Evidence map›Paper›PMID 33365329›Full record

ReviewFrontiers in cardiovascular medicine2020

Experimental Rodent Models of Cardiovascular Diseases.

Tian Jia, Chen Wang, Zhengxi Han, Xiaozhi Wang, Ming Ding, Quanyi Wang

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Review
  2. The Tricuspid Valve Maladapts in a Pulmonary Hypertension Rat Model.bioRxiv : the preprint server for biology · 2026
    Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. From bench to bedside and back: translational cardiovascular interventions in veterinary medicine.Postepy w kardiologii interwencyjnej = Advances in interventional cardiology · 2025
    Review
  8. Review
  9. Review
  10. Article
  11. Article
  12. Comparative analysis of autonomic effects of ketamine-xylazine in normotensive and hypertensive rats.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2025
    Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
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  20. 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

6 authors.

Tian JiaSchool of Life Science and Technology, China Pharmaceutical University, Nanjing, China.
Chen WangSchool of Life Science and Technology, China Pharmaceutical University, Nanjing, China.
Zhengxi HanSchool of Pharmacy, China Pharmaceutical University, Nanjing, China.
Xiaozhi WangDepartment of Cardiology, The First Affiliated Hospital With Nanjing Medical University, Nanjing, China.
Ming DingSchool of Life Science and Technology, China Pharmaceutical University, Nanjing, China.
Quanyi WangSchool of Life Science and Technology, China Pharmaceutical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular diseases, as the most common non-communicable disease in the world, cause a high mortality rate today and bring a serious medical burden to countries worldwide, especially in low- and middle-income countries. Experimental rodent models are widely used for cardiovascular diseases researches due to the effective simulation of human cardiovascular diseases, strong reproductive ability, and easy detection. Herein, we will summarize the pathological manifestations of common cardiovascular diseases and illustrate the establishment of corresponding experimental rodent models in detail.

Indexed as

cardiovascular diseasescoronary heart diseasehypertensionmodeling methodsrodent models

Identifiers

PMID33365329
PMCPMC7750387

What OpenQuestion holds

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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.