MétaCan
Menu
Back to cohort
Record W3203670526 · doi:10.3390/curroncol28050339

Cognitive Assessment Tools Recommended in Geriatric Oncology Guidelines: A Rapid Review

2021· review· en· W3203670526 on OpenAlex
Gina Tuch, Wee Kheng Soo, Ki-Yung Luo, Kinglsey Frearson, Ek Leone Oh, Jane Phillips, Meera Agar, Heather Lane

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.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCurrent Oncology · 2021
Typereview
Languageen
FieldMedicine
TopicCancer-related cognitive impairment studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGeriatric oncologyCognitionMedical physicsOncologyInternal medicineCancerPsychiatry

Abstract

fetched live from OpenAlex

Cognitive assessment is a cornerstone of geriatric care. Cognitive impairment has the potential to significantly impact multiple phases of a person's cancer care experience. Accurately identifying this vulnerability is a challenge for many cancer care clinicians, thus the use of validated cognitive assessment tools are recommended. As international cancer guidelines for older adults recommend Geriatric Assessment (GA) which includes an evaluation of cognition, clinicians need to be familiar with the overall interpretation of the commonly used cognitive assessment tools. This rapid review investigated the cognitive assessment tools that were most frequently recommended by Geriatric Oncology guidelines: Blessed Orientation-Memory-Concentration test (BOMC), Clock Drawing Test (CDT), Mini-Cog, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Short Portable Mental Status Questionnaire (SPMSQ). A detailed appraisal of the strengths and limitations of each tool was conducted, with a focus on practical aspects of implementing cognitive assessment tools into real-world clinical settings. Finally, recommendations on choosing an assessment tool and the additional considerations beyond screening are discussed.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.806
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.495
GPT teacher head0.591
Teacher spread0.097 · 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