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Record W4283796977 · doi:10.3390/medicina58070887

Combined Score of Perivascular Space Dilatation and White Matter Hyperintensities in Patients with Normal Cognition, Mild Cognitive Impairment, and Dementia

2022· article· en· W4283796977 on OpenAlexaboutno aff
Nauris Zdanovskis, Ardis Platkājis, Andrejs Kostiks, Kristı̄ne Šneidere, Ainārs Stepens, Roberts Naglis, Guntis Karelis

Bibliographic record

VenueMedicina · 2022
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
FundersEuropean Social Fund
KeywordsHyperintensityDementiaPerivascular spaceWhite matterMagnetic resonance imagingLeukoaraiosisMedicineMontreal Cognitive AssessmentCardiologyInternal medicinePathologyPsychologyAudiologyRadiologyDisease

Abstract

fetched live from OpenAlex

Background and Objectives: Cerebral perivascular spaces (PVS) are part of the cerebral microvascular structure and play a role in lymphatic drainage and the removal of waste products from the brain. White matter hyperintensities (WMH) are hyperintense lesions on magnetic resonance imaging that are associated with cognitive impairment, dementia, and cerebral vascular disease. WMH and PVS are direct and indirect imaging biomarkers of cerebral microvascular integrity and health. In our research, we evaluated WMH and PVS enlargement in patients with normal cognition (NC), mild cognitive impairment (MCI), and dementia (D). Materials and Methods: In total, 57 participants were included in the study and divided into groups based on neurological evaluation and Montreal Cognitive Assessment results (NC group 16 participants, MCI group 29 participants, D group 12 participants). All participants underwent 3T magnetic resonance imaging. PVS were evaluated in the basal ganglia, centrum semiovale, and midbrain. WMHs were evaluated based on the Fazekas scale and the division between deep white matter (DWM) and periventricular white matter (PVWM). The combined score based on PVS and WMH was evaluated and correlated with the results of the MoCA. Results: We found statistically significant differences between groups on several measures. Centrum semiovale PVS dilatation was more severe in MCI and dementia group and statistically significant differences were found between D-MCI and D-NC pairs. PVWM was more severe in patients with MCI and dementia group, and statistically significant differences were found between D-MCI and D-NC pairs. Furthermore, we found statistically significant differences between the groups by analyzing the combined score of PVS dilatation and WMH. We did not find statistically significant differences between the groups in PVS dilation of the basal ganglia and midbrain and DWM hyperintensities. Conclusions: PVS assessment could become one of neuroimaging biomarkers for patients with cognitive decline. Furthermore, the combined score of WMH and PVS dilatation could facilitate diagnostics of cognitive impairment, but more research is needed with a larger cohort to determine the use of PVS dilatation and the combined score.

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 score0.005
Threshold uncertainty score0.352

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 integrity0.0000.000
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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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
Published2022
Admission routes1
Has abstractyes

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