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Record W4307178533 · doi:10.1001/jamaneurol.2022.3472

Frequency and Underlying Pathology of Pure Vascular Cognitive Impairment

2022· article· en· W4307178533 on OpenAlex
Shahram Oveisgharan, Robert J. Dawe, Lei Yu, Alifiya Kapasi, Konstantinos Arfanakis, Vladimir Hachinski, Julie A. Schneider, David A. Bennett

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Neurology · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsWestern University
FundersNational Institute on Aging
KeywordsPathologicalDementiaMedicineNeuropsychologyAutopsyDiseaseCognitionOdds ratioNeuropathologyInternal medicineCognitive impairmentVascular dementiaPathologyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Importance: It is not clear how common pure vascular cognitive impairment (VCI) is in the absence of Alzheimer disease (AD) and/or other neurodegenerative pathologies. Objective: To identify participants without AD and other neurodegenerative pathologies and determine the extent to which cerebrovascular disease pathologies were associated with cognitive impairment. Design, Setting, and Participants: This clinical pathological study included participants from 2 ongoing community-based cohorts that began enrollment in 1994 and 1997. Prior to death, participants were observed for a mean (SD) of 8.4 (5.3) years with annual assessments. From 2096 participants who died, 1799 (85.8%) underwent autopsy and 1767 had complete postmortem pathological examination data at the time of data analyses. To identify participants without neurodegenerative pathologies, we categorized them in 3 subgroups. A vascular subgroup was composed of participants without significant levels of neurodegenerative brain pathologies. A neurodegenerative subgroup was composed of participants without significant levels of cerebrovascular disease pathologies. A mixed subgroup was composed of the rest of the participants. Data were analyzed from May 2021 to July 2022. Exposures: Brain pathology indices obtained by postmortem pathological assessments. Main Outcomes and Measures: The primary outcome was cognitive impairment defined by presence of mild cognitive impairment or dementia. The secondary outcome was cognition assessed by 19 neuropsychological tests. Results: Of 1767 included participants, 1189 (67.3%) were women, and the mean (SD) age at death was 89.4 (6.6) years. In the vascular subgroup (n = 369), cognitive impairment was present in 156 participants (42.3%) and was associated with cerebrovascular disease pathologies (macroinfarcts: odds ratio [OR], 2.05; 95% CI, 1.49-2.82; P < .001; arteriolosclerosis in basal ganglia: OR, 1.35; 95% CI, 1.04-1.76; P = .03) but not AD or other neurodegenerative pathologies, an indication of pure VCI. In mixed-effects models including all the pathologies, only macroinfarcts were associated with a faster cognitive decline rate (estimate, -0.019; SE, 0.005; P < .001) in the vascular subgroup. Further analyses identified macroinfarcts in the frontal white matter to be associated with faster cognitive decline rate when macroinfarcts of cortical and subcortical brain regions were examined in a single model. Conclusions and Relevance: In this study, pure VCI was not rare. Macroinfarcts, specifically in frontal white matter, were the main cerebrovascular disease pathologies associated with cognitive decline in pure VCI.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.305
Teacher spread0.281 · 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