Functional deficits among patients with mild cognitive impairment
Bibliographic record
Abstract
BACKGROUND: Diagnostic criteria for mild cognitive impairment (MCI) include no significant functional decline, but recent studies have suggested that subtle deficits often exist. It is not known whether these differ by MCI type. We investigated the level and type of functional impairment among patients with MCI. METHODS: We studied 498 patients, evaluated at the Alzheimer's Disease Research Centers of California between 2006 and 2009, who had multidisciplinary evaluations by experts, including neurologic examination and neuropsychological testing. Patients were diagnosed with MCI and subtype was determined using cognitive domain scores. In a cross-sectional descriptive study, we examined whether functional impairment differed by MCI subtype, using the Blessed Roth Dementia Rating Scale (range: 0-17, higher scores indicating more impairment). RESULTS: Among the participants, the mean age was 75.4 years, 50.7% were women, and 81.7% were white. Patients with amnestic- (n = 392, 78.7%) and nonamnestic-type (n = 106, 21.3%) MCI had similar total Blessed Roth Dementia Rating Scale (1.6 and 1.5, respectively; P = .84) and Mini-Mental State Examination (26.5 and 26.7, respectively; P = .60) scores. Patients with amnestic MCI were more likely to have difficulty in remembering lists and recalling recent events (P < .05 for both) and less likely to have difficulty in eating and with continence (P = .01 for both), as compared with those with nonamnestic MCI. CONCLUSIONS: Despite the MCI diagnostic criteria suggesting no functional impairment, our results indicate that patients with MCI experience mild functional deficits that vary according to the type of MCI.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".