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Record W4395679494 · doi:10.14283/jpad.2024.82

Predicting Cognitive Decline for Non-Demented Adults with High Burden of Tau Pathology, Independent of Amyloid Status

2024· article· en· W4395679494 on OpenAlexfundno aff
H.-S. Wu, Li Li, Q-Q Sun, C-C Tan, Lan Tan, Weili Xu

Bibliographic record

VenueThe Journal of Prevention of Alzheimer s Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationPfizerNovartis Pharmaceuticals CorporationUniversity of Southern CaliforniaBiogenEli Lilly and CompanyBristol-Myers SquibbBioClinicaU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsAlzheimer's Association
KeywordsAmyloid (mycology)Cognitive declineTau pathologyCognitionMedicineAmyloid βDementiaGerontologyPsychologyPathologyNeuroscienceAlzheimer's diseasePsychiatryDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Abnormal tau proteins are independent contributors to cognitive impairment. Nevertheless, not all individuals exposed to high-level tau pathology will develop cognitive dysfunction. We aimed to construct a model to predict cognitive trajectory for this high-risk population. METHOD: Longitudinal data of 181 non-demented adults (mean age= 73.1; female= 45%), who were determined to have high cerebral burden of abnormal tau by cerebrospinal fluid (CSF) measurements of phosphorylated tau (ptau181) or total tau, were derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Cognitive decline was defined as Mini-Mental State Examination scores decline ≥ 3 over three years. A predictive nomogram was constructed using stepwise backward regression method. The discrimination, calibration, and clinical usefulness of the nomogram were evaluated. The model was validated in another 189 non-demented adults via a cross-sectional set (n=149, mean age = 73.9, female = 51%) and a longitudinal set (n= 40, mean age = 75, female = 48%). Finally, the relationships of the calculated risk scores with cognitive decline and risk of Alzheimer's disease were examined during an extended 8-year follow-up. RESULT: Lower volume of hippocampus (odds ratio [OR] = 0.37, p< 0.001), lower levels of CSF sTREM2 (OR = 0.76, p = 0.003), higher scores of Alzheimer's Disease Assessment Scale-Cognitive (OR = 1.15, p = 0.001) and Functional Activities Questionnaire (OR = 1.16, p = 0.016), and number of APOE ε4 (OR = 1.88, p = 0.039) were associated with higher risk of cognitive decline independent of the amyloid status and were included in the final model. The nomogram had an area of under curve (AUC) value of 0.91 for training set, 0.93 for cross-sectional validation set, and 0.91 for longitudinal validation set. Over the 8-year follow-up, the high-risk group exhibited faster cognitive decline (p< 0.001) and a higher risk of developing Alzheimer's dementia (HR= 6.21, 95% CI= 3.61-10.66, p< 0.001 ). CONCLUSION: APOE ε4 status, brain reserve capability, neuroinflammatory marker, and neuropsychological scores can help predict cognitive decline in non-demented adults with high burden of tau pathology, independent of the presence of amyloid pathology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.399
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.330
Teacher spread0.312 · 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.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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