Evidence map›Paper›PMID 29259939›Full record

ArticleIranian journal of public health2017

Effect of High-quality Nursing on Improvement of Anxiety and Depression of Patients with Acute Stroke in MRI Examination.

Lin Wu, Li Zhang

Abstract read
In one paragraph

Article in Iranian journal of public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

2 authors.

Lin WuDept. of MRI, Liaocheng People's Hospital, Liaocheng, Shandong, China.
Li ZhangDept. of Cardiology, Liaocheng People's Hospital, Liaocheng, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to evaluate the effect of high-quality nursing on improvement of anxiety and depression of patients with acute stroke in magnetic resonance imaging (MRI) examination.

methodsA total of 120 patients diagnosed as acute stroke for the first time were enrolled in Liaocheng People's Hospital from 2016-2017 and randomly divided into control group (n=60) and observation group (n=60). All patients received cerebral MRI examination at 6h and 24h after admission and before discharge. The control group was treated with routine nursing, while the observation group was treated with high-quality nursing, and the specific nursing measures included the establishment of high-quality nursing group, full evaluation of the severity of disease, timely solving of difficulties in MRI examination, understanding of the patient's anxiety and depression, establishment of personal information files before discharge, etc. The completion rate and average duration of examination, the improvement of anxiety and depression and the nursing satisfaction were compared between the two groups.

resultsIn observation group, the completion rate of MRI examination was significantly increased (

conclusionHigh-quality nursing can significantly improve the anxiety and depression of patients with acute stroke in MRI examination, which has a better application value in increasing the completion rate of examination, shortening the duration of examination and improving the nursing satisfaction.

Indexed as

Acute strokeAnxietyDepressionHigh-quality nursingMRI examination

Identifiers

PMID29259939
PMCPMC5734964

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.