Place of death of people living with Parkinson’s disease: a population-level study in 11 countries
Bibliographic record
Abstract
BACKGROUND: Most people prefer to receive end-of-life care in familiar surroundings rather than in hospital. This study examines variation in place of death for people dying from Parkinson's disease (PD) across 11 European and non-European countries. METHODS: Using death certificate data of 2008 for Belgium, France, Italy, Hungary, Czech Republic, New Zealand, USA, Canada, Mexico, South Korea and Spain for all deaths with PD as an underlying cause (ICD-10 code: G20) cross-national differences in place of death were examined. Associations between place of death and patient socio-demographic and regional characteristics were evaluated using multivariable binary logistic regression analyses. RESULTS: The proportion of deaths in hospital ranged from 17% in the USA to 75% in South Korea. Hospital was the most prevalent place of death in France (40%), Hungary (60%) and South Korea; nursing home in New Zealand (71%), Belgium (52%), USA (50%), Canada (48%) and Czech Republic (44%); home in Mexico (73%), Italy (51%) and Spain (46%). The chances of dying in hospital were consistently higher for men (Belgium, France, Italy, USA, Canada), those younger than 80 years (Belgium, France, Italy, USA, Mexico), and those living in areas with a higher provision of hospital beds (Italy, USA). CONCLUSIONS: In several countries a substantial proportion of deaths from PD occurs in hospitals, although this may not be the most optimal place of terminal care and death. The wide variation between countries in the proportion of deaths from PD occurring in hospital indicates a potential for many countries to reduce these proportions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".