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Record W2800192774 · doi:10.21776/ub.mnj.2018.004.02.4

COMPARISON OF ACUTE ISCHEMIC STROKE FUNCTIONAL OUTCOME IN SMOKERS AND NONSMOKERS MEASURED BY CANADIAN NEUROLOGICAL SCALE (CNS) AND NIHSS

2018· article· en· W2800192774 on OpenAlexaboutno aff
Nila Novia Putri, Mohamad Saiful Islam, Imam Subadi

Bibliographic record

VenueMNJ (Malang Neurology Journal) · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Internal medicineIschemic strokeMann–Whitney U testAcute strokeCardiologyPhysical therapyIschemia

Abstract

fetched live from OpenAlex

Background. Stroke is the world’s second leading cause of death and main cause of disability. Smoking is a well-known risk factor of stroke. However, the correlation between smoking and stroke outcome is still remains a controversy.Objective. To analyze the differences of functional outcome between smokers and non-smokers in acute ischemic stroke patients.Methods. The design used in this study is retrospective cross-sectional. The functional outcomes of acute ischemic stroke were measured by Canadian Neurologic Scale (CNS) and NIHSS over a period of seven days after the onset of stroke. Differences of CNS and NIHSS were analyzed using Mann-Whitney U test.Results. Median of CNS in smokers and non-smokers were 9.0 and 11.0, respectively. Median of NIHSS in smokers and non-smokers were 4.0 and 2.0, respectively. There were no significant differences in the analysis of CNS score between smokers and non-smokers and NIHSS score analysis between smokers and non-smokers.Conclusion. Smoking is not correlated with the functional outcome in acute ischemic stroke patients measured by CNS and NIHSS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.284
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2018
Admission routes1
Has abstractyes

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