Upadacitinib Plus Intensive Granulocyte and Monocyte Adsorptive Apheresis for Ulcerative Colitis Achieved Ulcer Healing for Pyoderma Gangrenosum
Bibliographic record
Abstract
A 44-year-old woman who had been diagnosed with ulcerative colitis (UC) at 22 years old was diagnosed with severe flare-up of UC based on endoscopic findings associated with new-onset active pyoderma gangrenosum (PG) on both lower legs after she decided to discontinue UC treatment. Systemic treatment with intravenous prednisolone at 30 mg/day had achieved insufficient response to UC and PG, resulting in a diagnosis of corticosteroid-refractory UC and PG. Combination therapy with upadacitinib at 45 mg/day plus intensive granulocyte and monocyte adsorptive apheresis (GMA) was started to achieve clinical remission of UC. Ten weeks after starting this combination therapy, clinical improvement of UC was achieved with PG ulcer healing on both lower legs. A combination of upadacitinib plus intensive GMA may offer an effective therapeutic option for patients with active PG in addition to UC but has yet to be approved for induction or maintenance treatment of PG worldwide. PG is a dermatological involvement in UC patients that requires attention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".