Current management of acute ischemic stroke. Part 2: Antithrombotics, neuroprotectives, and stroke units.
Bibliographic record
Abstract
OBJECTIVE: To help family physicians who care for patients with acute stroke or who are involved in planning service delivery or resource allocation to understand recent developments in acute stroke care. QUALITY OF EVIDENCE: A MEDLINE search indicated that most data were derived from well designed, randomized, double-blind, placebo-controlled trials, including all the largest international studies and large systematic reviews. MAIN MESSAGE: Routine anticoagulation is not recommended except for circumstances such as cardioembolic stroke or deep vein thrombosis prophylaxis. Antiplatelet therapy with low-dose acetylsalicylic acid (or another antiplatelet agent if ASA is contraindicated) should be initiated within 48 hours of stroke onset, although benefit is modest. Dedicated care for stroke patients reduces morbidity and mortality and can be cost effective. Recent research into defibrinogenating and neuroprotective agents suggests some benefit, although none are currently licensed for use. Combination therapy might be the answer. CONCLUSION: Management of acute stroke is an emerging discipline; many potential therapies are still experimental.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".