Perfusion Changes in Acute Stroke Treated with Theophylline as an Add-on to Thrombolysis
Bibliographic record
Abstract
PURPOSE: Theophylline has been suggested to have a neuroprotective effect in ischemic stroke; however, results from animal stroke models and clinical trials in humans are controversial. The aim of this study was to assess the effect of theophylline on the cerebral perfusion with multiparametric magnetic resonance imaging (MRI). METHODS: The relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), and relative mean transit time (rMTT) in the infarct core, penumbra, and unaffected tissue were measured using multi-parametric MRI at baseline and 3‑h follow-up in patients treated with theophylline or placebo as an add-on to thrombolytic therapy. RESULTS: No significant differences in mean rCBF, rCBV, and rMTT was found in the penumbra and unaffected tissue between the theophylline group and the control group between baseline and 3‑h follow-up. In the infarct core, mean rCBV increased on average by 0.05 in the theophylline group and decreased by 0.14 in the control group (p < 0.04). Mean rCBF and mean rMTT in the infarct core were similar between the two treatment groups. CONCLUSION: The results indicate that theophylline does not change the perfusion in potentially salvageable penumbral tissue but only affects the rCBV in the infarct core. In contrast to the penumbra, the infarct core is unlikely to be salvageable, which might explain why theophylline failed in clinical trials.
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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) | 0.001 | 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".