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Record W2619945698 · doi:10.1001/jamaneurol.2017.0892

Association of Longitudinal Cognitive Decline With Amyloid Burden in Middle-aged and Older Adults

2017· article· en· W2619945698 on OpenAlexaff
Michelle E. Farrell, Kristen M. Kennedy, Karen M. Rodrigue, Gagan S. Wig, Gérard N. Bischof, Xi Chen, Sara B. Festini, Michael D. Devous, Denise C. Park

Bibliographic record

VenueJAMA Neurology · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBaycrest Hospital
FundersNational Institute on Aging
KeywordsPittsburgh compound BCognitive declineLongitudinal studyCognitionMedicineCohortMini–Mental State ExaminationCohort studyApolipoprotein EPsychologyInternal medicineGerontologyDementiaPsychiatryCognitive impairmentPathologyDisease

Abstract

fetched live from OpenAlex

Importance: Presently, the clinical standard for reporting the results of an amyloid positron emission tomography scan is to assign a dichotomous rating of positive or negative for the presence of amyloid. In a 4-year longitudinal study, we investigated whether using a continuous measure of the magnitude of baseline amyloid burden would provide valuable information about the rate of future cognitive decline over the subsequent 4 years compared with a dichotomous measure in middle-aged and older adults. Objective: To examine whether a continuous, dose-response relationship between amyloid burden and cognitive decline was present among middle-aged and older adults. Design, Setting, and Participants: This cohort study included 174 participants from the Dallas Lifespan Brain Study who were 40 to 89 years old at the beginning of the study, were cognitively normal at baseline (a Mini-Mental State Examination score of 26 or higher) with no history of neurological or psychiatric disorders, and had completed amyloid imaging ([18F]-florbetapir) at baseline and cognitive assessments at baseline and a 4-year follow-up. Continuous amyloid burden was measured as the mean cortical standardized uptake value ratio (SUVR) at baseline. Main Outcomes and Measures: Linear mixed models assessed the effect of increasing baseline amyloid over time (SUVR × time interaction) on episodic memory, reasoning, processing speed, vocabulary, and Mini-Mental State Examination performance. Age, sex, education, apolipoprotein ε4, and the random effect of intercepts were included as covariates. Results: The mean (SD) age for all participants (n = 174) was 66.44 (11.74) years, and 65 participants (37%) were men. The primary analyses yielded significant SUVR × time interactions in episodic memory, processing speed, vocabulary, and Mini-Mental State Examination performance, but not in reasoning performance. Higher baseline SUVR projected greater cognitive decline over 4 years. When controlling for variance related to a dichotomized positive/negative classification, most effects on cognition remained. Dichotomized amyloid status alone yielded fewer significant effects of amyloid on cognitive decline than continuous SUVR. Among amyloid-positive participants, increasing baseline SUVR predicted an increasing decline in episodic memory, but other effects on cognition were more limited. Finally, higher baseline amyloid burden among middle-aged adults was related to changes in vocabulary, with the effect driven by 3 apolipoprotein ε4 homozygotes. Conclusions and Relevance: These results suggest that the magnitude of amyloid burden at baseline is associated with the rate of cognitive decline over 4 years and potentially provides important information about the rate of future cognitive decline that is not available from a dichotomous positive/negative categorization.

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)0.002
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.296
Teacher spread0.279 · 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

Citations106
Published2017
Admission routes1
Has abstractyes

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