Factors Associated with Improvement in Uncontrolled Cancer Pain without Increasing the Opioid Daily Dose among Patients Seen by an Inpatient Palliative Care Team
Bibliographic record
Abstract
Background: Increasing the total opioid dose is the standard approach for managing uncontrolled cancer pain. Other than simply increasing the opioid dose, palliative care interventions are multidimensional and may improve pain control in the absence of opioid dose increase. Objective: The purpose of this study was to determine the proportion of patients referred to our inpatient palliative care (IPC) team who achieved clinically improved pain (CIP) without opioid dose increase. Design: We reviewed consecutive patients referred to our IPC team. Setting/Subjects: Eligibility criteria included (1) taking opioid medication; (2) having ≥2 consecutive visits with the IPC team; and (3) an Edmonton Symptom Assessment Scale (ESAS) pain score ≥4 at consultation. Measurements: We assessed patient demographics and clinical variables, including cancer type, opioid prescription data (type, route, and oral morphine equivalent daily dose [MEDD]), presence of opioid rotation, psychological consultation, changes in adjuvant medications (e.g., corticosteroids; antiepileptics—gabapentin and pregabalin; benzodiazepines; and neuroleptics), and achievement of CIP. Results: Of the 300 patients enrolled, CIP was achieved in 196 (65%) patients. Of CIP patients, 85 (43%) achieved CIP without an increase in MEDD. CIP without MEDD increase was associated with more adjuvant medication changes (p = 0.003), less opioid rotation (p = 0.005), and lower symptom distress scale of ESAS (p = 0.04). Conclusions: Nearly half of the patients achieved CIP without MEDD increase, suggesting that the multidimensional palliative care intervention is effective in improving pain control in many opioid-tolerant patients without the need to increase the opioid dose.
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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 | 0.002 | 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 | 0.001 |
| 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".