Is Off-label repeat prescription of ketamine as a rapid antidepressant safe? Controversies, ethical concerns, and legal implications
Bibliographic record
Abstract
BACKGROUND: Depressive disorders are a common form of psychiatric illness and cause significant disability. Regulation authorities, the medical profession and the public require high safety standards for antidepressants to protect vulnerable psychiatric patients. Ketamine is a dissociative anaesthetic and a derivative of a hallucinogen (phencyclidine). Its abuse is a major worldwide public health problem. Ketamine is a scheduled drug and its usage is restricted due to its abuse liability. Recent clinical trials have reported that ketamine use led to rapid antidepressant effects in patients suffering from treatment-resistant depression. However, various flaws in study designs, and possible biased reporting of results, may have influenced those findings. Further analyses of ketamine use are needed to ensure patient safety. DISCUSSION: The use of ketamine in research and treatment of depressive disorders is controversial. Recently, mental health professionals raised ethical concerns about an ongoing ketamine trial in the UK. Also, a Canadian agency reviewed the existing evidence and did not recommend prescribing ketamine to treat depressive disorders. Findings obtained from tightly controlled research settings cannot be easily translated to clinical practice as substance abuse is commonly comorbid with depressive disorders. An effective antidepressant should reduce severity of depressive symptoms without liability problems. Although the US FDA has not approved the use of ketamine to treat depressive disorders, some psychiatrists offer off-label repeat prescription of ketamine. Prescribing ketamine for treating depressive disorders requires substantial empirical evidence. Clinicians should also consider research findings on ketamine abuse. Depressive disorders can be chronic conditions and the current evidence does not rule out the risk of substance abuse after repeat prescription of ketamine. Off-label ketamine use in treating depressive disorders may breach ethical and moral standards, especially in countries seriously affected by ketamine abuse. This article presents two real-world clinical vignettes which highlight ethical principles and theories, including autonomy, nonmaleficience, fidelity and consequentialism, as related to off-label ketamine use. CONCLUSION: We urge clinicians to minimise the risk of harming patients by considering the empirical evidence on ketamine properties and attempting all standard antidepressant therapies before considering the off-label use of ketamine.
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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 | 0.113 | 0.361 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.024 | 0.021 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".