PERBANDINGAN DERAJAT DISABILITAS PASIEN STROKE ISKEMIK AKUT YANG DIUKUR DENGAN SKALA NEUROLOGIK KANADIAN DAN NIHSS PADA PEROKOK DAN BUKAN PEROKOK DI RSUD DR. SOETOMO SURABAYA
Bibliographic record
Abstract
Introduction. Stroke is the second leading cause of death in the world after heart \ndisease and is a major cause of disability.Smoking is a well-known risk factor which \nmay increase the risk of ischemic stroke by 2-3. However, the correlation between \nsmoking and stroke outcome is still remains a controversy. Thus, the aim of this study \nis to analyze the differences of the degree of disability between smokers and nonsmokersin \nacute ischemic stroke patients, measured by Canadian Neurological Scale \n(CNS) and NIHSS. \nMethod.The design used in this study was retrospective cross-sectional. Differences \nof Canadian Neurological Scale (CNS) and NIHSS was analyzed using Mann- \nWhitney U test. \nResult. This study included 43 patients with acute ischemic stroke on their first \nattack. The mean age of study subjects was 56.30 ± 9.89 years. There were 23 male \npatients (53.5%) and 20 female patients (46.5%) with 13 patients are smokers and 30 \npatients are non-smokers.There were no female smokers in this study, thus only the \nmale group’s CNS and NIHSS value were analyzed. Means of CNS in smokers and \nnon-smokers were 8.62 ± 2.69 and 9.55 ± 1.98, respectively. Median of NIHSS in \nsmokers and non-smokers were 4.0 and 3.0, respectively. There were no significant \ndifferences in the analysis of CNS score between smokers and non-smokers (p = \n0,446) and NIHSS score analysis between smokers and non-smokers (p= 0,522). \nConclusion. Smoking does not affect the degree of disability in acute ischemic stroke \npatients measured by CNS and NIHSS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".