A Scoping Review of Clinical Utility from the Montreal Cognitive Assessment Memory Index Score
Bibliographic record
Abstract
ObjectiveThe Montreal Cognitive Assessment (MoCA) Memory Index Score (MIS) is a supplemental assessment of memory composed of word list delayed free-recall followed by step-down category cued- and multiple-choice cued-recall. This paper reviews the MIS literature within Alzheimer's and other neurodegenerative dementias to synthesize evidence regarding its clinical utility, identify gaps, and inform future research directions.MethodWe searched electronic databases of OVID Medline, Embase, PsycINFO, and PubMed from 2014, when the MIS was first described, to July 2025. Peer-reviewed studies that reported data on the diagnostic or prognostic utility of the MIS in assessing neurodegenerative dementia populations were included.ResultsWe screened 278 articles, and 14 were included in the review. The current literature includes limited reporting on the diagnostic or prognostic utility of the MIS and is characterized by minimal diversity of samples and non-rigorous validation methods. Initial findings are promising and suggestive of incremental validity over the MoCA total score for identifying episodic memory impairment and therefore aiding in differentiation of suspected dementia etiology. However, evidence is insubstantial for the MIS as a tool for predicting progression and additional research is needed to evaluate the incremental validity of the MIS over the conventional MoCA five-word recall score.ConclusionsLarge literature gaps exist regarding the clinical utility of the MIS within neurodegenerative dementias. Additional research exploring the psychometric properties of the MIS using diverse samples with rigorous validation methods is needed to better inform its application.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.135 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.030 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".