Plasma levels of matrix metalloproteinases and their inhibitors in hypertension
Bibliographic record
Abstract
BACKGROUND: Hypertension is a major cause of cardiovascular remodeling. In the cardiovascular system, the remodeling of the extracellular matrix is controlled by the matrix metalloproteinases (MMPs) and the tissue inhibitors of MMPs (TIMPs). The aim of this meta-analysis is to elucidate the behavior of plasma MMP and TIMP levels in hypertension and their relationship to cardiovascular remodeling. METHODS: MEDLINE and EMBASE databases were searched up to July 2011. Studies were considered eligible if they provided values of plasma MMPs and TIMPs in hypertensive patients. Given the high variability of the plasma biomarker values among studies, the standardized mean difference (SMD) was calculated. RESULTS: Ten studies provided plasma MMP-9; the SMD between 778 hypertensive patients and 669 controls was 1.95 units (P < 0.05). Thirteen studies provided plasma TIMP-1; the SMD between 851 hypertensive patients and 646 normotensive individuals was 1.92 units (P < 0.01). Three studies investigated whether plasma TIMP-1 predicted left ventricular (LV) remodeling; the SMD between 92 hypertensive patients with and 88 hypertensive patients without LV hypertrophy was 5.81 units (P < 0.05). As for diastolic heart failure (HF), five studies provided data for plasma MMP-2; the SMD between 321 hypertensive patients with and 334 hypertensive patients without HF was 2.36 units (P < 0.01). The heterogeneity among studies was high. CONCLUSIONS: These results suggest that MMP-2, MMP-9 and TIMP-1 may have a role as biomarkers of cardiovascular remodeling in hypertension. If these results are confirmed in prospective clinical studies, they could provide new tools to stratify cardiovascular risk in hypertensive patients.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".