Randomized controlled trial of intraputamenal glial cell line–derived neurotrophic factor infusion in Parkinson disease
Bibliographic record
Abstract
OBJECTIVE: Glial cell line-derived neurotrophic factor (GDNF) exerts potent trophic influence on midbrain dopaminergic neurons. This randomized controlled clinical trial was designed to confirm initial clinical benefits observed in a small, open-label trial using intraputamenal (Ipu) infusion of recombinant human GDNF (liatermin). METHODS: Thirty-four PD patients were randomized 1 to 1 to receive bilateral continuous Ipu infusion of liatermin 15 microg/putamen/day or placebo. The primary end point was the change in Unified Parkinson Disease Rating Scale (UPDRS) motor score in the practically defined off condition at 6 months. Secondary end points included other UPDRS scores, motor tests, dyskinesia ratings, patient diaries, and (18)F-dopa uptake. RESULTS: At 6 months, mean percentage changes in "off" UPDRS motor score were -10.0% and -4.5% in the liatermin and placebo groups, respectively. This treatment difference was not significant (95% confidence interval, -23.0 to 12.0, p = 0.53). Secondary end point results were similar between the groups. A 32.5% treatment difference favoring liatermin in mean (18)F-dopa influx constant (p = 0.019) was observed. Serious, device-related adverse events required surgical repositioning of catheters in two patients and removal of devices in another. Neutralizing antiliatermin antibodies were detected in three patients (one on-study and two in the open-label extension). INTERPRETATION: Liatermin did not confer the predetermined level of clinical benefit to patients with PD despite increased (18)F-dopa uptake. It is uncertain whether technical differences between this trial and positive open-label studies contributed in any way this negative outcome.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".