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Record W3157995564 · doi:10.1002/alz.12242

The Clinician's Interview‐Based Impression of Change (Plus caregiver input) and goal attainment in two dementia drug trials: Clinical meaningfulness and the initial treatment response

2021· article· en· W3157995564 on OpenAlexafffund
Justin Stanley, Susan E. Howlett, Taylor Dunn, Kenneth Rockwood

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsDalhousie UniversityGreenfield Research (Canada)
FundersCanadian Institutes of Health ResearchAtlantic Canada Opportunities Agency
KeywordsGoal Attainment ScalingDementiaPsychologyClinical trialClinical Global ImpressionInternal medicineClinical psychologyPsychiatryMedicineDiseasePathologyAlternative medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The Clinician's Interview-Based Impression of Change Plus caregiver input (CIBIC-Plus) has been widely used in dementia drug trials to evaluate cognition, behavior, and function. New trials of symptomatic drugs forecast renewed interest in this measure. METHODS: To test its clinical meaningfulness, we examined how CIBIC-Plus performed in two cholinesterase inhibitor trials compared to goal attainment scaling Scale (GAS) scores, a patient-reported outcome measure. RESULTS: Net goal attainment was seen for all but one GAS domains in subjects who improved on the CIBIC-Plus. Subjects who improved initially on CIBIC-Plus scores were likely to remain improved across all other outcomes for each trial's duration, except for Disability Assessment for Dementia scores. DISCUSSION: The initial response to treatment, as assessed by CIBIC-Plus, remained stable for most outcome measures. Even small CIBIC-Plus improvement changes are associated with clinically meaningful change as assessed by GAS. Other tests detect decline better than improvement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.056
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0560.072
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.205
GPT teacher head0.464
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2021
Admission routes2
Has abstractyes

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