Comparative Study of the Prognosis of Ischemic Cerebral Stroke Subtypes
Bibliographic record
Abstract
Background: The aim of the study was to search if prognosis of ischemic cerebral stroke is affected by its subtypes with regard to its etiology, anatomical site, radiological size, and clinical severity. Methods: This study was conducted on 43 patients of both sexes with ischemic cerebral stroke admitted to the Neurology Department of Menoufia University Hospitals. Their ages were ranging from 48 to 72 years old and the mean age of cases was 61.26 ± 5.37, while in controls was 58.50 ± 4.70. Clinical severity of stroke was assessed using National Institutes of Health Stroke Scale (NIHSS). The etiological subtypes of stroke were classified according to Trial of Organization 10172 in Acute Stroke Treatment classification. The anatomical site of stroke was evaluated by using the Oxford Community Stroke Project classification. Its size was measured by neuroimaging. Favorable outcome (FO) was defined as modified Rankin scale (0 - 2) while unfavorable outcome (UO) was defined as modified Rankin scale (3 - 6) after 3 months of onset of the stroke. Results: The UO was correlated with the large vessel stroke (P 3 mm (P = 0.007). The FO was correlated with small vessel disease (P < 0.001), mild NIHSS score (P ≤ 0.0001), lacunar infarction (P < 0.001), and infarct size < 1.5 mm (P = 0.001). Conclusion: The outcome of cerebral ischemic stroke may be affected by its subtype. This may help the clinician to tailor better individual plan of management. J Neurol Res. 2017;7(4-5):80-84 doi: https://doi.org/10.14740/jnr450w
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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 | 0.002 |
| 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".