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Record W4298234532 · doi:10.17615/1vvv-1971

Comparative Health-Care Cost Advantage of Ipratropium over Tiotropium in COPD Patients

2021· article· en· W4298234532 on OpenAlexaboutno aff
Greg Carney, David Hosick, Colin R. Dormuth, Til Stürmer‎, Jesse Yamaguchi, Brett Wilmer

Bibliographic record

VenueUNC Libraries · 2021
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsnot available
Fundersnot available
KeywordsIpratropiumCOPDMedicineHealth careInternal medicineBronchodilatorAsthmaEconomics

Abstract

fetched live from OpenAlex

Objective: To compare the total direct health-care costs of patients treated with tiotropium and ipratropium. Methods: We conducted a cohort study of health-care costs in British Columbia, Canada, by comparing new patients on tiotropium with new patients on ipratropium. Direct health-care costs for study patients were measured in the first 2 years after initiating inhaled anticholinergic treatment. Differences in direct health-care costs between tiotropium and ipratropium patients were estimated by using quantile regression. We analyzed cost differences in the 10th percentile, median, and 90th percentile of patients by cost. High-dimensional propensity score analysis was used as a method of adjustment for potential confounding factors. Results: The study population had 3,140 tiotropium patients and 26,182 ipratropium patients. Higher health system costs in patients who started on tiotropium instead of ipratropium were observed in patients in the median and 10th percentile. The magnitude of these increases was comparable to the price difference between the two drugs. Health system costs in the 90th percentile were not significantly different between tiotropium and ipratropium patients. Conclusions: The results of this study did not support the preferential use of tiotropium over ipratropium as a basis for savings in direct health-care costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.304
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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