Deep brain stimulation: Postoperative issues
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.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".