Comorbidity as a contributor to frequent severe acute exacerbation in COPD patients
Bibliographic record
Abstract
BACKGROUND: Comorbidities have a serious impact on the frequent severe acute exacerbations (AEs) in patients with COPD. Previous studies have used the Charlson comorbidity index to represent a conglomerate of comorbidities; however, the respective contribution of each coexisting disease to the frequent severe AEs remains unclear. METHODS: A retrospective, observational study was performed in 77 COPD patients who experienced severe AE between January 2012 and December 2014 and had at least 1-year follow-up period from the date of admission for severe AE. We explored the incidence of frequent severe AEs (≥2 severe AEs during 1-year period) in these patients and investigated COPD-related factors and comorbidities as potential risk factors of these exacerbations. RESULTS: Out of 77 patients, 61 patients (79.2%) had at least one comorbidity. During a 1-year follow-up period, 29 patients (37.7%) experienced frequent severe AEs, approximately two-thirds (n=19) of which occurred within the first 90 days after admission. Compared with patients not experiencing frequent severe AEs, these patients were more likely to have poor lung function and receive home oxygen therapy and long-term oral steroids. In multiple logistic regression analysis, coexisting asthma (adjusted odds ratio [OR] =4.02, 95% confidence interval [CI] =1.30-12.46, P=0.016), home oxygen therapy (adjusted OR =9.39, 95% CI =1.60-55.30, P=0.013), and C-reactive protein (adjusted OR =1.09, 95% CI =1.01-1.19, P=0.036) were associated with frequent severe AEs. In addition, poor lung function, as measured by forced expiratory volume in 1 second (adjusted OR =0.16, 95% CI =0.04-0.70, P=0.015), was inversely associated with early (ie, within 90 days of admission) frequent severe AEs. CONCLUSION: Based on our study, among COPD-related comorbidities, coexisting asthma has a significant impact on the frequent severe AEs in COPD patients.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".