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Record W2127110772 · doi:10.1186/1745-6215-15-202

Toward onset prevention of cognitive decline in adults with Down syndrome (the TOP-COG study): study protocol for a randomized controlled trial

2014· article· en· W2127110772 on OpenAlexaff
Sally‐Ann Cooper, Muriel Caslake, Jonathan J. Evans, Angela Hassiotis, Andrew Jahoda, Alex McConnachie, Jill Morrison, Howard Ring, John M. Starr, Ciara Stiles, Frank Sullivan

Bibliographic record

VenueTrials · 2014
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsNorth York General HospitalUniversity of Toronto
FundersMedical Research Council
KeywordsMedicineRandomized controlled trialCognitive declinePopulationTolerabilityDementiaClinical endpointDiseaseInternal medicineAdverse effect

Abstract

fetched live from OpenAlex

BACKGROUND: Early-onset dementia is common in Down syndrome adults, who have trisomy 21. The amyloid precursor protein gene is on chromosome 21, and so is over-expressed in Down syndrome, leading to amyloid β (Aβ) over-production, a major upstream pathway leading to Alzheimer disease (AD). Statins (microsomal 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors), have pleiotropic effects including potentially increasing brain amyloid clearance, making them plausible agents to reduce AD risk. Animal models, human observational studies, and small scale trials support this rationale, however, there are no AD primary prevention trials in Down syndrome adults. In this study we study aim to inform the design of a full-scale primary prevention trial. METHODS/DESIGN: TOP-COG is a feasibility and pilot double-blind randomized controlled trial (RCT), with a nested qualitative study, conducted in the general community. About 60 Down syndrome adults, aged ≥50 will be included. The intervention is oral simvastatin 40 mg at night for 12 months, versus placebo. The primary endpoint is recruitment and retention rates. Secondary endpoints are (1) tolerability and safety; (2) detection of the most sensitive neurocognitive instruments; (3) perceptions of Down syndrome adults and caregivers on whether to participate, and assessment experiences; (4) distributions of cognitive decline, adaptive behavior, general health/quality of life, service use, caregiver strain, and sample size implications; (5) whether Aβ42/Aβ40 is a cognitive decline biomarker. We will describe percentages recruited from each source, the number of contacts to achieve this, plus recruitment rate by general population size. We will calculate summary statistics with 90% confidence limits where appropriate, for each study outcome as a whole, by treatment group and in relation to baseline age, cognitive function, cholesterol and other characteristics. Changes over time will be summarized graphically. The sample size for a definitive RCT will be estimated under alternative assumptions. DISCUSSION: This study is important, as AD is a major problem for Down syndrome adults, for whom there are currently no effective preventions or treatments. It will also delineate the most suitable assessment instruments for this population. Recruitment of intellectually disabled adults is notoriously difficult, and we shall provide valuable information on this, informing future studies. TRIAL REGISTRATION: Current Controlled Trials ISRCTN Register ID: ISRCTN67338640 (17 November 2011).

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)0.039
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.059
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.032
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0140.006
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0590.011

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 head0.131
GPT teacher head0.466
Teacher spread0.335 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations17
Published2014
Admission routes1
Has abstractyes

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