Tuberculosis (TB) remains a significant global health challenge with a large number of undiagnosed cases. Early detection is crucial for effective treatment and preventing transmission. The study aimed to evaluate the diagnostic accuracy of a simple and inexpensive point-of-care breath analyser (AACTS-3000[I]) for detecting TB. This analyser works by detecting volatile organic compounds (VOCs) emitted by infected cells in exhaled breath. A single-centre pilot study was conducted, comparing the breath analyser to the WHO-recommended TrueNat assay (a rapid molecular test) as the reference standard. 42.51% of the 334 enrolled participants with TB signs/symptoms were positive for mycobacterium tuberculosis on the TrueNat assay. The Tuberculosis Breath Analyser showed high sensitivity (95.7%) and specificity (91.3%) in detecting TB. The area under the ROC curve (AUC) was 0.935, indicating excellent diagnostic performance. The study found that the Tuberculosis Breath analyser demonstrated comparable efficiency to the TrueNat assay in detecting TB. However, the authors emphasise the need for a large, multicenter study to further validate and generalise these findings. The study provides promising initial evidence for the potential of the Tuberculosis breath Analyser as a valuable tool for TB screening. Its simplicity, low cost, and high accuracy make it a potential game-changer in TB diagnosis, especially in resource-limited settings.
This is the abstract of a research paper investigating a new method for tuberculosis (TB) detection using a breath analyser. Here’s a breakdown of the key points:
The Problem:
- Global Impact of TB: Tuberculosis affects a massive portion of the world’s population, with a significant number of infected individuals remaining undiagnosed. This makes the actual number of cases much higher than reported, hindering efforts to control the disease.
- Need for Better Diagnostics: Current TB screening methods are inadequate, particularly in finding infected individuals who are in close contact with diagnosed patients. This is crucial for achieving the Sustainable Development Goals (SDG) target of eliminating TB by 2030.
The Proposed Solution:
- Breath Analyser Technology: The study explores a point-of-care breath analyser (AACTS-3000 [I]) as a potential screening tool for TB. This device detects volatile organic compounds (VOCs) in exhaled breath, which are produced by infected cells.
- Simple and Inexpensive: The breath analyser is highlighted as a simple and low-cost solution, making it potentially more accessible, especially in resource-limited settings.
The Study:
- Pilot Study Design: A single-centre pilot study was conducted to evaluate the accuracy of the breath analyser in diagnosis TB.
- Comparison with Gold Standard: The performance of the breath analyser was compared against the WHO-recommended TrueNat assay, a rapid molecular test considered the reference standard for TB diagnosis in this study.
- Participants: 334 participants showing signs and symptoms of TB were enrolled in the study.
- Results: Out of the participants, 42.51% tested positive for TB using the TrueNat assay. The Breath analyser showed high sensitivity (95.7%) and specificity (91.3%), with an area under the receiver operating characteristic curve (ROC) of 0.935. This indicates good diagnostic accuracy.
Conclusions:
- Promising Results: The breath analyser demonstrated high sensitivity and specificity comparable to the TrueNat assay, suggesting its potential as an effective TB screening tool.
- Need for Further Research: The authors emphasise the need for larger, multi-centre studies to validate these findings and confirm the effectiveness of the breath analyser in diverse populations and settings.
Keywords:
- VOCs: Volatile Organic Compounds, the chemical markers detected by the breath analyser.
- Diagnostic Accuracy Study: Indicates the type of research conducted to evaluate the performance of a diagnostic test.
- Breath Testing: Refers to the use of exhaled breath as a source of diagnostic information.
- Mycobacterium tuberculosis: The bacterium that causes tuberculosis.
In, essence, this abstract presents a promising new tool for TB screening that is fast, non-invasive and potentially more accessible than current methods. However, further research is necessary to confirm these initial findings and establish its role in TB control programs.
TB Burden:
Leading Infectious Killer: TB remains a major global health threat, particularly in middle-income countries.
High Incidence: In 2021, an estimated 10.6 million people developed TB, with India accounting for a staggering 28% of global cases.
Underdiagnosis: A significant challenge is that roughly one in three TB patients remain undiagnosed, leading to a hidden spread of the disease.
Factors Hindering Diagnosis: The reasons for underdiagnosis are multifaceted, including Lack of awareness and resources, Poor infrastructure, Inadequate reporting, Societal issues like poverty, malnutrition, and stigma.
India’s Ambitious Target: India aims to eliminate TB by 2025, ahead of the global SDG target of 2030. However, achieving this goal seems unlikely with current detection and treatment rates.
Impact of COVID-19:
Setback of TB Control: The COVID-19 pandemic significantly disrupted TB elimination efforts.
Decline in Case Reporting: There was an 18% drop in reported TB cases, reverting back to 2012 levels, much lower than anticipated.
Diagnostic Gaps in India: India faced a substantial diagnostic gap, with limited use of rapid tests and bacteriological confirmation.
Reasons for Testing Gaps: Shortage of healthcare professionals, Lack of knowledge about TB diagnostic tools, Stigma and confidentially concerns, Suboptimal involvement of private healthcare facilities.
New Approach: Volatile Organic Compounds (VOCs):
Need for Efficient Techniques: The paper highlights the ongoing need for more reliable and efficient TB diagnostic methods.
VOCs as Potential Biomarkers: The research explores the analysis of VOCs in exhaled breath as a non-invasive diagnostic technique.
Rationale for VOC Analysis: TB infection alters VOCs in breath due to the activity of Mycobacteria and oxidative stress, Different Mycobacteria species produce unique VOC metabolites, creating chemical fingerprints.
Gas Chromatography as Gold Standard: Gas Chromatography (GC) is considered the gold standard for VOC detection and analysis.
Potential of VOCs: VOCs shows promise as biomarkers for various diseases, including respiratory illnesses like TB, offering rapid, cost-effective, and non-invasive diagnosis.
Preliminary Studies: Initial studies suggests the diagnostic potential of VOCs for TB.
A major concern is the high number of undiagnosed TB cases. This is attributed to various factors, including lack of awareness, limited resources, poor infrastructure, poverty, undernourishment, social stigma, and inadequate healthcare access. India bears a disproportionate burden of TB, accounting for a significant portion of global cases. The COVID-19 pandemic has severely disrupted TB control programs, leading to a decline in case detection and further exacerbating the issue of undiagnosed cases. The introduction points out significant diagnostic gaps in India, such as a low proportion of patients being tested with rapid tests and a lack of bacteriological confirmation. The need for more reliable and efficient TB diagnostic. techniques is emphasised. The introduction introduces breath analysis as a promising non-invasive approach for TB detection. It explains that Mycobacterial infection alters the volatile organic compounds (VOCs) in exhaled breath, which can potentially serve as biomarkers for TB. The primary objective of the study of the study is to evaluate the diagnostic accuracy of a novel point-of-care breath analyser (AACTS-3000[I]) compared to the gold standard PCR-based TRUENAT/CBNAAT test. The study will assess sensitivity, specificity, positive predictive value, and negative predictive value of the breath analyser. Additionally the study will explore socio-behavioural and epidemiological correlates that may influence test results. The introduction effectively sets the stage for the research by highlighting the critical need for improved TB diagnostics, particularly in India. It introduces the concept of breath analysis for TB detection and outlines the study’s objectives to evaluate the diagnostic performance of a novel breath analyser.
Sample Size:
- The study recruited a convenient sample of 334 consecutive TB suspects.
- These individuals were recruited from the pulmonology OPD (Outpatient Department) of the Government Doon Medical College.
- The recruitment period was between July to December 2022.
Study Tools:
- Socio-demographic Data: A study instrument was used to collect socio-demographic information about the participants, including age, gender, marital status, occupation, religion, ethnicity, and socio-economic status.
- AACTS Breath Analyser: This was the index test used in the study. Its described as a simple, rapid, and in-vitro diagnostic test designed to improve accessibility and reduce the need for more expensive confirmatory tests. Its intended for use in adults and children with suspected TB or high-risk factors for TB.
- TrueNat/CBNAAT Assay: This PCR-based test served as the gold standard (reference test) for TB diagnosis in the study.
Inclusion Criteria:
Participants aged 10 years and above were included. Individuals were included if they had symptoms suggestive of pulmonary TB (e.g, cough, sputum production, night sweats, weight loss, hemoptysis). Individuals with a history of recent exposure to TB infection were included. Participants with chest X-ray abnormalities consistent with active pulmonary TB were included. All participants provided informed written consent. Participants with HIV were included.
Exclusive Criteria:
Pregnant women were excluded. Individuals who were lost to follow-up were excluded. Participants with a previous history of tuberculosis were excluded. Individuals with invalid breath measurements were excluded.
Implementation Plan:
All TB suspects identified at the Pulmonology OPD during the study period were recruited. Eligible suspects were offered the index test (AACTS3000 Breath Analyser) after obtaining informed consent. All participants underwent the gold standard diagnostic test (TrueNat/CBNAAT).TrueNat-positive cases were considered reference positive (TB cases). TrueNat-negative cases were considered healthy controls. All TB cases were treated according to national TB treatment guidelines. HIV-infected individuals were started on antiretroviral therapy within 3 weeks of TB treatment initiation.
Point-of-Care (POC) Breath Test:
- Initial Pool: 408 potentially eligible participants were initially identified.
- Exclusions: 74 participants were excluded due to Lost to Follow-up (17 participants were lost to follow-up during the study) and Previous History of TB (57 participants had a previous history of tuberculosis, which excluded them from the study.
- Eligible Participants: After exclusions, 334 participants were deemed eligible for the study.
- Breath Test: 150 participants tested positive on the breath test (index test). 184 participants tested negative on the breath test.
- TrueNat Test (Gold Standard): All 334 participants underwent the TrueNat test (reference standard).
Final Diagnosis: 133 participants were diagnosed with TB (target condition present). This includes both those who tested positive on the breath test and some who tested negative but were positive on the TrueNat test. 201 participants were diagnosed as not having TB (target condition absent). This includes those who tested negative on the breath test and some who tested positive on the breath test but negative on the TrueNat test.
Characteristics of Human Subjects:
- The mean age of the study participants was 35.8 years with a standard deviation of 15.2. 187 (55.99%) were males, and 147(44.01%) were females. 139 (41.6%) were diagnosed with TB (positive), while 195(58.4%) were diagnosed as not having TB (negative). 186 (55.68%) participants had no lesions on their chest X-ray. 103(30.83%) participants had lesions present on their chest X-ray. 45 (13.47%) participants did not have a chest X-ray performed.
- HIV Status: 21(6.28%) participants were HIV positive. 212 (63.47%) participants were HIV negative. 101 (30.23%) participants had unknown HIV status.
- Diabetic Status: 21(6.28%) participants were diabetic. 209 (62.57%) participants were not diabetic. 104 (31.13%) participants had unknown diabetic status.
- Smoker Status: 34(10.17%) participants were current smokers. 52(15.56%) participants were past smokers. 248(74.25%) participants were never smokers.
- Disease Status: 133 participants were correctly identified as having TB (True Positives – TP). 6 participants were incorrectly identified as not having TB (False Negatives – FN). 17 participants were incorrectly identified as having TB (False Positives – FP). 178 participants were correctly identified as not having TB (True Negatives – TN).
Performance Metrics:
- Sensitivity: 95.7% (95% CI: 90.8-94.8%) The ability of the test to correctly identify individuals with TB.
- Specificity: 91.3% (95% CI: 86.45-94.8%) The ability of the test to correctly identify individuals without TB.
- Positive Predictive Value (PPV): 88.7% The probability that an individual with a positive test result actually has TB.
- Negative Predictive Value (NPV): 96.7% The probability that an individual with a negative test result does not have TB.
- Area under the ROC Curve (AUC): 0.935 A measure of the overall accuracy of the test, with values closer to 1 indicating better performance.
Interpretation of Results:
The Tuberculosis Breath Analyser demonstrated high sensitivity and specificity in detecting TB. The AUC of 0.935 indicates excellent discriminative ability of the test. The sub-analysis showed that the test’s performance was relatively consistent across different age groups, with some variations observed.
Limitations:
The study acknowledges potential limitations, such as potential interference from environmental factors (e.g, smoking, diet, other patient habits) that could influence VOCs and affect test accuracy. Future research could explore the use of neural network models to identify deeper association between VOC patterns and TB, which may improve risk stratification.
Result of Diagnostic Accuracy Tests:
This table provides the diagnostic accuracy metrics of the Tuberculosis Breath Analyser across different age groups. The metrics include:
The ability of the test to correctly identify individuals with TB. The ability of the test to correctly identify individuals without TB. The probability that an individual with a positive test result actually has TB. The probability that an individual with a negative test result does not have TB. A measure of the overall accuracy of the test.
Age Group Results:
Total:
Sensitivity: 95.7%
Specificity: 91.3%
PPV: 88.7%
NPV: 96.7%
AUC: 0.935
Age Group 15-29:
Sensitivity: 97.1%
Specificity: 89.7%
PPV: 89.5%
NPV: 97.2%
AUC: 0.934
Age Group 30-44:
Sensitivity: 89.2%
Specificity: 89.7%
PPV: 84.6%
NPV: 92.9%
AUC: 0.894
Age Group 45-59:
Sensitivity: 100%
Specificity: 95.1%
PPV: 89.5%
NPV: 100%
AUC: 0.976
Interpretation of Age Group Results:
The overall performance of the breath analyser was high across all age groups. The highest sensitivity and AUC were observed in the 15-29 and 45-59 age groups. The lowest sensitivity and AUC were observed in the 30-44 age group.
Spectroscopic Display/Topographic Map
The x-axis represents retention time, and y-axis represents drift time. The colours in the map may represent different intensities of volatile organic compounds (VOCs) detected in the breath samples. The pattern of colours can potentially be used to identify unique signatures associated with TB infection.
Discussion:
The discussion section likely delves into the implications of the study findings. It may discuss the strengths and limitations of the breath analyser as a diagnostic tool for TB. It may also explore the potential of using breath analysis for risk stratification and early detection of TB.
The Tuberculosis Breath Analyser showed promising diagnostic accuracy in detecting TB across different age groups. The study highlights the potential of breath analysis as a non-invasive and rapid tool for TB screening. Further research is needed to validate these findings in larger populations and to investigate the impact of environmental factors on test performance.
Key Points:
Breath Analysis for TB Diagnosis: It highlights the advantages of breath analysis as a potential tool for TB diagnosis. These advantages include being point-of-care, non-invasive, reagent-free, and suitable for low-resource settings.
Breath Analyser Technology: The study used a Breath Analyser equipped with a fast ion mobility spectrometer (IMS). This device analyses volatile organic compounds (VOCs) in exhaled breath to detect TB.
Reference Standard: The TrueNat assay, a WHO-recommended rapid molecular test, served as the reference standard for TB diagnosis.
Study Findings: The Tuberculosis Breath Analyser demonstrated high diagnostic accuracy, with an overall sensitivity of 95.7% and specificity of 91.3%. The study compared the breath analyser to the TrueNat assay and found that it showed considerable reliability.
COVID-19 Impact: The COVID-19 pandemic has significantly impacted TB screening and diagnosis, emphasising the need for accurate triage tests at the initial point of contact.
Other Triage Tests: The text mentions other emerging triage tests for TB, such as computer-aided detection of X-ray-biomarkers-based assays and e-nose technology.
Comparison with Previous Studies: The study compares its findings with results from previous research on breath analysis for TB diagnosis, showing consistent high sensitivity and specificity across different studies.
Limitations: The study acknowledges limitations, such as being a single-centre pilot study with a limited sample size.
The information highlights the potential of breath analysis as a promising non-invasive tool for TB diagnosis. The study demonstrates high diagnostic accuracy of the Tuberculosis Breath Analyser, supporting its potential as a valuable tool for TB screening and diagnosis, especially in resource-limited settings. The text emphasises the need for further research with larger and more diverse populations to validate the findings. It also suggests exploring the use of breath analysis for detecting atypical mycobacteria.
Conclusions:
High Diagnostic Accuracy: The study concluded that the Tuberculosis Breath Analyser demonstrated high diagnostic accuracy for detecting TB.
Potential as a Point-of-Care (POC) Triage Test: The researchers suggest that the breath analyser has the potential to be used as a POC triage test for TB. This means it could be used to quickly identify individuals who are likely to have TB, allowing for prompt referral for further testing and treatment.
Need for Further Research: The study emphasises the need for further multicenter studies with larger sample sizes to validate the findings and confirm the breath analyser’s potential as a reliable diagnostic tool. These future studies should ideally be conducted in point-of-care settings (such as primary care centres) and compare the breath analyser’s results with a gold standard procedure like microbial culture.
Limitations:
Limited Sample Size and Single-Centre Study: The study acknowledges that being a single-centre pilot study with a limited sample size may limit the generalisability of the findings to a larger population.
Confounding Factors: The study mentions that comorbidities (other health conditions), age-related factors, and other risk factors could potentially confound the results.
Despite these limitations, the study concludes that the breath analyser shows promise as a valuable screening tool for TB, especially in resource-limited settings with high TB prevalence. The information presented highlights the potential of breath analysis as a non-invasive and rapid screening tool for TB diagnosis. The study provides promising initial results, but further research is needed to confirm its clinical utility and establish its role in TB control programs.
Author Contributions:
Specifies the roles and contributions of each author to the research.
M.B. and A.A: Conceived the study (came up with the initial idea and design).
A.A., D.R., and R.s.: Developed the methodology (specific procedures and techniques used).
A.A., A.G., and N.J: Were involved in data acquisition (collecting the data for the study).
M.B., D.R., and R.S.: Wrote the original draft of the manuscript.
A.A., A.G., and N.J.: Reviewed and edited the manuscript.
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