Age and Life-Sustaining Treatment Preferences in Parkinson Disease
Bibliographic record
Abstract
OBJECTIVE: Advance Care Planning (ACP) is one of 10 key elements in the American Academy of Neurology Parkinson disease (PD) clinical practice quality measures. We know little about how aging influences ACP views in people with PD. METHODS: We conducted a cross-sectional survey of 39 participants (mean age 70.3 years; range: 52-81) with PD to explore correlations between older age and life-sustaining treatment preferences while controlling for confounders including years of education, Montreal Cognitive Assessment score and Movement Disorders Society Unified Parkinson's disease Rating Scale motor score. Scenarios asked participants to choose their level of interest in pursuing life-sustaining measures in the setting of specific medical illnesses including stroke, metastatic cancer, severe heart attack, and dementia. All participants were men and were recruited from the Veterans Affairs Ann Arbor Healthcare System. RESULTS: In the hypothetical stroke, metastatic colon cancer, and dementia scenarios, older age correlated with more aggressive care goals related to the use cardiopulmonary resuscitation to treat cardiopulmonary arrest. CONCLUSIONS: Advancing age in PD may correlate with paradoxically more aggressive goals as it relates to life-sustaining treatment preferences including cardiopulmonary resuscitation. This may reflect a response to heightened concern among older adults with PD about the potential for compromised autonomy in the setting of aging.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".