Evidence map›Paper›PMID 36229816›Full record

ArticleBMC medicine2022

Non-invasive assessment of HFpEF in mouse models: current gaps and future directions.

María Villalba-Orero, Pablo Garcia-Pavia, Enrique Lara-Pezzi

Open access · goldAbstract readLetter
In one paragraph

Article in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.8field-weighted citation impact, top 5% 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

19 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Review
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  4. Doppler Echocardiography for Assessment of Diastolic Function in Mice.Journal of visualized experiments : JoVE · 2026
    Article
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  6. Low and High Pressor Doses of Ang II Lead to Two Distinct Phenotypes of Hypertensive Heart Disease in Mice.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2026
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  7. Review
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  15. Characterization of a robust mouse model of heart failure with preserved ejection fraction.American journal of physiology. Heart and circulatory physiology · 2023
    Article
  16. Review
  17. Article
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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

3 authors at 3 institutions in 1 country.

María Villalba-OreroDepartamento de Medicina y Cirugía Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Av. Puerta de Hierro, s/n, 28040, Madrid, Spain. mvorero@ucm.es.ORCID 0000-0002-7680-3980
Pablo Garcia-PaviaMyocardial Pathophysiology Area, Centro Nacional de Investigaciones Cardiovasculares Carlos III, Melchor Fernández Almagro, 3, 28029, Madrid, Spain.
Enrique Lara-PezziMyocardial Pathophysiology Area, Centro Nacional de Investigaciones Cardiovasculares Carlos III, Melchor Fernández Almagro, 3, 28029, Madrid, Spain. elara@cnic.es.
Centro de Investigación Biomédica en Red · ESUniversidad Complutense de Madrid · ESUniversidad Francisco de Vitoria · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure (HF) with preserved ejection fraction (HFpEF) prevalence is increasing, and large clinical trials have failed to reduce mortality. A major reason for this outcome is the failure to translate results from basic research to the clinics. Evaluation of HFpEF in mouse models requires assessing three major key features defining this complex syndrome: the presence of a preserved left ventricular ejection fraction (LVEF), diastolic dysfunction, and the development of HF. In addition, HFpEF is associated with multiple comorbidities such as systemic arterial hypertension, chronic obstructive pulmonary disease, sleep apnea, diabetes, and obesity; thus, non-cardiac disorders assessment is crucial for a complete phenotype characterization. Non-invasive procedures present unquestionable advantages to maintain animal welfare and enable longitudinal analyses. However, unequivocally determining the presence of HFpEF using these methods remains challenging. MAIN TEXT: Transthoracic echocardiography (TTE) represents an invaluable tool in HFpEF diagnosis, allowing evaluation of LVEF, diastolic dysfunction, and lung congestion in mice. Since conventional parameters used to evaluate an abnormal diastole like E/A ratio, isovolumic relaxation time, and E/e' may pose limitations in mice, including advanced TTE techniques to characterize cardiac motion, including an assessment under stress, will improve diagnosis. Patients with HFpEF also show electrical cardiac remodelling and therefore electrocardiography may add valuable information in mouse models to assess chronotropic incompetence and sinoatrial node dysfunction, which are major contributors to exercise intolerance. To complete the non-invasive diagnosis of HF, low aerobic exercise capacity and fatigue using exercise tests, impaired oxygen exchange using metabolic cages, and determination of blood biomarkers can be determined. Finally, since HFpEF patients commonly present non-cardiac pathological conditions, acquisition of systemic and pulmonary arterial pressures, blood glucose levels, and performing glucose tolerance and insulin resistance tests are required for a complete phenotyping.

conclusionIdentification of reliable models of HFpEF in mice by using proper diagnosis tools is necessary to translate basic research results to the clinics. Determining the presence of several HFpEF indicators and a higher number of abnormal parameters will lead to more reliable evidence of HFpEF.

Indexed as

Heart FailureVentricular Function, LeftAnimalsBiomarkersBlood GlucoseMiceOxygenStroke VolumeBiomarkersBlood GlucoseOxygenEchocardiographyHeart failureMouse modelsPhenotypePreserved ejection fractionResearch

Identifiers

PMID36229816
PMCPMC9563110
OpenAlexW4306153819

What OpenQuestion holds

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LicenceCC BY
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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.