Prognostički značaj biohemijskih, radioloških i kliničkih parametara za razvoj perifokalnog moždanog edema i ishod kod pacijenata sa intracerebralnom hemoragijom
Bibliographic record
Abstract
Background: In the present study, we have assessed the prognostic role of the biochemical (plasma glutamate and TNF-α), radiological and clinical variables for the development of the brain perifocal edema and the outcome in patients with intracerebral hemorrhage (ICH). Methods: This longitudinal study includes fifty patients with ICH and fifty healthy controls. Their peripheral blood plasma glutamate and TNF-α levels were detected by high-sensitivity ELISA. The initial hematoma volume, the volume of the hematoma and perifocal edema after five days and, the volume of the residual cavity 3 months after ICH were carefully evaluated by using computer tomography (CT); the Canadian Stroke Scale (CSS) was used for estimation of the symptom severity at admission and for estimation of the 3-month functional status and outcome after ICH. Results: We have revealed highly significant differences in blood plasma glutamate and TNF-α levels between patients and healthy controls, with good separation of their values. The two biochemical variables correlated with the admission symptom severity, the initial volume of ICH at admission, the volume of ICH five days after ICH and the volume of the perifocal edema. Both peripheral glutamate and TNF-α levels at admission were estimated as significant predictors for the volume of perifocal edema five days after ICH, but it was shown that they independently contribute (without any effect of interaction) to the volume of the edema, regardless the localization of the ICH. A priori, the anatomic localization of ICH was estimated as the only significant predictor for poor neurological outcome 3 months after ICH; patients with deep ICH had 96 times higher odds for poor outcome. Nevertheless, after the anatomic localization of ICH was omitted from the model, TNF-α was also confirmed as significant predictor for poor outcome. Conclusions: Our results support the idea for the significance of glutamate and TNF-α as peripheral markers for excitotoxicity and inflammation in ICH patients. Moreover, we believe that the developed multiple regression models for prediction of the volume of the perifocal edema and the clinical outcome could help in the dilemma between conservative treatment and surgical intervention in the clinical practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".