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Record W3049234056 · doi:10.3389/fnagi.2020.00190

Osteoarthritis Was Associated With a Faster Decline in Hippocampal Volumes in Cognitively Normal Older People

2020· article· en· W3049234056 on OpenAlexfundno aff
Xiang Li, Qiaowen Tong, Jianqing Gao, Cailong Liu

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2020
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationF. Hoffmann-La RocheUniversity of Southern CaliforniaBiogenEli Lilly and CompanyBristol-Myers SquibbBioClinicaU.S. Department of DefenseMeso Scale DiagnosticsAlzheimer's Disease Neuroimaging InitiativeNovartis Pharmaceuticals CorporationPfizerNational Institute on AgingAlzheimer's Association
KeywordsConfoundingAlzheimer's Disease Neuroimaging InitiativeCognitive declineOsteoarthritisHippocampal formationNeuroimagingLongitudinal studyDementiaMedicineCognitionInternal medicinePsychologyGerontologyDiseasePsychiatryPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: ) over time among cognitively normal older people. METHODS: We examined the cross-sectional and longitudinal associations of OA with HpVR among individuals with normal cognition (NC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. At baseline, a total of 372 individuals with NC were included. RESULTS: In the cross-sectional analyses of baseline data, we did not find a significant relationship between OA and HpVR among individuals with NC. However, in the longitudinal analyses, OA was significantly associated with change in HpVR over time among individuals with NC. Specifically, compared with individuals without OA, those with OA showed a faster decline in HpVR over time when controlling for other potential confounders, including age, educational attainment, gender, and APOE4 genotype. CONCLUSION: OA status was significantly associated with a change in HpVR over time among individuals with NC.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.859

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)0.0000.000

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 head0.013
GPT teacher head0.233
Teacher spread0.219 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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