Survey of intrathecal opioid usage in the UK
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Intrathecal opioids are now used routinely in the UK for intra- and postoperative analgesia. The opioids of choice have altered over recent years and the dosage regimens used can vary between institutions. Concerns over safety have been reduced probably because much lower doses of opioids are now being used. This survey explored the practice of intrathecal opioid usage in the UK. METHODS: We sent a questionnaire survey to 270 anaesthetic departments and received 199 replies, a response rate of 73.7%. RESULTS: Intrathecal opioids were used in 175 (88.4%) departments. Of these departments, 107 (61.1%) had local guidelines or protocols in place. Opioids such as diamorphine (used in 136 (78.2%) of departments) and fentanyl (129 (74.1%)) with a shorter duration of action are now more commonly used than morphine (37 (21.3%)) for intrathecal analgesia. In 96 (54.5%) departments, patients were nursed on regular surgical wards following administration of spinal opioids. CONCLUSIONS: The use of low-dose lipophilic intrathecal opioids for postoperative analgesia is widespread in the UK. Patients are commonly nursed in low-dependency post-anaesthetic care areas. The low incidence of adverse events reported by the respondents along with the popularity of the technique suggests that low-dose spinal opioid administration is safe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".