Evidence map›Paper›PMID 34737849›Full record

ArticleJournal of healthcare engineering2021

Dynamic Observation of the Effect of L-Theanine on Cerebral Ischemia-Reperfusion Injury Using Magnetic Resonance Imaging under Mathematical Model Analysis.

Hui Ye, Zaiming Liu, Long Zhou, Qiang Cai

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Hui YeRenmin Hospital of Wuhan University, Department of Neurosurgery, Wuhan, Hubei 430060, China.
Zaiming LiuRenmin Hospital of Wuhan University, Department of Neurosurgery, Wuhan, Hubei 430060, China.
Long ZhouRenmin Hospital of Wuhan University, Department of Neurosurgery, Wuhan, Hubei 430060, China.
Qiang CaiRenmin Hospital of Wuhan University, Department of Neurosurgery, Wuhan, Hubei 430060, China.ORCID 0000-0002-2595-9061
Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was to use the partial differential mathematical model to analyze the magnetic resonance imaging (MRI) images of cerebral ischemia-reperfusion injury (CIRI) and to dynamically observe the role of L-theanine in CIRI based on this. 30 patients with cerebral ischemia in a hospital in a certain area were selected and divided into a cerebral ischemia group and a L-theanine treatment group. The two groups of patients were examined by MRI within 48 hours, and the relative apparent diffusion coefficient (rADC) of the cerebral ischemic part of the patients was determined. The partial differential mathematical model was used for data processing to obtain the function of cerebral ischemia time and infarct area, and the data of patients in the cerebral ischemia group and L-theanine treatment group were compared and analyzed. The results showed that the partial differential mathematical model could effectively analyze the linear relationship between the rADC value and time in the treatment of CIRI using L-theanine. The rADC values of the four points of interest in the L-theanine treatment group all increased with time, and there was a positive correlation between the variables

Indexed as

Brain IschemiaReperfusion InjuryAdultAgedDiffusion Magnetic Resonance ImagingGlutamatesHumansMagnetic Resonance ImagingMiddle AgedModels, TheoreticalGlutamatestheanine

Identifiers

PMID34737849
PMCPMC8563127
OpenAlexW3209869171

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.