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Record W4390193441 · doi:10.1002/alz.073080

Alabama Brief Cognitive Screener scores correlate proportionally with MoCA and DRS‐2 scores and vary appropriately by diagnosis

2023· article· en· W4390193441 on OpenAlexaboutno aff
Giovanna Pilonieta, Charles Murchison, Marissa C. Natelson Love

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentClinical Dementia RatingDementiaCognitionMedicineRating scaleCognitive impairmentPsychologyGerontologyInternal medicineClinical psychologyPsychiatryDiseaseDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Background The Alabama Brief Cognitive Screener (ABCs) was developed as a nonproprietary replacement for the MMSE (Mini‐Mental State Examination) in order to screen for cognitive deficits. It requires 5‐10 minutes to complete and participants can score up to 30 points. Method To assess the clinical correspondence of Alabama Brief Cognitive Screener (ABCs) scores relative to both the Montreal Cognitive Assessment (MoCA) and Dementia Rating Scale (DRS‐2) and also compare score differences by education attainment and the subject’s clinical diagnosis‐ of either Normal Cognition (NC), Mild Cognitive Impairment (MCI), or Dementia. Participants from the UAB Alzheimer’s Disease Center (ADC) from 2018 to 2022 were analyzed retrospectively. The ABCs, MoCA, and DRS‐2 were administered at the initial visit to subjects (n = 116) and their scores were compared to each other using Spearman’s rank correlation along with their clinical diagnosis which included NC (n = 47), MCI (n = 41) and Dementia (n = 28) and their previous education using the Kruskal‐Wallis test. Result Median scores for all three assessments were found to be associated with clinical diagnosis (MoCA: χ2 = 62.3, p = <.0001; ABCs: χ2 = 51.3, p = <.0001; DRS‐2: χ2 = 56.5, p = <.0001) and education level (MoCA: χ2 = 24.8 p = <.0001; ABCs: χ2 = 18.1, p = 0.0001; DRS‐2: χ2 = 11.15, p = 0.0038). Cognitive differences observed higher scores in the cognitively unimpaired relative to either MCI or subjects with dementia and in subjects with college or graduate degrees compared to those with only a high school education. Strong correspondence was observed between all assessments with significant correlations for all pairwise comparisons (MoCA v ABCs: ρ = 0.73; MoCA v DRS‐2: ρ = 0.72; ABCs v DRS‐2: ρ = 0.61, p = <.0001). When comparing sub‐types of the ABCs and DRS‐2, significant correlations were observed in the domains of memory (ρ = 0.61, p<0.001), attention (ρ = 0.26, p = 0.0054), construction (ρ = 0.37, p<0.001), and conceptualization (ρ = 0.30, p = 0.011). Conclusion ABCs correlates proportionally with MoCA and DRS‐2 scores while also varying appropriately by diagnosis. ABCs shows promise as a non‐proprietary alternative to the MMSE for use as a screening instrument to identify and assess severity of cognitive deficits in medical practice, as well as measure progression of those deficits in patients with neurodegenerative disease.

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)0.005
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
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.285
Teacher spread0.262 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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