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    Misdiagnosis in Occupational and Environmental Medicine

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    ν•™μœ„λ…Όλ¬Έ(박사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : λ³΄κ±΄λŒ€ν•™μ› ν™˜κ²½λ³΄κ±΄ν•™κ³Ό, 2021.8. 백도λͺ….Introduction: Even though the topic, misdiagnosis in general medicine, was dealt with in many previous studies, the topic, misdiagnosis in occupational and environmental medicine was not dealt with properly and completely in previous literature. This study aims 4 objectives: (β…°) The first objective is to build up a conceptual serial diagnostic framework for occupational diseases (ODs) and environmental diseases (EDs). (β…±) The second objective is to develop a classification framework for the causes of misdiagnoses in occupational and environmental medicine (OEM). (β…²) The third objective is to conduct a scoping review for delayed and wrong diagnoses in OEM. (β…΅) The final objective is to estimate the magnitude of missed nonfatal occupational injury reporting using the International Labor Organization (ILO) occupational injury datasets. Conceptual diagnostic framework and classification framework: With the 2 types of cognitive functions and the role of each sub-components of the social system considered, a conceptual serial diagnostic framework was devised. With reference to misdiagnosis articles in general medicine and the unique features of OEM considered, the causation model with 6 serial steps was devised. Scoping review for wrong diagnosis (including delayed diagnosis): A total of 79 articles were included in the scoping review. For clinical specialty, pulmonology (30 articles) and dermatology or allergy (13 articles) specialty were most frequent. For each disease, occupational and environmental interstitial lung diseases (ILD), misdiagnosed as sarcoidosis (8 articles), and other lung diseases (8 articles) were most frequent. For the causation model, the first step, Knowledge base, was the most vulnerable step (42 articles). For reported articles, the frequency of false-negative (55 articles) outnumbered the frequency of false-positive (15 articles). Original research for missed occupational injury reporting: The ratio of discovered nonfatal occupational injuries to total nonfatal occupational injuries was 0.33 (95% CI 0.28-0.40) for Convention 029, 0.13 (95% CI 0.12-0.15) for Convention 105, and 0.48 (95% CI 0.42-0.54) for Convention 087. In other words, about 52 to 87% of nonfatal occupational injuries are not being reported. Overall discussion: Without the established criteria for the probability of causation, compensation disputes surrounding the OD or ED case would occur. The clarification of the concept between the probability of causation and relative risk is needed. According to the exposure assessment method and applied biological model, the dose-response relationship can be markedly different. Imperfect exposure assessment is another essential problem. OEM education and training for treating physicians and understanding the intentional behaviors of stakeholders are important. Previous literature about the causes of missed nonfatal occupational injury reporting due to employers, employees, and the government, respectively, was discussed. The role of the occupational health and safety system of the society in reducing the missed nonfatal occupational injury reporting was discussed.μ„œλ‘ : 비둝 μ΄μ „κΉŒμ§€μ˜ λ§Žμ€ μ—°κ΅¬λ“€μ—μ„œ 일반 μ˜ν•™ κ΄€μ μ—μ„œμ˜ μ˜€μ§„μ€ 많이 λ‹€λ£¨μ–΄μ‘Œμ§€λ§Œ μ§μ—…ν™˜κ²½μ˜ν•™μ—μ„œμ˜ μ˜€μ§„μ€ μ œλŒ€λ‘œ 닀루어지지 μ•Šμ•˜μŠ΅λ‹ˆλ‹€. 이 μ—°κ΅¬μ˜ λͺ©ν‘œλŠ” 4κ°€μ§€μž…λ‹ˆλ‹€. μ²«μ§ΈλŠ” 직업성 μ§ˆλ³‘κ³Ό ν™˜κ²½μ„± μ§ˆλ³‘μ˜ 진단에 κ΄€ν•œ 순차적인 κ°œλ…μ  틀을 μ •λ¦½ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€. 두 λ²ˆμ§ΈλŠ” μ§μ—…ν™˜κ²½μ˜ν•™μ—μ„œμ˜ μ˜€μ§„μ„ κ·Έ 원인에 따라 λΆ„λ₯˜ν•˜λŠ” κ°œλ…μ  틀을 μ •λ¦½ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€. μ„Έ λ²ˆμ§ΈλŠ” μ§μ—…ν™˜κ²½μ˜ν•™μ—μ„œμ˜ μ§€μ—°λœ 진단과 잘λͺ»λœ 진단에 κ΄€ν•œ μ£Όμ œλ²”μœ„ λ¬Έν—Œκ³ μ°°μ„ μˆ˜ν–‰ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€. λ„€ λ²ˆμ§ΈλŠ” λΉ„μΉ˜λͺ…적인 직업성 μ†μƒμ˜ λˆ„λ½ 규λͺ¨λ₯Ό 세계 노동 기ꡬ 직업성 손상 데이터λ₯Ό μ‚¬μš©ν•˜μ—¬ μΆ”μ •ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€. 순차적인 μ§„λ‹¨μ˜ κ°œλ…μ  ν‹€ 및 원인 λΆ„λ₯˜μ˜ κ°œλ…μ  ν‹€: 인간 인지 κ³Όμ •μ˜ 2가지 μ’…λ₯˜ 및 μ‚¬νšŒ μ‹œμŠ€ν…œ μ„ΈλΆ€ ꡬ성 μš”μ†Œμ˜ 각 역할에 따라 순차적인 μ§„λ‹¨μ˜ κ°œλ…μ  틀이 μ •λ¦½λ˜μ—ˆμŠ΅λ‹ˆλ‹€. 일반 μ˜ν•™μ—μ„œμ˜ μ˜€μ§„μ— κ΄€ν•œ λ¬Έν—Œλ“€κ³Ό μ§μ—…ν™˜κ²½μ˜ν•™μ˜ λ…νŠΉν•œ νŠΉμ„±μ„ κ³ λ €ν•˜μ—¬, μ§„λ‹¨μ˜ 각 μ„ΈλΆ€κ³Όμ • 6개 단계에 따라 μ˜€μ§„ 원인 λΆ„λ₯˜μ˜ 틀이 μ •λ¦½λ˜μ—ˆμŠ΅λ‹ˆλ‹€. 잘λͺ»λœ 진단에 λŒ€ν•œ 주제 λ²”μœ„ λ¬Έν—Œ κ³ μ°° (μ§€μ—°λœ 진단을 포함): 총 79개의 λ¬Έν—Œμ΄ μ£Όμ œλ²”μœ„ λ¬Έν—Œκ³ μ°°μ— ν¬ν•¨λ˜μ—ˆμŠ΅λ‹ˆλ‹€. μž„μƒ κ³Όλͺ©μ— λ”°λΌμ„œ λΆ„λ₯˜ν•˜λ©΄ ν˜Έν‘κΈ°λ‚΄κ³Όκ°€ 30개 λ¬Έν—ŒμœΌλ‘œ κ°€μž₯ λ§Žμ•˜κ³ , λ‹€μŒμ΄ 피뢀과와 μ•ŒλŸ¬μ§€λ‚΄κ³Όλ‘œ 13개의 λ¬Έν—Œλ³΄κ³ κ°€ μžˆμ—ˆμŠ΅λ‹ˆλ‹€. κ°œλ³„ μ§ˆλ³‘μ— 따라 λΆ„λ₯˜ν•˜λ©΄ μœ μœ‘μ’…μ¦ (8개 λ¬Έν—Œ) 및 λ‹€λ₯Έ νμ§ˆν™˜ (8개 λ¬Έν—Œ)으둜 잘λͺ» μ§„λ‹¨λœ 직업성 λ˜λŠ” ν™˜κ²½μ„± κ°„μ§ˆμ„± νμ§ˆν™˜μ΄ κ°€μž₯ λ§Žμ•˜μŠ΅λ‹ˆλ‹€. μ•žμ„œ μ •λ¦½ν•œ 원인 λΆ„λ₯˜μ˜ κ°œλ…μ  틀에 λ”°λ₯΄λ©΄ (causation model), 첫 번째 단계인 β€˜κΈ°λ°˜ 지식 (knowledge base)’ 단계가 κ°€μž₯ μ˜€μ§„μ΄ 많이 μΌμ–΄λ‚œ λ‹¨κ³„μ˜€μŠ΅λ‹ˆλ‹€ (42개 λ¬Έν—Œ). μ΄λ ‡κ²Œ μˆ˜μ§‘λœ λ¬Έν—Œμ„ 기반으둜 ν–ˆμ„ λ•Œ, μœ„μŒμ„±μ˜ λΉˆλ„κ°€ 55개 λ¬Έν—ŒμœΌλ‘œ μœ„μ–‘μ„±μ˜ λ¬Έν—Œ λΉˆλ„μΈ 15개 λ¬Έν—Œλ³΄λ‹€ 훨씬 λ§Žμ•˜μŠ΅λ‹ˆλ‹€. λΉ„μΉ˜λͺ…적 직업성 μ†μƒμ˜ λˆ„λ½ 규λͺ¨μ— κ΄€ν•œ 원저: λΉ„μΉ˜λͺ…적인 직업성 μ†μƒμ˜ 총 λΉˆλ„μˆ˜μ—μ„œ 보고된 μΌ€μ΄μŠ€μ˜ λΆ„μœ¨μ€ ꡭ제 노동 기ꡬ 29번 쑰약에 λŒ€ν•΄μ„œλŠ” 0.33 (95% 신뒰ꡬ간 0.28-0.40) μ΄μ—ˆκ³ , ꡭ제 노동 기ꡬ 105번 쑰약에 λŒ€ν•΄μ„œλŠ” 0.13 (95% 신뒰ꡬ간 0.12-0.15) μ˜€μœΌλ©°, ꡭ제 노동 기ꡬ 87번 쑰약에 λŒ€ν•΄μ„œλŠ” 0.48 (95% 신뒰ꡬ간 0.42-0.54) μ˜€μŠ΅λ‹ˆλ‹€. λ‹€λ₯Έ 말둜 ν•˜λ©΄ 총 λΉ„μΉ˜λͺ…적 직업성 μ†μƒμ˜ 52~87%κ°€ λ³΄κ³ λ˜μ§€ μ•Šκ³  λˆ„λ½λ˜κ³  μžˆμŒμ„ μΆ”μ •ν•˜μ˜€μŠ΅λ‹ˆλ‹€. μ „λ°˜μ  κ³ μ°°: 인과 ν™•λ₯  (probability of causation)에 λŒ€ν•œ ν™•λ¦½λœ 기쀀이 μ—†λ‹€λ©΄, 직업성 μ§ˆλ³‘κ³Ό ν™˜κ²½μ„± μ§ˆλ³‘μ„ λ‘˜λŸ¬μ‹Ό 보상에 κ΄€ν•œ λΆ„μŸμ΄ λ°œμƒν•  여지가 λ†’μŠ΅λ‹ˆλ‹€. 인과 ν™•λ₯  (probability of causation)κ³Ό μƒλŒ€μœ„ν—˜λ„ (relative risk)의 μ •μ˜μ— λŒ€ν•œ λΆ„λͺ…ν•œ ꡬ뢄이 ν•„μš”ν•©λ‹ˆλ‹€. λ…ΈμΆœ ν‰κ°€μ˜ 방법과 적용된 생물학적 λͺ¨λΈμ— 따라 μš©λŸ‰-λ°˜μ‘ 관계가 μœ μ˜λ―Έν•˜κ²Œ λ‹¬λΌμ§ˆ 수 μžˆμŠ΅λ‹ˆλ‹€. λΆˆμ™„μ „ν•œ λ…ΈμΆœν‰κ°€λŠ” 또 λ‹€λ₯Έ μ€‘μš”ν•œ μ˜€μ§„μ˜ μ›μΈμž…λ‹ˆλ‹€. μ§μ—…ν™˜κ²½μ˜ν•™μ— λŒ€ν•œ ꡐ윑과 수련이 μ˜μ‚¬ μ–‘μ„± κ³Όμ •μ—μ„œ ν•„μˆ˜μ μ΄λ©°, 각 μ΄ν•΄κ΄€κ³„μžμ˜ μ˜λ„μ μΈ 행동도 μΆ©λΆ„νžˆ κ³ λ €λ˜μ–΄μ•Ό ν•©λ‹ˆλ‹€. λ§ˆμ§€λ§‰ 원저 뢀뢄에 λŒ€ν•΄μ„œλŠ” λΉ„μΉ˜λͺ…적 직업성 손상이 λˆ„λ½λ˜λŠ” 원인에 λŒ€ν•œ μ„ ν–‰ λ¬Έν—Œλ“€μ˜ 뢄석을 μ œμ‹œν•˜μ˜€λŠ”λ°, 고용주, λ…Έλ™μž, 그리고 μ •λΆ€ μΈ‘μ—μ„œ κΈ°μΈν•œ 원인을 각각 μš”μ•½ μ œμ‹œν•˜μ˜€μŠ΅λ‹ˆλ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ ν•œ μ‚¬νšŒμ—μ„œ λˆ„λ½λ˜λŠ” λΉ„μΉ˜λͺ…적 직업성 μ†μƒμ˜ λΆ„μœ¨μ„ 쀄이기 μœ„ν•œ 직업 건강 및 μ•ˆμ „ μ‹œμŠ€ν…œμ˜ 역할이 κ°•μ‘°λ˜μ—ˆμŠ΅λ‹ˆλ‹€.1. Introduction 5 1.1. Misdiagnosis in general medicine 5 1.2. Misdiagnosis in Occupational and Environmental Medicine 8 1.3. System perspective in OEM 9 1.4. Overall scope of this study 10 1.5. The rationale for the estimation of missed OIs using the ILO OI datasets 11 1.6. The objective of this study 13 2-1. Methods and results: theoretical reviews 16 2.1. A conceptual serial diagnostic framework in OEM 16 2.2. A classification framework for the causes of misdiagnoses in OEM 21 2.3. System perspective model in OEM 24 2-2. Methods: a scoping review 26 2.4. A scoping review for misdiagnosis in OEM 26 2-3. Method: an original research 28 2.5. The estimation of the magnitude of missed nonfatal occupational injury reporting 28 3-1. Results: a scoping review 34 3.1. A scoping review for misdiagnosis in OEM 34 3-2. Results: an original research 49 3.2. The estimation of the magnitude of missed nonfatal occupational injury reporting 49 4-1. General discussion 59 4-2. Discussion: a scoping review 61 4.1. β€˜Medical misdiagnosis’ versus β€˜Causal misdiagnosis’: the probability of causation 61 4.2. The confusion between the probability of causation and rate fraction (attributable fraction) 62 4.3. Dose-response relationship and causal inference in OEM 63 4.4. Misdiagnosis in general medicine versus misdiagnosis in OEM 65 4.5. The role of education and training for treating physicians 65 4.6. Intentional behaviors of stakeholders 67 4.7. Risk of bias: case report and case series studies 67 4.8. Other limitations of this study 68 4-3. Discussion: an original research 70 4.9. Causes due to employers, employees, and the government, respectively 70 4.10. The role of occupational health and safety system of the society 71 4.11. Limitations 72 5. Conclusion 74 References 76 Abstract in Korean 93 Disclosure 95λ°•

    κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό ν™˜μžμ—μ„œ λ°”μ΄μ˜€λ§ˆμ»€μ™€ 폐 λ³‘λ³€μ˜ μ—°κ΄€μ„±

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    ν•™μœ„λ…Όλ¬Έ(석사)--μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› :μ˜κ³ΌλŒ€ν•™ μ˜ν•™κ³Ό,2020. 2. μ΄μ€μ˜.Introduction: About 40% of patients with rheumatoid arthritis are known to have interstitial lung disease. This greatly affects mortality in patients with rheumatoid arthritis. Despite this clinical significance, however, few studies have been conducted on rheumatoid arthritis patients with interstitial lung disease. The purpose of this study is to elucidate the pathological characteristics of lung tissue in patients with rheumatoid arthritis with interstitial lung disease and to identify the association of cytokines, biomarkers and lung lesions in prospective cohorts. Methods and Results: Pulmonary pathology The subjects were pulmonary pathology in patients diagnosed with rheumatoid arthritis with interstitial lung disease (RA-ILD), systemic sclerosis with interstitial lung disease (SSc-ILD) and idiopathic pulmonary fibrosis (IPF). Interleukin-17A (IL-17A), peptidyl arginine deiminase, type IV (PAD-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and alpha-enolase (ENO1) immunohistochemistry (IHC) were performed on 8, 5, and 5 lung pathological samples, respectively. Ten observation areas were randomly selected for each pathological specimen. IL-17A, PAD-4, GM-CSF, and ENO1 slides were observed 167, 167, 152 and 163 regions, respectively, and the percentage of uptake cells to total immune cells in this region was identified at 400 times magnification. IL-17A was statistically significant (RA-ILD vs SSC-ILD, p = 0.00; RA-ILD vs IPF, p = 0.002). ENO1 also showed statistical significance (RA-ILD vs SSC-ILD, p = 0.00; RA -ILD vs IPF, p = 0.024). Cohort Study This prospective, multicenter study included 167 patients with rheumatoid arthritis with interstitial lung disease. Anti-cyclic citrullinated peptide antibody (anti-CCP), tumor necrosis factor alpha (TNF-Ξ±), interleukin-6 (IL-6), IL-17A, and GM-CSF, matrix metalloproteinase (MMP)-7, surfactant protein-D (SP-D) and Krebs von den Lungen-6 (KL-6) were measured in the serum of the patients and correlated with the results of computed tomography and pulmonary function test. Computed tomography results were interpreted semi-quantitatively according to the extent of lung lesions (grade 1, 0-25%; grade 2, 26-50%; grade 3, 51-75%; grade 4, 76-100%). MMP-7, SP-D and KL-6 had a negative correlation with forced lung capacity (FVC; MMP-7, r = -0.192, p = 0.018; SP-D, r = -0.262, p = 0.001; KL-6, r = -0.181, p = 0.041) and diffusing capacity for carbon monoxide (DLco; MMP-7, r = -0.398, p = 0.000; SP-D, r = -0.253, p = 0.002; KL-6, r = -0.309, p <0.01). TNF-Ξ± showed association with DLco. In addition, MMP-7 and SP-D tended to increase with higher grades of lung lesions on computed tomography. Anti-CCP decreased with increasing CT grade. TNF-Ξ±, IL-6 have not been found to be meaningfully related. Conclusions: IHC of lung pathology specimens of RA-ILD, SSc-ILD and IPF showed statistical differences in IL-17A and ENO1 expressions suggesting biological differences in those diseases. In the cohort of RA-ILD, MMP-7, SP-D and KL-6 had a negative correlation with FVC and DLco. MMP-7 and SP-D were also correlated with the semiquantitative grade of computed tomography. These biomarkers can be used to evaluate functional and anatomical status of lung involvement in RA-ILD.μ„œλ‘ : λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό ν™˜μžμ˜ μ•½ 40%λŠ” κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•˜κ³  μžˆλŠ” κ²ƒμœΌλ‘œ μ•Œλ €μ Έ μžˆλ‹€. μ΄λŠ” λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό ν™˜μžμ˜ 사망λ₯ μ— 큰 영ν–₯을 λ―ΈμΉœλ‹€. ν•˜μ§€λ§Œ μ΄λŸ¬ν•œ μž„μƒμ  μ€‘μš”μ„±μ—λ„ λΆˆκ΅¬ν•˜κ³  μ§€κΈˆκΉŒμ§€ κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό ν™˜μžμ— λŒ€ν•˜μ—¬ 이루어진 μ—°κ΅¬λŠ” λ§Žμ§€ μ•Šλ‹€. 이에 λ³Έ μ—°κ΅¬μ—μ„œλŠ” κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό ν™˜μž 폐 쑰직의 병리학적 νŠΉμ„±μ„ 밝히고 μ „ν–₯적 μ½”ν˜ΈνŠΈ λ‚΄μ—μ„œ 사이토카인, λ°”μ΄μ˜€ λ§ˆμ»€μ™€ 폐 λ³‘λ³€μ˜ 연관성에 λŒ€ν•˜μ—¬ ν™•μΈν•˜κ³ μž ν•œλ‹€. 방법 및 κ²°κ³Ό: 폐병리연ꡬ μ„œμšΈλŒ€ν•™κ΅λ³‘μ›μ—μ„œ κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό, κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ 전신경화증, νŠΉλ°œμ„± 폐 μ„¬μœ μ¦μ„ 진단받은 ν™˜μžμ˜ 폐 병리 검체λ₯Ό λŒ€μƒμœΌλ‘œ ν•˜μ˜€λ‹€. 각각 8, 5, 5 개의 폐 병리 검체λ₯Ό λŒ€μƒμœΌλ‘œ IL-17A, PAD-4, GM-CSF, ENO1 면역쑰직화학 염색을 μ‹€μ‹œν•˜μ˜€λ‹€. 각 병리검체 λ‹Ή 10개의 κ΄€μ°°μ˜μ—­μ„ λ¬΄μž‘μœ„λ‘œ μ„ μ •ν•˜μ˜€λ‹€. IL-17A, PAD-4, GM-CSF, ENO1λŠ” 각각 167, 167, 152, 163 개의 μ˜μ—­μ„ κ΄€μ°°ν•˜μ˜€κ³  이 μ˜μ—­μ—μ„œ 전체 면역세포에 λŒ€ν•œ μ—Όμƒ‰λœ μ„Έν¬μ˜ λΉ„μœ¨ (%)을 400배의 λ°°μœ¨μ—μ„œ ν™•μΈν•˜μ˜€λ‹€. IL-17AλŠ” 각 κ΅° 간에 ν†΅κ³„μ μœΌλ‘œ μœ μ˜ν•œ 차이λ₯Ό λ³΄μ˜€λ‹€ (RA-ILD vs SSC-ILD, p = 0.00; RA-ILD vs IPF, p = 0.002). ENO1 μ—­μ‹œ 톡계적인 μœ μ˜μ„±μ΄ κ΄€μ°°λ˜μ—ˆλ‹€ (RA-ILD vs SSC-ILD, p = 0.00; RA-ILD vs IPF, p = 0.024). μ½”ν˜ΈνŠΈμ—°κ΅¬ 이 μ „ν–₯적, λ‹€κΈ°κ΄€μ—°κ΅¬λŠ” 167λͺ…μ˜ κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό ν™˜μžλ₯Ό ν¬ν•¨ν•œλ‹€. ν™˜μžμ˜ ν˜ˆμ²­μ—μ„œ anti-CCP, TNF-Ξ±, IL-6, IL-17A, GM-CSF, MMP-7, SP-D, KL-6λ₯Ό μΈ‘μ •ν•˜μ˜€μœΌλ©° μ „μ‚°ν™” λ‹¨μΈ΅μ΄¬μ˜κ³Ό 폐기λŠ₯검사 κ²°κ³Όμ™€μ˜ 연관성을 ν™•μΈν•˜μ˜€λ‹€. μ „μ‚°ν™” λ‹¨μΈ΅μ΄¬μ˜μ˜ κ²°κ³ΌλŠ” 폐 λ³‘λ³€μ˜ λ²”μœ„μ— 따라 λ°˜μ •λŸ‰μ μœΌλ‘œ ν•΄μ„ν•˜μ˜€λ‹€ (grade 1, 0-25%, grade 2, 26-50%, grade 3, 51-75%, grade 4, 76-100%). MMP-7, SP-D, KL-6 λŠ” κ°•μ œνν™œλŸ‰ (FVC; MMP-7, r = -0.192, p = 0.018; SP-D, r = -0.262, p = 0.001; KL-6, r = -0.181, p = 0.041) 및 폐확산λŠ₯검사 (DLco; MMP-7, r = -0.398, p = 0.000; SP-D, r = -0.253, p = 0.002; KL-6, r = -0.309, p <0.01)μ—μ„œ 음의 상관관계λ₯Ό λ³΄μ˜€λ‹€. TNF-Ξ± 의 경우 DLcoμ™€μ˜ 연관성을 λ³΄μ˜€λ‹€. λ˜ν•œ MMP-7κ³Ό SP-DλŠ” μ „μ‚°ν™” λ‹¨μΈ΅μ΄¬μ˜μ—μ„œ νλ³‘λ³€μ˜ λ“±κΈ‰ (grade) 이 λ†’μ„μˆ˜λ‘ μ¦κ°€ν•˜λŠ” κ²½ν–₯을 λ³΄μ˜€λ‹€. TNF-Ξ±, IL-6 λŠ” μ˜λ―ΈμžˆλŠ” 연관성이 ν™•μΈλ˜μ§€ μ•Šμ•˜λ‹€. κ²°λ‘ : κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό, κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ 전신경화증 및 νŠΉλ°œμ„± νμ„¬μœ μ¦μ˜ 폐 병리 κ²€μ²΄μ˜ 면역쑰직화학 염색은 IL-17A 및 ENO1 λ°œν˜„μ—μ„œ 톡계적 차이λ₯Ό 보여 μ£Όμ–΄ κ·Έ μ§ˆν™˜μ—μ„œμ˜ 생물학적 차이λ₯Ό μ‹œμ‚¬ν•œλ‹€. κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Ό μ½”ν˜ΈνŠΈμ—μ„œ, MMP-7, SP-D 및 KL-6은 κ°•μ œνν™œλŸ‰ 및 폐확산λŠ₯검사와 음의 상관 관계λ₯Ό κ°€μ‘Œλ‹€. λ˜ν•œ MMP-7 및 SP-DλŠ” 컴퓨터 λ‹¨μΈ΅μ΄¬μ˜ λ°˜μ •λŸ‰μ  λ“±κΈ‰κ³Ό 상관 관계가 μžˆμ—ˆλ‹€. μ΄λŸ¬ν•œ λ°”μ΄μ˜€λ§ˆμ»€λŠ” κ°„μ§ˆμ„± νμ§ˆν™˜μ„ λ™λ°˜ν•œ λ₯˜λ§ˆν‹°μŠ€ κ΄€μ ˆμ—Όμ—μ„œ 폐 μΉ¨λ²”μ˜ κΈ°λŠ₯적 및 해뢀학적 μƒνƒœλ₯Ό ν‰κ°€ν•˜λŠ”λ° μ‚¬μš©λ  수 μžˆλ‹€.Introduction 1 Methods 4 Results 8 Discussion 19 References 22 Abstract in Korean 25Maste

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