[The Swiss Memory Clinics recommendations for the diagnosis of dementia - an update].
Bibliographic record
Abstract
INTRODUCTION: The early and accurate diagnosis is the basic prerequisite for timely, targeted and individually tailored counselling, treatment and support for people developing cognitive impairment. The association Swiss Memory Clinics (SMC) has elaborated detailed quality standards for the assessment of cognitive disorders, published them for the first time in 2018 and updated them in 2024. These recommendations present the current diagnostic guidelines and examination options, along with proposed standards for the relevant procedures. Single areas such as anamnesis, clinical examination, laboratory assessments, neuropsychological testing and neuroradiological procedures are discussed as part of the standard diagnostics and the complementary investigation methods for differential diagnostics. Furthermore, the disclosure of the diagnosis and counselling are now described as an integral part of the diagnostic process. The most important objectives of the recommendations for the diagnosis of dementia disorders remain to enable high-quality early and accurate diagnostics of cognitive disorders throughout Switzerland; and to provide a practical guide for clinicians in primary care and memory clinics.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".