Deep brain stimulation: Postoperative issues
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
Numerous factors need to be taken into account when managing a patient with Parkinson's disease (PD) after deep brain stimulation (DBS). Questions such as when to begin programming, how to conduct a programming screen, how to assess the effects of programming, and how to titrate stimulation and medication for each of the targeted sites need to be addressed. Follow-up care should be determined, including patient adjustments of stimulation, timing of follow-up visits and telephone contact with the patient, and stimulation and medication conditions during the follow-up assessments. A management plan for problems that can arise after DBS such as weight gain, dyskinesia, axial symptoms, speech dysfunction, muscle contractions, paresthesia, eyelid, ocular and visual disturbances, and behavioral and cognitive problems should be developed. Long-term complications such as infection or erosion, loss of effect, intermittent stimulation, tolerance, and pain or discomfort can develop and need to be managed. Other factors that need consideration are social and job-related factors, development of dementia, general medical issues, and lifestyle changes. This report from the Consensus on Deep Brain Stimulation for Parkinson's Disease, a project commissioned by the Congress of Neurological Surgeons and the Movement Disorder Society, outlines answers to a series of questions developed to address all aspects of DBS postoperative management and decision-making with a systematic overview of the literature (until mid-2004) and by the expert opinion of the authors. The report has been endorsed by the Scientific Issues Committee of the Movement Disorder Society and the American Society of Stereotactic and Functional Neurosurgery.
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 | 0.000 | 0.000 |
| 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 it