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Record W2883176237 · doi:10.1080/14656566.2018.1499727

A pharmacoeconomic evaluation of cholinesterase inhibitors and memantine for the treatment of Alzheimer’s disease

2018· article· en· W2883176237 on OpenAlexaff
Anees Shajhan Ebrahem, Mark Oremus

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMedicineMEDLINECochrane LibraryDonepezilEconomic evaluationDiseaseMoodMemantineRivastigmineCognitionCognitive declineDementiaQuality of life (healthcare)PlaceboPsychiatryAlternative medicineIntensive care medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Alzheimer's disease (AD) results in progressively worsening cognitive decline, leading to loss of functional ability, behavior/mood disturbances, institutionalization, and death. Current pharmaceutical therapies only treat the symptoms of cognitive decline yet can be expensive for payers. Areas covered: The authors undertook a systematic review of economic evaluations of pharmaceutical therapies for AD. The literature search encompassed English-language studies indexed in PubMed (Medline), Cochrane Library Current, and Web of Science. The search included articles published between 1 January 1995 and 10 February 2018. The literature suggested AD medications generally dominated comparator treatments (e.g. placebo). Expert opinion: The authors noted several limitations of the included economic evaluations. These limitations suggest the results of the economic evaluations should be interpreted with caution. Many economic models were not transparent with respect to sources of probabilities and cost data, and data collected in certain jurisdictions were applied to other jurisdictions without considering the validity of such applications. Measuring health utilities in cognitively impaired populations raises questions about the validity of quality-adjusted life years, but this issue was unaddressed in the included studies. Most included studies were sponsored by industry and the results tended to overwhelmingly support the manufacturer's product.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.477
GPT teacher head0.538
Teacher spread0.061 · 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 designNot applicable
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

Citations15
Published2018
Admission routes1
Has abstractyes

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