Accuracy and usefulness of the Palliative Prognostic Index in a community setting
Bibliographic record
Abstract
PURPOSE: In a community setting characterised by scarce inpatient palliative care resources, a precise prognosis could help determine which patients should be prioritised for end-of-life admission. AIM: The aim of this study was to assess the validity of the Palliative Prognostic Index (PPI) and to determine whether it is a helpful tool for nurses to administer as part of the admission protocol in the palliative care service of a community hospital. RESULTS: The PPI was a moderately accurate prognostic tool when assessing the frequency of 14-day overstay; 81% of patients died within 14 days of their expected prognosis. Based on sensitivity and specificity, the accuracy of the prognoses was acceptable for the 6-week prognosis group (80%), and poor for the 3-week prognostic group (53%). The tool was easy to administer by the admission nurse receiving referrals. CONCLUSION: A nurse-administered and minimally-invasive prognostic tool was helpful in this context.
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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 | 0.005 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".