Rate of All-cause Hospitalization at Year 2 Between Treatment Groups Following Diagnosis of Nontuberculous Mycobacterial Lung Disease in the USA
Bibliographic record
Abstract
The study compared rates of hospitalization between treatment groups in patients with nontuberculous mycobacterial lung disease (NTMLD) in a US national managed care claims database. Patient (N = 1039) pharmacy claims at year 1 following NTMLD diagnosis were classified into 3 treatment groups including triple combo (macrolide + ethambutol + rifamycin ± other drugs) (G1), other antibiotics used by physicians for NTMLD (G2), and no treatment (G3). Hospitalization rates at year 2 were compared between treatment groups using mixed effects logistic regression to adjust for patient characteristics and comorbidities measured by Charlson Comorbidity Index (CCI) during the 12 months prior to NTMLD diagnosis (baseline). Mean age was 66, 66 and 73 years with 65%, 70% and 66% women in G1 (n = 353), G2 (n = 388) and G3 (n = 298) respectively. At baseline, there was no difference on CCI (CCI≈2) between treatment groups. However, comorbidity distribution differed prominently in asthma (22.1%, 26.3% and 11.4%), arrhythmia (19.3%, 19.3% and 27.2%), cystic fibrosis (0.8%, 4.6% and 0%), immune disorder (7.6%, 9% and 2.7%), pneumonia (49.0%, 41.8% and 32.6%), and tuberculosis (9.3%, 8.2% and 5.4%), and in immunosuppressant use (51%, 51.5% and 25.2%). Baseline hospitalization was 31.7% in G1, 33.0% in G2, and 25.8% in G3. At year 2, CCI stayed almost unchanged from the baseline scores (1.9 in G1, 2.0 in G2, and 1.9 in G3). Unadjusted hospitalization rates were 19.6%, 27.8% vs 20.8%, and adjusted rates were 44.5%, 56.1% and 47.8% in 3 groups respectively (Figure). G2 had a 60% increase in risk of hospitalization after adjustment (odds ratio (OR)=1.60, 95% CI: 1.11–2.29, P = 0.01) compared with G1 but no statistically significant difference compared with G3 (OR=1.40, P = 0.08). Cerebrovascular disease (OR=1.8, P < 0.02), COPD (OR=1.60, P < 0.01), cystic fibrosis (OR=5.85, P < 0.01), depression (OR=1.64, P < 0.05), and other lung disease (OR=1.42, P < 0.05) were associated with a higher risk of hospitalization at year 2 after NTMLD diagnosis. We observed a lower hospitalization rate in NTMLD patients receiving antibiotics that were concordant with first line ATS/IDSA guidelines recommendations in comparison with those who used other antibiotic regimens. E. Chou, Insmed Incorporated: Employee, Salary; G. Eagle, Insmed Incorporated: Employee, Salary; R. Zhang, Insmed Incorporated: Consultant, Consulting fee; P. Wang, Insmed Incorporated: Employee, Salary; Q. Zhang, Insmed Incorporated: Employee, Salary
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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 | 0.003 |
| 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".