Intravenous Ketamine Infusion as an Adjuvant to Morphine in a 2-Year-Old With Severe Cancer Pain From Metastatic Neuroblastoma
Bibliographic record
Abstract
A 2.8-year-old female patient (11.6 kg) was admitted to the hospital for uncontrolled pain and swelling in the left leg relating to a metastatic neuroblastoma. Initially, her pain was managed with oral morphine 2 mg (approx. 0.2 mg/kg) every 4 hours. Because she was quite somnolent but still in significant pain, analgesia was then changed to methadone 1 mg orally every 6 hours (approximately 0.1 mg/kg/dose) and was eventually increased over 36 hours to 2 mg every 6 hours (approximately 0.2 mg/kg/dose). She received oral methadone 0.6 mg (approximately 0.05 mg/kg) every 4 hours as needed for breakthrough pain. She continued to have severe pain and experienced side effects, including respiratory depression, sedation, visual hallucinations, and vomiting. An intravenous ketamine infusion was started at 100 microg/kg/hour. Regular opioid administration was ceased, but she was given intravenous morphine 0.5 to 0.75 mg for breakthrough pain. She required only zero to three doses of breakthrough morphine per day, initially. After starting the ketamine infusion, her pain control improved and her symptoms of opioid toxicity abated. She was more alert and able to partake in limited activities. As a result of pain from progressive disease, the ketamine infusion was increased to 200 microg/kg/hour after 6 days with positive results. Her condition continued to deteriorate. An intravenous morphine infusion was initiated 2 weeks after starting the ketamine infusion and was eventually increased to 50 microg/kg/hour. One week later, she died with reasonable pain control. This case illustrates the use of ketamine as an effective analgesic in an adjuvant setting in a pediatric patient with advanced poorly controlled cancer pain. Ketamine not only eased the child's suffering while preserving life but also improved her quality of life by maintaining the child's ability to communicate and engage in activities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".