Evidence map›Paper›PMID 42050606›Full record

ArticleCritical care (London, England)2026

Machine learning models for predicting limb ischemia during VA-ECMO: an analysis of the Chinese extracorporeal life support registry.

Liangshan Wang, Kexin Wang, Chenglong Li, Yan Wang, Haixiu Xie, Huiruo Liu, Xing Hao, Hong Wang, Zhongtao Du, Xiaotong Hou

Abstract readLetter
PubMed Full text at PMC Publisher
In one paragraph

Article in Critical care (London, England), 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

10 authors.

Liangshan Wang *Center for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Kexin Wang *Center for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Chenglong Li *Center for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Yan WangCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Haixiu XieCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Huiruo LiuCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Xing HaoCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Hong WangCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Zhongtao DuCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China. zhongtaodu@126.com.
Xiaotong HouCenter for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China. xt.hou@ccmu.edu.cn.

Funding

Beijing Anzhen Hospital High Level Research Funding 2025AZB6017National Natural Science Foundation of China 82200433Young Elite Scientists Sponsorship Program by CAST 2022QNRC001
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID42050606
PMCPMC13126924

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.