Body iron stores and early neurologic deterioration in acute cerebral infarction
Bibliographic record
Abstract
BACKGROUND: Iron-dependent free radicals formation has been related to greater damage in cerebral ischemia. The authors analyzed whether increased body iron stores were associated with early neurologic worsening and excitatory amino acid release in patients with acute ischemic stroke. METHODS: Ferritin, total iron, and glutamate concentrations in plasma and CSF were measured on admission in 100 consecutive patients with a cerebral infarction of <24 hours' duration. The authors diagnosed progressing stroke when the Canadian Stroke Scale score decreased one or more points between admission and 48 hours. Cranial CT was performed on admission and repeated on days 4 to 7 of hospitalization. RESULTS: Ferritin concentrations in plasma (median 391, range 119 to 500 versus 148, 21 to 399 ng/mL) and in CSF (17.4, 6.8 to 82, versus 4.8, 0.6 to 14 ng/mL) were significantly higher in the 45 patients with subsequent progressing stroke than in those with nonprogressing stroke (p < 0.001). There was a positive correlation between ferritin and glutamate concentrations in plasma (r = 0.81, p < 0.001) and CSF (r = 0.64, p < 0.001). Plasma ferritin concentrations >275 ng/mL in plasma (OR, 33.5; 95% CI, 4.7 to 235) and >11 ng/mL in CSF (OR, 11.4; 95% CI, 3. 1 to 41) were independently and significantly related to early neurologic worsening. The effect was reduced by >60% after controlling for glutamate concentrations, but remained significant. CONCLUSIONS: High plasma and CSF ferritin concentrations within the first 24 hours from the onset of ischemic stroke are associated with early neurologic deterioration. Increased body iron stores may contribute to stroke progression by enhancing the cytotoxic mechanisms in cerebral ischemia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".