Physician-Reported Symptoms and Interventions in People with Intellectual Disabilities Approaching End of Life
Bibliographic record
Abstract
BACKGROUND: Insights into symptoms and interventions at the end of life are needed for providing adequate palliative care, but are largely lacking for people with intellectual disabilities (IDs). OBJECTIVES: We aimed at determining the prevalence rates of physician-reported symptoms from the Edmonton Symptom Assessment System (ESAS) at the moment that physicians recognized patient's death in the foreseeable future. In addition, we aimed at exploring provided interventions as reported by physicians in the period between physicians' recognition of death in the foreseeable future and patients' death. MEASUREMENTS: In this study, 81 physicians for people with IDs (ID-physicians) completed a retrospective survey about their last patient with IDs with a nonsudden death. RESULTS: On average, patients suffered from three of the eight ESAS symptoms. Fatigue (83%), drowsiness (65%), and decreasing intake (57%) were most reported. ID-physicians reported a median number of four interventions. Interventions were mostly aimed at somatic problems, such as pain and shortness of breath. Burdensome interventions such as surgery or artificial respiration were least or not reported. Palliative sedation was provided in a third of all cases. CONCLUSION: Although ID-physicians reported a variety of their patients' symptoms and of provided interventions at the end of life, using adequate symptom assessment tools suitable for people with IDs and continuous multidisciplinary collaboration in palliative care are essential to capture symptoms as fully as possible.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".