Minor ischemic stroke and transient ischemic attack in young adults
Bibliographic record
Abstract
Background Minor stroke and transient ischemic attack are markers of reduced cerebral blood flow; they rarely occur in the young but may have a long-lasting impact and also lifelong cognitive impairment. Aim The objective of our work was to estimate the possible etiologies and early functional and disability outcome in young adults. Patients and methods This study was carried out on 52 patients aged from 18 to 50 years submitted to history taking, general medical examination, neurological evaluation, cardiologic assessment including (ECG, transthoracic echo, and transesophageal echo if needed), laboratory investigation, and radiological imaging including [computed tomography (CT) brain, MRI brain with diffusion, carotid duplex, transcranial duplex (TCD), and/or CT angiography when needed]. Modified Rankin scale and Montreal Cognitive Assessment scale were done at admission and 3 months after onset to assess physical dependence and cognitive impairment. Results The main risk factors for the development of minor stroke and transient ischemic attack were smoking (40.38%), hypertension (38.46%), diabetes mellitus (25%), cardiac disease (25%), and addiction (11.54%). The leading causes were small-artery disease (26.92%) and cardioembolic subtype (25%). The radiological finding of acute ischemic lesion was more common on diffusion-weighed imaging MRI than CT. Conclusions Smoking and hypertension were the most common risk factors. The most common causes are small-artery and cardioembolic diseases. Cognitive functions showed improvement within 3 months.
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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 | 0.000 | 0.001 |
| 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".