Evidence map›Paper›PMID 41710021›Full record

ArticleFrontiers in physiology2025

Computational physiological modeling for lung-specific ventilation and perfusion management in

Daan Imholz, Sue A Braithwaite, Paul Blankman, Eline Oppersma, Frans H C de Jongh, Linda M de Heer, Bart Luijk, Wolfgang F F A Buhre, Dirk W Donker, Lex M van Loon

Abstract read
In one paragraph

Article in Frontiers in physiology, 2025. 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.

Daan ImholzCardiovascular and Respiratory Physiology, Technical Medical Centre, University of Twente, Enschede, Netherlands.
Sue A BraithwaiteDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.
Paul BlankmanDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.
Eline OppersmaCardiovascular and Respiratory Physiology, Technical Medical Centre, University of Twente, Enschede, Netherlands.
Frans H C de JonghDepartment of Respiratory Medicine, Medisch Spectrum Twente, Enschede, Netherlands.
Linda M de HeerDepartment of Cardiothoracic Surgery, University Medical Center Utrecht, Utrecht, Netherlands.
Bart LuijkDepartment of Pulmonology, University Medical Center Utrecht, Utrecht, Netherlands.
Wolfgang F F A BuhreDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.
Dirk W DonkerCardiovascular and Respiratory Physiology, Technical Medical Centre, University of Twente, Enschede, Netherlands.
Lex M van LoonCardiovascular and Respiratory Physiology, Technical Medical Centre, University of Twente, Enschede, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Methods: We developed and validated a computational physiological model (CPM) of lungs on EVLP. The CPM integrates established principles of lung mechanics, gas exchange, and perfusion with clinical input data. It provides mechanistic insight into Results: Simulation results closely aligned with clinical measurements of left atrial partial oxygen pressure (root mean squared error (RMSE) of 6.4 mmHg). Sensitivity analysis and uncertainty quantification further elucidated key determinants of oxygen and carbon dioxide dynamics, including the inspired oxygen fraction, intrapulmonary shunt, dead space, and perfusate flow. Discussion: This CPM enhances understanding of

Indexed as

alveolar dead spacecomputational physiological modeldigital twinex vivo lung perfusionintrapulmonary shunt

Identifiers

PMID41710021
PMCPMC12909158

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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 OpenQuestion graph.