Bibliographic record
Abstract
A number of times I have commented on the remarkable advances we have made in acute stroke therapy and secondary prevention over the last 30 years. For acute stroke, we now have a series of proven interventions, which include management in a stroke unit, aspirin administered within 48 h, thrombolysis, hemicraniectomy, and more recently endovascular thrombectomy. Likely to be added to the list is the aggressive lowering of blood pressure as per the INTERACT II trial, which if supported by other trials will certainly provide level one evidence. For secondary prevention, we have the categories of antiplatelet agents, blood pressure and lipid lowering agents, oral anticoagulants, and carotid stenting/angioplasty for symptomatic carotid stenosis. This dazzling array of proven interventions, the first of which appeared in 1978, with the Canadian aspirin trial, should not blind us to the even greater need to prevent stroke all together. That is, a continuing emphasis on primary prevention since this is what we and society would generally regard as the most laudable aim. A massive task lies ahead, as developing countries transition from infectious to chronic diseases as the most important causes of morbidity and mortality. Concurrently, western societies face epidemics of obesity and an alarming rise in metabolic disorders such as diabetes. Through agencies such as the World Health Organization and campaigns promoted by the World Stroke Organization, we should continue our attack on modifiable primary prevention risk factors such as hypertension, smoking, therapy for AF, diet and lifestyle, and even air pollution. Protocols are important in our current edition, with some interesting ones including the HeadPoST study in which the long-standing conundrum of whether to manage patients flat or in the sitting position poststroke is addressed. ECASS-4: ExTEND is also presented, which is the sister study to ExTEND, both aiming to determine whether the time window for thrombolysis can be extended out to 9 h, including wake-up stroke. Finally, this is going to be a busy year, with our usual early International Stroke Conference, followed by the European Stroke Organisation Conference in Barcelona, and leading into the World Stroke Congress (WSC) in Hyderabad, India. You will recall that the first positive endovascular trial, Mr Clean was presented at the last WSC in Istanbul, in 2014; we look forward to a similar standard in Hyderabad, see you there!
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.027 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".