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 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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".