MétaCan
Menu
Back to cohort
Record W1622647717 · doi:10.1186/1471-2318-3-6

Rational choice of cholinesterase inhibitor for the treatment of Alzheimer's disease in Canada: a comparative economic analysis

2003· article· en· W1622647717 on OpenAlexaboutno aff
J. Jaime, Denis Getsios, Kristen Migliaccio–Walle, Jack Ishak, Wissam El-Hadi

Bibliographic record

VenueBMC Geriatrics · 2003
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsGalantamineDonepezilRivastigmineMedicineClinical trialDiseaseCholinesteraseDementiaAlzheimer's diseaseIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cholinesterase inhibitors, such as galantamine, donepezil and rivastigmine are approved for symptomatic treatment of Alzheimer's Disease (AD) in Canada. In making choices amongst these drugs, one should consider their clinical merits and their economic implications. METHODS: Each drug's short-term efficacy was estimated based on independent Cochrane reviews of the clinical trials. Long-term clinical and economic outcomes were estimated using the Assessment of Health Economics in Alzheimer's Disease (AHEAD) model. RESULTS: While all treatments reduced the need for full-time care, only galantamine and donepezil 10 mg reduced the overall management costs of AD patients. The somewhat greater cognitive effect provided over six months by galantamine leads to the longest estimated delay before full-time care is required and, consequently to lower overall costs, with savings estimated at between 323 dollars and 4,246 dollars. CONCLUSION: Although there is uncertainty in estimated results, the best information currently available suggests that the first choice for treatment of AD should be galantamine. These results should be interpreted with caution, however, as results are not based on direct comparisons among the drugs and the differences emerging from meta-analyses of the trials are relatively small.

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 score0.284
Threshold uncertainty score0.909

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 head0.060
GPT teacher head0.344
Teacher spread0.284 · 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

Citations18
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueBMC GeriatricsSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207