CURRENT AND EXPERIMENTAL TREATMENT OF STROKE
Bibliographic record
Abstract
Stroke is the third leading cause of death in the United States; approximately 730,000 Americans have a new or recurrent stroke each year. That’s one every minute and it costs the health care system $30 billion annually. The incidence of stroke is expected to rise dramatically as the population ages because stroke risk increases with age. The risk of stroke doubles for each decade after age 55. Stroke is a major factor in the late-life dementia that affects more than 40 % of Americans over the age of 80. One in four men will have had a disabling stroke by the age of 80 and one in five women by the age of 85. Currently Alteplase (recombinant tissue plasminogen ac-tivator [rtPA]) is the only treatment for acute stroke ap-proved in the United States. Alteplase is a thrombolytic agent that restores cerebral blood flow by removing the vas-cular occlusion. Alteplase is only an appropriate therapy for a small proportion of stroke patients (2%) because it must be given early to achieve efficacy and functional recovery following delayed reperfusion. Less than 15 % of patients, however, are admitted to the hospital within the 3-hour safety window (1). Several other new treatments are being tested in the clinic and even more are in preclinical develop-ment. Antiplatelet therapy and thrombolytics are aimed at improving cerebral blood flow but there are other therapeu-tic strategies such as neuroprotectants, antiinflammatory agents, free radical scavengers, and neurotrophic agents. In this chapter we survey the current status of clinical trials for stroke and review these therapeutic strategies. PATHOPHYSIOLOGY AND PRECLINICAL MODELS OF STROKE Stroke in the clinic is represented predominantly by is-chemic stroke (80%), in which there is a loss of cerebral
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".