Off‐label use of aprepitant for scleroderma‐associated nausea and vomiting: A case report
Bibliographic record
Abstract
WHAT IS KNOWN AND OBJECTIVE: Scleroderma is a disease characterized by excessive deposition of collagen and extracellular matrix proteins in affected organ systems, which results in tissue fibrosis and organ dysfunction. It is estimated that 90% of patients with systemic sclerosis have gastrointestinal involvement, with approximately 50% being symptomatic. Clinical manifestations of gastrointestinal scleroderma manifestations relate to impaired motility and absorption and ultimately malnutrition. Treatments for these symptoms often fail and are limited. The objective of this case report is to highlight the potential use of a substance P antagonist in the treatment of scleroderma associated nausea. CASE SUMMARY: A 56-year-old woman presented with GI complications of her underlying systemic sclerosis. The majority of her stay was marked by severe nausea and vomiting, resistant to numerous therapies. Obstructive causes for her symptoms were ruled out with a gastroscopy. A motility study revealed completely absent peristalsis in her esophagus, likely due to complete fibrosis of smooth muscle fibres. For the first time, off-label use of aprepitant 80 mg once daily was trialed with success in hospital. With this medication, she was able to maintain an adequate oral intake and ultimately achieve discharge from hospital. WHAT IS NEW AND CONCLUSION: Despite the wide array of medications for gastrointestinal scleroderma, their effect is very limited. In this article, we report to the best of our knowledge the first successful use of the substance P antagonist aprepitant to treat refractory nausea and vomiting in a patient with gastrointestinal scleroderma. Not only does this medication carry promise in treating the GI symptoms of scleroderma, but it may also prove cost effective as compared to PEG insertions or TPN. This case study is congruent with recent evidence of the utility of aprepitant in other infiltrative disease conditions. This may spur interest randomized control trials for expanding the role of this medication.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".