology with abnormal respiratory findings in approximately 90% of cases. Spirometry is the most common lung function test used for assessing lung function in diagnosis and monitoring pulmonary health. Respiratory oscillometry allows a simple alternative for the analysis of respiratory abnormalities. Integer-order and fractional-order modeling have increasingly been used to interpret measurements obtained from oscillometry, offering a detailed description of the respiratory system. In this study, we aimed to enhance our understanding of the pathophysiological changes in sarcoidosis and assess the diagnostic accuracy of these models.

METHODS

This observational study includes 25 controls and 50 individuals with sarcoidosis divided into normal to spirometry (SNS) and abnormal spirometry (SAS). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC).

RESULTS

The integer-order model showed significant airway and total resistance increases in the SNS and SAS groups. There was a reduction in compliance and an increase in peripheral resistance in the SAS group (p < 0.001). The fractional-order model showed increased energy dissipation and hysteresivity in the SNS and SAS groups. Correlation analysis revealed significant associations among model and spirometric parameters, where the strongest associations were between total resistance and FEV1 (r: -0.600, p = 0.0001). The diagnostic accuracy analysis showed that total resistance and hysteresivity were the best parameters, reaching an AUC = 0.986 and 0.938 in the SNS and SAS groups, respectively.

CONCLUSION

The studied models provided a deeper understanding of pulmonary mechanical changes in sarcoidosis. The results suggest that parameters obtained through the studied models enhance evaluation and enable better management of these patients. Specifically, total resistance and hysteresivity parameters demonstrated diagnostic potential, which may be beneficial for the early identification of individuals with sarcoidosis, even when spirometry results are within normal ranges.

Combined forced oscillation and fractional-order modeling in patients with work-related asthma: a case-control study analyzing respiratory biomechanics and diagnostic accuracy

BACKGROUND

Fractional-order (FrOr) models have a high potential to improve pulmonary science. These models could be useful for biomechanical studies and diagnostic purposes, offering accurate models with an improved ability to describe nature. This paper evaluates the performance of the Forced Oscillation (FO) associated with integer (InOr) and FrOr models in the analysis of respiratory alterations in work-related asthma (WRA).

METHODS

Sixty-two individuals were evaluated: 31 healthy and 31 with WRA with mild obstruction. Patients were analyzed pre- and post-bronchodilation. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curve (AUC). To evaluate how well do the studied models correspond to observed data, we analyzed the mean square root of the sum (MSEt) and the relative distance (Rd) of the estimated model values to the measured resistance and reactance measured values.

RESULTS AND DISCUSSION

Initially, the use of InOr and FrOr models increased our understanding of the WRA physiopathology, showing increased peripheral resistance, damping, and hysteresivity. The FrOr model (AUC = 0.970) outperformed standard FO (AUC = 0.929), as well as InOr modeling (AUC = 0.838) in the diagnosis of respiratory changes, achieving high accuracy. FrOr improved the curve fitting (MSEt = 0.156 ± 0.340; Rd = 3.026 ± 1.072) in comparison with the InOr model (MSEt = 0.367 ± 0.991; Rd = 3.363 ± 1.098). Finally, we demonstrated that bronchodilator use increased dynamic compliance, as well as reduced damping and peripheral resistance.

CONCLUSIONS

Taken together, these results show clear evidence of the utility of FO associated with fractional-order modeling in patients with WRA, improving our knowledge of the biomechanical abnormalities and the diagnostic accuracy in this disease.

Oscillation Mechanics, Integer and Fractional Respiratory Modeling in COPD: Effect of Obstruction Severity

Purpose

This research examines the emerging role of respiratory oscillometry associated with integer (InOr) and fractional order (FrOr) respiratory models in the context of groups of patients with increasing severity. The contributions to our understanding of the respiratory abnormalities along the course of increasing COPD severity and the diagnostic use of this method were also evaluated.

Patients and Methods

Forty-five individuals with no history of smoking or pulmonary diseases (control group) and 141 individuals with diagnoses of COPD were studied, being classified into 45 mild, 42 moderate, 36 severe and 18 very severe cases.

Results

This study has shown initially that the course of increasing COPD severity was adequately described by the model parameters. This resulted in significant and consistent correlations among these parameters and spirometric indexes. Additionally, this evaluation enhanced our understanding of the respiratory abnormalities in different COPD stages. The diagnostic accuracy analyses provided evidence that hysteresivity, obtained from FrOr modeling, allowed a highly accurate identification in patients with mild changes [area under the receiver operator characteristic curve (AUC)= 0.902]. Similar analyses in groups of moderate and severe patients showed that peripheral resistance, derived from InOr modeling, provided the most accurate parameter (AUC=0.898 and 0.998, respectively), while in very severe patients, traditional, InOr and FrOr parameters were able to reach high diagnostic accuracy (AUC>0.9).

Conclusion

InOr and FrOr modeling improved our knowledge of the respiratory abnormalities along the course of increasing COPD severity. In addition, the present study provides evidence that these models may contribute in the diagnosis of COPD. Respiratory oscillometry exams require only tidal breathing and are easy to perform. Taken together, these practical considerations and the results of the present study suggest that respiratory oscillometry associated with InOr and FrOr models may help to improve lung function tests in COPD.

Lung Function Assessment by Impulse Oscillometry in Adults

Over the past decades, impulse oscillometry (IOS) has gained ground in the battery of pulmonary function tests. Performing the test requires minimal cooperation of the patient; therefore, it is a useful tool, especially in evaluating lung mechanics in children, elderly patients, and those who cannot perform spirometry. Oscillometry has also been used in both clinical and research departments. Studies were published mainly in asthma regarding detection of bronchodilator response and the therapeutic response to different drugs. Furthermore, it has been shown to be a sensitive technique to evaluate disease control. Other studied diseases were COPD, interstitial lung diseases, small airway disease, impairment of lung function due to exposure to occupational hazards or smoking, central airways obstruction, cystic fibrosis, monitoring lung mechanics during mechanical ventilation and sleep, neuromuscular diseases, lung transplant, and graft function. The aim of this review is to present the utility of oscillometry on the previously mentioned clinical fields.

Evaluation of forced oscilometry technique's parameters in severe obstructive sleep apnea patients without breathing disorder

Background:

Forced oscillometry technique (FOT) is a noninvasive technique that measures reactance and resistance capacity of the lung and is a practical and less time-consuming technique for respiratory effort assessment. Recently, FOT has provided beneficial data regarding the screening of the patients with obstructive sleep apnea (OSA) and assessing the disease progression. The current study aimed to evaluate the correlation of FOT parameters with severity of the apnea-hypnea index (AHI).

Methods:

In the current case series, all patients who had a body mass index ranging between 30 and 35, suffering severe OSA with AHI of more than 30 times per hour, were enrolled. Patients underwent FOT before treatment to measure the following FOT parameters: Respiratory resistance at 5 and 20 Hz (R5 and R20, respectively), resistance difference between R5 and R20, reactance at 5 Hz (X5), and resonant frequency (Fres).

Results:

In the current study, 22 patients were enrolled; whereas 12 (54.5%) were male and 10 (45.5%) were female with a mean age of 5.27 ± 4.34. A statistically significant, strong negative correlation was observed between Fres and AHI, during Pearson correlation analysis (r (20) =0.59, P < 0.0001). However, the relationship between the AHI and R5, R20, R5-R20 and X5 was not statistically significant. Similarly, the multiple regression model showed that, only Fres variable added statistically significantly to the prediction, P = 0.01.

Conclusion:

FOT is a useful tool in evaluation of AHI severity in patients suffering OSA and can be used as a diagnostic material in monitoring and management of these patients.

Association of respiratory integer and fractional-order models with structural abnormalities in silicosis

BACKGROUND AND OBJECTIVE

Integer and fractional-order models have emerged as powerful methods for obtaining information regarding the anatomical or pathophysiological changes that occur during respiratory diseases. However, the precise interpretation of the model parameters in light of the lung structural changes is not known. This study analyzed the associations of the integer and fractional-order models with structural changes obtained using multidetector computed tomography densitometry (MDCT) and pulmonary function analysis.

METHODS

Integer and fractional-order models were adjusted to data obtained using the forced oscillation technique (FOT). The results obtained in controls (n = 20) were compared with those obtained in patients with silicosis (n = 32), who were submitted to spirometry, body plethysmograph, FOT, diffusing capacity of the lungs for carbon monoxide (DLCO), and MDCT. The diagnostic accuracy was also investigated using ROC analysis.

RESULTS

The observed changes in the integer and fractional-order models were consistent with the pathophysiology of silicosis. The integer-order model showed association only between inertance and the non-aerated compartment (R = -0.69). This parameter also presented the highest associations with spirometry (R = 0.81), plethysmography (-0.61) and pulmonary diffusion (R = 0.53). Considering the fractional-order model, the increase in the poorly aerated and non-aerated regions presented direct correlations with the fractional inertance (R = 0.48), respiratory damping (R = 0.37) and hysteresivity (R = 0.54) and inverse associations with its fractional exponent (R = -0.62) and elastance (-0.35). Significant associations were also observed with spirometry (R = 0.63), plethysmography (0.37) and pulmonary diffusion (R = 0.51). Receiver operator characteristic analysis showed a higher accuracy in the FrOr model (0.908) than the eRIC model (0.789).

CONCLUSIONS

Our study has shown clear associations of the integer and fractional-order parameters with anatomical changes obtained via MDCT and pulmonary function measurements. These findings help to elucidate the physiological interpretation of the integer and fractional-order parameters and provide evidence that these parameters are reflective of the abnormal changes in silicosis. We also observed that the fractional-order model showed smaller curve-fitting errors, which resulted in a higher diagnostic accuracy than that of the eRIC model. Taken together, these results provide strong motivation for further studies exploring the clinical and scientific use of these models in respiratory medicine.

Respiratory resistance and reactance in adults with sickle cell anemia: Part 2-Fractional-order modeling and a clinical decision support system for the diagnosis of respiratory disorders

BACKGROUND

A better understanding of sickle cell anemia (SCA) and improvements in drug therapy and health policy have contributed to the emergence of a large population of adults living with this disease. The mechanisms by which SCA produces adverse effects on the respiratory system of these patients are largely unknown. Fractional-order (FrOr) models have a high potential to improve pulmonary clinical science and could be useful for diagnostic purposes, offering accurate models with an improved ability to mimic nature. Part 2 of this two-part study examines the changes in respiratory mechanics in patients with SCA using the new perspective of the FrOr models. These results are compared with those obtained in traditional forced oscillation (FOT) parameters, investigated in Part 1 of the present study, complementing this first analysis.

METHODOLOGY/PRINCIPAL FINDINGS

The data consisted of three categories of subjects: controls (n = 23), patients with a normal spirometric exam (n = 21) and those presenting restriction (n = 24). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Initially, it was observed that biomechanical changes in SCA included increased values of fractional inertance, as well as damping and hysteresivity (p<0.001). The correlation analysis showed that FrOr parameters are associated with functional exercise capacity (R = -0.57), pulmonary diffusion (R = -0.71), respiratory muscle performance (R = 0.50), pulmonary flows (R = -0.62) and airway obstruction (R = 0.60). Fractional-order modeling showed high diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.93), outperforming spirometry (p<0.03) and standard FOT analysis (p<0.01) used in Part 1 of this study. A combination of machine learning methods with fractional-order modeling further improved diagnostic accuracy (AUC = 0.97).

CONCLUSIONS

FrOr modeling improved our knowledge about the biomechanical abnormalities in adults with SCA. Changes in FrOr parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FrOr modeling outperformed spirometric and traditional forced oscillation analyses, showing a high diagnostic accuracy in the diagnosis of early respiratory abnormalities that was further improved by an automatic clinical decision support system. This finding suggested the potential utility of this combination to help identify early respiratory changes in patients with SCA.

Forced oscillation technique for early detection of the effects of smoking and COPD: contribution of fractional-order modeling

Purpose

The aim of the present study was to evaluate the performance of the forced oscillation technique (FOT) for the early diagnosis of the effects of smoking and COPD. The contributions of the integer-order (InOr) and fractional-order (FrOr) models were also evaluated.

Patients and methods

In total, 120 subjects were analyzed: 40 controls, 40 smokers (20.3±9.3 pack-years) and 40 patients with mild COPD.

Results

Initially, it was observed that traditional FOT parameters and the InOr and FrOr models provided a consistent description of the COPD pathophysiology. Mild COPD introduced significant increases in the FrOr inertance, damping factor and hysteresivity (P<0.0001). These parameters were significantly correlated with the spirometric parameters of central and small airway obstruction (P<0.0001). The diagnostic accuracy analyses indicated that FOT parameters and InOr modeling may adequately identify these changes (area under the receiver operating characteristic curve – AUC >0.8). The use of FrOr modeling significantly improved this process (P<0.05), allowing the early diagnosis of smokers and patients with mild COPD with high accuracy (AUC >0.9).

Conclusion

FrOr modeling improves our knowledge of modifications that occur in the early stages of COPD. Additionally, the findings of the present study provide evidence that these models may play an important role in the early diagnosis of COPD, which is crucial for improving the clinical management of the disease.

Respiratory resistance and reactance in adults with sickle cell anemia: Correlation with functional exercise capacity and diagnostic use

BACKGROUND

The improvement in sickle cell anemia (SCA) care resulted in the emergence of a large population of adults living with this disease. The mechanisms of lung injury in this new population are largely unknown. The forced oscillation technique (FOT) represents the current state-of-the-art in the assessment of lung function. The present work uses the FOT to improve our knowledge about the respiratory abnormalities in SCA, evaluates the associations of FOT with the functional exercise capacity and investigates the early detection of respiratory abnormalities.

METHODOLOGY/PRINCIPAL FINDINGS

Spirometric classification of restrictive abnormalities resulted in three categories: controls (n = 23), patients with a normal exam (n = 21) and presenting pulmonary restriction (n = 24). FOT analysis showed that, besides restrictive changes (reduced compliance; p<0.001), there is also an increase in respiratory resistance (p<0.001) and ventilation heterogeneity (p<0.01). FOT parameters are associated with functional exercise capacity (R = -0.38), pulmonary diffusion (R = 0.66), respiratory muscle performance (R = 0.41), pulmonary volumes (R = 0.56) and airway obstruction (R = 0.54). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). A combination of FOT and machine learning (ML) classifiers showed adequate diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.82).

CONCLUSIONS

In this study, the use of FOT showed that adults with SCA develop a mixed pattern of respiratory disease. Changes in FOT parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FOT associated with ML methods accurately diagnosed early respiratory abnormalities. This suggested the potential utility of the FOT and ML clinical decision support systems in the identification of respiratory abnormalities in patients with SCA.