A Prospective Evaluation of the Temporal Matrix Metalloproteinase Response after Severe Traumatic Brain Injury in Humans
Bibliographic record
Abstract
Abstract Accumulating pre-clinical data suggests that matrix metalloproteinase (MMP) expression plays a critical role in the pathophysiology of secondary brain injury. We conducted a prospective multimodal monitoring study in order to characterize the temporal MMP response after severe traumatic brain injury (TBI) in eight critically ill humans and its relationship with outcomes. High-cutoff, cerebral microdialysis (n=8); external ventricular drainage (n=3); and arterial and jugular venous bulb catheters were used to collect microdialysate, cerebrospinal fluid, and arterial and jugular bulb blood over 6 days. Levels of MMP-8 and -9 were initially high in microdialysate and then gradually declined over time. After these MMPs decreased, a spike in the microdialysate levels of MMP-2 and -3 occurred, followed by a gradual rise in the microdialysate concentration of MMP-7. Use of generalized estimating equations suggested that MMP-8 concentration in microdialysate was associated with mortality (p=0.019) and neurological outcome at hospital discharge (p=0.013). Moreover, the mean microdialysate concentration of MMP-8 was 2.4-fold higher among those who died after severe TBI than in those who survived. Mean microdialysate levels of MMP-8 also rose with increasing intracranial pressure (ICP), whereas those of MMP-7 decreased with increasing cerebral perfusion pressure (CPP). Significant changes in the mean microdialysate concentrations of MMP-1, -2, -3, and -9 and MMP-1, -2, -3, -7, and -9 also occurred with increases in microdialysate glucose and the lactate/pyruvate ratio, respectively. These results imply that monitoring of MMPs following severe TBI in humans is feasible, and that their expression may be associated with clinical outcomes, ICP, CPP, and cerebral metabolism.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".