Epidural ketamine for postoperative analgesia in the elderly.
Bibliographic record
Abstract
BACKGROUND: We assessed the epidural use of ketamine in elderly patients undergoing major abdominal surgery. METHODS: Patients older than 65 years were randomly allocated to receive preemptive epidural bupivacaine 0.125% (20 ml) combined with either epidural ketamine 40 mg (ketamine group), or epidural morphine 2 mg (morphine group). Postoperatively, boluses of 0.125% bupivacaine (5 ml) supplemented with ketamine (2 mg/ml) or morphine (0.1 mg/ml) were given until a pain score of two was established. Analgesia at rest was assessed by a verbal rating score (0 = no pain, 1 = mild pain, 2 = moderate pain, 3 = severe pain) at 1 h, 2h, 6h, 12h and 24h after surgery. The patient's degree of sedation was assessed using the Ramsay sedation score and episodes of nausea and vomiting (PONV) were recorded. RESULTS: Patients in the morphine group were more sedated but had significantly lower pain scores and requested less rescue analgesic than patients receiving epidural ketamine (P < 0.05). In the morphine group three patients were treated for PONV while none of the patients in the ketamine group showed PONV. CONCLUSION: Epidural ketamine, when compared to epidural morphine, appears to be associated with less sedation and a smaller risk of PONV, but necessitates more frequent or continuous administration to achieve comparable analgesia.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".