Evidence map›Paper›PMID 41514334›Full record

ArticleBiomedical engineering online2026

Impact of EIT-based regional ventilation distribution on outcomes in different types of critical illness: a retrospective cohort study.

Qing Liu, Jia-Wang Cao, Zhao-Jin Wang, Yan-Mei Gu

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Article in Biomedical engineering online, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Qing Liu *Department of Critical Care Medicine, Beijing You'an Hospital, affiliated to Capital Medical University, No.8 Wai Xi Tou Tiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Jia-Wang Cao *Department of Critical Care Medicine, Beijing You'an Hospital, affiliated to Capital Medical University, No.8 Wai Xi Tou Tiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Zhao-Jin WangDepartment of Critical Care Medicine, Beijing You'an Hospital, affiliated to Capital Medical University, No.8 Wai Xi Tou Tiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Yan-Mei GuDepartment of Critical Care Medicine, Beijing You'an Hospital, affiliated to Capital Medical University, No.8 Wai Xi Tou Tiao, Youanmen Street, Fengtai District, Beijing, 100069, China. yanmeigu@yeah.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectrical impedance tomography (EIT) is a non-invasive bedside tool for real-time regional ventilation data, but its correlation with outcomes in different critical illnesses remains unclear.

methodsThis retrospective study included 108 ICU patients (liver disease, n = 48; respiratory failure, n = 36; gastrointestinal bleeding, n = 24) who underwent EIT monitoring between December 2023 and March 2025. EIT measured tidal volume percentage in four regions of interest (ROIs), with 28-day mortality as the primary outcome. Multivariate logistic regression adjusted for key confounders was used for analysis.

resultsVentilation distribution patterns differed significantly among the three disease groups. The liver disease group showed predominant ventilation in ROI 1-2 (anterior regions), with a mean dorsal-to-ventral ratio (DVR) of 0.41 ± 0.18. The respiratory failure group exhibited more homogeneous distribution with a DVR of 0.76 ± 0.34. Patients with higher ventilation heterogeneity (coefficient of variation > 40%) had significantly higher 28-day mortality (29.5% vs 16.7%, p = 0.022), longer duration of mechanical ventilation (8.7 vs 5.4 days, p = 0.012), and fewer ventilator-free days (14.3 vs 19.6 days, p = 0.009). Multivariate analysis identified DVR < 0.4 (OR 2.84, 95% CI 1.46-5.53, p = 0.002) and ventilation heterogeneity (OR 2.31, 95% CI 1.18-4.52, p = 0.014) as independent predictors of 28-day mortality after adjusting for disease severity, age, and mechanical ventilation parameters.

conclusionsRegional ventilation patterns vary by underlying disease. Greater heterogeneity and lower DVR independently correlate with worse outcomes. EIT-derived parameters may be prognostic indicators and therapeutic targets for optimizing ventilation in critical illness.

Indexed as

Critical IllnessElectric ImpedanceRespiration, ArtificialTomographyAgedFemaleHumansMaleMiddle AgedRetrospective StudiesCritical careElectrical impedance tomographyMechanical ventilationPrognosisVentilation distribution

Identifiers

PMID41514334
PMCPMC12882238

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