Estimating severity of illness and disability in Frontotemporal Dementia: Preliminary analysis of the Dementia Disability Rating (DDR).
Bibliographic record
Abstract
BACKGROUND: Current measures of severity and disability do not stage or track the progression of disability in frontotemporal dementia (FTD) well. We investigated the reliability of the newly developed Dementia Disability Rating (DDR) in the measurement and staging of illness severity in FTD and dementia of the Alzheimer type (DAT). MATERIAL/ METHODS: We studied 48 consecutive patients of the Johns Hopkins FTD and Young-Onset Dementias Clinic, with diagnoses of DAT, FTD, vascular dementia and "other" cognitive disorder (CDNOS). Cases were scored on the CDR and DDR by three trained raters, based on neuropsychiatric examinations performed at first visit and other assessments performed within the preceding year. Consensus ratings were assigned in conference. RESULTS: Inter-rater correlations of DDR sum of ranks scores for DAT ranged from 0.88 to 0.91, for FTD 0.89-0.96 and for CDNOS 0.85-0.97. Similar correlations were observed of the CDR sum of rank scores for DAT and FTD. Correlations of DDR summary scores for DAT were 0.67-0.91 and for FTD 0.79-0.91, as compared to CDR data: 0.87-0.92 (p<0.0001) and 0.80-0.93 (p<0.0001) for DAT and FTD respectively. In DAT patients the correlation between CDR and DDR summary scores was higher than in FTD patients, whereas correlations based on sum of ranks scores were high in both groups. CONCLUSIONS: These preliminary data indicate the DDR measures disability in DAT and FTD, with reliability comparable to the CDR. Convergent validity was demonstrated for the DDR.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".