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Record W4390191938 · doi:10.1002/alz.083098

Are there baseline structural MRI differences between individuals who progress along the Alzheimer’s disease continuum and those who remain cognitively stable? A systematic review

2023· review· en· W4390191938 on OpenAlexaff
Nazanin Saadat, Ashleigh F. Parker, Heather Kwan, Riley Grewcock, Jodie R. Gawryluk

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAlzheimer's Disease Neuroimaging InitiativeCognitionNeuroimagingPsycINFOMagnetic resonance imagingDiseasePsychologyDementiaNeurodegenerationMedicineNeuroscienceCognitive impairmentMEDLINEClinical psychologyPathologyRadiology

Abstract

fetched live from OpenAlex

Abstract Background Early identification of individuals that will progress along the continuum from normal cognition to mild cognitive impairment (MCI) and to Alzheimer’s disease (AD) is imperative for timely prevention and intervention measures. Structural magnetic resonance imaging (MRI) is a non‐invasive technique commonly used to examine neurodegeneration. The current review summarizes the literature on structural brain differences between individuals who experience conversion to MCI from normal cognition or AD from MCI and those who remain stable. Method Medline and PsycINFO databases were searched for studies that compared baseline structural MRI of individuals who converted from normal cognition to MCI, or from MCI to AD, to those with normal cognition or MCI who remained cognitively stable. Inclusion criteria included studies with baseline structural MRI, cognitive follow‐up to assess conversion/stability, and comparison between converters and non‐converters. Two authors reviewed each abstract and a third review resolved any conflicts. The same process was used for full‐text articles. Information regarding sample size, acquisition and analysis and results were extracted and all studies were reviewed for quality using the AXIS tool. Result A total of 1670 studies were imported for screening in Covidence and 440 duplicates were removed. Following abstract screening, 293 studies were eligible for full‐text review. Many of the identified studies took a region of interest approach focused on hippocampal volume and found significant differences between converters and non‐converters. Many studies used multi‐site, multimodal databases (e.g., Alzheimer’s Disease Neuroimaging Initiative) to retrospectively examine converters and non‐converters. Many more studies looked at individuals who converted from MCI to AD than normal cognition to MCI. Further analyses of the full text review and findings will be presented. Conclusion Characterization of baseline differences in brain structure between those who progress on the AD continuum and those who remain stable is crucial for early diagnosis and treatment. The current review indicates that such differences are evident on structural MRI. The medial temporal lobes have been identified as a region of interest. However, it will be important for future research to use a whole brain approach and for further examination of individuals who convert from normal cognition to MCI.

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)0.011
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0110.009
Bibliometrics0.0110.011
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.099
GPT teacher head0.384
Teacher spread0.284 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2023
Admission routes1
Has abstractyes

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