Effects of early lumbar cistern drainage of cerebrospinal fluid and combination of edaravone and nimodipine on vasospasm, intracranial pressure, inflammatory factors in traumatic subarachnoid hemorrhage
Bibliographic record
Abstract
Purpose: To investigate the effect of early lumbar cistern drainage (LCD) of cerebrospinal fluid (CSF) and combination of edaravone and nimodipine on vasospasm, intracranial pressure (ICP), serum inflammation, S100 and vascular endothelial growth factor (VEGF) levels in traumatic subarachnoid hemorrhage (tSAH).
 Methods: Treatment was administered to 136 patients divided into control group (n = 68) and study group (n = 68). Serum inflammation was determined by assessing the levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) while nitric oxide (NO), endothelin-1 (ET-1), S100 and VEGF levels were determined by enzyme-linked immunosorbent assay (ELISA). Serum C-reactive protein (CRP) level was measured by immunoturbidimetry. Perfusion weighted imaging was performed and the mean transit time (MTT), cerebral blood flow (CBF), cerebral blood volume (CBV), mean flow velocity (Vm) and pulsatility index (PI) were recorded. Glasgow coma scale (GCS) score and Montreal cognitive assessment (MoCA) score were used to compare the differences in therapeutic effect.
 Results: Compared with values before treatment, Vm, PI, NO, CBF, CBV, GCS score and MoCA score were significantly increased (p < 0.05), while ICP, serum levels of TNF-α, IL-6, CRP, ET-1, S100 and VEGF and MTT significantly decreased (p < 0.05). Therapeutic response rate of the study group (89.71 %) was higher than that of control group (66.18%) (p < 0.05).
 Conclusion: Early LCD of CSF and combination of edaravone and nimodipine reduces the degree of cerebral vasospasm and contribute to brain function recovery in the treatment of patients with tSAH. This therapeutic strategy requires further clinical trials before application in clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".