Evidence map›Paper›PMID 36335169›Full record

ReviewJournal of human hypertension2023

Sex differences in preclinical models of hypertension.

Sol Olivera, Delyth Graham

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of human hypertension, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

16 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. The impact of sex on blood pressure.Current opinion in nephrology and hypertension · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. 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.

Sol OliveraSchool of Cardiovascular and Metabolic Health, University of Glasgow, 126 University Place, Glasgow, G12 8TA, UK.
Delyth GrahamSchool of Cardiovascular and Metabolic Health, University of Glasgow, 126 University Place, Glasgow, G12 8TA, UK. Delyth.Graham@glasgow.ac.uk.ORCID http://orcid.org/0000-0002-7328-4708
University of Glasgow · GB

Funding

British Heart Foundation FS/4yPhD/F/20/34127
6 · The paper itself

Abstract

Hypertension remains the primary contributor in the development of cardiovascular disease which is rapidly increasing worldwide. High blood pressure affects men and women differently and understanding these sex differences is the ultimate unmet need for researchers in this field. Due to the inherent differences in hypertension prevalence, control and outcomes between men and women, novel research needs to be carried out to tackle these disparities and improve targeted treatment. Animal models of hypertension have provided valuable insights into the sexual dimorphism of blood pressure mechanisms. The availability of genetic and non-genetic hypertensive strains allows the opportunity to study diverse environmental and genetic factors that affect blood pressure, therefore presenting a valuable tool for researchers. Sex differences are present before birth and throughout life, which presents a challenge for the study of disease development in humans, but these complexities can be resolved with the use of in vivo models that display similarities to human disease. The aim of the present review is to provide an overview of the different available animal models of hypertension that present sexual dimorphisms and to discuss their relevance to humans.

Indexed as

Cardiovascular DiseasesHypertensionAnimalsBlood PressureFemaleMaleSex CharacteristicsSex Factors

Identifiers

PMID36335169
PMCPMC10403342
OpenAlexW4308207694

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.