Successful Treatment With Baricitinib in a Patient With Refractory Eosinophilic Fasciitis
Bibliographic record
Abstract
BACKGROUND Extracorporeal shockwave lithotripsy (ESWL) has been used since the mid-1980s to fragment bile duct stones which cannot be removed endoscopically. Early machines required general anaesthesia and immersion in a waterbath. AIMS To investigate the effectiveness of the third generation Storz Modulith SL20 lithotriptor in fragmenting bile duct stones that could not be cleared by mechanical lithotripsy. METHODS Eighty three patients with retained bile duct stones were treated. All patients received intravenous benzodiazepine sedation and pethidine analgesia. Stones were targeted by fluoroscopy following injection of contrast via a nasobiliary drain or T tube. Residual fragments were cleared at endoscopic retrograde cholangiopancreatography. RESULTS Complete stone clearance was achieved in 69 (83%) patients and in 18 of 24 patients (75%) who required more than one ESWL treatment. Stone clearance was achieved in all nine patients (100%) with intrahepatic stones and also in nine patients (100%) referred following surgical exploration of the bile duct. Complications included six cases of cholangitis and one perinephric haematoma which resolved spontaneously. CONCLUSION Using the Storz Modulith, 83% of refractory bile duct calculi were cleared with a low rate of complications. These results confirm that ESWL is an excellent alternative to surgery in those patients in whom endoscopic techniques have failed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 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".