A longitudinal study of pain in hospice and pre-hospice patients
Bibliographic record
Abstract
Pain continues to be a very formidable foe in the care of the hospice patient. The incidence among hospice admissions may range from 50 to 80 percent. With such a high initial incidence of pain, the rapidity with which pain can be controlled becomes a very high priority for the hospice effort. The assessment and management of pain in a home-based hospice program presents some unique problems--and opportunities, in that much of this work is done by hospice nurses on site, rather than by the physician, who might remain quite removed from the process. In the study described below, 250 consecutive admissions to either a hospice, or pre-hospice (bridge) program were assessed for pain on admission. Those with pain scores of 5 or greater (on a 1 to 10 scale) were followed daily for 15 days by phone to reassess pain and treatment effects. Of the 250 consecutive patients surveyed, 41 (16 percent) gave pain scores of 5 or greater. Mean pain scores for the 41 patients dropped to < 5 within 24 hours of admission.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".