Prognostic factors in acute stroke, regarding to stroke severity by Canadian Neurological Stroke Scale: A hospital-based study
Bibliographic record
Abstract
INTRODUCTION: Stroke is an acute vascular disease and the second leading cause of death in the world. We have assessed the patients on hospital admission with some other prognostic factors besides the preliminary neurological examinations in order to estimate their clinical status in the future. MATERIALS AND METHODS: The present study was performed on the patients admitted to Valiasr Hospital of Arak within 72 h of stroke onset from April to October 2011. Diagnosis of stroke in the suspected patients was done by a neurologist and verified by the findings of the computed tomography scans. For each patient, a specific questionnaire, which described its stroke severity according to canadian neurological scale of stroke (CNSS), was prepared in order to define the severity of the stroke. Systolic as well as diastolic blood pressure of the patients was measured at the admission and their level of blood sugar, cholesterol, and triglyceride was also determined. RESULTS: Out of 62 patients under study (mean age, 66.14 ± 10.9 years), 36 (58.1%) were males and 26 (41.9%) were females. Overall, 66.1% of the patients were diagnosed with the ischemic stroke, while 33.9% were diagnosed with the hemorrhagic stroke. Regression analysis showed that cholesterol and diastolic blood pressure were the most important prognostic factors of the severity of stroke (CNSS). CONCLUSION: Diastolic blood pressure and serum cholesterol level have the potential to be used for assessing the stroke outcome as well as to improve the stroke rehabilitation.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".