P3–072: Mild cognitive impairment – the danger of basing the diagnosis on published normative groups
Bibliographic record
Abstract
The value of published neuropsychological normative values has become a recent focus of attention, since many researchers want to define MCI in terms of 1.0 s.d. or 1.5 s.d. below means for published normal controls on standardized neuropsychological tests. The most widely used tests and batteries (WAIS, WMS–R, Boston Naming Test) acquired population norms from large mixed American populations with varying educational background. But how closely do these published norms reflect the reality in the local urban elderly multicultural population of Montreal, Canada who are assessed in our Memory Clinic? To evaluate the local normative population, and assess to what degree MCI based on their values would differ from MCI based on published norms. We carried out a slightly modified neuropsychological battery in 118 volunteer community subjects screened by a physician and judged to be neuropsychologically normal. We compared their results with published norms. A cohort of 60 patients judged as meeting criteria for MCI clinically were evaluated against both sets of normative stimuli. Our normal control group deviates significantly from published norms for virtually all tests utilized. Minor variation in technique (eg, we do the Logical Memory with one story and double the score) was perhaps contributive to one score difference. Almost all our normal controls exceeded published norms on construction and executive function tasks, sometimes by several standard deviations. Results on BNT were lower than published norms. These results are explained by cultural and educational factors such as multilingualism. The overall impact was that the degree of short term memory loss in our MCI cohort was much greater (mean 1.8 SD vs. 1.1 SD) when local normals were utilized. Furthermore, most were judged as multiple domain involvement rather than strictly amnestic loss when local norms were used. The sum effect is that published norms may be substantially different from the local community base. It is proposed that normative means and standard deviations may need to be checked locally before coherence with published norms is assumed. Basing a diagnosis of MCI on published norms (rather than clinical evaluation) will underestimate the impairment of many MCI patients.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".