PEG-J replacement for duodenal levodopa infusion in Parkinson’s disease patients: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Reducing percutaneous endoscopic gastrostomies with jejunal extension tubes (PEG-J) related complications is vital to the long-term preservation of duodenal levodopa infusion (DLI) in advanced Parkinson's disease (APD). Here, we provide data on the frequency of complications for both the standard "pull" and the non-endoscopic, radiologic assisted, "push" replacement PEG-J techniques in APD. METHODS: We retrospectively identified all patients treated with DLI from October 2009 to January 2020 at the Movement Disorders Center. Patients features and demographics, PEG-J procedures, causes for any discontinuation, reported complications and mortality were collected. In this cohort, PEG-J replacements were performed using the standard "pull" procedure or the radiologic assisted "push" method. Descriptive statistical analysis, t-test and paired t-test with False Discovery Rate correction was performed. RESULTS: This retrospective study included 30 APD patients [median age 72 ± 5.6 years; mean disease duration 17.2 + 5.7 years]. Mean treatment duration was 35.6 (30.6) months. Overall, 156 PEG-J procedures were performed, and Nineteen patients (63.3%) had a total of 185 reported complications, 85 of which were peristomal complications. 17 (56.6%) underwent 100 replacement procedures due to complications. The most commonly reported complication for replacement was J-tube dislocation (36%). One patient discontinued treatment after 6 months, due to peripheral neuropathy. Six patients died for causes not related to DLI. PEG-J replacements performed with the "push" method had a higher turnover (5.6 vs. 7.6 mo.), but fewer reported complications (67 vs. 75%). CONCLUSION: The overall rate of complications was lower for "push" technique. This result might have been due to a higher replacement turnover that acted as a protective factor.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".