The Risk of Tuberculosis in Chronic Obstructive Pulmonary Disease Across Different Comorbidities
Bibliographic record
Abstract
Background: Chronic obstructive pulmonary disease (COPD) is a progressive respiratory disorder with significant global morbidity and mortality. COPD is increasingly recognized as a systemic inflammatory condition that predisposes patients to multiple comorbidities, including tuberculosis (TB). There are limited data on how comorbidities in COPD influence the development of TB. Methods: We conducted a nationwide, retrospective cohort study using data from Taiwan's National Health Insurance Research Database (NHIRD) between 2011 and 2021. Patients aged ≥ 40 years with a diagnosis of COPD, confirmed by ≥ 3 outpatient visits or ≥ 1 hospitalization, were included. Individuals with prior TB were excluded. Non-COPD controls were matched 1:1 using propensity score matching for demographics and comorbidities. The primary outcome was incident TB (ICD-9-CM 010-018). Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) for TB, accounting for a variety of comorbidities. Results: A total of 117,989 COPD patients and an equal number of matched controls were analyzed. During follow-up, TB incidence was significantly higher in the COPD group (3.20 vs. 1.45 per 10,000 person-years). COPD was associated with a 74% increased risk of TB (aHR 1.74; 95% confidence interval (CI): 1.42 - 2.14; P < 0.001). Stratified analysis demonstrated that TB risk rose progressively with age and was markedly amplified by comorbidities. Notably, pneumoconiosis conferred a nearly sevenfold higher TB risk among COPD patients (aHR 6.94; 95% CI: 2.72 - 17.71; P < 0.001), followed by lung cancer (aHR 1.81; 95% CI: 1.07 - 3.05; P < 0.027) and rheumatoid arthritis (aHR 2.05; 95% CI: 1.01 - 4.12; P < 0.046). Conclusion: After adjustment for available covariates, COPD was associated with an increased risk of TB; however, residual confounding due to factors such as corticosteroid use, immunosuppressive therapy, and smoking cannot be excluded.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".