Abstract 99: Diagnosis of Uncertain Origin Benign Transient Events (DOUBT)
Bibliographic record
Abstract
Background and Aims: TIA and minor stroke offer a massive opportunity for stroke prevention. Patients with motor or speech symptoms have a higher risk of early recurrent stroke. Many patients with transient or mild neurological deficits do not have high-risk features (eg sensory symptoms). The aim of the DOUBT study was to assess what proportion of these lower risk patients have true brain ischemia and secondarily to establish whether clinically we can predict what clinical factors predict a higher risk of brain ischemia. Method: DOUBT was a multicentre, international, prospective, observational, cohort study assessing the diagnosis and prognosis of patients with lower risk focal neurological symptoms. Patients aged ≥ 40, with no previous stroke, with either very brief (<5 minutes) motor or speech symptoms, or non-motor or speech focal neurological symptoms were included. Patients had a detailed neurological assessment and an MRI brain within 7 days of onset. Proportion of patients with an acute DWI lesion on MRI was the primary outcome. Results: 1047 patients in Canada, Europe and Australia were prospectively enrolled in the study. All patients had a detailed neurological assessment prior to undergoing MRI brain. Preliminary analysis shows 13% true brain schema rate (DWI positive). Patients were less likely to have a DWI lesion if their symptoms were fully resolved at assessment (RR 0.57, 95%CI: 0.38-0.79, p <0.001), if they reported any psychological stress (RR 0.57: 0.33-0.99, p=0.04) or if male (RR 0.58, 0.42-0.81, p=0.001). Patients were more likely to have a DWI lesion if they had any motor or speech symptoms (RR 1.7 (0.17-2.55, p=0.009). Secondary analysis looking at detailed clinical predictors of DWI lesions status will be presented. Conclusion: We found a low but real risk of true brain ischemia in these lower risk patients. Further analysis is needed to explain why woman are more likely to have DWI lesions with low risk symptoms. Detailed neurological assessment may help us stratify these patients further.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".