Association of plasma MMP-2 levels and prognosis of patients with intracerebral hemorrhage: a prospective cohort study
Bibliographic record
Abstract
Objective The role of MMP-2 in patients with ICH is controversial and the impact of plasma MMP-2 level on clinical outcome is still unclear. Materials and methods In this study, the peripheral venous blood was acquired from 93 patients with ICH and 88 healthy controls within 24 h of hospitalization and at enrollment. We retrospectively investigated plasma MMP-2 levels of patients and healthy controls. The edema volume, the NIHSS score, the GCS score, and mRS were used to assess and quantify neurological deficit following ICH. Logistic regression analysis was configured to determine the independent relation of plasma MMP-2 levels with clinical outcomes. In addition, the plasma MMP-14 levels and complement C4 level were tested to explore the relationship with plasma MMP-2 level. Results There was a significant reduction of plasma MMP-2 levels in ICH patients than that in healthy controls (38.02 ± 1.71 vs. 54.03 ± 2.15, p < 0.0001), and MMP-2 is negatively correlated with the edema volume (r = −0.2187, p < 0.05), NIHSS score (r = −0.2194, p < 0.05), blood leucocyte count (r = −0.2549, p = 0.012), and complement C4 level (r = −0.2723, p = 0.005). There is positive correlation between MMP-2 level and GCS score (r = 0.2451, p = 0.01) and MMP-14 level (r = 0.7013, p = 0.005). The multivariate analysis revealed that reduced plasma MMP-2 level is associated with elevated edema volume (OR = 0.2604, 95% CI [0.07 to 0.84], p = 0.02). Conclusion The plasma MMP-2 level in patients with ICH is significantly lower than that of healthy controls, and plasma MMP-2 level may be a prognostic factor. Plasma MMP-2 levels are correlated with the clinical outcomes of patients and negatively correlated with blood leucocyte count and complement C4 level in patients with ICH.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".