Cytoprotective agents in stroke: Still uncertainty in the next frontier
Bibliographic record
Abstract
INTRODUCTION: Despite substantial improvement of acute ischemic stroke (AIS) care with the advent of extended time windows for intravenous thrombolysis (IVT) and endovascular thrombectomy (EVT), a substantial portion of patients still suffer poor outcomes. Additional adjuvant therapies are needed but pharmacologic interactions among therapies may dictate how they could be used. We conducted a survey to determine physician decision-making regarding the use of cytoprotective agents in patients presenting with AIS. METHODS: The survey was structured, web-based, anonymous, and invite-only among physicians across the world treating patients presenting with AIS. Respondents were asked about the use of a hypothetical cytoprotective agent (that provided an added 10% benefit) in the context of a treatment interaction with IVT or its timing in relation to IVT. RESULTS: A total of 282 stroke physicians (74.9% males, mean age 46 years) participated in the survey. When the respondent could give both the cytoprotective agent and IVT with no treatment interaction, 177 (78.0%) chose to administer both. In the presence of treatment interaction, 88 (38.3%) would withhold IVT, 83 (36.1%) would withhold the cytoprotective agent and 56 (24.4%) were uncertain. Lastly, 111 (48.9%) were willing to administer the cytoprotective agent if it meant a necessary 10-minute delay in IVT administration. CONCLUSIONS: Pharmacologic interactions result in major uncertainty about cytoprotective treatment choices.
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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 | 0.028 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".