Evidence map›Paper›PMID 34712285›Full record

ArticlePakistan journal of medical sciences2021

Application of Quantitative CT Imaging in Rehabilitation Nursing of Cerebral Apoplexy Patients.

Bing Yan, Huanhuan Zhang, Jie Liu

Open access · goldAbstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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 50% 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Bing YanBing Yan, Bachelor's Degree, Department of Nursing, Huaihe Hospital of Henan University, Kaifeng 475000, Henan Province, China.
Huanhuan ZhangHuanhuan Zhang, Master of Degree, Department of Nursing, Huaihe Hospital of Henan University, Kaifeng 475000, Henan Province, China.
Jie LiuJie Liu, Master of Degree, Department of Nursing, Huaihe Hospital of Henan University, Kaifeng 475000, Henan Province, China.
Henan University Huaihe Hospital and Huaihe Clinical Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesElectronic computed tomography (CT) is an important imaging method for the diagnosis of cerebral infarction. This paper explores the preventive effects of quantitative CT imaging and early rehabilitation nursing on patients with cerebral apoplexy and shoulder-hand syndrome.

methodsSixty cerebral apoplexy patients treated were included as control group and given routine care from September 2018 to May 2020. Sixty cerebral apoplexy patients were included as observation group, and early rehabilitation nursing intervention was given based on control group. The incidence of shoulder-hand syndrome and upper limb function were compared between the two groups, to explore the effectiveness of the CT examination in promoting the physical function restoration.

resultsThe incidence of shoulder-hand syndrome in observation group after three months of intervention was lower than that in control group, and the severity was less than that in control group (P<0.05); The Ashworth score of muscle tension in observation group after three months of intervention was lower than that in control group, and the simplified FMA score of the upper limbs was higher than that in control group.

conclusionEarly rehabilitation nursing intervention after CT examination can prevent the occurrence of cerebral apoplexy and shoulder-hand syndrome and improve upper limb function, which is worthy of promotion.

Indexed as

Cerebral apoplexyComputed tomographyRehabilitation nursingUpper limb

Identifiers

PMID34712285
PMCPMC8520363
OpenAlexW3190826522

What OpenQuestion holds

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LicenceCC BY
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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.