Association of MBI‐C scores with clinical outomes in patients with MCI during a 3‐year follow‐up
Bibliographic record
Abstract
BACKGROUND: As previously shown, mild behavioral impairment (MBI), characterized by late-life emergent and persistant neuropsychiatric symptoms (NPS) with minimal impact on daily life, is associated with increased dementia risk. Z. Ismail et al. have proposed an informant-based checklist (MBI-C), a 34-item list, structured into 5 domains in accordance with ISTAART criteria, to quantify MBI. This study examines the MBI-C utility in Russian-speaking patients with mild cognitive impairment (MCI). METHOD: Eighty-six patients (age 71 [65;76] years, 70 female) with MCI (according to R. Petersen criteria) underwent a clinical, neuropsychological, and behavioral assessment in a specialized Alzheimer's disease department, with a 3-year follow-up. Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating (CDR), and MBI-C scores were obtained at baseline and follow-up visits. MBI was diagnosed based on ISTAART criteria and with an MBI-C total score of >6. A diagnosis of dementia was based on ICD-10 criteria and CDR total score of >1. Statistical analysis included the Wilcoxon signed-rank test to evaluate differences between two time points, a two-way ANOVA was performed to evaluate the effect of the MBI-C total score over time on conversion to dementia. RESULT: Eighteen patients converted to dementia (16-AD, 2-bvFTD). Converters had significantly higher baseline MBI-C scores (8 [6;15.5]) compared to non-converters (4 [1;10], p = 0.002). Differences were also significant in all domains except affective dysregulation. Pairwise comparisons showed that the mean MBI-C scores in impulse dyscontrol (p = 0.03) and in total (p = 0.009) increased significantly in converters over time. A significant interaction between baseline MBI-C total score and clinical outcome was found (F(1,164) = 56.6, p <0.001) with a large effect size (ges=0.26). While time alone had no effect on MBI-C and conversion, patients with MCI and MBI showed significant MoCA decline (22.6 to 20.6, p = 0.007), unlike MCI-only patients (24.2 to 24.3). CONCLUSION: The MBI-C shows strong utility in a Russian-speaking MCI population. It demonstrates relevance as a sensitive measure of behavioral symptoms that precede dementia. The strong association between baseline MBI-C scores and subsequent decline highlights its predictive power for the progression of neurodegenerative disorders, complementing routine cognitive measures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".