Breakthrough and Episodic Cancer Pain from a Palliative Care Perspective
Bibliographic record
Abstract
Cancer pain intensity (PI) fluctuates, but the relationship between pain flares and background pain with respect to pain management is not settled. We studied how flare and background PIs corresponded with treatment results for background cancer pain. Patients admitted to an acute palliative care unit with average and/or worst PI ≥ 1 on the 11-point numeric rating scale were included. Average and worst PI at admission and average PI at discharge were collected. We examined how the difference and ratio between worst and average PI and average PI at admission, were associated with average PI development during hospitalization. Positive differences between worst and average PI at admission were defined as pain flares. Ninety out of 131 patients had pain flares. The reduction in average PI for patients with flares was 0.9 and for those without, 1.9 (p = 0.02). Patients with large worst minus average PI differences reported the least improvement, as did those with large worst/average PI ratios. Patients with pain flares and average PI ≤ 4 at admission had unchanged average PI during hospitalization, while those with pain flares and average PI > 4 experienced pain reduction (2.1, p < 0.001). Large pain flares, in absolute values and compared to background PI, were associated with inferior pain relief.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".