Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Triggers, Causes, and Outcome (SECRETO): Rationale and design
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Worldwide, about 1.3 million annual ischaemic strokes (IS) occur in adults aged <50 years. Of these early-onset strokes, up to 50% can be regarded as cryptogenic or associated with conditions with poorly documented causality like patent foramen ovale and coagulopathies. KEY HYPOTHESES/AIMS: (1) Investigate transient triggers and clinical/sub-clinical chronic risk factors associated with cryptogenic IS in the young; (2) use cardiac imaging methods exceeding state-of-the-art to reveal novel sources for embolism; (3) search for covert thrombosis and haemostasis abnormalities; (4) discover new disease pathways using next-generation sequencing and RNA gene expression studies; (5) determine patient prognosis by use of phenotypic and genetic data; and (6) adapt systems medicine approach to investigate complex risk-factor interactions. DESIGN: Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Etiology, Triggers, and Outcome (SECRETO; NCT01934725) is a prospective multi-centre case-control study enrolling patients aged 18-49 years hospitalised due to first-ever imaging-proven IS of undetermined etiology. Patients are examined according to a standardised protocol and followed up for 10 years. Patients are 1:1 age- and sex-matched to stroke-free controls. Key study elements include centralised reading of echocardiography, electrocardiography, and neurovascular imaging, as well as blood samples for genetic, gene-expression, thrombosis and haemostasis and biomarker analysis. We aim to have 600 patient-control pairs enrolled by the end of 2018. SUMMARY: SECRETO is aiming to establish novel mechanisms and prognosis of cryptogenic IS in the young and will provide new directions for therapy development for these patients. First results are anticipated in 2019.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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 it