Progress on the Development of the Lewy Body Dementia‐Domain Rating Scale
Bibliographic record
Abstract
Abstract Background No specific clinical rating scale currently exists for Lewy body dementia (LBD). Clinical rating scales developed for other diseases are therefore used instead for LBD clinical trials. However, these scales are not optimized for LBD and may not sufficiently reflect the complex array of LBD‐related phenomenology, making it more difficult to interpret outcome data from LBD clinical trials. Method A working group comprised of 14 members bridging various international LBD‐focused research groups was convened to develop the first iteration of the LBD‐DRS with a focus on inclusion of key LBD related symptom domains, ensuring that any scale is mapped to regulatory expectations, and an emphasis on being patient‐centered. This draft was then subsequently presented to a broader stakeholder group (»50 participants) at the International Lewy body Dementia Conference in June 2022 for further feedback, leading to a further iteration of the scale. Result The LBD‐DRS has been designed to capture ratings of the frequency and severity of symptoms across the key domains relevant to LBD – cognitive, neuropsychiatric, motor, autonomic and sleep – as well as the functional impact and perceived burden of symptoms for patients and their care partners. An international Delphi exercise is now planned with many LBD‐relevant stakeholders, which will be coupled with workgroup engagement (for example, with patient‐caregiver groups) to further develop the scale with the resulting final draft anticipated for pilot use in the near future. Conclusions In this presentation we will elaborate on the development of the scale, key areas that it will cover as well as challenge points and next steps. Upon completion of the development and refinement of the LBD‐DRS, we propose that this scale will have utility as valid and LBD specific outcome measure in LBD clinical trials.
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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 | 0.056 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".