ArticleBioengineering (Basel, Switzerland)2024
In Vivo Evaluation of Two Hemorrhagic Shock Resuscitation Controllers with Non-Invasive, Intermittent Sensors.
Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Comparison of Controller Logics for Automating Vasopressor Administration Using a Hardware-in-Loop Test Platform.Bioengineering (Basel, Switzerland) · 2026Article
- Development of a vasopressor control module for testing hemorrhagic shock resuscitation controllers.Biomedical engineering online · 2026Article
- Machine Learning Prediction of Mean Arterial Pressure from the Photoplethysmography Waveform During Hemorrhagic Shock and Fluid Resuscitation.Sensors (Basel, Switzerland) · 2025Article
- Enhancing Trauma Care: Machine Learning-Based Photoplethysmography Analysis for Estimating Blood Volume During Hemorrhage and Resuscitation.Bioengineering (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Hemorrhage is a leading cause of preventable death in military and civilian trauma medicine. Fluid resuscitation is the primary treatment option, which can be difficult to manage when multiple patients are involved. Traditional vital signs needed to drive resuscitation therapy being unavailable without invasive catheter placement is a challenge. To overcome these obstacles, we propose using closed-loop fluid resuscitation controllers managed by non-invasive, intermittent signal sensor inputs to simplify their use in far-forward environments. Using non-invasive, intermittent sensor controllers will allow quicker medical intervention due to negating the need for an arterial catheter to be placed for pressure-guided fluid resuscitation. Two controller designs were evaluated in a swine hemorrhagic shock injury model, with each controller only receiving non-invasive blood pressure (NIBP) measurements simulated from invasive input signals every 60 s. We found that both physiological closed-loop controllers were able to effectively resuscitate subjects out of life-threatening hemorrhagic shock using only intermittent data inputs with a resuscitation effectiveness of at least 95% for each respective controller. We also compared this intermittent signal input to a NIBP cuff and to a deep learning model that predicts blood pressure from a photoplethysmography waveform. Each approach showed evidence of tracking blood pressure, but more effort is needed to refine these non-invasive input approaches. We conclude that resuscitation controllers hold promise to one day be capable of non-invasive sensor input while retaining their effectiveness, expanding their utility for managing patients during mass casualty or battlefield conditions.
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Registered trials
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.