Diagnosis and treatment of dementia: 6. Management of severe Alzheimer disease
Bibliographic record
Abstract
BACKGROUND: The management of severe Alzheimer disease often presents difficult choices for clinicians and families. The disease is characterized by a need for full-time care and assistance with basic activities of daily living. We outline an evidence-based approach for these choices based on recommendations from the Third Canadian Consensus Conference on the Diagnosis and Treatment of Dementia. METHODS: We developed evidence-based guidelines using systematic literature searches, with specific criteria for the selection and quality assessment of articles, and a clear and transparent decision-making process. We selected articles published from January 1996 to December 2005 that dealt with the management of severe Alzheimer disease. Subsequent to the conference, we searched for additional articles published from January 2006 to March 2008 using the same search terms. We graded the strength of the evidence using the criteria of the Canadian Task Force on Preventive Health Care. RESULTS: We identified 940 articles, of which 838 were selected for further study. Thirty-four articles were judged to be of at least good or fair quality and were used to generate 17 recommendations. Assessment of severe Alzheimer disease should include the measurement of cognitive function and the assessment of behaviour, function, medical status, nutrition, safety and caregiver status. Management could include treatment with a cholinesterase inhibitor or memantine, or both. Treatment of neuropsychiatric symptoms begins with nonpharmacologic approaches to addressing behavioural problems. Severe agitation, aggression and psychosis, which are potentially dangerous to the patient, the caregiver and others in the environment, can be treated with atypical antipsychotics, with consideration of their increased risk of cerebrovascular events and death. All pharmacologic approaches require careful monitoring and periodic reassessment to determine whether continued treatment is necessary. Caregiver support and use of community resources are essential. INTERPRETATION: Severe Alzheimer disease requires frequent monitoring by health professionals. Simple nonpharmacologic approaches may address problems with mood and agitation. Antipsychotic drug therapy is occasionally necessary despite the inherent risks. Therapy with a cholinesterase inhibitor and memantine may be useful for selected patients.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".