Do Colonic Mucosal Tumor Necrosis Factor Alpha Levels Play a Role in Diverticular Disease? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Diverticular disease (DD) is the most frequent condition in the Western world that affects the colon. Although chronic mild inflammatory processes have recently been proposed as a central factor in DD, limited information is currently available regarding the role of inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α). Therefore, we conducted a systematic review and meta-analysis aiming to assess the mucosal TNF-α levels in DD. We conducted a systematic literature search using PubMed, Embase, and Scopus to identify observational studies assessing the TNF-α levels in DD. Full-text articles that satisfied our inclusion and exclusion criteria were included, and a quality assessment was performed using the Newcastle-Ottawa Scale (NOS). The principal summary outcome was the mean difference (MD). The results were reported as MD (95% confidence interval (CI)). A total of 12 articles involving 883 subjects were included in the qualitative synthesis, out of which 6 studies were included in our quantitative synthesis. We did not observe statistical significance related to the mucosal TNF-α levels in symptomatic uncomplicated diverticular disease (SUDD) vs. the controls (0.517 (95% CI -1.148-2.182)), and symptomatic vs. asymptomatic DD patients (0.657 (95% CI -0.883-2.196)). However, the TNF-α levels were found to be significantly increased in DD compared to irritable bowel disease (IBS) patients (27.368 (95% CI 23.744-30.992)), and segmental colitis associated with diverticulosis (SCAD) vs. IBS patients (25.303 (95% CI 19.823-30.784)). Between SUDD and the controls, as well as symptomatic and asymptomatic DD, there were no significant differences in the mucosal TNF-α levels. However, the TNF-α levels were considerably higher in DD and SCAD patients than IBS patients. Our findings suggest that TNF-α may play a key role in the pathogenesis of DD in specific subgroups and could potentially be a target for future therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".