MétaCan
Menu
Back to cohort
Record W4309018312 · doi:10.1093/neuonc/noac209.572

INNV-32. COMPARING THE MONTREAL COGNITIVE ASSESSMENT (MOCA) FULL AND 5-MINUTE PROTOCOLS IN MILD COGNITIVE IMPAIRMENT SCREENING OF ADULT CNS TUMOR PATIENTS

2022· article· en· W4309018312 on OpenAlexaboutno aff
Yeonju Kim, James L. Rogers, Varna Jammula, Elizabeth Vera, Alexa Christ, Heather Leeper, Alvina Acquaye, Lisa Boris, Nicole Briceno, Eric Burton, Anna Choi, Ewa Grajkowska, Edina Komlódi-Pásztor, Jason Levine, Matthew Lindsley, Nicole Lollo, Marissa Panzer, Marta Peñas-Prado, Valentina Pillai, Lily Polskin, Jennifer Reyes, Kayla Roche, Matthew Smith-Cohn, Brett Theeler, Jing Wu, Mark Gilbert, Terri S. Armstrong

Bibliographic record

VenueNeuro-Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineCognitive impairmentCognitionInternal medicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Mild cognitive impairment (MCI) commonly occurs in primary CNS tumor patients (PCTP). Our group and others have reported on the Montreal Cognitive Assessment (MoCA) as an MCI screening tool. Several abbreviated MoCA protocols have been developed for telehealth administration in other neurological diseases, with varied literature on scoring and clinical utility. We compared MoCA Full and 5-minute scores to assess utility in neuro-oncology. METHODS 71 PCTP completed the MoCA Full (abnormal: < 26/30) assessing: visuospatial/executive functioning, naming, memory, attention, language, abstraction, delayed recall, and orientation. Full scores were retrospectively recoded to the Pendlebury MoCA 5-minute protocol (abnormal: < 10/12) assessing: memory, delayed recall, and orientation. Correlation was assessed using Pearson’s coefficient. Disagreements between tests were examined using t-test and chi-square test. RESULTS Patients were primarily White (83%), college-educated (71%) males (54%) diagnosed with glioblastoma (20%), with average age of 43 years (range: 19-75), KPS > 80 (57%), prior radiation treatment (78%), and imaging surveillance at time of testing (79%). MoCA Full and 5-minute mean scores were 25.3 (SD: 4.8) and 9.9 (SD: 2.3), respectively. MCI was indicated in 32% (n= 23) of patients using MoCA Full and 27% (n= 19) using MoCA 5-minute. Where the protocols disagreed, MCI was detected only by MoCA Full in 6 patients (8%), and MoCA 5-minute in 2 patients (3%). Visuospatial/executive (p= 0.025) and abstraction (p< 0.001) subdomain scores, unique to MoCA Full, were significantly associated with MCI detected only by the MoCA Full; other subdomains, patient characteristics, and total score were not significant. The MoCA versions were highly correlated (r= 0.90). CONCLUSION High correlation and agreement between MoCA Full and 5-minute scores in this neuro-oncology patient population highlight potential telehealth utility of the MoCA 5-minute. Future prospective assessment of the MoCA 5-minute is warranted to describe optimal scoring threshold and utility in neuro-oncology.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.033
GPT teacher head0.333
Teacher spread0.301 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNeuro-OncologySame topicGlioma Diagnosis and TreatmentFrench-language works237,207