A Canadian Outpatient Experience of Intrajejunal Levodopa/Carbidopa Intestinal Gel
Bibliographic record
Abstract
Introduction: Levodopa/carbidopa intestinal gel (LCIG) is a form of levodopa that can be delivered continuously through an intrajejunal percutaneous tube. LCIG has been found to significantly reduce “Off” time and increase “On” time without troublesome dyskinesia in patients with advanced Parkinson’s disease (PD). Adverse events have been largely attributed to the procedure and the device, rather than the LCIG preparation itself. To date, the data evaluating long-term efficacy and safety are limited. This study is a quality improvement self-audit of our outpatient LCIG model at Toronto Western Hospital (TWH). Through this audit, we aim to describe the current method of percutaneous endoscopic gastrostomy with jejunal tube (PEG-J) insertion, document short and long-term adverse events (AEs), hospitalization rates and frequency of PEG-J removal and/or exchange. Methods: All PD patients who underwent PEG-J insertion for LCIG therapy at TWH (from January 2015-2018) were identified prospectively. All patients who underwent PEG-J insertion for LCIG initiation as an outpatient were included. The following variables were collected using a standardized data collection sheet: patient demographics, PD factors and PEG-J factors. Data was analyzed using standard descriptive statistical methods. Results: A total of 45 patients were identified and included in the final analysis. Mean age at study recruitment was 72 years (standard deviation, SD=7 years), with a mean duration of PD of 15 years (SD=7 years). 60% of patients were male, and 40% were female. Mean time from PEG-J insertion was 21.95 months (SD=13.74 months). Patient medications at time of PEG-J insertion were collected (Table 1). Post-procedure complications were documented (Table 2). There were no reported serious adverse events (SAEs), including post-procedure perforations, bleeds, fistulas, intra-abdominal collections or buried bumper syndrome. Conclusion: Our experience with outpatient PEG-J insertion for LCIG therapy included 45 patients. Study population was comparable to that described in previous studies. The main relevant finding was the absence of serious adverse events. This was significantly lower than the rates reported in the literature. In conclusion, LCIG has been proven to be a promising treatment option for patients with advanced PD. This study supports that the current method of PEG-J practice using the outpatient LCIG model is safe and effective. Similar outpatient models may help decrease rates of SAEs.481_A Figure 1. Patient PD medications.481_B Figure 2. PEG-J tube complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".