Left-Sided Neurological Symptoms and Negative Diffusion-Weighted MRI in Suspected Minor Stroke Patients
Bibliographic record
Abstract
ABSTRACT Background: Historically, it has been proposed that functional neurological symptoms occur more frequently on the left side of the body due to a distinct body representation and emotional processing of the right hemisphere, yet objective imaging data to support this are lacking. We aimed to investigate whether patients with acute left-sided symptoms (right hemisphere) suspected of having a minor stroke are more likely to show negative diffusion-weighted imaging (DWI) compared to those with right-sided symptoms. Methods: Data are from the SpecTRA (Spectrometry for Transient Ischemic Attack Rapid Assessment) multicenter prospective cohort study conducted between 2013 and 2017. Patients with mild persistent unilateral hemiparesis and/or hemisensory symptoms (National Institute of Health Stroke Scale ≤ 3) and available DWI were included. The primary outcome was the proportion of patients with a negative DWI. Results: Of 1731 patients, 584 (30.8%) were included. Of these, 310 (53.1%) patients presented with left-sided symptoms and 274 (46.9%) with right-sided symptoms. Overall, 214 (36.6%) patients had a negative DWI, 126 (58.9%) with left-sided symptoms and 88 (41.1%) with right-sided symptoms: risk ratio (RR) 1.27 (95% CI = 1.02–1.57). Left-sided hemiparesis was associated with negative DWI (RR 1.42 [95% CI = 1.08–1.87]), while left-sided hemisensory symptoms were not (RR 1.11 [95% CI = 0.87–1.41]). There was no effect modification by age or sex on this association (P interaction 0.787 and 0.057, respectively). Conclusions: Unilateral left-sided neurological symptoms were more frequently associated with negative DWI compared to right-sided symptoms in suspected minor stroke patients. This observation is exploratory, as the final diagnosis in DWI-negative cases was not established.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".