122. All-Cause Mortality Increased With Nontuberculous Mycobacterial Lung Disease in US Medicare
Notice bibliographique
Résumé
Abstract Background Nontuberculous Mycobacterial Lung Disease (NTMLD) is a chronic, debilitating, and progressive disease. This study evaluates all-cause mortality in patients with NTMLD in the US Medicare. Methods Patients (n = 43,394) were identified from the Medicare database (excluding Part C) based on physician claims for NTMLD on ≥2 separate occasions ≥30 days apart between 2007 and 2015. About 12% patients were <65 years and qualified for Medicare due to disability. A control cohort (n = 84,814) was randomly selected and matched to the NTMLD sample by age and sex. The NTMLD diagnosis date was assigned to the matched controls as an index date. Poisson and Cox regression were used to derive descriptive rates and adjusted risk of mortality accounting for baseline comorbidities of pulmonary, immune, cardiovascular, cancer, and other disorders. Results Mean age was 74 (±10) years and 68% were female in both NTMLD and control cohorts. Mean Charlson comorbidity index (CCI) was 2.9 (standard deviation ±2.6) in NTMLD vs. 1.3 (±1.9) in control cohort. In Medicare members ≥65 years, mean age was 76 (±7) years and 70% were female. Mean CCI was 2.8 (±2.5) in NTMLD cohort vs. 1.4 (±2.0) in control cohort. In Medicare members <65, mean age was 53 (±10) and 49% were female. Mean CCI was 3.8 (±3.3) in NTMLD vs. 1.1 (±1.9) in the control. Observed yearly mortality rates were 9.8% in NTMLD vs. 4.7% in control cohort (rate ratio [RR] = 2.1; 95% CI: 2.03–2.13). In ≥65 Medicare members, the observed rates were 9.7% in NTMLD vs. 5.0% in control cohort (RR = 2.0; 1.9–2.0). In Medicare members <65, the observed rates were 10.4% in NTMLD vs. 2.5% in control cohort (RR = 4.1; 3.8–4.5). Compared with the Asian race, observed mortality was higher in NTMLD patients of Native American (hazard ratio [HR] = 1.69, 1.30–2.19), Black (HR = 1.23; 1.08–1.39), Hispanic (HR = 1.27, 1.07–1.51), or White (HR = 1.18, 1.06–1.31) race (Figure 1). Mortality rates were elevated with NTMLD relative to controls in all age categories from ≥65 years (Figure 2). Adjusted mortality increased with NTMLD by 35% overall (HR = 1.35; 1.3–1.4), by 23% in age group ≥65 (HR = 1.23, 1.19–1.27), and almost doubled in age group <65 (HR = 1.97, 1.80–2.15). Conclusion Among US Medicare enrollees, NTMLD was associated with a 35% increased risk of mortality overall. Disclosures T. Marras, Insmed Incorporated: Investigator, Consulting fee and Research grant. Horizon Pharmaceuticals: Consultant, Consulting fee. Red Hill: Consultant, Consulting fee. AstraZeneca: CME, Speaker honorarium. Q. Zhang, Insmed Incorporated: Employee, Salary. G. Eagle, Insmed Incorporated: Employee, Salary. P. Wang, Insmed Incorporated: Employee, Salary. R. Zhang, Insmed Incorporated: Consultant, Consulting fee. E. Chou, Insmed Incorporated: Employee, Salary. K. L. Winthrop, Insmed Incorporated: Consultant and Scientific Advisor, Consulting fee and Research grant.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».