The Scottish Intercollegiate Guidelines Network: risk reduction and management of delirium
Bibliographic record
Abstract
Clinical and research interest in delirium has been rising over the last 15 years. The Scottish Intercollegiate Guidelines Network (SIGN) publication on delirium is a state-of-the-art synthesis of the field, and the first UK guideline since 2010. There is new guidance around delirium detection, particularly in recommending the 4 'A's Test (4AT). The 4AT has the advantage of being brief, embeds and operationalises cognitive testing, and is scalable with little training. The guidelines highlight the importance of non-pharmacological management for all hospital presentations involving the spectrum of cognitive disorders (delirium, dementia but at risk of delirium, delirium superimposed on dementia). Pharmacotherapy has a minimal role, but specific indications (e.g. intractable distress) are discussed. Advances in delirium research, education and policy, have come together with steady changes in the sociocultural context in which healthcare systems look after older people with cognitive impairment. However, there remains a gap between desired and actual clinical practice, one which might be bridged by re-engaging with compassionate, patient-centred care. In this respect, these SIGN guidelines offer a key resource.
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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 | 0.034 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".