Abstract TMP117: Characterization of Patients With Embolic Strokes of Uncertain Source in the Navigate-ESUS Trial
Bibliographic record
Abstract
Background: The New Approach riVaroxaban Inhibition of Factor Xa in a Global trial vs. ASA to prevenT Embolism in Embolic Stroke of Undetermined Source (NAVIGATE-ESUS) trial is an international randomized phase III trial comparing rivaroxaban versus aspirin in patients with recent ESUS. While these patients share the common stroke mechanism of ESUS, the underlying potential embolic sources vary, and therefore a detailed description of the baseline characteristics across key subgroups is essential. Methods: A total of 7000 patients were enrolled and the study will continue until at least 450 primary events have occurred. The primary efficacy outcome is time to recurrent stroke or systemic embolism. Baseline characteristics collected in the trial include demographic features, medical history, qualifying stroke information, baseline functional and cognitive status, and the results of diagnostic testing. Pre-specified subgroups analyses for the primary safety and efficacy outcomes include: age, sex, race, global region, body mass index, weight, estimated glomerular filtration rate, stroke or TIA prior to qualifying event, time from qualifying stroke to randomization, duration of cardiac rhythm monitoring, PFO, hypertension, and diabetes mellitus. Results: Participants were recruited from 460 sites in 31 countries between December 2014 and September 2017. A summary of baseline characteristics for the initial 6271 participants (will be updated) according to prespecified age subgroups are shown in the Table. Additional subgroup comparisons will be presented. Conclusions: NAVIGATE ESUS will be the largest randomized trial comparing antithrombotic therapeutic strategies for secondary stroke prevention in patients with ESUS. The study population encompasses a wide array of patients across multiple continents with important differences according to age. The results are expected to have a global impact.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".