Evidence map›Paper›PMID 30167317›Full record

ArticleBMJ open sport & exercise medicine2018

Can resistance training improve the symptoms of polycystic ovary syndrome?

Paraskevi Pericleous, Savvas Stephanides

Open access · goldAbstract read
In one paragraph

Article in BMJ open sport & exercise medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Effects of physical activity in women with polycystic ovary syndrome: a systematic review and meta-analysis.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2025
    Pooled it
  2. Review
  3. Exercise and Polycystic Ovary Syndrome.Advances in experimental medicine and biology · 2020
    Review
  4. Article
  5. 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 at 1 institution in 1 country.

Paraskevi PericleousHealth eResearch Center, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID 0000-0001-7598-3062
Savvas StephanidesHealth eResearch Center, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Manchester Academic Health Science Centre · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIt has been suggested that the symptoms of Polycystic Ovary Syndrome (PCOS) could be improved by resistance training.

designThis review focuses on identifying studies that use resistance training to examine how it can affect the symptoms of polycystic ovary syndrome (PCOS).

methodsMedline, Cochrane, Dare and PubMed databases were searched to find relevant articles. All studies were assessed in terms of their design and methods.

resultsWe found 10 studies that used resistance training to examine how it affects the symptoms of PCOS.

conclusionsThere is a need for further investigation. Most studies that examine the effects of resistance training on the symptoms of PCOS needed to consider the diet (macronutrient) of the participants along with the resistance training to have a better picture of how resistance training can affect the PCOS symptoms. Many questions are still unanswered.

Indexed as

BMIdietexercisePCOSstrength trainingweight training

Identifiers

PMID30167317
PMCPMC6109818
OpenAlexW2883234585

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.