Serum Visfatin as a Diagnostic Marker of Active Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Inflammatory bowel diseases (IBD) have been reported to be caused by a complex interplay of immunological, infectious, and genetic factors. Previous studies have suggested that adipokines play a role in IBD by inducing proinflammatory cytokines. We aimed to evaluate the role of visfatin in the diagnosis algorithm of active IBD. METHODS: 85 newly diagnosed IBD patients [56 diagnosed with ulcerative colitis (UC) and 29 with Crohn's disease (CD)] and 30 healthy controls were included. IBD phenotypes were described accordingly to Montreal classification. Hemoglobin, total leucocytic count (TLC), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), albumin, fecal calprotectin and serum visfatin were measured. RESULTS: The serum visfatin level was found to be significantly higher in patients with IBD than those in the control group (p<0.001). It was significantly positively correlated with CRP, ESR, and FC in both IBD groups. Receiver operating characteristic curve analysis of visfatin in diagnosis of UC revealed an area under curve of 0.911. At cutoff ≥1.4 ng/ml, the sensitivity was 92.9% and the specificity was 86.7%.. In CD group, at the same cutoff, AUC was 0.974, sensitivity was 96.6% and specificity was 86.7%. There was a statistically significant elevation of serum visfatin in extensive UC (E3) as compared to the other groups. A cutoff ≥3.25 ng/ml revealed 88.9% sensitivity, and 100% specificity in detection of E3 UC. Serum visfatin was significantly increased in CD stricturing phenotype (B2) as compared to non-stricturing non-penetrating CD (B1). A cutoff ≥3.5 ng/ml revealed 83.3% sensitivity, and 100% specificity in detection of B2. CONCLUSIONS: The serum visfatin level were significantly higher in patients with IBD than in controls. Serum visfatin might be a novel noninvasive marker to detect activity in IBD patients and can be used as predictor of disease extension in patients with UC.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".