Drug use evaluation of transdermal fentanyl in a tertiary hospital
Bibliographic record
Abstract
OBJECTIVES: The primary objective of the study was to assess the rationale of fentanyl patch initiation and continuation for pain. The secondary objectives were to analyse prescribing pattern between disciplines, monitoring criteria and adverse events profile of fentanyl patch in the inpatient wards for a tertiary hospital. METHODS: A retrospective case series review was undertaken of patients who received transdermal fentanyl for pain from April to June 2013 at the National University Hospital, Singapore. Relevant data were collected from electronic and physical medical records and audit criteria applied for indication, opioid tolerance, dosage regimen, adverse events and monitoring criteria. RESULTS: 40 patients were prescribed fentanyl patches for pain in the study period. 15 patients (62.5%) had one or more problems during initiation of fentanyl patch. Appropriate use during initiation was low with only 9 (38%) patients meeting all the required criteria. Most of the inappropriate use involved a lack of bridging opioids (58%), wrong opioid conversion dose (42%) and use in opioid-naïve patients (42%). In addition, three cases of inappropriate placement were observed. Monitoring for efficacy and adverse effects generally met audit criteria. There was a low incidence of discontinuation (21%) due to its well-tolerated side effect profile. CONCLUSIONS: This study highlighted high incidence of inappropriate initiation of fentanyl patch, and we proposed an in-house guideline to aid physicians in initiating fentanyl patches during admission and to educate nursing staff of the monitoring parameters for efficacy and toxicity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".