Association Between Duration of Transient Neurological Events and Diffusion‐Weighted Brain Lesions
Bibliographic record
Abstract
Background The relationship between duration of transient neurological events and presence of diffusion-weighted lesions by symptom type is unclear. Methods and Results This was a substudy of SpecTRA (Spectrometry for Transient Ischemic Attack Rapid Assessment), a multicenter prospective cohort of patients with minor ischemic cerebrovascular events or stroke mimics at academic emergency departments in Canada. For this study we included patients with resolved symptoms and determined the presence of diffusion-weighted imaging (DWI) lesion on magnetic resonance imaging within 7 days. Using logistic regression, we evaluated the association between symptom duration and DWI lesion, assessing for interaction with symptom type (focal only versus nonfocal/mixed), and adjusting for age, sex, education, comorbidities, and systolic blood pressure. Of 658 patients included, a DWI lesion was present in 232 (35.1%). There was a significant interaction between symptom duration and symptom type. For those with focal-only symptoms, there was a continuous increase in DWI probability up to 24 hours in duration (ranging from ≈40% to 80% probability). In stratified analyses, the increase in probability of DWI lesion with increased duration of focal symptoms was seen in women but not men. For those with nonfocal or mixed symptoms, predicted probability of DWI lesion was ≈35% and was greater in men, but did not increase with longer duration. Conclusions Increased duration of neurological deficits is associated with greater probability of DWI lesion in those with focal symptoms only. For individuals with nonfocal or mixed symptoms, about one-third had DWI lesions, but the probability did not increase with duration. These results may be important to improve risk stratification of transient neurological events.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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 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".