Severe hemodilutional anemia increases cerebral tissue injury following acute neurotrauma
Bibliographic record
Abstract
Anemia may worsen neurological outcomes following traumatic brain injury (TBI) by undefined mechanisms. We hypothesized that hemodilutional anemia accentuates hypoxic cerebral injury following TBI. Anesthetized rats underwent unilateral TBI or sham injury (n > or = 7). Target hemoglobin concentrations between 50 and 70 g/l were achieved by exchanging 40-50% of the blood volume (1:1) with pentastarch. The effect of TBI, anemia, and TBI-anemia was assessed by measuring brain tissue oxygen tension (Pbr(O(2))), regional cerebral blood flow (rCBF), jugular venous oxygen saturation (Sjv(O(2))), cerebral contusion area, and nuclear staining for programmed cell death. Baseline postinjury Pbr(O(2)) values in the TBI and TBI-anemia groups (9.3 +/- 1.3 and 11.3 +/- 4.1 Torr, respectively) were lower than the uninjured controls (18.2 +/- 5.2 Torr, P < 0.05 for both). Hemodilution caused a further reduction in Pbr(O(2)) in the TBI-anemia group relative to the TBI group without anemia (7.8 +/- 2.7 vs. 14.8 +/- 3.9 Torr, P < 0.05). The rCBF remained stable after TBI and increased comparably after hemodilution in both anemia and TBI-anemia groups. The Sjv(O(2)) was elevated after TBI (87.4 +/- 8.9%, P < 0.05) and increased further following hemodilution (95.0 +/- 1.6%, P < 0.05). Cerebral contusion area and nuclear counts for programmed cell death were increased following TBI-anemia (4.1 +/- 3.0 mm(2) and 686 +/- 192, respectively) relative to TBI alone (1.3 +/- 0.3 mm(2) and 404 +/- 133, respectively, P < 0.05 for both). Hemodilutional anemia reduced cerebral Pbr(O(2)) and oxygen extraction and increased cell death following TBI. These results support our hypothesis that acute anemia accentuated hypoxic cerebral injury after neurotrauma.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".