Preload & Frank-Starling curves, from textbook to bedside: clinically applicable non-additionally invasive model-based estimation in pigs

Smith, R; Chase, JG; Pretty, CG; Davidson, S; Shaw, GM; Desaive, T

Journal article

Preload & Frank-Starling curves, from textbook to bedside: clinically applicable non-additionally invasive model-based estimation in pigs

Abstract:: Background Determining physiological mechanisms leading to circulatory failure can be challenging, contributing to the difficulties in delivering effective hemodynamic management in critical care. Continuous, non-additionally invasive monitoring of preload changes, and assessment of contractility from Frank-Starling curves could potentially make it much easier to diagnose and manage circulatory failure. Method This study combines non-additionally invasive model-based methods to estimate left ventricle end-diastolic volume (LEDV) and stroke volume (SV) during hemodynamic interventions in a pig trial (N = 6). Agreement of model-based LEDV and measured admittance catheter LEDV is assessed. Model-based LEDV and SV are used to identify response to hemodynamic interventions and create Frank-Starling curves, from which Frank-Starling contractility (FSC) is identified as the gradient. Results Model-based LEDV had good agreement with measured admittance catheter LEDV, with Bland-Altman median bias [limits of agreement (2.5th, 97.5th percentile)] of 2.2 ml [-13.8, 22.5]. Model LEDV and SV were used to identify non-responsive interventions with a good area under the receiver-operating characteristic (ROC) curve of 0.83. FSC was identified using model LEDV and SV with Bland-Altman median bias [limits of agreement (2.5th, 97.5th percentile)] of 0.07 [-0.68, 0.56], with FSC from admittance catheter LEDV and aortic flow probe SV used as a reference method. Conclusions This study provides proof-of-concept preload changes and Frank-Starling curves could be non-additionally invasively estimated for critically ill patients, which could potentially enable much clearer insight into cardiovascular function than is currently possible at the patient bedside.

Publication status:: Published

Peer review status:: Peer reviewed

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APA Style

Smith, R., Chase, J. G., Pretty, C. G., Davidson, S., Shaw, G. M., & Desaive, T. (2021). Preload & Frank-Starling curves, from textbook to bedside: clinically applicable non-additionally invasive model-based estimation in pigs. Computers in Biology and Medicine, 135.

MLA Style

Smith, R., et al. “Preload & Frank-Starling Curves, from Textbook to Bedside: Clinically Applicable Non-Additionally Invasive Model-Based Estimation in Pigs.” Computers in Biology and Medicine, vol. 135, Elsevier, 2021.

Chicago Style

Smith, R, JG Chase, CG Pretty, S Davidson, GM Shaw, and T Desaive. 2021. “Preload & Frank-Starling Curves, from Textbook to Bedside: Clinically Applicable Non-Additionally Invasive Model-Based Estimation in Pigs.” Computers in Biology and Medicine 135.
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