Evidence map›Paper›PMID 34257847›Full record

SynthesisJournal of healthcare engineering2021

Multislice Spiral CT Image Analysis and Meta-Analysis of Inspiratory Muscle Training on Respiratory Muscle Function.

Lijuan An, Baiyan Li, Dan Ming, Weizhan Wang

Open access · hybridAbstract readMeta-Analysis
In one paragraph

Synthesis in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

4 authors at 1 institution in 1 country.

Lijuan AnPeople's Hospital of Hengshui, Clinical Medicine Major, Hebei, Hengshui 053000, China.
Baiyan LiPeople's Hospital of Hengshui, Clinical Medicine Major, Hebei, Hengshui 053000, China.
Dan MingPeople's Hospital of Hengshui, Clinical Medicine Major, Hebei, Hengshui 053000, China.
Weizhan WangPeople's Hospital of Hengshui, Clinical Medicine Major, Hebei, Hengshui 053000, China.ORCID 0000-0002-5477-4293
Hengshui University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiratory muscle function has a significant effect on stroke. Stroke is one of the most common cardiovascular and cerebrovascular diseases in the clinic and has a significant impact on the quality of life of patients. Hemiplegia, cerebral hemorrhage, and even death can occur, mainly in the elderly. In this paper, we meta-analyzed the effect of inspiratory muscle training on respiratory muscle function. In this article, we used a topic search method to search for relevant literature on respiratory muscle training and obtained 58 and 32 literature studies from CNKI and Wanfang Data, respectively. As a result of the screening, 36 and 28 documents were obtained. In this paper, 64 selected articles were studied. The authors make statistics on the literature of designing serum content index and multislice spiral CT (Member of the Society of Cardiological Technicians) image of patients, so as to analyze the influence of CT image and inspiratory muscle training on respiratory muscle function. The study showed that FVC, FEV1, MIP, and diaphragm mobility of the experimental group were significantly improved after treatment in more than 85% of the studies (

Indexed as

Quality of LifeRespiratory MusclesAgedBreathing ExercisesHumansRespirationTomography, Spiral Computed

Identifiers

PMID34257847
PMCPMC8249157
OpenAlexW3176674824

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.