Management of behavioral problems in Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is a complex progressive brain degenerative disorder that has effects on multiple cerebral systems. In addition to cognitive and functional decline, diverse behavioral changes manifest with increasing severity over time, presenting significant management challenges for caregivers and health care professionals. Almost all patients with AD are affected by neuropsychiatric symptoms at some point during their illness; in some cases, symptoms occur prior to diagnosis of the dementia syndrome. Further, behavioral factors have been identified, which may have their origins in particular neurobiological processes, and respond to particular management strategies. Improved clarification of causes, triggers, and presentation of neuropsychiatric symptoms will guide both research and clinical decision-making. Measurement of neuropsychiatric symptoms in AD is most commonly by means of the Neuropsychiatric Inventory; its utility and future development are discussed, as are the limitations and difficulties encountered when quantifying behavioral responses in clinical trials. Evidence from clinical trials of both non-pharmacological and pharmacological treatments, and from neurobiological studies, provides a range of management options that can be tailored to individual needs. We suggest that non-pharmacological interventions (including psychosocial/psychological counseling, interpersonal management and environmental management) should be attempted first, followed by the least harmful medication for the shortest time possible. Pharmacological treatment options, such as antipsychotics, antidepressants, anticonvulsants, cholinesterase inhibitors and memantine, need careful consideration of the benefits and limitations of each drug class.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".