Patterns of Relapse and Complications of Immunoglobulin G4–Related Disease
Bibliographic record
Abstract
BACKGROUND: Immunoglobulin G4-related disease (IgG4-RD) is a multisystemic fibroinflammatory condition potentially resulting in organ dysfunction. We aimed to evaluate imaging characteristics of disease relapse and complications in this cohort of patients. METHODS: This was a cohort study of IgG4-RD patients imaged between 2010 and 2020. Radiological manifestations of disease activity (remission/stability vs. relapse and complications) were correlated with clinical symptoms. Univariate analyses were performed with χ2 , Fisher exact, and Mann-Whitney U tests. Times to relapse and organ atrophy were studied with Kaplan-Meier analyses. RESULTS: A total of 69 patients had imaging surveillance over a median duration of 47 months. Radiological relapse occurred in 50.7% (35/69) with median time to relapse at 74 months (95% confidence interval, 45-122 months); 42.8% (15/35) of this cohort had different-site relapse with the following recognized primary-secondary patterns: pancreas-hepatobiliary ( p = 0.005), hepatobiliary-pancreas ( p = 0.013), and periaortitis-mesenteric ( p = 0.006). Clinical symptoms were significantly associated with imaging characteristics ( p < 0.001). Abdominal complications were detected in 52.2% (36/69) of patients, mostly solid organ atrophy (97.2% [35/36]). New-onset diabetes was more likely in pancreatic IgG4-RD (n = 51) when accompanied by gland atrophy (4/21 vs. 0/30 nonatrophy, p = 0.024). CONCLUSION: Radiological relapse of IgG4-RD is common over prolonged imaging surveillance and is significantly associated with symptomatic relapse. A multisystem review to detect new/different sites of disease and abdominal complications may help predict future organ dysfunction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".