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| Name | Class |
|---|---|
| The First Affiliated Hospital of Guangzhou Medical University | OTHER |
| First People's Hospital of Foshan | OTHER |
| Sichuan Cancer Hospital and Research Institute | OTHER |
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The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound (VOC) marker molecules. This model aims to accurately diagnose mutiple pulmonary diseases. The primary objectives it strives to accomplish are:
This is a prospective, cross-sectional, observational cohort study aimed at recruiting 10,000 participants with multiple pulmonary disease, including lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), bronchitis, pulmonary fibrosis, pulmonary embolism, pulmonary arterial hypertension, tuberculosis, lung abscess, emphysema, radioactive lung injury, cystic fibrosis of the lung, Bronchial Asthma, Bronchiectasis, interstitial lung disease (ILD), preserved ratio impaired spirometry (PRISm) etc . Exhaled breath samples from these participants will be collected and analyzed using Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system. Upon obtaining the μGC-PID results, a comprehensive evaluation of the diagnostic capabilities of exhaled breath samples in differentiating various pulmonary diseases will be performed, leveraging clinical diagnostic results, CT examination data, and clinical data.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| pulmonary disease | Individuals with abnormalities in lung CT imaging and clinically diagnosed with lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), bronchitis, pulmonary fibrosis, pulmonary embolism, pulmonary arterial hypertension, tuberculosis, lung abscess, emphysema, radioactive lung injury, cystic fibrosis of the lung, Bronchial Asthma, Bronchiectasis, interstitial lung disease (ILD), preserved ratio impaired spirometry (PRISm) etc . |
| |
| normal individual | Individuals with no abnormalities detected in lung CT imaging. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system | Other | Exhaled breath samples from these participants will be collected and analyzed to detect volatile organic compound molecules in human exhaled breath by GC-MS and μGC-PID |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in the diagnosis of several common pulmonary diseases. | The diagnostic performance of the exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model will be compared with clinical diagnosis and CT/LDCT diagnosis, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). | 2 years |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in the diagnosis of more pulmonary diseases. | The diagnostic performance of the exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model will be compared with clinical diagnosis and CT/LDCT diagnosis, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). |
| Measure | Description | Time Frame |
|---|---|---|
| Establish an exhaled breath VOC model for predicting specific gene mutations in some lung diseases. | Establish an exhaled breath VOC model for predicting specific gene mutations in some lung diseases. And evaluate the prediction accuracy by comparing the results of specific gene testing | 2 years |
Inclusion Criteria:
Exclusion Criteria:
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Patients with abnormal lung CT images within the past six months, including lung cancer, lung infection, chronic obstructive pulmonary disease (COPD), bronchitis, pulmonary fibrosis, pulmonary embolism, pulmonary arterial hypertension, tuberculosis, lung abscess, emphysema, radioactive lung injury, cystic fibrosis of the lung, Bronchial Asthma, Bronchiectasis, interstitial lung disease (ILD), preserved ratio impaired spirometry (PRISm), etc .
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Hengrui Liang, MD | Contact | +86 15625064712 | hengrui_liang@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Jianxing He, MD | The First Affiliated Hospital of Guangzhou Medical University | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The First Affiliated Hospital of Guangzhou Medical University | Recruiting | Guangzhou | Guangdong | 510140 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32526187 | Background | GBD Chronic Respiratory Disease Collaborators. Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Respir Med. 2020 Jun;8(6):585-596. doi: 10.1016/S2213-2600(20)30105-3. | |
| 33374433 | Background | Ratiu IA, Ligor T, Bocos-Bintintan V, Mayhew CA, Buszewski B. Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD. J Clin Med. 2020 Dec 24;10(1):32. doi: 10.3390/jcm10010032. |
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| Liwan District Central Hospital |
| UNKNOWN |
| Shanghai Chest Hospital | OTHER |
| Peking Union Medical College Hospital | OTHER |
| Guangzhou Development Zone Hospital | UNKNOWN |
| Huangpu District Hongshan Street Community Health Service Center | UNKNOWN |
| Huangpu District Chinese Medicine Hospital | UNKNOWN |
| Fifth Affiliated Hospital of Guangzhou Medical University | OTHER |
| Huangpu District Jiufo Street Community Health Service Center | UNKNOWN |
| Huangpu District Xinlong Town Central Hospital | UNKNOWN |
| Huangpu District Yonghe Street Community Health Service Center | UNKNOWN |
| Huangpu District Lianhe Street Second Community Health Service Center | UNKNOWN |
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Volatile Organic Compounds in Human Exhaled Breath
|
| 2 years |
| 23259710 | Background | van de Kant KD, van der Sande LJ, Jobsis Q, van Schayck OC, Dompeling E. Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review. Respir Res. 2012 Dec 21;13(1):117. doi: 10.1186/1465-9921-13-117. |
| 36690293 | Background | Wang J, Janson C, Gislason T, Gunnbjornsdottir M, Jogi R, Orru H, Norback D. Volatile organic compounds (VOC) in homes associated with asthma and lung function among adults in Northern Europe. Environ Pollut. 2023 Mar 15;321:121103. doi: 10.1016/j.envpol.2023.121103. Epub 2023 Jan 21. |
| 34415806 | Background | V A B, Subramoniam M, Mathew L. Noninvasive detection of COPD and Lung Cancer through breath analysis using MOS Sensor array based e-nose. Expert Rev Mol Diagn. 2021 Nov;21(11):1223-1233. doi: 10.1080/14737159.2021.1971079. Epub 2021 Aug 27. |
| ID | Term |
|---|---|
| D008175 | Lung Neoplasms |
| D029424 | Pulmonary Disease, Chronic Obstructive |
| D001991 | Bronchitis |
| D011658 | Pulmonary Fibrosis |
| D011655 | Pulmonary Embolism |
| D000081029 | Pulmonary Arterial Hypertension |
| D014397 | Tuberculosis, Pulmonary |
| D008169 | Lung Abscess |
| D004646 | Emphysema |
| D055370 | Lung Injury |
| D003550 | Cystic Fibrosis |
| D001249 | Asthma |
| D001987 | Bronchiectasis |
| D017563 | Lung Diseases, Interstitial |
| D008171 | Lung Diseases |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D012140 | Respiratory Tract Diseases |
| D008173 | Lung Diseases, Obstructive |
| D002908 | Chronic Disease |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
| D001982 | Bronchial Diseases |
| D005355 | Fibrosis |
| D004617 | Embolism |
| D016769 | Embolism and Thrombosis |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D006976 | Hypertension, Pulmonary |
| D014376 | Tuberculosis |
| D009164 | Mycobacterium Infections |
| D000193 | Actinomycetales Infections |
| D016908 | Gram-Positive Bacterial Infections |
| D001424 | Bacterial Infections |
| D001423 | Bacterial Infections and Mycoses |
| D000038 | Abscess |
| D013492 | Suppuration |
| D013898 | Thoracic Injuries |
| D014947 | Wounds and Injuries |
| D010182 | Pancreatic Diseases |
| D004066 | Digestive System Diseases |
| D030342 | Genetic Diseases, Inborn |
| D009358 | Congenital, Hereditary, and Neonatal Diseases and Abnormalities |
| D007232 | Infant, Newborn, Diseases |
| D012130 | Respiratory Hypersensitivity |
| D006969 | Hypersensitivity, Immediate |
| D006967 | Hypersensitivity |
| D007154 | Immune System Diseases |
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| ID | Term |
|---|---|
| D016503 | Drug Delivery Systems |
| ID | Term |
|---|---|
| D004358 | Drug Therapy |
| D013812 | Therapeutics |
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