Evidence map›Paper›PMID 42743428›Full record

ReviewThe journal of extra-corporeal technology2026

Challenges and opportunities in ECMO monitoring: A mixed-methods appraisal.

Wei Yin, Alisa Permessur, George Pittas, Shiffoni Sukhlal, Nicholas Chow, Steven Pinheiro, Andrew Cobos, Giancarlo Sabetta, Jan Cahill, Saleem Zaidi and 2 more

Abstract readReview
In one paragraph

Review in The journal of extra-corporeal technology, 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

12 authors.

Wei YinDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-2853-0375
Alisa PermessurDepartment of Physiology and Biophysics, Stony Brook University, Stony Brook, NY 11794, USA.
George PittasDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Shiffoni SukhlalDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Nicholas ChowDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Steven PinheiroDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Andrew CobosDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Giancarlo SabettaRenaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.
Jan CahillCardiovascular Perfusion Division, Department of Cardiac Surgery, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.
Saleem ZaidiDepartment of Anesthesiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.
Jon LongtinDepartment of Mechanical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Jonathon SchwartzDepartment of Anesthesiology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.

Funding

American Heart Association Innovative Project Award 24IPA1275689Stony Brook University VDR Fusion Grant JS 2024
6 · The paper itself

Abstract

Extracorporeal membrane oxygenation (ECMO) provides heart/lung support for critically ill patients. While advances in research have improved the overall design and performance of ECMO circuits, complications such as hemolysis and thrombosis persist, and the dysfunction of the ECMO machine itself can pose significant risk to patients. Many parameters need to be closely monitored during an ECMO run, and it is often labor and resource-intensive. Currently, there are few commercially available automated ECMO circuit monitoring systems that can provide continuous, holistic monitoring for ECMO circuit health and provide real-time clinical recommendations. This mixed-methods review (through literature review and customer discovery interviews) discussed key parameters relevant to ECMO circuits and monitoring, including bleeding, thrombosis, hemolysis, flow and pressure conditions, and gas exchange. Their importance in ECMO monitoring, current practices, and available technologies were highlighted. In addition, a customer discovery study, supported by the New York regional I-Corps program, was conducted to identify the "pain points" in ECMO circuit monitoring through interviews with healthcare professionals and other stakeholders experienced in ECMO care/use. Findings from both the literature review and the customer discovery study indicated that ECMO monitoring and management require significant resources, due to the variability and complexity of patients' conditions, challenges in collecting patient and ECMO circuit data, and the need for a comprehensive understanding of the entire patient-ECMO ecosystem. Improvements in understanding complex ECMO data, incorporating new sensors into the monitoring system, and establishing comprehensive ECMO data pipelines represent key steps towards developing "smart" ECMO monitoring that can serve as a clinical decision support system.

Indexed as

Extracorporeal Membrane OxygenationHumansMonitoring, PhysiologicBioengineeringBlood coagulationDatabaseDeviceECMO

Identifiers

PMID42743428
PMCPMC13577623

What OpenQuestion holds

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Read underepoch 390

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.