Levodopa–carbidopa intestinal gel in advanced Parkinson’s disease: long-term results from COSMOS
Bibliographic record
Abstract
BACKGROUND: While immediate benefits of levodopa-carbidopa intestinal gel (LCIG) are evident in patients with Parkinson's disease (PD), long-term LCIG effects require further study. OBJECTIVES: We explored long-term LCIG on motor symptoms, nonmotor symptoms (NMS), and LCIG treatment settings in patients with advanced PD (APD). METHODS: Data were obtained (medical records and patient visit) from COSMOS, a multinational, retrospective, cross-sectional post-marketing observational study in patients with APD. Patients were stratified into 5 groups based on LCIG treatment duration at the patient visit, from 1-2 to > 5 years LCIG. Between-group differences were assessed for changes from baseline in LCIG settings, motor symptoms, NMS, add-on medications, and safety. RESULTS: Out of 387 patients, the number of patients per LCIG group was: > 1- ≤ 2 years LCIG (n = 156); > 2- ≤ 3 years LCIG (n = 80); > 3- ≤ 4 years LCIG (n = 61); > 4- ≤ 5 years LCIG (n = 30); > 5 years LCIG (n = 60). Baseline values were similar; data reported are changes from the baseline. There were reductions in "off" time, dyskinesia duration, and severity across LCIG groups. Prevalence, severity, and frequency of many individual motor symptoms and some NMS were reduced amongst all LCIG groups, with few differences between groups. Doses for LCIG, LEDD and LEDD for add-on medications were similar across groups both at LCIG initiation and patient visit. Adverse events were similar across all LCIG groups and consistent with the established safety profile of LCIG. CONCLUSIONS: LCIG may provide sustained, long-term symptom control, while potentially avoiding increases in add-on medication dosages. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03362879. Number and date: P16-831, November 30, 2017.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".