Differentiating Nontuberculous Mycobacterial Pulmonary Disease from Pulmonary Tuberculosis in Resource-Limited Settings: A Pragmatic Model for Reducing Misguided Antitubercular Treatment
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients
2.2. Collection of Clinical Data
2.3. Statistical Analysis
3. Results
3.1. Demographic and Clinical Characteristics of NTM-PD and PTB Patients
3.2. Laboratory and Microbiological Characteristics
3.3. Comparative Analysis of Thoracic CT Features
3.4. Multivariable Predictors and Diagnostic Model Performance
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | NTM-PD | PTB | p |
---|---|---|---|
Age (years) | 53.1 ± 14.3 | 45.1 ± 17.6 | 0.001 |
Female [n (%)] | 62 (59.0) | 38 (36.2) | 0.001 |
Height (cm) | 161.40 ± 7.27 | 163.56 ± 7.95 | 0.041 |
Weight (kg) | 50.68 ± 9.39 | 53.56 ± 10.46 | 0.037 |
BMI (kg/m2) | 19.19 ± 3.36 | 20.59 ± 3.13 | 0.009 |
Time from symptom onset to diagnosis (month) | 16 (5~37) | 3 (2~9) | 0.001 |
Comorbidities [n (%)] | |||
COPD | 13 (12.4) | 5 (4.8) | 0.049 |
DM | 5 (4.8) | 18 (17.1) | 0.004 |
PMH [n (%)] | |||
Chest trauma and surgery | 8 (7.6) | 1 (1.0) | 0.041 |
Chronic dust exposure | 6 (5.7) | 6 (5.7) | 1.000 |
Symptoms [n (%)] | |||
Expectoration | 85 (81.0) | 77 (73.3) | 0.189 |
Irritating dry cough | 6 (5.7) | 11 (10.5) | 0.206 |
Hemoptysis | 54 (51.4) | 29 (27.6) | 0.001 |
Dyspnea | 76 (72.4) | 58 (55.2) | 0.010 |
Chest pain | 14 (13.3) | 10 (9.5) | 0.386 |
Systemic symptoms 1 | 42 (40.0) | 62 (59.0) | 0.006 |
Fever | 14 (13.3) | 24 (22.9) | 0.073 |
Night sweats | 17 (16.2) | 30 (28.6) | 0.031 |
asthenia | 10 (9.5) | 9 (8.6) | 0.810 |
Weight loss | 17 (16.2) | 34 (32.4) | 0.006 |
Test Items | NTM-PD | PTB | p |
---|---|---|---|
Routine blood test | |||
WBC (×109/L) | 5.92 (4.88~7.55) | 6.68 (5.01~8.42) | 0.144 |
Neutrophils (×109/L) | 3.53 (2.78~4.94) | 4.23 (3.02~6.00) | 0.020 |
Lymphocytes (×109/L) | 1.43 (1.10~1.91) | 1.35 (0.93~1.66) | 0.059 |
Monocytes (×109/L) | 0.47 (0.35~0.63) | 0.51 (0.42~0.76) | 0.042 |
ML ratio 1 | 0.30 (0.21~0.55) | 0.45 (0.29~0.64) | 0.001 |
PLT (×109/L) | 211 (163~275) | 251 (202~341) | 0.001 |
Serum proteins (g/L) | |||
TP | 66.4 (62.6~71.2) | 69.8 (63.5~74.9) | 0.010 |
ALB | 39.6 (36.8~43.0) | 40.2 (34.6~43.7) | 0.601 |
GLB | 26.3 (23.7~28.9) | 29.4 (26.4~32.7) | 0.001 |
Immunological test | |||
C3 (g/L) | 1.15 (1.01~1.27) | 1.26 (1.17~1.49) | 0.001 |
C4 (g/L) | 0.27 (0.23~0.31) | 0.31 (0.26~0.36) | 0.004 |
IgG (g/L) | 14.8 (12.2~16.6) | 15.4 (12.4~18.2) | 0.276 |
IgA (g/L) | 2.67 (1.96~3.65) | 2.49 (1.84~3.17) | 0.234 |
IgM (g/L) | 1.28 (0.80~1.79) | 1.07 (0.73~1.68) | 0.197 |
Infection indicators | |||
CRP (mg/L) | 5.6 (1.4~33.2) | 22.4 (6.9~49.1) | 0.001 |
PCT (ng/mL) | 0.16 (0.11~0.32) | 0.19 (0.13~0.41) | 0.312 |
ESR (mm/h) | 23 (11~47) | 34 (15~69) | 0.013 |
PPD test [n (%)] | 0.005 | ||
Negative | 60 (57.1) | 20 (19.0) | |
Weakly positive | 6 (5.7) | 10 (9.5) | |
Positive | 25 (23.8) | 52 (49.5) | |
Strongly positive | 14 (13.3) | 23 (21.9) | |
TB antibody [n (%)] | |||
Positive | 18 (17.1) | 37 (35.2) | 0.003 |
T-SPOT [n (%)] | |||
Positive | 44 (41.9) | 84 (80.0) | 0.001 |
Sputum acid-fast stain 2 [n (%)] | 0.280 | ||
+ | 17 (16.2) | 12 (11.4) | |
++ | 18 (17.1) | 11 (10.5) | |
+++ | 9 (8.6) | 10 (9.5) | |
++++ | 5 (4.8) | 11 (10.5) | |
Sputum culture 3 [n (%)] | 50 | 0.001 | |
+ | 23 (21.9) | 7 (6.7) | |
++ | 36 (34.3) | 9 (8.6) | |
+++ | 38 (36.2) | 25 (23.8) | |
++++ | 8 (7.6) | 64 (60.9) | |
1+~2+:3+~4+ ratio | 59/46 | 16/89 | 0.001 |
CT Findings [n (%)] | NTM-PD | PTB | p |
---|---|---|---|
Bilateral lung lesions | 95 (90.5) | 80 (76.2) | 0.005 |
Multiple lobe involvement | 98 (93.3) | 89 (84.8) | 0.047 |
Upper lobe | 89 (84.8) | 78 (74.3) | 0.060 |
Right middle lobe/Left lingual lobe | 81 (77.1) | 59 (56.2) | 0.001 |
Lower lobe | 83 (79.0) | 87 (82.9) | 0.482 |
Patchy shadow | 89 (84.8) | 84 (80.0) | 0.365 |
Fibrous stripe | 77 (73.3) | 54 (51.4) | 0.001 |
Nodular shadow | 73 (69.5) | 76 (72.4) | 0.648 |
Ground glass opacity | 4 (3.8) | 7 (6.7) | 0.353 |
Consolidation | 9 (8.6) | 22 (21.0) | 0.011 |
Cavity | 50 (47.6) | 56 (53.3) | 0.408 |
Bronchiectasis | 65 (61.9) | 16 (15.2) | 0.001 |
Emphysema/pulmonary bulla | 48 (45.7) | 22 (21.0) | 0.001 |
Atelectasis | 19 (18.1) | 11 (10.5) | 0.115 |
Pleural effusion | 16 (15.2) | 24 (22.9) | 0.160 |
Risk Factors | β Regression Coefficient | p | OR | 95%CI |
---|---|---|---|---|
NTM-PD predictors | ||||
Female sex | 0.919 | 0.025 | 2.51 | 1.12–5.60 |
Bronchiectasis | 1.779 | 0.001 | 5.92 | 2.56–13.71 |
Hemoptysis | 0.789 | 0.037 | 2.20 | 1.05–4.62 |
Emphysema/pulmonary bulla | 0.991 | 0.021 | 2.69 | 1.16–6.24 |
PTB predictor | ||||
Systemic symptoms 1 | −0.802 | 0.046 | 0.45 | 0.20–0.99 |
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Zhang, W.; Chen, J.; Chen, Z.; Quan, J.; Huang, Z. Differentiating Nontuberculous Mycobacterial Pulmonary Disease from Pulmonary Tuberculosis in Resource-Limited Settings: A Pragmatic Model for Reducing Misguided Antitubercular Treatment. Healthcare 2025, 13, 1065. https://doi.org/10.3390/healthcare13091065
Zhang W, Chen J, Chen Z, Quan J, Huang Z. Differentiating Nontuberculous Mycobacterial Pulmonary Disease from Pulmonary Tuberculosis in Resource-Limited Settings: A Pragmatic Model for Reducing Misguided Antitubercular Treatment. Healthcare. 2025; 13(9):1065. https://doi.org/10.3390/healthcare13091065
Chicago/Turabian StyleZhang, Wei, Jun Chen, Zhenhua Chen, Jun Quan, and Zebing Huang. 2025. "Differentiating Nontuberculous Mycobacterial Pulmonary Disease from Pulmonary Tuberculosis in Resource-Limited Settings: A Pragmatic Model for Reducing Misguided Antitubercular Treatment" Healthcare 13, no. 9: 1065. https://doi.org/10.3390/healthcare13091065
APA StyleZhang, W., Chen, J., Chen, Z., Quan, J., & Huang, Z. (2025). Differentiating Nontuberculous Mycobacterial Pulmonary Disease from Pulmonary Tuberculosis in Resource-Limited Settings: A Pragmatic Model for Reducing Misguided Antitubercular Treatment. Healthcare, 13(9), 1065. https://doi.org/10.3390/healthcare13091065