Clinical refinement of the automatic lung parameter estimator (ALPE)

Thomsen, Lars Pilegaard; Karbing, Dan Stieper; Smith, Bram Wallace; Murley, David; Weinreich, Ulla Møller; Kjærgaard, Søren; Toft, Egon; Thorgaard, Per; Andreassen, Steen; Rees, Stephen Edward

doi:10.1007/s10877-013-9442-9

Cited by 17 publications

(11 citation statements)

References 19 publications

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“…Figure 1 summarizes the study protocol, indicating which measurements were performed in the intensive care unit and CT lab. Shunt and V/Q mismatch were measured using the automatic lung parameter estimator (ALPE) method [20,21] (ALPE integrated, Mermaid Care A/S, Nørresundby, Denmark). Lung aeration was assessed by CT scan analysis.…”

Section: Study Protocolmentioning

confidence: 99%

Changes in shunt, ventilation/perfusion mismatch, and lung aeration with PEEP in patients with ARDS: a prospective single-arm interventional study

et al. 2020

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Background: Several studies have found only a weak to moderate correlation between oxygenation and lung aeration in response to changes in PEEP. This study aimed to investigate the association between changes in shunt, low and high ventilation/perfusion (V/Q) mismatch, and computed tomography-measured lung aeration following an increase in PEEP in patients with ARDS. Methods: In this preliminary study, 12 ARDS patients were subjected to recruitment maneuvers followed by setting PEEP at 5 and then either 15 or 20 cmH 2 O. Lung aeration was measured by computed tomography. Values of pulmonary shunt and low and high V/Q mismatch were calculated by a model-based method from measurements of oxygenation, ventilation, and metabolism taken at different inspired oxygen levels and an arterial blood gas sample.Results: Increasing PEEP resulted in reduced values of pulmonary shunt and the percentage of non-aerated tissue, and an increased percentage of normally aerated tissue (p < 0.05). Changes in shunt and normally aerated tissue were significantly correlated (r = − 0.665, p = 0.018). Three distinct responses to increase in PEEP were observed in values of shunt and V/Q mismatch: a beneficial response in seven patients, where shunt decreased without increasing high V/Q; a detrimental response in four patients where both shunt and high V/Q increased; and a detrimental response in a patient with reduced shunt but increased high V/Q mismatch. Non-aerated tissue decreased with increased PEEP in all patients, and hyperinflated tissue increased only in patients with a detrimental response in shunt and V/Q mismatch. Conclusions:The results show that improved lung aeration following an increase in PEEP is not always consistent with reduced shunt and V/Q mismatch. Poorly matched redistribution of ventilation and perfusion, between dependent and non-dependent regions of the lung, may explain why patients showed detrimental changes in shunt and V/Q mismatch on increase in PEEP, despite improved aeration. Trial registration: ClinicalTrails.gov, NCT04067154. Retrospectively registered on August 26, 2019.

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Section: Study Protocolmentioning

confidence: 99%

Changes in shunt, ventilation/perfusion mismatch, and lung aeration with PEEP in patients with ARDS: a prospective single-arm interventional study

et al. 2020

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“…In addition, recent attempts have been made to speed this process. Rule-based suggestions of FIO 2 control included in Beacon have shown that the process can be completed in 7.2 ± 2.4 min [51], and further reduction in time has been shown possible by fitting gas exchange parameters to data describing the dynamic response to FIO 2 change [50].…”

Section: Discussionmentioning

confidence: 99%

Determining the appropriate model complexity for patient-specific advice on mechanical ventilation

Rees

Karbing

2017

Biomedical Engineering / Biomedizinische Technik

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Mathematical physiological models can be applied in medical decision support systems. To do so requires consideration of the necessary model complexity. Models that simulate changes in the individual patient are required, meaning that models should have a complexity where parameters can be uniquely identified at the bedside from clinical data and where the models adequately represent the individual patient's (patho)physiology. This paper describes the models included in a system for providing decision support for mechanical ventilation. Models of pulmonary gas exchange, respiratory mechanics, acid-base, and respiratory control are described. The parameters of these models are presented along with the necessary clinical data required for their estimation and the parameter estimation process. In doing so, the paper highlights the need for simple, minimal models for application at the bedside, directed toward well-defined clinical problems.

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“…(ALPE) [4]. This same group also recently assessed new methods to reduce the time required to measure V A /Q distributions by this approach [5].…”

Section: Gas Exchange Methods For Ventilation/perfusion Distributionsmentioning

confidence: 99%

Ventilation/perfusion distributions revisited

Baumgardner

Hedenstierna

2016

Current Opinion in Anaesthesiology

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Clinical refinement of the automatic lung parameter estimator (ALPE)

Cited by 17 publications

References 19 publications

Changes in shunt, ventilation/perfusion mismatch, and lung aeration with PEEP in patients with ARDS: a prospective single-arm interventional study

Changes in shunt, ventilation/perfusion mismatch, and lung aeration with PEEP in patients with ARDS: a prospective single-arm interventional study

Determining the appropriate model complexity for patient-specific advice on mechanical ventilation

Ventilation/perfusion distributions revisited

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