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Record W4312087827 · doi:10.1002/alz.062560

Diagnosing Alzheimer Disease: Which Dementia Screening Tool to Use in Elderly Puerto Ricans with Mild Cognitive Impairment and Early Alzheimer Disease?

2022· article· en· W4312087827 on OpenAlexaboutno aff
María Rodríguez-Santiago, Vanessa Sepulveda, Eric Miranda Valentin, Steven E. Arnold, Ivonne Z. Jiménez‐Velázquez, Valerie Wojna

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsClinical Dementia RatingDementiaMontreal Cognitive AssessmentDiseaseCognitive impairmentInternal medicineCorrelationCognitionMedicineAlzheimer's diseaseMemory clinicRating scalePsychologyAudiologyGerontologyClinical psychologyPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Background Most of the time, Alzheimer Disease (AD)’s diagnosis is not made at its earliest periods and prodromal stages, for instance at Mild Cognitive Impairment (MCI) and Early Alzheimer Disease (E‐AD) stage. Commonly, AD’s diagnosis is made when significant impairment interferes with the habitual daily activities (1). Our pilot study, serves to demonstrate a correlation between the screening tools, including the Mini‐mental Status Exam (MMSE), Montreal Cognitive Assessment (MoCA) and Clinical Dementia Rating Scale (CDR), and the biological biomarkers in the cerebral spinal fluid (CSF) (Amyloid Beta 1‐42 (Aβ42 pg/mL), Tau proteins (tTau (pg/mL) and tTau/Aβ42 ratio in Puerto Ricans > 55 years old with MCI and E‐AD. To our knowledge, this is the first study trying to create a correlation between memory tests scores and underlying AD pathology to improve early detection in elderly Puerto Ricans. Method Thirty participants were evaluated including, demographics, clinical characteristics, memory scales and CSF biomarkers. CSF biomarkers (Aβ42, tTau protein, and tTau/Aβ42 ratio) were determined using the Meso Scale Discovery Platform (MSD). Associations between memory scales (MOCA, MMSE, CDR) and CSF markers were performed using Spearman’s rho correlation. Result Our study revealed statistical association in favor of a direct relationship between MMSE and tTau/Aβ42 ratio in CSF (p= .022, 95.00% CI = [‐.69, ‐.07] (Figure 1). We found a trend towards significance with an inverse relationship with MMSE and Aβ42 (p=.069) (Figure 2) and a direct relationship with MMSE and tTau (p= .098) (Figure 3). Besides, MoCA and tTau/Aβ42 ratio had a statistically significant direct relationship (p = 0.035) (Figure 4). There was no significant statistical association between CDR test with CSF biomarkers in elderly Puerto Ricans. Conclusion MMSE was the dementia screening test consistently identifying a statistically significant or a‐trend‐towards a significant association with the CSF Alzheimer Disease’ s biomarkers (Aβ42, tTau protein, and tTau/Aβ42 ratio) in elderly Puerto Ricans with MCI and E‐AD. Clinically, > 55 y/o Puerto Rican patients with MCI and E‐AD should be screened with MMSE for a higher likelihood of earlier detection and, thus, initiation of disease‐modifying treatment.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.300
Teacher spread0.263 · 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 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
Published2022
Admission routes1
Has abstractyes

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