Optimizing COPD Acute Care Patient Outcomes Using a Standardized Transition Bundle and Care Coordinator
Bibliographic record
Abstract
BACKGROUND: Acute exacerbations of COPD (AECOPD) are associated with high morbidity and mortality and frequent readmissions. RESEARCH QUESTION: What is the effectiveness of a COPD transition bundle, with and without a care coordinator, on rehospitalizations and ED revisits? STUDY DESIGN AND METHODS: Two patient cohorts were selected: (1) the group exposed to the transition bundle and (2) the group not exposed to the transition bundle (usual care group). Patients exposed subsequently were randomized to a care coordinator. An AECOPD transition bundle was implemented in the hospital; patients randomized to the care coordinator were contacted ≤ 72 h after discharge. Six hundred four patients (320 to the care coordinator and 284 to routine care) who met eligibility criteria from five hospitals across three cities in Alberta, Canada, were exposed to the transition bundle, whereas 3,106 patients discharged from the same hospitals received the usual care. Primary outcomes were 7-day, 30-day, and 90-day readmissions, median length of stay (LOS), and 30-day ED revisits. RESULTS: The transition bundle cohort were 83% (relative risk [RR], 0.17; 95% CI, 0.07-0.35) less likely to be readmitted within 7 days and 26% (RR, 0.74; 95% CI, 0.60-0.91) less likely to be readmitted within 30 days of discharge. Ninety-day readmissions were unchanged (RR, 1.05; 95% CI, 0.93-1.18). The transition bundle was associated with a 7.3% (RR, 1.07; 95% CI, 1.0-1.15) relative increase in LOS and a 76% (RR, 1.76; 95% CI, 1.53-2.02) greater risk of a 30-day ED revisit. The care coordinator did not influence readmission or ED revisits. INTERPRETATION: The COPD transition bundle reduced 7- and 30-day hospital readmissions while increasing LOS and ED revisits. The care coordinator did not improve outcomes. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT03358771; URL: www. CLINICALTRIALS: gov.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".