The Association of High Mobility Group Box-1 with Sepsis Susceptibility and Mortality Risk: A Meta-Analysis
Bibliographic record
Abstract
High mobility group box-1 (HMGB1) regulates inflammation, immune response, DNA repair, and cell death, which is crucial in the pathogenesis of sepsis; while its role in sepsis susceptibility and mortality risk remains inconsistent. Hence, this meta-analysis systemically investigated the dysregulation level of HMGB1 and its association with mortality risk. PubMed, Web of Science, Embase, and Cochrane Library databases were searched until May 2024. Studies written in English and comparing HMGB1 level in serum or plasma detected by enzyme-linked immunosorbent assay between adult sepsis patients and controls, or non-survivors and survivors of sepsis, were eligible. Twenty-eight studies containing 3,110 subjects were included. The quality of studies was satisfactory evaluated by the Newcastle-Ottawa scale. Pooled analyses showed that HMGB1 was increased in sepsis patients versus controls (P < 0.001). Subgroup analysis revealed that HMGB1 was increased in sepsis patients versus healthy controls (P < 0.001), but less varied between sepsis patients and non-sepsis controls (P = 0.081). Additionally, HMGB1 was elevated in non-survivors versus survivors of sepsis (P = 0.030). Publication bias existed in HMGB1 differences between sepsis patients and controls; but it was adjusted using the trim-and-fill method, and the statistical significance did not change after that. Sensitivity analysis indicated acceptable robustness. In conclusion, this study suggests the potential of HMGB1 to serve as a possible biomarker for sepsis diagnosis and mortality risk stratification.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.036 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".