Inflammatory mediators in intra-abdominal sepsis or injury – a scoping review
Bibliographic record
Abstract
INTRODUCTION: Inflammatory and protein mediators (cytokine, chemokine, acute phase proteins) play an important, but still not completely understood, role in the morbidity and mortality of intra-abdominal sepsis/injury. We therefore systematically reviewed preclinical and clinical studies of mediators in intra-abdominal sepsis/injury in order to evaluate their ability to: (1) function as diagnostic/prognostic biomarkers; (2) serve as therapeutic targets; and (3) illuminate the pathogenesis mechanisms of sepsis or injury-related organ dysfunction. METHODS: We searched MEDLINE, PubMed, EMBASE and the Cochrane Library. Two investigators independently reviewed all identified abstracts and selected articles for full-text review. We included original studies assessing mediators in intra-abdominal sepsis/injury. RESULTS: Among 2437 citations, we selected 182 studies in the scoping review, including 79 preclinical and 103 clinical studies. Serum procalcitonin and C-reactive protein appear to be useful to rule out infection or monitor therapy; however, the diagnostic and prognostic value of mediators for complications/outcomes of sepsis or injury remains to be established. Peritoneal mediator levels are substantially higher than systemic levels after intra-abdominal infection/trauma. Common limitations of current studies included small sample sizes and lack of uniformity in study design and outcome measures. To date, targeted therapies against mediators remain experimental. CONCLUSIONS: Whereas preclinical data suggests mediators play a critical role in intra-abdominal sepsis or injury, there is no consensus on the clinical use of mediators in diagnosing or managing intra-abdominal sepsis or injury. Measurement of peritoneal mediators should be further investigated as a more sensitive determinant of intra-abdominal inflammatory response. High-quality clinical trials are needed to better understand the role of inflammatory mediators.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".