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Record W2393841134

Comparative study of underwent carotid stent implantation and drug therapy in patients with cerebral infarction combined cognitive impairment

2015· article· en· W2393841134 on OpenAlexaboutno aff
Han Bingsh

Bibliographic record

VenueChina Medicine and Pharmacy · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCerebral infarctionBarthel indexInternal medicineStentCognitive impairmentCognitionDrug treatmentSurgeryCardiologyPhysical therapyIschemiaActivities of daily livingPsychiatryDisease
DOInot available

Abstract

fetched live from OpenAlex

Objective To study the influence of cognitive impairment of underwent carotid stent implantation in patients with cerebral infarction combined cognitive impairment. Methods Of the 80 patients with cerebral infarction combined cognitive impairment, based on the routine treatment, 45 patients with indication in stent group were treated with underwent carotid stent transluminal angioplasty, and the other 35 patients in drug group were treated with drug therapy. To observe the changes of cognitive function by mini mental state examination(MMSE), Montreal cognitive function scale(Mo CA), daily living measuring scale(Barthel index) before treatment and treatment after 1, 3, 6 months. Results The MMSE, Mo CA score, and Barthel index in drug group after treatment 6 months and in stent group after operation 1, 3, 6 months were obviously increased compared with before treatment, the differences was statistically significant(P 0.05), and which in stent group was obviously increased compared with which in drug group, the differences was statistically significant(P 0.05). Conclusion Underwent carotid stent implantation could improve the cognitive impairment in patients with cerebral infarction combined cognitive impairment.

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 score0.037
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.074
GPT teacher head0.338
Teacher spread0.264 · 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
Published2015
Admission routes1
Has abstractyes

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