Sickle cell cerebrovascular reactivity to a CO2 stimulus: Too little, too slow
Bibliographic record
Abstract
Background: Despite increased cerebral blood flow (CBF), cerebral infarcts occur in patients with sickle cell disease (SCD). This suggests increased CBF does not meet metabolic demand possibly due to compromised cerebral vasodilatory response. Hypothesis: In adult SCD patients, cerebrovascular reactivity (CVR) and speed of vasodilatory response (tau) to a standardized vasodilatory stimulus, are reduced compared to normal subjects. Methods: Functional brain imaging performed as part of routine care in adult SCD patients without known large vessel cerebral vasculopathy was reviewed retrospectively. CVR was calculated as the change in CBF measured as the blood-oxygenation-level-dependent (BOLD)-magnetic resonance imaging signal, in response to a standard vasoactive stimulus of carbon dioxide (CO 2 ). The tau corresponding to the best fit between the convolved end-tidal partial pressures of CO 2 and BOLD signal was defined as the speed of vascular response. CVR and tau were normalized using a previously generated atlas of 42 healthy controls. Results: Fifteen patients were included. CVR was reduced in grey and white matter (mean Z-score for CVR −0.5 [−1.8 to 0.3] and −0.6 [−2.3 to 0.7], respectively). Tau Z-scores were lengthened in grey and white matter (+0.9 [−0.5 to 3.3] and +0.8 [−0.7 to 2.7], respectively). Hematocrit was the only significant independent predictor of CVR on multivariable regression. Conclusion: Both measures of cerebrovascular health (CVR and tau) in SCD patients were attenuated compared to normal controls. These findings show that CVR represents a promising tool to assess disease state, stroke risk, and therapeutic efficacy of treatments in SCD and merits further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".