Eosinophil counts in first COPD hospitalizations: a 1-year cost analysis in Quebec, Canada
Bibliographic record
Abstract
Background: Exacerbations explain much of the cost of COPD. Higher blood eosinophil cell counts at admission for acute exacerbation of COPD increase the risk of subsequent exacerbations and hospitalizations. However, there is no literature on the economic burden of patients with this inflammatory profile. The objective of this study is to assess the cost of health-care service utilization according to different counts of blood eosinophils. Methods: The observational retrospective cohort included all first hospitalizations for COPD exacerbation between April 2006 and March 2013. The eosinophilic group was defined by blood eosinophil counts on admission ≥200 cells/µL and/or ≥2% of the total white blood cell count. Study outcomes were: total costs (2016 Canadian dollars) (index hospitalization and 1-year follow-up), total index hospitalization costs, total 1-year costs (all-cause readmissions, ambulatory and emergency service use), and 1-year COPD-related costs (only cost for COPD after initial discharge). Sensitivity analyses were conducted to evaluate the impact of different eosinophil cut-offs on outcomes. Results: In total, 479 patients were included, 173 in the eosinophilic group (92 in the higher cut-off). The average total cost was $18,263 ($6,706 for the index hospitalization), without significant difference between groups ( P =0.3). The average 1-year COPD-related cost was higher in the eosinophilic group ($3,667 vs $2,472, P =0.006), with an adjusted mean difference of $1,416. Analysis of data using the higher cut-off of ≥400 cells or ≥3% was associated with a slightly larger difference in 1-year COPD-related costs between groups ($4,060 vs $2,629, P =0.003), with an adjusted mean difference of $1,640. Conclusion: A higher blood eosinophil cell count at admission for a first hospitalization is associated with an increase in total 1-year COPD-related costs. Keywords: chronic obstructive pulmonary disease, exacerbations, health-care utilization, cohort study, Canada, Quebec
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".