Evidence map›Paper›PMID 36107230›Full record

SynthesisArchives of gynecology and obstetrics2023

PFMT relevant strategies to prevent perineal trauma: a systematic review and network meta-analysis.

Xiao Cao, Qiuyu Yang, Qi Wang, Shasha Hu, Liangying Hou, Mingyao Sun, Honghao Lai, Cailiang Wu, Yu Wu, Lin Xiao and 4 more

Abstract readSystematic ReviewNetwork Meta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Archives of gynecology and obstetrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

14 authors at 5 institutions in 2 countries.

Xiao CaoEvidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou, China.
Qiuyu YangEvidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou, China.
Qi WangDepartment of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China.
Shasha HuDepartment of Obstetrics and Gynecology, First Hospital of Lanzhou University, Lanzhou, China.
Liangying HouDepartment of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China.
Mingyao SunEvidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou, China.
Honghao LaiDepartment of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China.
Cailiang WuDepartment of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai, China.
Yu WuDepartment of Obstetrics and Gynecology, First Hospital of Lanzhou University, Lanzhou, China.
Lin XiaoEvidence-Based Nursing and Midwifery Practice Center, School of Nursing, Southern Medical University, Guangzhou, China.
Xiaofeng LuoSchool of Public Health, Lanzhou University, Lanzhou, China.
Jinhui TianEvidence-Based Medicine Center, School of Basic Medicine Science, Lanzhou University, Lanzhou, China.
Long GeDepartment of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China. gelong2009@163.com.ORCID http://orcid.org/0000-0002-3555-1107
Chenling LuoEvidence-Based Nursing and Midwifery Practice Center, School of Nursing, Southern Medical University, Guangzhou, China. 824223178@qq.com.
Lanzhou University · CNFirst Hospital of Lanzhou University · CNSouthern Medical University · CNMinistry of Education · BDShanghai First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost women suffer from perineal trauma during childbirth, whether it is natural tears or episiotomy.

objectivesTo perform a systematic review and network meta-analysis investigating the effectiveness of different PFMT relevant strategies in the prevention of perineal trauma. SEARCH STRATEGY: PubMed, Embase, the Cochrane Library, CINAHL, CNKI, CBM, WANFANG DATABASE, and ClinicalTrials.gov were searched for citations published in any language from inception to 1 July 2021. SELECTION CRITERIA: Randomized controlled trials (RCTs) of PFMT relevant prevention strategies for preventing perineal trauma during childbirth. DATA COLLECTION AND ANALYSIS: Data were independently extracted by two reviewers. Relative treatment effects were estimated using network meta-analysis (NMA). MAIN

resultsOf 12 632 citations searched, 21 RCTs were included. Comparing with usual care, "PFMT combine with perineal massage" and PFMT alone showed more superiority in intact perineum (RR = 5.37, 95% CI: 3.79 to 7.60, moderate certainty; RR = 2.58, 95% CI 1.34-4.97, moderate certainty, respectively), episiotomy (RR = 0.26, 95% CI 0.14-0.49, very low certainty; RR = 0.63, 95% CI 0.45-0.90, very low certainty, respectively), and OASIS (RR = 0.35, 95% CI 0.16-0.78, moderate certainty; RR = 0.49, 95% CI 0.28-0.85, high certainty, respectively). "PFMT combine with perineal massage" showed superiority in reducing perineal tear (RR = 0.41, 95% CI 0.20-0.85, moderate certainty).

conclusionsIn view of the results, antenatal "PFMT combine with perineal massage" and PFMT were effective strategies for the prevention of perineal trauma.

Indexed as

LacerationsParturitionDelivery, ObstetricEpisiotomyFemaleHumansPregnancyNetwork meta-analysisPerineal traumaPFMTVaginal delivery

Identifiers

PMID36107230
OpenAlexW4295908243

What OpenQuestion holds

Textmetadata
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.