Measurement of cerebral venous oxygenation with quantitative susceptibility mapping after subarachnoid hemorrhage: A pilot study
Bibliographic record
Abstract
Objective We measured cerebral venous oxygenation after aneurysmal subarachnoid hemorrhage (aSAH) using quantitative susceptibility mapping (QSM) to explore its relationship with cognitive function. Methods Twenty participants, including 10 patients with aSAH and 10 healthy volunteers as the control group, were included. Patients with aSAH were evaluated at 2 days, 3 weeks, and 6 months after aSAH. Each participant underwent magnetic resonance imaging and completed the Montreal Cognitive Assessment (MoCA) at baseline, midpoint, and endpoint. QSM was used to determine the magnetic susceptibility of the cerebral veins. Furthermore, the relationship between MoCA and oxygen saturation in the cerebral veins was examined. Results The first scans of the cerebral veins and straight sinus susceptibility were considerably more significant in the aSAH group than in the healthy control group. At the 6-month follow-up, the mean oxygen saturation steadily increased in the aSAH group. Cerebral venous oxygen saturation was moderately correlated with MoCA (r = 0.5319, P = .0025). Conclusion QSM can be used to measure changes in cerebral venous oxygenation levels in patients with aSAH. During the acute phase of aSAH, there is a reduction in the oxygen saturation in the cerebral veins, and the shift in oxygen saturation levels may correlate with cognitive outcomes in patients with aSAH.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".