Invasive experimental brain surgery for dementia: Ethical shifts in clinical research practices?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The increasing dementia prevalence worldwide is driving the testing of novel therapeutic approaches, such as invasive brain technologies, despite limited clinical evidence and the risk of accelerating cognitive decline. Our manuscript (a) reviews the NIH Clinicaltrials.gov database for deep brain stimulation, stem cell implantation, and gene therapy trials on people with dementia; (b) discusses issues on beneficence, nonmaleficence, and autonomy associated with these trials; and (c) proposes nine recommendations that build on elements from the Declaration of Helsinki. We found 49 preregistered high-risk trials from nine countries planning to or involving 11,801 people with Alzheimer's or Lewy body dementia or dementia secondary to Parkinson's or Huntington's disease. Most of the people with Alzheimer's who are in these trials are from North America and East Asia. There is substantial heterogeneity in the enrolment criteria, even for trials recruiting only those with Alzheimer's disease. Although most trials enrol people in mild to moderate stages of Alzheimer's disease, trials in China enrol people who have severe Alzheimer's. Our findings highlight a pressing need to review and refine the enrolment criteria for invasive neural trials in people with dementia, considering risks, potential benefits, and capacity for informed consent. As a multidisciplinary team from Australia, the USA, Canada, and Germany with expertise in neurology, neuroscience, and ethics, we examine how it is essential to balance the risks of invasive neural research in a vulnerable population with limited capacity to provide informed consent to help advance the body of knowledge regarding a disease with limited therapeutic options.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.035 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it