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Cognition, Function, and Caregiving Time Patterns in Patients With Mild-to-Moderate Alzheimer Disease

2005· article· en· W2120320356 on OpenAlexaff
Howard Feldman, B. Van Baelen, Shane M. Kavanagh, Koen Torfs

Bibliographic record

VenueAlzheimer Disease & Associated Disorders · 2005
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsActivities of daily livingDementiaAlzheimer's diseasePlaceboCognitionMedicineGerontologyCognitive declineDiseasePsychologyPhysical therapyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Placebo data were pooled from two 1-year, randomized, double-blind, placebo-controlled trials of sabeluzole in patients with mild-to-moderate Alzheimer disease (AD). Cognition was assessed using the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) and activities of daily living (ADL) with the Disability Assessment in Dementia (DAD). Time spent assisting with ADL was estimated according to the caregiver for each DAD domain in the 2 weeks before assessment. Progressive annual decline was seen on ADAS-cog (5.6 +/- 7.3 [mean +/- SD]) and DAD (-12.4 +/- 17.8), with greater decline in moderate patients (Mini-Mental State Examination [MMSE] < or =18) than mild patients (MMSE >18). An MMSE score of 16 appeared to be a key transition point at which most instrumental ADL were lost and major losses of basic ADL began to occur over the next 12 months. Caregivers spent, on average, 14 hours more assisting with ADL over 2 weeks at the end of 1 year. The proportion of care provided by paid caregivers increased relative to the time spent by informal caregivers. Patients with mild-to-moderate AD experience predictable annual decline in cognition and daily functioning, with measurably increased caregiver time. Small changes in ADAS-cog are nevertheless associated with a substantial measurable effect on the daily lives of both patients and caregivers.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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.

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

Citations106
Published2005
Admission routes1
Has abstractyes

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