End-of-life issues in advanced dementia: Part 1: goals of care, decision-making process, and family education.
Bibliographic record
Abstract
OBJECTIVE: To review the issues with setting goals of care for patients with advanced dementia, describe the respective roles of the physician and the patient's family in the decision-making process, and suggest ways to support families who need more information about the care options. SOURCES OF INFORMATION: Ovid MEDLINE was searched for relevant articles that were published before March 7, 2014. There were no level I studies identified; most articles provided level III evidence. MAIN MESSAGE: For patients with advanced dementia, their families have an important role in medical decision making. Families should receive timely information about the course of dementia and the care options. They need to understand that a palliative approach to care might be appropriate and does not mean abandonment of the patient. They might also want clarification about their role in the decision-making process, especially if withholding or withdrawing life-prolonging measures are considered. CONCLUSION: Physicians should consider advanced dementia as a terminal disease for which there is a continuum of care that goes from palliative care with life-extending measures to symptomatic interventions only. Clarification of goals of care and family education are of paramount importance to avoid unwanted and burdensome interventions.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".