Evidence mapPaperPMID 42420652Full record

ReviewBasic research in cardiology2026

Cardiac unloading models for myocardial reverse remodeling.

Xinjie Xu, Yukun Luo, Tao Lei, Zichen Wu, Jiaying Cao, Jiansong Huang, Henan Zhang, Xiaoyan Li, Xiaying Deng, Dongjing Zhou and 3 more

Abstract readReview
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In one paragraph

Review in Basic research in cardiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Xinjie Xu *State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yukun Luo *The Second School of Clinical Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Tao Lei *State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Zichen Wu *The Second School of Clinical Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Jiaying CaoThe First School of Clinical Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Jiansong HuangThe First School of Clinical Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Henan ZhangThe First School of Clinical Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xiaoyan LiThe First School of Clinical Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xiaying DengThe First School of Clinical Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Dongjing ZhouThe Second School of Clinical Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Yibo ZhangState Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Antoni Bayes-GenisHeart Institute, Hospital Universitari Germans Trias i Pujol, CIBERCV, Badalona, Spain. abayes.germanstrias@gencat.cat.
Liang ChenState Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. chenliang@fuwaihospital.org.

Funding

Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2023-I2M-2-003National High Level Hospital Clinical Research Funding National High Level Hospital Clinical Research FundingNational Natural Science Foundation of China 823B2006National Natural Science Foundation of China 82470373National Natural Science Foundation of China 82522007Noncommunicable Chronic Diseases-National Science and Technology Major Project 2025ZD0547800
6 · The paper itself

Abstract

Myocardial reverse remodeling (RR) represents the structural, functional, cellular, and molecular recovery of the failing heart, leading to long-term prognostic improvements. This process can be mediated by various clinical modalities, including pharmacological treatment and interventional/surgical procedures. Among these approaches, left ventricular assist devices (LVADs) exhibit the most potent capacity for mechanical unloading and inducing RR, which has profoundly transformed the treatment paradigm and prognosis of end-stage heart failure. Furthermore, the implantation and explantation of LVAD devices facilitate the collection of paired patient samples before and after treatment, providing a unique real-world model for investigating this phenomenon. However, the scarcity of human myocardial samples is insufficient to meet the demands of elucidating the mechanisms of reverse cardiac remodeling and identifying novel therapeutic targets. Findings derived from human specimens require validation through experimental unloading models, which inherently offer novel perspectives on cardiac pathophysiology. Thus, reproducible models of myocardial unloading have become valuable complementary resources. This review systematically summarizes progress in understanding the relationship between mechanical load and myocardial phenotypes within various unloading models. We further discuss how these reproducible unloading models provide a solid foundation for elucidating the mechanisms of RR and ultimately developing novel therapies to improve patient outcomes.

Indexed as

DeTACHeterotopic transplantationLeft ventricular assist deviceModelReverse remodelingUnloading

Identifiers

PMID42420652

What Socratic holds

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Registered trials

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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 Socratic graph.