Serum IgG4 cut-off of 70 mg/dL is associated with a shorter time to cirrhosis decompensation and liver transplantation in primary sclerosing cholangitis patients
Bibliographic record
Abstract
BACKGROUND: Primary sclerosing cholangitis (PSC) is an immune-mediated biliary disorder of unknown etiology with no effective treatment. The purpose of this study was to better prognosticate the development of cirrhosis, decompensation, and requirement for liver transplantation (LT) in PSC patients based on serum immunoglobulin G4 (IgG4) levels. METHODS: A retrospective chart review was conducted on PSC patients seen at the University of Alberta Hospital between 2002 and 2017. PSC patients were categorized as high IgG4 group (≥70 mg/dL) or normal IgG4 group (<70 mg/dL). Laboratory parameters, clinical characteristics, and outcomes were compared between the groups. RESULTS: One hundred and ten patients were followed over a mean period of 7.3 (SD 5) years. Seventy-two patients (66%) were male, the mean age at diagnosis of PSC was 35 (SD 15) years, and inflammatory bowel disease (IBD) was present in 80 patients (73%). High IgG4 levels were found in 37 patients (34%). PSC patients with high IgG4 had a shorter mean cholangitis-free survival time (5.3 versus 10.4 years, p = 0.02), cirrhosis-free survival time (8.7 versus 13.0 years, p = 0.02), and LT-free survival time (9.3 years versus 18.9 years, p <0.001). IgG4 ≥70 mg/dL was independently associated with liver decompensation and LT-free outcomes. A cut-off IgG4 value of ≥70 mg/dL performed better than a cut-off value of ≥140 mg/dL to predict time to LT (area under the curve [AUC] 0.68, p = 0.03, sensitivity 72%, specificity 78%). CONCLUSIONS: Serum IgG4 ≥70 mg/dL in PSC predicts a shorter time to cirrhosis decompensation and LT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".