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Record W1986471715 · doi:10.1517/14656566.9.15.2575

Pharmacological treatment in moderate-to-severe Alzheimer's disease

2008· review· en· W1986471715 on OpenAlexaff
Ging‐Yuek Robin Hsiung, Howard Feldman

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2008
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsMedicineDonepezilMemantineDiseaseRandomized controlled trialPopulationClinical trialAlzheimer's diseaseStage (stratigraphy)Caregiver burdenIntensive care medicineInternal medicinePediatricsDementia

Abstract

fetched live from OpenAlex

BACKGROUND: Moderate-to-severe stage Alzheimer's disease (AD) is a clinically diagnosable entity that represents a substantial burden to our healthcare system in terms of its prevalence, symptomatology, caregiver stress and economics. OBJECTIVE: In this paper, we review the data from currently available clinical trials aimed at treatment of this later stage of the disease. METHODS: A literature search was performed and published randomized controlled trials (RCTs) in which the majority of the study population consisted of Alzheimer patients in the moderate-to-severe stage were selected for review. RESULTS: A total of nine RCTs were identified in which the study population consisted of mainly moderate-to-severe AD patients. The results from these studies suggest that memantine and donepezil, individually or in combination, provide measurable global, cognitive and behavioral benefits in AD patients. CONCLUSION: Pharmacological treatment of moderate-to-severe AD patients can be beneficial. However, cost-benefit data are limited, and the long-term effects and the optimal duration of treatment as patients continue to progress to more severe stages are unknown and require further investigation.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.156
GPT teacher head0.488
Teacher spread0.332 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2008
Admission routes1
Has abstractyes

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