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Record W4283764603 · doi:10.1007/s40120-022-00379-z

Clinical Staging of Alzheimer’s Disease: Concordance of Subjective and Objective Assessments in the Veteran’s Affairs Healthcare System

2022· article· en· W4283764603 on OpenAlex
Peter J. Morin, Mingfei Li, Ying Wang, Byron J. Aguilar, Dan R. Berlowitz, Amir Abbas Tahami Monfared, Michael C. Irizarry, Quanwu Zhang, Weiming Xia

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNeurology and Therapy · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
FundersEisai IncorporatedNational Institute on AgingNational Institutes of HealthEisaiU.S. Department of Veterans Affairs
KeywordsConcordanceMedicineVeterans AffairsNeurologyHealth careDiseaseHealthcare systemGerontologyFamily medicinePsychiatryPathologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Uncertainty surrounding the accurate assessment of the early-stage Alzheimer's disease (AD) may cause delayed care and inappropriate patient access to new AD therapies. METHODS: To analyze clinical assessments of patients with AD in the Veteran's Affairs (VA) Healthcare System and evaluate concordance between subjective and objective assessments, we processed clinical notes extracted by text integration utilities between April 1, 2008 and October 14, 2021. Veterans who had mild, moderate, or severe AD with clinical notes documenting both clinician's judgement of AD severity and objective test scores from the Mini-Mental State Examination or the Montreal Cognitive Assessment were included. Using clinician-defined severity cohorts, we determined concordance between the clinician's (subjective) assessments and the test-derived (objective) assessments of AD severity. Concordance was assessed over time and by selected symptoms and comorbidities, as well as healthcare system factors. RESULTS: A total of 8888 notes were initially extracted; the final analysis sample included 7514 notes corresponding to 4469 unique patients (mean [standard deviation] age of 78 [9] years; 96.5% male; 77.8% White). Subjective and objective assessments were concordant in approximately half (53%) of overall notes. In the mild Alzheimer's cohort, patients were assessed to have more severe disease by objective test scores in 40% of notes. Concordance varied about 21-73%, 47-58%, and 40-64% across symptoms/comorbidities, clinician types, and Veteran's Integrated Service Networks, respectively. The proportion of concordant notes was higher in visits to dementia (61%) instead of non-dementia clinics (53%). CONCLUSIONS: We found higher concordance between clinician's assessment and test-based assessment of Alzheimer's disease severity in dementia specialty clinics. Discordance is especially high for the subjectively assessed mild AD cohort where objective assessments showed a higher severity level in 40% of notes. These data indicate a critical need for improved understanding of clinical assessments and decision-making to identify appropriate patients for anti-amyloid therapy.

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)0.001
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 score0.013
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.404
Teacher spread0.355 · 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