Disease burden and health-related outcomes of patients discharged from hospital following a COPD exacerbation in the United States
Bibliographic record
Abstract
BACKGROUND: Evidence on trajectory of readmission rates post-hospitalization for COPD exacerbations and combined cardiopulmonary risk in the U.S. is sparse. OBJECTIVE: To describe incidence of outcomes and treatment patterns post-hospitalization for a COPD exacerbation. METHODS: This was an observational study of patients discharged from hospital post-COPD exacerbation in the U.S. (01.01.18-09.30.21) using data from the Optum® Clinformatics® Data Mart database. Index date was the discharge date of first recorded hospitalization for a COPD exacerbation during the study period. Primary outcomes were frequency and time to post-discharge events (hospital readmissions, all-cause mortality, and severe cardiopulmonary events). Post-discharge COPD medication prescription patterns, frequency and time-to-triple-therapy escalation were assessed secondarily. RESULTS: Overall, 38,483 patients were included. One-year post-discharge, 34.6 % of patients (incidence rate [IR] 42.2/100 patient years [PY], 95% CI: 41.5, 42.9) experienced ≥1 severe cardiopulmonary event, 16.7 % (IR 20.4/100 PY; 95 % CI: 19.8, 20.9) had a COPD readmission and 18.2 % (IR 22.2/100 PY; 95 % CI: 21.7, 22.7) died. Upon discharge, 27.4 % and 17.5 % of patients were prescribed reliver only/no COPD treatment and triple-therapy, respectively. Of 17,991 not prescribed triple maintenance COPD therapy 6-months pre-hospitalization or within 14-days post-discharge, 29.5 % eventually escalated to triple-therapy (mean (SD) time-to-escalation: 337.6 (340.2) days). CONCLUSION: Treatment patterns post-hospitalization for a COPD exacerbation in the U.S. don't align with recognized standards (e.g. GOLD recommendations). Patients discharged from hospital post-COPD exacerbation have a high risk of severe cardiopulmonary events, hospital readmission and death. Opportunities exist to improve post-hospitalization COPD management practices, including timely intervention with triple-therapy as appropriate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".