Prognostic value of monocyte chemoattractant protein-1 in sepsis: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Monocyte chemoattractant protein-1 (MCP-1) has been utilized as a prognostic indicator for sepsis patients; however, the findings have been inconsistent. This meta-analysis seeks to elucidate the prognostic significance of MCP-1 in individuals diagnosed with sepsis. METHODS: We systematically queried four databases (Web of Science, PubMed, EMBASE, Cochrane Library) to identify studies published from the establishment of the databases until January 2025. Hazard ratios (HRs) with 95% CIs were employed to evaluate the prognostic significance of MCP-1 in this patient population. In our study, the Newcastle-Ottawa Quality Assessment Scale was evaluated for quality assessment, and Funnel plot was used for publication offset. RESULTS: A total of 592 patients from eight studies were included in the evaluation. The findings revealed that MCP-1 levels were significantly elevated in non-survivors compared to those who survived [SMD = 0.54, 95% CI: 0.25-0.82, P = 0.0002]. Our study demonstrated that elevated levels of MCP-1 were significantly associated with an unfavorable prognosis in patients with sepsis, with a hazard ratio (HR) of 1.36 (95% confidence interval: 1.25-1.48; P < 0.00001) using a random-effects model. The funnel plot indicated no publication bias. CONCLUSION: This meta-analysis suggests that elevated levels of MCP-1 could serve as a valuable prognostic indicator in sepsis patients, however, this conclusion still requires validation through higher-quality studies with longer-term follow-up.
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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 | 0.017 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".