Evidence map›Paper›PMID 40061273›Full record

ArticleWorld journal of cardiology2025

Comprehensive understanding of a rare disease: Cardiac metastatic tumor, a double-center 10-year case review.

Ling-Yun Luo, Tian-Shu Yang, Zhen He, Li Lin, Xue-Lian Luo

Abstract read
In one paragraph

Article in World journal of cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Ling-Yun LuoDepartment of Cardiology, Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430034, Hubei Province, China.
Tian-Shu YangDepartment of Cardiology, Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430034, Hubei Province, China.
Zhen HeDepartment of Cardiac Surgical Intensive Care Unit, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510000, Guangdong Province, China.
Li LinDepartment of Internal Medicine, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China.
Xue-Lian LuoDepartment of Oncology, Chongqing Medical University Affiliated Third Hospital, Chongqing 400020, China. 806850653@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiac metastatic tumors (CMTs) are rare yet pose significant medical concerns. Clinical studies on CMT are limited, particularly those involving multicenter data analysis.

aimTo systematically analyze the etiology, sources, classification, treatment, and prognosis of CMT.

methodsA total of 226 CMT patients from two centers (2013 to 2023) were reviewed, and 153 tumor patients from China Health and Retirement Longitudinal Study were used as controls. The survival rates of 96 CMT patients were tracked through medical records and telephone follow-ups. Logistic regression and survival analyses were conducted to characterize CMT.

resultsCMTs were predominantly male (67.26%

conclusionClinicians should consider CMT in the male lung or liver cancer patients with cardiac symptoms. Abnormal coagulation, impaired heart function, tumor location, and age are key prognostic factors for CMT. Surgical intervention is the preferred treatment option, as it significantly prolongs median survival.

Indexed as

Cardiac metastatic tumorCoagulationPrimary tumorPrognosisSubtype

Identifiers

PMID40061273
PMCPMC11886389

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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 OpenQuestion graph.