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Evaluation of stroke prognostication using age and National Institute of Health Stroke Scale index for outcome after early endovascular treatment for anterior circulation large vessel occlusion

2018· article· en· W3032344398 on OpenAlexaboutno aff
Xianjun Huang, Wusheng Zhu, Qian Yang, Yujuan Zhu, Xiaolei Shi, Zhenhui Duan, Liang Ge, Xianhui Ding, Xiangjun Xu

Bibliographic record

VenueChin J Neurol · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineModified Rankin ScaleStroke (engine)Logistic regressionPerioperativeOcclusionIntracerebral hemorrhageInternal medicineSurgeryIschemic strokeSubarachnoid hemorrhageIschemia

Abstract

fetched live from OpenAlex

Objective To evaluate the value of stroke prognostication using age and National Institute of Health Stroke Scale index(SPAN) for outcome after early endovascular treatment for anterior circulation large vessel occlusion. Methods The patients who underwent early endovascular treatment were prospectively, sequentially collected in Yijishan Hospital of Wannan Medical College from December 2014 to September 2017 and Jinling Hospital from March 2014 to March 2017. Individuals whose age in years plus NIHSS score was greater than or equal to 100 were designated as SPAN-100-positive patients, while those with a score less than 100 were designated as SPAN-100-negative patients. We compared the baseline data and perioperative data between the two groups. The 90 days modified Rankin Scale score≤2 was regarded as favorable outcome. Single factor and multivariable Logistic regression analyses were used to determine the association between SPAN-100 and outcomes. Results One hundred and ninety patients were enrolled, 20(10.5%) of which were SPAN-100 positive, and 170(89.5%) were SPAN-100 negative. There were no significant differences between the two groups on postoperative intracerebral hemorrhage and 90 days mortality. Ninety days independence rates were higher in SPAN-100-negative patients(77/170, 45.3%) than in SPAN-100 positive patients (4/20, 20.0%; χ2=4.681, P=0.030). Multi-factor Logistic regression analysis showed that the higher preoperation systolic pressure (OR=1.030, 95% CI 1.008-1.052, P=0.007), the lower Alberta Stroke Program Early CT Score (OR=1.609, 95% CI 1.056-2.453, P=0.027) and poor collateral circulation(OR=5.714, 95% CI 1.668-19.570, P=0.006) were the independent risk factors of outcomes. Conclusion SPAN-100 is not an independent predictor of favorable outcome after adjusting for factors of outcomes in patients with anterior circulation large vessel occlusion. Key words: Stroke; Age; Mechanical thrombectomy; Prognosis; Risk factors

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)0.001
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 score0.197
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.355
Teacher spread0.297 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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