Tuberc Respir Dis > Volume 85(2); 2022 > Article
Shanmugasundaram, Talwar, Madan, and Bade: Pulmonary Functions and Inflammatory Biomarkers in Post-Pulmonary Tuberculosis Sequelae

Abstract

Background

Post-tuberculosis (TB) sequelae is a commonly encountered clinical entity, especially in high TB burden countries. This may represent chronic anatomic sequelae of previously treated TB, with frequent symptomatic presentation. This pilot study was aimed to investigate the pulmonary functions and systemic inflammatory markers in patients with post-TB sequelae (PTBS) and to compare them with post-TB without sequelae (PTBWS) participants and healthy controls.

Methods

A total of 30 participants were enrolled, PTBS (n=10), PTBWS (n=10), and healthy controls (n=10). Pulmonary function tests included spirometry and measurement of airway impedance by impulse oscillometry. Serum levels of matrix metalloproteinase (MMP)-1, transforming growth factor-β, and interferon-γ were estimated.

Results

Slow vital capacity (SVC), forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEV1/FVC, and peak expiratory flow were significantly lower in PTBS as compared to controls. SVC and FEV1 were significantly less in PTBS as compared to PTBWS. Total airway impedance (Z5), total airway resistance (R5), central airway resistance (R20), area of reactance (Ax), and resonant frequency (Fres) were significantly higher and respiratory reactance at 5 and 20 Hz (X5, X20) were significantly lower in PTBS as compared to PTBWS. Spirometry parameters correlated with impulse oscillometry parameters in PTBS. Serum MMP-1 level was significantly higher in PTBS as compared to other groups.

Conclusion

Significant pulmonary function impairment was observed in PTBS, and raised serum MMP-1 levels compared with PTBWS and healthy controls. Follow-up pulmonary function testing is recommended after treatment of TB for early diagnosis and treatment of PTBS.

Introduction

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. Every year worldwide, around 10 million people are affected by TB. It is one of the top 10 causes of death [1]. About 85% of people who develop TB can be successfully treated with a 6-month first-line drug regimen. It is estimated that nearly half of the microbiologically cured pulmonary TB patients may develop post-TB sequelae (PTBS) [2].
Post TB sequelae is chronic anatomic and symptomatic (dyspnea/cough) sequelae from previously treated (microbiologically cured) pulmonary TB. Post-TB lung dysfunction often goes unrecognized, despite its relatively high prevalence and it is associated with reduced quality of life [3]. Pulmonary dysfunction includes minor abnormalities to severe breathlessness with an increased risk of death [4]. Treated TB patients contribute to a growing worldwide burden of chronic obstructive pulmonary disease (COPD) [5]. Post TB patients are prone to develop a wide variety of non-infectious disorders; these include parenchymal disorders (thin-walled cavities, lung fibrosis), chronic airflow obstruction, bronchiectasis, subglottic and tracheobronchial stenosis, pleural thickening, corpulmonale, and chronic respiratory failure [6]. Chung et al. [7] found that the major nadir of pulmonary function impairment occurs approximately 18 months after completion of treatment. Several studies have reported that there is a decline in lung volumes and capacities that lead to obstructive and restrictive ventilatory defects during TB and also after completion of TB treatment [3,4,7]. Importantly, specific host and pathogen factors causing post TB lung impairment remain unclear. It is proposed that host immune responses may play a dominant role in lung damage, as excessive inflammation and elevated expression of lung matrix-degrading proteases are the hallmarks of TB pathogenesis. The inflammatory markers and cytokines that are released in response to active TB infection may cause severe damage and remodeling of the airways [8]. Matrix metalloproteinases (MMPs) are a family of 25 potent proteases that may degrade extracellular matrix components and are probably central to TB-associated lung injury [9]. Transforming growth factor-β (TGF-β), which is associated with lung inflammation, plays a crucial role in lung fibrosis [10]. Interferon-γ (IFN-γ) is also implicated in lung injury observed during TB [11].
No studies have specifically investigated airway impedance changes in patients diagnosed with post TB sequelae. The present pilot study aimed to assess lung functions using spirometry, impulse oscillometry and to estimate serum inflammatory biomarkers in patients with or without post TB sequelae.

Materials and Methods

1. Study design

The study protocol was approved by the Institute Ethics Committee of All India Institute of Medical Sciences (AIIMS), New Delhi (Reference No: IECPG-791/31.01.2020). Enrolment of subjects was done as per the inclusion and exclusion criteria after obtaining written informed consent and willingness to participate in the study. The primary objectives of this pilot study were to compare lung functions and systemic inflammatory markers in patients with PTBS, post-TB without sequelae (PTBWS) and healthy controls. The study population included patients who had a history of microbiologically confirmed pulmonary TB, had completed anti-TB treatment and were declared bacteriologically cured. Based on a review of the clinical/clinico-radiological presentations, they were divided into two groups. Patients who had clinical symptoms and radiological evident abnormality on the chest radiograph were included in the PTBS group. Patients who had completed anti-TB treatment with no evidence of residual chest radiographic abnormality were included in the group PTBWS. Patients with a past/current history of smoking, asthma, COPD, sarcoidosis, interstitial lung diseases, and other respiratory diseases were excluded from this study. Also participants with active TB, history of multi-drug resistant TB, extra-pulmonary TB, human immunodeficiency virus-TB, evidence of cardiovascular, musculoskeletal, chronic immunological diseases and inflammatory disorders were excluded from the study. A total of 30 participants were enrolled in this study with 10 participants in each group: PTBS (5 males and 5 females), PTBWS (10 males), and healthy controls (5 males and 5 females). Patient enrolment was carried out from the outpatient clinic at the Department of Pulmonary, Critical Care and Sleep Medicine, AIIMS, New Delhi. Age-matched healthy controls were also recruited. Assessment of lung functions and inflammatory markers was done at Respiratory Research Laboratory, Department of Physiology, AIIMS, New Delhi.

2. Data collection

History was taken regarding the duration of anti-TB treatment taken by the patients. All the recruited patients had completed anti-TB treatment and the treatment duration varied from 6 to 12 months. Baseline demographic data was recorded after recruitment.

3. Assessment of airway impedance by impulse oscillometry system

Assessment of airway impedance was done using the impulse oscillometry system (IOS; Eric Jaeger, Hochberg, Germany). Impulse oscillometry is a simple, non-invasive method to assess the mechanics of lungs and airways and it uses the forced oscillation technique. It requires minimal participant effort as compared to spirometry. Oscillating sound waves of different frequencies ranging between 5 Hz and 35 Hz are produced by loudspeaker and superimposed over normal tidal breathing. The lower frequencies travel deep into the lungs up to peripheral airways and reflected whereas the higher frequencies are reflected back from central airways. The test was performed in a sitting position for 90 seconds. A tight seal between lips and mouthpiece was ensured. The cheeks were held firmly by the patient with his/her hands. The parameters recorded were total airway impedance (Z5), airway resistance at 5 and 20 Hz (R5, R20) and airway reactance at 5 and 20 Hz (X5, X20). The other oscillometry indices taken into consideration were peripheral airway resistance (R5-R20), resonant frequency (Fres), and area of reactance (Ax) [12,13].

4. Spirometry

The slow vital capacity (SVC) and forced vital capacity (FVC) maneuver were performed using the spirometer (Medisoft, Spiro Air, Kent, UK) and the parameters recorded were SVC, FVC, forced expiratory volume in 1 second (FEV1), FEV1/FVC ratio, and peak expiratory flow (PEF). The tests were performed as per the guidelines of the American Thoracic Society and European Respiratory Society [14].

5. Assessment of systemic inflammatory markers using enzyme-linked immunosorbent assay

Peripheral venous blood (3 mL) was collected under all aseptic precautions for the estimation of inflammatory markers: MMP-1, TGF-β, and IFN-γ. Serum was separated and stored at -20°C. Human enzyme-linked immunosorbent assay (ELISA) kits of Bioassay Technology Laboratory, China (cat Nos. E0916Hu, E0134Hu, E0105Hu) were used to quantify serum levels of MMP-1, TGF-β, and IFN-γ, respectively. ELISA was performed according to the manufactures guidelines and the color developed in the 96-well plates was read using a microplate reader (BioTek, Epoch 2 microplate reader, Winooski, VT, USA). Samples were estimated in duplicate and average values were used for analysis.

6. Statistical analysis

All statistical tests were done using GraphPad Prism version 9.0.1 for Windows (GraphPad Software, Inc., San Diego, CA, USA). Each parameter was tested for distribution of the data based on standard normality tests (D’Agostino-Pearson omnibus normality test, Anderson-Darling test, Shapiro-Wilk test). Multi-group comparisons were performed using oneway ANOVA or Kruskal-Wallis test with appropriate post hoc comparison test based on normality of data. The correlation between two parameters was evaluated using Pearson’s correlation coefficient or Spearman’s rank correlation coefficient if they were appropriate. Receiver operating characteristics (ROC) curve analysis was performed and likelihood ratio was used to determine the cutoff values of IOS parameters to distinguish between PTBS and PTBWS groups. The level of statistical significance was set at p<0.05.

Results

A total of 30 participants were enrolled in this pilot study with 10 participants in each group (PTBS, PTBWS, and healthy controls). The demographic data of these participants are presented in Table 1.
We observed that spirometry parameters: i.e., SVC (% predicted), FVC (% predicted), FEV1 (% predicted), FEV1/FVC, and PEF (% predicted) were significantly lower in PTBS as compared to healthy controls, while SVC (% predicted) and FEV1 (% predicted) were significantly lower in PTBS as compared to PTBWS (Table 2).
Total airway impedance (Z5), total airway resistance (R5), peripheral airway resistance (R5-R20), area of reactance (Ax), and resonant frequency (Fres) were significantly higher and respiratory reactance at 20 Hz (X20) were significantly lower in PTBS as compared to controls. In addition, central airway resistance (R20) was significantly higher and reactance at 5 Hz (X5) was significantly lower in PTBS as compared to PTBWS (Table 3, Figures 1, 2).
In PTBS patients, IOS parameters correlated with their spirometry parameters. There is a significant negative correlation between R5, R5 (% predicted), Z5, Z5 (% predicted), Ax, R5-R20 with SVC (% predicted), FVC (% predicted), FEV1 (% predicted), and PEF (% predicted). Likewise, R5-R20 and Ax negatively correlated with all the spirometry parameters. The reactance parameters X5 and X20 positively correlated with SVC (% predicted), FVC (% predicted), FEV1 (% predicted), PEF (% predicted), and maximal expiratory flow (% predicted). R20, R20 (% predicted), and Fres did not correlate with any of the spirometry parameters (Table 4). The correlation was also observed between IOS parameters and SVC, FVC in PTBWS subjects. As a significant difference was observed for IOS and spirometry parameters between PTBS and PTBWS, ROC curves were plotted to explore the ability of these parameters to discriminate between PTBS and PTBWS. The area under the curve (AUC), likelihood ratio, specificity, sensitivity, and their respective cutoff frequency to distinguish between the sequelae and without sequelae group are stated in Table 5. It was observed that all the parameters except FEV1/FVC, PEF, and delta X5 have AUC >0.8 and Z5, R5, and Ax are the most promising determining factors with AUC >0.9.
The median value of serum MMP-1 was significantly higher in PTBS (3.13 ng/mL) as compared to PTBWS (2.92 ng/mL). TGF-β levels were higher in PTBS (195.3 ng/L) as compared with PTBWS (141.1 ng/L) but the difference was statistically insignificant and both the data were comparable with healthy controls (Table 6). Serum IFN-γ levels are comparable within the study groups. A statistically significant positive correlation was observed between the serum levels of MMP-1 and TGF-β in PTBS (r=0.785, p=0.027).

Discussion

In the present study, we have measured the airway impedance and spirometry parameters in patients diagnosed with post TB sequelae. To the best of our knowledge, this is the first study investigating the airway impedance in post-TB patients using IOS. We observed significantly lower lung volumes and capacities in PTBS patients as compared with PTBWS and healthy controls. Most of the parameters like SVC, FVC, FEV1, FEV1/FVC ratio, and PEF were reduced in sequelae patients. Out of 10 patients, nine patients had mixed restrictive and obstructive respiratory impairment and one had normal lung function. Previous studies also indicate that there is an impaired lung function in patients who had sequelae at the end of TB treatment. The radiological signs of these patients were correlated with spirometry parameters [4,15,16].
The total airway impedance (Z5) is the sum of all resistive, inertial, and elastic forces of the respiratory system, the sound waves have to encounter during their travel through the respiratory system. The significant increase in total airway impedance (Z5) (Z5 % predicted) in PTBS patients shows that there is impaired lung mechanics in these patients. Resistance shows the amount of resistance offered to the flow by the airways. We observed higher total airway resistance (R5) (R5 % predicted), central airway resistance (R20) (R20 % predicted) and peripheral airway resistance (R5-R20) in PTBS as compared to PTBWS and controls.
Reactance is the rebound resistance produced by distensible airways. It includes the mass-inertial forces of the moving air column expressed in terms of inertance (I) and the elastic properties or compliance of the lung periphery expressed as capacitance (C). At lower frequencies, i.e., 5 Hz, capacitative properties of the small peripheral airways dominate. In this study, we have observed X5 significantly lower (more negative) in PTBS as compared to PTBWS. Reduced elasticity of the lungs, due to the presence of fibrosis and hyperinflation can make the capacitance increasingly negative [12]. Thus lower X5 may suggest the presence of disturbed physical properties of the lung parenchyma and its inability to expand and facilitate alveolar filling in the PTBS patient group. We also found that the area of reactance (Ax) and resonant frequency (Fres) in PTBS patients were higher as compared with other study groups. Ax, Fres, and X5 act as sensitive parameters to determine the small airway obstruction and restrictive airway diseases [17]. The change in all of these IOS and spirometric parameters show that PTBS patients have significant impairment in the airway mechanics and have combined airway obstruction and restriction. This impairment in airway mechanics is may be due to remodeling of lung tissue observed during TB infection and its recovery. The release of different inflammatory mediators like MMP-1 and TGF-β during TB destroy the peripheral lung extracellular matrix and lead to pulmonary fibrosis respectively [15,16].
We have also studied the correlation between spirometry and IOS parameters in PTBS and observed that SVC (% predicted), FVC (% predicted), FEV1 (% predicted) and PEF (% predicted) correlate negatively with Z5, Z5 (% predicted), R5, R5 (% predicted), Ax and R5-R20 and positively with X5 and X20. This shows that a decrease in lung volumes and capacities is associated with an increase in airway resistance and a decrease in airway reactance. The increase in airway resistance is mainly caused due to damage and remodeling of peripheral airways during the TB infection, course of treatment and posttreatment depending upon the pathogen-host interaction. Our results are in agreement with the study conducted by Xia Wei et al., where they observed a correlation between spirometry parameters FEV1 (% predicted), maximal (mid-) expiratory flow 75%-25%, and residual volume/total lung capacity and IOS parameters Z5 (% predicted), R5, R20, R5-R20% R5, R5, R5% predicted, Fres, Ax, X5, and also reported that IOS can be an alternative diagnostic method for COPD18. ROC curve analysis shows that IOS parameters like Z5, R5, R20, X5, Ax, and Fres act as the most sensitive parameter to differentiate PTBS from PTBWS. There was no correlation found between IOS parameters and inflammatory biomarkers in PTBS.
We observed significantly higher serum levels of MMP-1 in PTBS patients as compared with PTBWS. Serum MMP-1 is one of the proteases in the family of 25 potent proteases of MMPs that usually degrade extracellular matrix components and play a key role in TB-associated lung injury. Studies suggest that there is an increase in the levels of MMP-1 and MMP-9 gene expression that is associated with damage to lung parenchyma during TB [19]. We also observed that MMP-1 levels in both post TB groups were comparable to healthy controls. It is observed that levels of MMP-1 significantly decrease during the course of treatment [20] and the first-line antimycobacterial agents specifically, moxifloxacin suppress MMP-1 secretion and gene expression in human airway epithelial cells [21]. Another inflammatory biomarker we assessed was TGF-β, found to be the principal mediator of pulmonary fibrogenesis [22]. It stimulates differentiation of fibroblasts into myofibroblasts that then produce α-smooth muscle actin, a key indicator and contributor to fibrotic pathogenesis. In our study, we found that the serum levels of TGF-β were comparable within the study groups. But, there is a trend of increased TGF-β levels observed in PTBS patients as compared with PTBWS. Christine et al. [10], have reported similar findings just after the completion of TB treatment. A positive correlation was observed between MMP-1 and TGF-β levels of PTBS; it indicates that increased levels of these inflammatory markers may simultaneously play a role in the remodeling of the airways during the course of the disease process and its treatment. IFN-γ, or type II interferon, is a cytokine that is critical for innate and adaptive immunity against viral, some bacterial and protozoal infections. IFN-γ released by CD4+ T cells of the TH1 subset act as an important activator of macrophages. This leads to the release of more inflammatory mediators by macrophages and the recruitment of more and more inflammatory cells that form the granuloma during TB [23-25]. In the present study, the serum levels of IFN-γ were comparable within all the study groups. It has also been reported that IFN-γ levels are increased during TB and decrease at the end of anti-TB treatment [26-28].
Post-pulmonary TB sequelae is an emerging worldwide burden of lung function impairment after a complete course of TB treatment. It is likely that specific host-pathogen interactions occur during TB treatment. There is an urgent need to investigate the profile of inflammatory markers and host-pathogen interaction during the course of TB treatment and post-treatment follow-up for a prolonged period to understand the exact pathophysiological basis of PTBS. It may facilitate early detection of post TB sequelae, optimization of the treatment methods and improvement in the quality of life of post-TB patients.
PTBS patients have reduced lung volumes and capacities along with impaired lung mechanics. In these patients, spirometry parameters correlated significantly with impulse oscillometry parameters. Significantly higher serum MMP-1 level is observed in post TB with sequelae as compared to PTBWS subjects.
This study provides the importance of doing follow-up spirometry and impulse oscillometry in patients diagnosed with pulmonary TB after completing the anti-TB treatment. It will help in early diagnosis of pulmonary impairment.
To the best of our knowledge, this is the first of its kind study in which lung volumes, capacities and airway mechanics are studied in patients having post-pulmonary TB sequelae and compared with post-pulmonary TB without sequelae participants and healthy controls. The most important limitations of this study are its small sample size and less number of estimated serum cytokines. But with this small sample size also we observed significant impairment in lung volumes, capacities and airway mechanics in patients having post-pulmonary TB sequelae. Further to understand pathophysiology of post-pulmonary TB sequelae, it is important to do a follow-up study in patients during and after completion of anti-TB treatment with large sample size and whole profile of biomarkers must be estimated.

Notes

Authors’ Contributions

Conceptualization: Bade G, Talwar A, Madan K. Formal analysis: Shanmugasundaram K. Data curation: Shanmugasundaram K. Writing - original draft preparation: Shanmugasundaram K. Writing - review and editing: Shanmugasundaram K, Talwar A, Madan K, Bade G. Approval of final manuscript: all authors.

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Funding

This study was supported and funded by the Department of Physiology, All India Institute of Medical Sciences, New Delhi.

Acknowledgments

We acknowledge all the participants who took part in this study.

Fig. 1.
(A-F) Graph depicting the impulse oscillometry values of controls, post-tuberculosis without sequelae (PTBWS), and post-tuberculosis with sequelae (PTBS). Values are plotted as mean±standard deviation. *p<0.05, **p<0.01, and ***p<0.001 for intra group comparison. Z5: total airway impedance; R5: resistance at 5 Hz; R20: resistance at 20 Hz.
trd-2021-0127f1.jpg
Fig. 2.
(A-H) Graph depicting the impulse oscillometry values of controls, post-tuberculosis without sequelae (PTBWS) and post-tuberculosis with sequelae (PTBS). Values are plotted as mean±standard deviation. *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001 for intra group comparison. X5: reactance at 5 Hz; X20: reactance at 20 Hz; R5-R20: peripheral airway resistance; Ax: area of reactance.
trd-2021-0127f2.jpg
Table 1.
Demographic data of the study groups
Parameter Control (n=10) PTBS (n=10) PTBWS (n=10) p-value
Age, yr 37.50±9.95 46.20±10.05 37.10±9.52 0.083
Height, cm 166.50±14.19 158.40±12.63 167.90±4.47 0.146
Weight, kg 75.24±17.33 54.53±14.24 68.86±12.96 0.013*
BMI, kg/m2 26.82±3.07 21.60±4.11 23.96±3.51 0.010*
Smoking history - - - -
Sex (male:female) 5:5 5:5 10:0 -

Values are expressed as mean±standard deviation, analyzed by one-way ANOVA.

* p<0.05 statistically significant.

PTBS: post-tuberculosis with sequelae; PTBWS: post-tuberculosis without sequelae; BMI: body mass index.

Table 2.
Spirometry parameters of the study groups
Parameter Control (n=10) PTBS (n=10) PTBWS (n=10) p-value Multiple comparisons test
SVC (% predicted) 86.20±17.20 60.60±18.28 79.21±10.12 0.003** 0.003**
0.033*§
FVC (% predicted) 91.70±17.54 62.90±18.38 80.37±11.00 0.001** 0.001**
FEV1 (% predicted) 85.30±17.18 49.50±21.32 71.98±11.66 <0.001*** <0.001***
0.018*§
FEV1/FVC 78.05 (74.01-81.08) 63.21 (56.99-73.80) 77.88 (70.69-79.19) 0.048* 0.044*
PEF (% predicted) 82.00±29.16 43.40±24.66 45.00±15.84 0.001** 0.004**
0.003**

Values expressed are mean±standard deviation or median with inter-quartile range, analyzed by one-way ANOVA (post hoc -Turkey) or Kruskal-Wallis test (post hoc-Dunn’s), respectively.

* p<0.05, **p<0.01, and ***p<0.001 statistically significant.

Control vs. PTBWS.

Control vs. PTBS.

§ PTBWS vs. PTBS.

PTBS: post-tuberculosis with sequelae; PTBWS: post-tuberculosis without sequelae; SVC: slow vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 second; PEF: peak expiratory flow.

Table 3.
Impulse oscillometry parameters of the study groups
Parameter Control (n=10) PTBS (n=10) PTBWS (n=10) p-value Multiple comparisons test
Z5 0.38±0.12 0.63±0.31 0.28±0.05 0.001** 0.020*
0.001**§
Z5 (% predicted) 117.70±28.53 195.30±100.80 102.30±20.16 0.004** 0.023*
0.006**§
R5 0.35±0.11 0.55±0.23 0.26±0.05 <0.001*** 0.021*
<0.001***§
R5 (% predicted) 111.50±27.57 171±73.66 97.59±19.15 0.003** 0.021*
0.004**§
R20 0.31±0.10 0.33±0.09 0.19±0.02 0.002** 0.012*
0.002**§
R20 (% predicted) 93.49±26.91 120.40±34.43 83.99±9.96 0.011* 0.010*§
Ax 0.43±0.25 3.06±2.43 0.56±0.37 <0.001*** <0.001***
0.001**§
Fres 14.39±3.76 28.75±7.87 18.63±3.21 <0.001**** <0.001****
<0.001***§
X5 -0.09 (-0.18 to 0.07) -0.22 (-0.45 to -0.10) -0.07 (-0.08 to 0.06) 0.004** 0.003**§
X5 (% predicted) 343.80 (-400 to 750) 1,163 (235.4 to 5,252) -375 (-1,387 to 181) 0.015* 0.012*§
X20 0.05±0.04 -0.07±0.07 0.003±0.01 <0.001**** <0.001****
0.004**§
X20 (% predicted) 100 (27.68 to 111.10) -113.30 (-267.50 to 16.94) 12.50 (-12.48 to 27.08) 0.001*** <0.001***
R5-R20 0.05 (0.03 to 0.07) 0.13 (0.08 to 0.40) 0.08 (0.03 to 0.10) 0.009** 0.011*
DeltaX5 0.01 (0.01 to 0.02) 0.04 (0.02 to 0.09) 0.03 (0.01 to 0.05) 0.048* 0.048*

Values presented are mean±standard deviation or median with inter-quartile range, analyzed by one-way ANOVA (post hoc-Turkey) or Kruskal-Wallis test (post hoc-Dunn’s), respectively.

* p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001 statistically significant.

Control vs. PTBWS.

Control vs. PTBS.

§ PTBWS vs. PTBS.

PTBS: post-tuberculosis with sequelae; PTBWS: post-tuberculosis without sequelae; Z5: total airway impedance; R5: resistance at 5 Hz; R20: resistance at 20 Hz; Ax: area of reactance; Fres: resonant frequency; X5: reactance at 5 Hz; X20: reactance at 20 Hz; R5-R20: peripheral airway resistance.

Table 4.
Correlation between IOS with spirometry parameters of post-tuberculosis sequelae patients (n=10)
SVC (% predicted)
FVC (% predicted)
FEV1 (% predicted)
FEV1/FVC
PEF (% predicted)
r value p-value r value p-value r value p-value r value p-value r value p-value
R5 (% predicted) -0.715 0.019* -0.725 0.017* -0.776 0.008** -0.606 0.063 -0.719 0.019*
R5 -0.750 0.012* -0.768 0.009** -0.787 0.006** -0.551 0.098 -0.726 0.017*
R20 (% predicted) -0.477 0.163 -0.483 0.157 -0.470 0.170 -0.359 0.308 -0.555 0.095
R20 -0.511 0.130 -0.530 0.114 -0.489 0.151 -0.300 0.399 -0.582 0.077
X5 (% predicted) -0.565 0.093 -0.600 0.073 -0.636 0.054 -0.430 0.218 -0.697 0.030*
X5 0.704 0.022* 0.736 0.015* 0.720 0.018* 0.494 0.146 0.669 0.034*
X20 (% predicted) 0.695 0.030* 0.674 0.036* 0.784 0.009** 0.601 0.070 0.826 0.004**
X20 0.681 0.029* 0.677 0.031* 0.777 0.008** 0.602 0.065 0.661 0.037*
R5-R20 -0.737 0.018* -0.741 0.017* -0.863 0.002** -0.644 0.049* -0.820 0.005**
Ax -0.733 0.015* -0.741 0.014* -0.827 0.003** -0.652 0.040* -0.742 0.014*
Fres -0.426 0.219 -0.417 0.229 -0.591 0.071 -0.540 0.106 -0.548 0.100
Z5 (% predicted) -0.695 0.025* -0.716 0.019* -0.747 0.013* -0.566 0.088 -0.704 0.022*
Z5 -0.749 0.012* -0.777 0.008** -0.780 0.007** -0.535 0.110 -0.728 0.016*

* p<0.05, **p<0.01 statistically significant.

Pearson correlation.

Spearman correlation.

IOS: impulse oscillometry system; SVC: slow vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 second; PEF: peak expiratory flow; R5: resistance at 5 Hz; R20: resistance at 20 Hz; X5: reactance at 5 Hz; X20: reactance at 20 Hz; R5-R20: peripheral airway resistance; Ax: area of reactance; Fres: resonant frequency; Z5: total airway impedance.

Table 5.
IOS a sensitive tool for lung function impairment in post TB sequelae
Parameter Cutoff frequency Sensitivity Specificity Likelihood ratio AUC
Z5 >0.355 0.9000 0.9000 9.00 0.9300
Z5 (% predicted) >131.5 0.6000 0.9000 6.00 0.8650
R5 >0.325 0.9000 0.8000 4.50 0.9350
R5 (% predicted) >122.4 0.6000 0.9000 6.00 0.8500
R20 > 0.215 0.8000 0.9000 8.00 0.8800
R20 (% predicted) >95.55 0.8000 0.9000 8.00 0.8300
X5 <-0.105 0.8000 0.9000 8.00 0.8950
X5 (% predicted) >1.312 0.5000 0.9000 5.00 0.8600
R5-R20 >0.110 0.6000 0.8000 3.00 0.8150
Fres >22.44 0.8000 0.9000 8.00 0.8700
Ax >0.955 0.8000 0.9000 8.00 0.9300
Delta X5 >0.055 0.3000 0.9000 3.00 0.6100
SVC (% predicted) <67.72 0.7000 0.9000 7.00 0.8200
FVC (% predicted) <70.34 0.7000 0.9000 7.00 0.8100
FEV1 (% predicted) <60.22 0.7000 0.9000 7.00 0.8300
FEV1/FVC <67.17 0.6000 0.9000 6.00 0.7000
PEF (% predicted) <28.67 0.4000 0.9000 4.00 0.5700

IOS: impulse oscillometry system; TB: tuberculosis; AUC: area under the curve; Z5: total airway impedance; R5: resistance at 5 Hz; R20: resistance at 20 Hz; X5: reactance at 5 Hz; R5-R20: peripheral airway resistance; Fres: resonant frequency; Ax: area of reactance; SVC: slow vital capacity; FVC: forced vital capacity; FEV1: forced expiratory volume in 1 second; PEF: peak expiratory flow.

Table 6.
Levels of inflammatory markers in the study groups
Control (n=10) PTBS (n=10) PTBWS (n=10) p-value
MMP-1 (ng/mL) 2.928 (1.136-5.366) 3.134 (1.847-3.600) 1.115 (0.866-1.915) 0.020*
TGF-β (ng/L) 173.7 (120.2-264.5) 195.3 (147.5-212.6) 141.1 (111.8-150.5) 0.100
INF-γ (ng/mL) 20.62 (17.99-25.80) 14.20 (12.27-17.98) 15.59 (10.22-18.65) 0.102

Values expressed are median with inter-quartile range, analyzed by Kruskal-Wallis test.

* p<0.05 statistically significant.

PTBS: post-tuberculosis with sequelae; PTBWS: post-tuberculosis without sequelae; MMP-1: matrix metalloproteinase-1; TGF-β: transforming growth factor β; INF-γ: interferon γ.

REFERENCES

1. World Health Organization. Global tuberculosis report 2020 [Internet]. Geneva: World Health Organization; 2020 [cited 2021 Feb 8]. Available from: https://www.who.int/publications-detail-redirect/9789240013131.

2. Rachow A, Ivanova O, Wallis R, Charalambous S, Jani I, Bhatt N, et al. TB sequel: incidence, pathogenesis and risk factors of long-term medical and social sequelae of pulmonary TB - a study protocol. BMC Pulm Med 2019;19:4.
crossref pmid pmc
3. Ravimohan S, Kornfeld H, Weissman D, Bisson GP. Tuberculosis and lung damage: from epidemiology to pathophysiology. Eur Respir Rev 2018;27:170077.
crossref pmid pmc
4. Pasipanodya JG, Miller TL, Vecino M, Munguia G, Garmon R, Bae S, et al. Pulmonary impairment after tuberculosis. Chest 2007;131:1817-24.
crossref pmid
5. Yakar HI, Gunen H, Pehlivan E, Aydogan S. The role of tuberculosis in COPD. Int J Chron Obstruct Pulmon Dis 2017;12:323-9.
crossref pmid pmc
6. Irfan M. Post-tuberculosis pulmonary function and noninfectious pulmonary disorders. Int J Mycobacteriol 2016;5 Suppl 1:S57.
crossref pmid
7. Chung KP, Chen JY, Lee CH, Wu HD, Wang JY, Lee LN, et al. Trends and predictors of changes in pulmonary function after treatment for pulmonary tuberculosis. Clinics (Sao Paulo) 2011;66:549-56.
crossref pmid pmc
8. Casarini M, Ameglio F, Alemanno L, Zangrilli P, Mattia P, Paone G, et al. Cytokine levels correlate with a radiologic score in active pulmonary tuberculosis. Am J Respir Crit Care Med 1999;159:143-8.
crossref pmid
9. Subbian S, Tsenova L, Kim MJ, Wainwright HC, Visser A, Bandyopadhyay N, et al. Lesion-specific immune response in granulomas of patients with pulmonary tuberculosis: a pilot study. PLoS One 2015;10:e0132249.
crossref pmid pmc
10. Christine T, Tarigan AP, Ananda FR. The correlation between levels of transforming growth factor-beta with pulmonary fibrosis in post pulmonary tuberculosis in Medan, North Sumatera - Indonesia. Open Access Maced J Med Sci 2019;7:2075-8.
crossref pmid pmc pdf
11. Rhee CK, Yoo KH, Lee JH, Park MJ, Kim WJ, Park YB, et al. Clinical characteristics of patients with tuberculosis-destroyed lung. Int J Tuberc Lung Dis 2013;17:67-75.
crossref pmid
12. Brashier B, Salvi S. Measuring lung function using sound waves: role of the forced oscillation technique and impulse oscillometry system. Breathe (Sheff) 2015;11:57-65.
crossref pmid pmc
13. Bickel S, Popler J, Lesnick B, Eid N. Impulse oscillometry: interpretation and practical applications. Chest 2014;146:841-7.
crossref pmid
14. Graham BL, Steenbruggen I, Miller MR, Barjaktarevic IZ, Cooper BG, Hall GL, et al. Standardization of spirometry 2019 update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am J Respir Crit Care Med 2019;200:e70-88.
crossref pmid pmc
15. Akkara SA, Shah AD, Adalja M, Akkara AG, Rathi A, Shah DN. Pulmonary tuberculosis: the day after. Int J Tuberc Lung Dis 2013;17:810-3.
crossref pmid
16. Santra A, Dutta P, Manjhi R, Pothal S. Clinico-radiologic and spirometric profile of an Indian population with post-tuberculous obstructive airway disease. J Clin Diagn Res 2017;11:OC35-8.
crossref pmid pmc
17. Gupta N, Sachdev A, Gupta D, Gupta S. Oscillometry: the future of estimating pulmonary functions. Karnataka Paediatr J 2020;35:79-87.
crossref
18. Wei X, Shi Z, Cui Y, Mi J, Ma Z, Ren J, et al. Impulse oscillometry system as an alternative diagnostic method for chronic obstructive pulmonary disease. Medicine (Baltimore) 2017;96:e8543.
crossref pmid pmc
19. Elkington PT, Green JA, Emerson JE, Lopez-Pascua LD, Boyle JJ, O’Kane CM, et al. Synergistic up-regulation of epithelial cell matrix metalloproteinase-9 secretion in tuberculosis. Am J Respir Cell Mol Biol 2007;37:431-7.
crossref pmid
20. Ugarte-Gil CA, Elkington P, Gilman RH, Coronel J, Tezera LB, Bernabe-Ortiz A, et al. Induced sputum MMP-1, -3 & -8 concentrations during treatment of tuberculosis. PLoS One 2013;8:e61333.
crossref pmid pmc
21. Singh S, Kubler A, Singh UK, Singh A, Gardiner H, Prasad R, et al. Antimycobacterial drugs modulate immunopathogenic matrix metalloproteinases in a cellular model of pulmonary tuberculosis. Antimicrob Agents Chemother 2014;58:4657-65.
crossref pmid pmc
22. Wynn TA. Integrating mechanisms of pulmonary fibrosis. J Exp Med 2011;208:1339-50.
crossref pmid pmc
23. Yamauchi M, Kinjo T, Parrott G, Miyagi K, Haranaga S, Nakayama Y, et al. Diagnostic performance of serum interferon gamma, matrix metalloproteinases, and periostin measurements for pulmonary tuberculosis in Japanese patients with pneumonia. PLoS One 2020;15:e0227636.
crossref pmid pmc
24. Farr K, Ravindran R, Strnad L, Chang E, Chaisson LH, Yoon C, et al. Diagnostic performance of blood inflammatory markers for tuberculosis screening in people living with HIV. PLoS One 2018;13:e0206119.
crossref pmid pmc
25. Koksal D, Unsal E, Poyraz B, Kaya A, Savas H, Sipit T, et al. The value of serum interferon-gamma level in the differential diagnosis of active and inactive pulmonary tuberculosis. Tuberk Toraks 2006;54:17-21.
pmid
26. Vankayalapati R, Wizel B, Weis SE, Klucar P, Shams H, Samten B, et al. Serum cytokine concentrations do not parallel Mycobacterium tuberculosis-induced cytokine production in patients with tuberculosis. Clin Infect Dis 2003;36:24-8.
crossref pmid
27. Tsao TC, Huang CC, Chiou WK, Yang PY, Hsieh MJ, Tsao KC. Levels of interferon-gamma and interleukin-2 receptor-alpha for bronchoalveolar lavage fluid and serum were correlated with clinical grade and treatment of pulmonary tuberculosis. Int J Tuberc Lung Dis 2002;6:720-7.
pmid
28. Juffermans NP, Verbon A, van Deventer SJ, van Deutekom H, Belisle JT, Ellis ME, et al. Elevated chemokine concentrations in sera of human immunodeficiency virus (HIV)-seropositive and HIV-seronegative patients with tuberculosis: a possible role for mycobacterial lipoarabinomannan. Infect Immun 1999;67:4295-7.
crossref pmid pmc


ABOUT
ARTICLE & TOPICS
Article category

Browse all articles >

Topics

Browse all articles >

BROWSE ARTICLES
FOR CONTRIBUTORS
Editorial Office
101-605, 58, Banpo-daero, Seocho-gu (Seocho-dong, Seocho Art-Xi), Seoul 06652, Korea
Tel: +82-2-575-3825, +82-2-576-5347    Fax: +82-2-572-6683    E-mail: katrdsubmit@lungkorea.org                

Copyright © 2022 by The Korean Academy of Tuberculosis and Respiratory Diseases. All rights reserved.

Developed in M2PI

Close layer
prev next