Reliability and Validity of the Clinical Dementia Rating for Community-Living Elderly Subjects without an Informant
Bibliographic record
Abstract
BACKGROUND: The Clinical Dementia Rating (CDR) scale is widely used to assess cognitive impairment in Alzheimer's disease. It requires collateral information from a reliable informant who is not available in many instances. We adapted the original CDR scale for use with elderly subjects without an informant (CDR-NI) and evaluated its reliability and validity for assessing mild cognitive impairment (MCI) and dementia among community-dwelling elderly subjects. METHOD: At two consecutive visits 1 week apart, nurses trained in CDR assessment interviewed, observed and rated cognitive and functional performance according to a protocol in 90 elderly subjects with suboptimal cognitive performance [Mini-Mental State Examination (MMSE) <26 and/or Montreal Cognitive Assessment (MOCA) <26] and without informants according to a protocol. CDR domains and global scores were assigned after the second visit based upon corroborative information from the subjects' responses to questions, role-play, and observed performance in specifically assigned tasks at home and within the community. RESULTS: The CDR-NI scores (0, 0.5, 1) showed good internal consistency (Crohnbach's α 0.83-0.84), inter-rater reliability (κ 0.77-1.00 for six domains and 0.95 for global rating) and test-retest reliability (κ 0.75-1.00 for six domains and 0.80 for global rating), good agreement (κ 0.79) with the clinical assessment status of MCI (n = 37) and dementia (n = 4) and significant differences in the mean scores for MMSE, MOCA and Instrumental Activities of Daily Living (ANOVA global p < 0.001). CONCLUSION: Owing to the protocol of the interviews, assessments and structured observations gathered during the two visits, CDR-NI provides valid and reliable assessment of MCI and dementia in community-living elderly subjects without an informant.
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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 | 0.023 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".