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Record W4386796023 · doi:10.14715/cmb/2023.69.8.3

Management of Acute Cerebral Infarction by Intravenous Thrombolysis with Recombinant T Cell Receptor and Plasminogen Activator and Association of Emergency Nursing Route in the Prognosis

2023· article· en· W4386796023 on OpenAlexaboutno aff
Yuqi Liu, Chengyong Wang, Yuanpeng Han

Bibliographic record

VenueCellular and Molecular Biology · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsThrombolysisMedicineRecombinant tissue plasminogen activatorPlasminogen activatorRecombinant DNAReceptorCerebral infarctionInternal medicineIntensive care medicineMyocardial infarctionBiologyIschemiaIschemic strokeGeneBiochemistry

Abstract

fetched live from OpenAlex

The purpose of this study is to determine the impact and prognosis of the emergency nursing approach in conjunction with the use of recombinant T cell receptors and plasminogen activators in patients who have just had an acute stroke. In this study, 100 patients were randomly selected that were equally divided into experimental and control groups. The period of hospital admission, the results of the Montreal Cognitive Assessment (MoCA) and the Mini-mental State Examination (MMSE), the results of the Glasgow Outcome Scale (GOS), and the results of the Activities of Daily Living were all analysed before and after the intervention.. Both the amount of time it took to get a diagnosis after being admitted and the amount of time it took to receive specialised therapy after receiving a diagnosis were significantly reduced in the observation group (both P values less than 0.05). At one month after discharge, the scores of ADL, MoCA, MMSE, and GOS rose in both groups, with more significant changes occurring in the observation group (all P<0.05). This was due to the fact that ADL scores declined while scores for MoCA, MMSE, and GOS increased. The percentage of people who were disabled in the observation group was significantly lower than the percentage in the control group (P<0.05). Including emergency, nursing might drastically reduce the time it takes for patients with acute stroke to be admitted and begin receiving specialised care.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.006
GPT teacher head0.241
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2023
Admission routes1
Has abstractyes

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