Evidence map›Paper›PMID 30524985›Full record

ArticleIranian journal of public health2018

Application of Doctor-Nurse-Patient Integration Management Mode in Patients with Endometriosis.

Yao Chen, Zhihuai Mo, Jianyong Cao, Zhaojuan Su, Yuexia Zhang, Fang Chen, Jianying Wang

Abstract read
In one paragraph

Article in Iranian journal of public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Trial
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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

7 authors.

Yao ChenDept. of Obstetrics, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.
Zhihuai MoDept. of Neurology, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.
Jianyong CaoDept. of Obstetrics, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.
Zhaojuan SuDept. of Obstetrics, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.
Yuexia ZhangDept. of Obstetrics, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.
Fang ChenDept. of Obstetrics, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.
Jianying WangDept. of Obstetrics, The Fifth Affiliated Hospital Sun Yat-Sen University, Zhuhai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo investigate the effect of applying doctor-nurse-patient integration management mode to patients with endometriosis (EMT).

methodsA total of 160 patients with EMT from the Department of Neurology of The Fifth Affiliated Hospital Sun Yat-Sen University from January 2017 to October 2017 were selected. They were divided into control group and experimental group according to the time sequence of hospitalization, with 80 patients in each group. The traditional nursing management mode was implemented in the control group, and doctor-nurse-patient integration mode was implemented in the experimental group. The psychological status, quality of life, and satisfaction of the 2 groups of patients were compared one year after surgery.

resultsThe anxiety and depression scores in the observation group were (41.89±7.50) and (42.40±7.40) points, respectively, and those in the control group were (57.55±9.68) and (55.00±9.35) points, respectively. The differences between the two groups were statistically significant (

conclusionThe doctor-nurse-patient integration management mode can effectively improve the negative psychological status and quality of life of patients with EMT and improve patient satisfaction, which is worth popularizing.

Indexed as

Doctor-nurse-patient integrationEndometriosisPsychological statusQuality of life

Identifiers

PMID30524985
PMCPMC6277728

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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.