Palliative ketamine: the use of ketamine in central post-stroke pain syndrome—a case report
Bibliographic record
Abstract
Ketamine has played a versatile role in medicine due to its wide spectrum of uses in history including use in sedation, catalepsy, somatic analgesia, bronchodilation, and recent trial in complex chronic pain syndromes. There is very little, if any, discussion in the literature of ketamine use in stroke, particularly in improving symptoms of pain after stroke. We present a case of a 40-year-old female with a past medical history of right-sided thalamic ischemic stroke complicated by Central post-stroke pain syndrome (CPSP) presented for refractory severe diffuse pain causing debility and immobility. The patient failed outpatient medical therapy consisting of anxiolytics, serotonin, and norepinephrine reuptake inhibitors. This led to increased opioid use which resulted in dependence and opioid-hyperalgesia. Upon admission, the patient was unable to sit still, with severe, sharp 10/10 pain localized to her left lower extremity. Palliative medicine was consulted for management of refractory central neuropathic pain. Inpatient oral ketamine was initiated, and titrated over the patient's hospital course. During this time, the patient showed marked improvement in GAD-7, PHQ-9, and Short Mcgill pain scores while significantly decreasing opioid requirements. We present this case to demonstrate how oral ketamine usage in centrally mediated neuropathic pain such as in CPSP can lead to pain control, decreased opioid usage, and overall improved quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".