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Record W2407157345 · doi:10.12669/pjms.304.4930

Blood pressure levels and prognosis of intracranial trauma patients with cognitive dysfunction

2014· article· en· W2407157345 on OpenAlexaboutno aff
Weiyu Wang, Junbiao Fang, Bing Lei

Bibliographic record

VenuePakistan Journal of Medical Sciences · 2014
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBlood pressureCognitionMontreal Cognitive AssessmentLogistic regressionTraumatic brain injuryInternal medicineCardiologyDiseaseEmergency medicineCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the effects of blood pressure levels on prognosis of intracranial trauma patients with cognitive dysfunction. METHODS: One hundred and twenty intracranial trauma patients enrolled in our hospital from February 2011 to July 2013 were selected, including 40 hypertension and 80 non-hypertension cases. They were investigated by MiniMental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales, and the clinical data were retrospectively analyzed. RESULTS: Compared with the control group, the MoCA, visuospatial executive function, attention, language, delayed recall, MMSE, orientation and memory scores of the hypertension group were significantly lower. Unconditional Logistic regression analysis showed that age, history of cerebrovascular disease and triglyceride level were the independent risk factors of cognitive function. CONCLUSION: The blood pressure levels of intracranial trauma patients were associated with cognitive function, with age, history of cerebrovascular disease and triglyceride level as the independent risk factors. Therefore, it is necessary to control blood pressure level to improve prognosis.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.464
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.289
Teacher spread0.267 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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