Assessment of pharmacologic pain management modalities for patients on hemodialysis
Bibliographic record
Abstract
Objective: The aim of this project was to assess the change in pain level for hospitalized patients on hemodialysis when using non-opioid medications alone compared to opioid medications alone to establish support for a clinical pain management model that would provide acute pain management guidance for patients on hemodialysis.Methods: This was a non-interventional survey completed at an acute care hospital in Chicago, IL. Patients over the age of 18 on hemodialysis reporting acute pain completed the Short Form McGill Pain Questionnaire-2 on day one and day three of hospitalization to assess pain levels over a three-day period. Results: The results demonstrate a decrease in total pain for patients using non-opioid medications and opioid medications; however, there is no statistically significant decrease in total pain scores between participants using non-opioid medications alone versus opioid medications alone (p = .743).Conclusions: Patients in the non-opioid group perceived their pain management to improve between day one and day three; however, their pain management did not improve to the degree that opioid medications provided. Care should be taken when dosing opioid medications for patients on hemodialysis given the patients’ decreased renal function.
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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 | 0.001 | 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) | 0.003 | 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".