Critical Illness–Associated Cerebral Microbleeds
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cerebral microbleeds (petechial hemorrhages) are a well-known consequence of cerebral amyloid angiopathy and chronic hypertension among other causes. We report 12 patients with a clinically and radiologically distinct microbleed phenomenon in the cerebral white matter. METHODS: These patients were assessed at the University Health Network (Toronto, Canada) between 2004 and 2014. RESULTS: Median age was 40 years (range, 27-63 years), and 7 out of 12 patients were women. All patients had brain magnetic resonance imaging during or immediately after an intensive care unit admission. All patients had respiratory failure, 11 out of 12 received mechanical ventilation, and 3 out of 12 received extracorporeal life support. Magnetic resonance imaging in all 12 patients showed extensive microbleeds, diffusely involving the juxtacortical white matter and corpus callosum but sparing the cortex, deep and periventricular white matter, basal ganglia, and thalami. Several patients also had internal capsule or posterior fossa involvement. CONCLUSIONS: We have described a distinct microbleed phenomenon in the cerebral white matter of patients with critical illness. The specific cause of the microbleeds is unclear, but the pathogenesis may involve hypoxemia as the microbleeds are similar to those described with high-altitude exposure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".