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A clinical study on weakness of eye closure in supranuclear facial paralysis after stroke

2007· article· en· W3028812035 on OpenAlexaboutno aff
林健雯, 温红梅, 杨智云, 曾进胜

Bibliographic record

VenueChin J Neurol · 2007
Typearticle
Languageen
FieldMedicine
TopicFacial Nerve Paralysis Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsWeaknessMedicineParalysisFacial paralysisStroke (engine)Physical medicine and rehabilitationFacial weaknessClosure (psychology)Surgery

Abstract

fetched live from OpenAlex

目的 确切了解脑卒中后中枢性面瘫闭目乏力的发生率,探讨其发生机制.方法 观察1年内所有起病7 d内入院的脑卒中患者.使用美国国立卫生院脑卒中量表(National Institute of Health stroke scale,NIHSS)中第4项面瘫评分及日本面瘫评分(Japan facial score,JFS)进行面瘫评估,使用拉力测量器测量双侧眼轮匝肌的闭目力量差值.比较中枢性面瘫者伴与不伴闭目乏力两组的临床资料.结果 共收集病例914例,中枢性面瘫者伴闭目乏力且头颅MRI显示脑干无病灶者共40例,发生率为4.4%.脑卒中后中枢性面瘫伴闭目乏力者的双眼闭目力量差值随时间延长而递减(F=36.049,P<0.01),而不伴闭目乏力者双眼闭目力量无差异.伴闭目乏力者的责任病灶在右侧大脑半球的比例较不伴闭目乏力者高(72.50% vs 32.01%,χ2=32.95,P<0.01).两组的责任病灶的性质、分布部位、体积、Alberta卒中计划早期CT评分、有双侧病灶的比例均无差异.责任病灶分布在右侧大脑半球、年龄、性别以及是否有脑干病变这四项因素作为Cox回归的协变量,对中枢性面瘫闭目乏力的持续时间均无影响.结论 脑卒中后中枢性面瘫伴闭目乏力的发生率达4.4%,其发生机制可能与右侧大脑半球受损有关。

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 score0.007
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.408
Teacher spread0.371 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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