Evaluation of Pulse Arrival Times during Lower Body Negative Pressure Test for the Non-Invasive Detection of Hypovolemia

Tigges, Timo; Feldheiser, Aarne; Pielmuş, Alexandru; Klum, Michael; Wiegank, Ludwig; Orglmeister, Reinhold

doi:10.1109/embc.2019.8856652

Cited by 4 publications

(5 citation statements)

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“…The project included several research questions to minimize the risks of volunteers and reduce research funds. The first publication of this project covered methodological aspects [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…It was sealed with commercially available silicone gel. The simulated progressive central hypovolaemia of the LBNP chamber was haemodynamically and humorally extensively characterized, and the protocol was previously published by our group [ 16 ]. Negative pressure was applied by fitting the hose of a commercially available vacuum cleaner (VS06B1110, Siemens AG, Berlin and Munich, Germany) into a hole in the chamber wall.…”

Section: Methodsmentioning

confidence: 99%

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Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia

Stetzuhn

Tigges

Pielmuş

et al. 2022

Sensors

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Compensated shock and hypovolaemia are frequent conditions that remain clinically undetected and can quickly cause deterioration of perioperative and critically ill patients. Automated, accurate and non-invasive detection methods are needed to avoid such critical situations. In this experimental study, we aimed to create a prediction model for stroke volume index (SVI) decrease based on electrical cardiometry (EC) measurements. Transthoracic echo served as reference for SVI assessment (SVI-TTE). In 30 healthy male volunteers, central hypovolaemia was simulated using a lower body negative pressure (LBNP) chamber. A machine-learning algorithm based on variables of EC was designed. During LBNP, SVI-TTE declined consecutively, whereas the vital signs (arterial pressures and heart rate) remained within normal ranges. Compared to heart rate (AUC: 0.83 (95% CI: 0.73–0.87)) and systolic arterial pressure (AUC: 0.82 (95% CI: 0.74–0.85)), a model integrating EC variables (AUC: 0.91 (0.83–0.94)) showed a superior ability to predict a decrease in SVI-TTE ≥ 20% (p = 0.013 compared to heart rate, and p = 0.002 compared to systolic blood pressure). Simulated central hypovolaemia was related to a substantial decline in SVI-TTE but only minor changes in vital signs. A model of EC variables based on machine-learning algorithms showed high predictive power to detect a relevant decrease in SVI and may provide an automated, non-invasive method to indicate hypovolaemia and compensated shock.

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“…The project included several research questions to minimize the risks of volunteers and reduce research funds. The first publication of this project covered methodological aspects [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia

Stetzuhn

Tigges

Pielmuş

et al. 2022

Sensors

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“…Changes in impedance in relation to the cardiac cycle are recorded over time in a continuous fashion and used to calculate various haemodynamic parameters [ 12 ]. A description of the relevant parameters can be found in the supplement (Additional file 1 : Text S1 [ 13 – 22 ] and Additional file 2 : Table S1 [ 23 , 24 ]).…”

Section: Methodsmentioning

confidence: 99%

Perioperative advanced haemodynamic monitoring of patients undergoing multivisceral debulking surgery: an observational pilot study

Middel,

Stetzuhn,

Sander

et al. 2023

ICMx

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Background Patients undergoing high-risk surgery show haemodynamic instability and an increased risk of morbidity. However, most of the available data concentrate on the intraoperative period. This study aims to characterise patients with advanced haemodynamic monitoring throughout the whole perioperative period using electrical cardiometry. Methods In a prospective, observational, monocentric pilot study, electrical cardiometry measurements were obtained using an Osypka ICON™ monitor before surgery, during surgery, and repeatedly throughout the hospital stay for 30 patients with primary ovarian cancer undergoing multivisceral cytoreductive surgery. Severe postoperative complications according to the Clavien–Dindo classification were used as a grouping criterion. Results The relative change from the baseline to the first intraoperative timepoint showed a reduced heart rate (HR, median – 19 [25-quartile − 26%; 75-quartile − 10%]%, p < 0.0001), stroke volume index (SVI, − 9.5 [− 15.3; 3.2]%, p = 0.0038), cardiac index (CI, − 24.5 [− 32; − 13]%, p < 0.0001) and index of contractility (− 17.5 [− 35.3; − 0.8]%, p < 0.0001). Throughout the perioperative course, patients had intraoperatively a reduced HR and CI (both p < 0.0001) and postoperatively an increased HR (p < 0.0001) and CI (p = 0.016), whereas SVI was unchanged. Thoracic fluid volume increased continuously versus preoperative values and did not normalise up to the day of discharge. Patients having postoperative complications showed a lower index of contractility (p = 0.0435) and a higher systolic time ratio (p = 0.0008) over the perioperative course in comparison to patients without complications, whereas the CI (p = 0.3337) was comparable between groups. One patient had to be excluded from data analysis for not receiving the planned surgery. Conclusions Substantial decreases in HR, SVI, CI, and index of contractility occurred from the day before surgery to the first intraoperative timepoint. HR and CI were altered throughout the perioperative course. Patients with postoperative complications differed from patients without complications in the markers of cardiac function, a lower index of contractility and a lower SVI. The analyses of trends over the whole perioperative time course by using non-invasive technologies like EC seem to be useful to identify patients with altered haemodynamic parameters and therefore at an increased risk for postoperative complications after major surgery.

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“…As published previously, the volunteers underwent a measurement protocol within a LBNP chamber (Supplement document 1, http://links.lww.com/EJA/A846). 14,[16][17][18] After a ten-minute period of stabilisation and baseline measurements of vital signs and the initial TTE, three stages of increasing negative pressure were applied to the lower body of the participants (explanation of pressure stages in Supplement document 1, http://links.lww.com/ EJA/A846) to simulate an increasing degree of central hypovolaemia (À15 mmHg ¼ mild, À30 mmHg ¼ mildto-moderate and À45 mmHg ¼ moderate). In this context, it must be emphasised that these LBNP stages cannot directly be converted to a certain amount of blood loss.…”

Section: Study Design and Settingmentioning

confidence: 99%

A comprehensive echocardiographic analysis during simulated hypovolaemia

Feldheiser

Juhl-Olsen

Nordine

et al. 2023

European Journal of Anaesthesiology

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BACKGROUND Peri-operative and critically ill patients often experience mild to moderate hypovolaemic shock with preserved mean arterial pressure (MAP), heart rate (HR) and decreased stroke volume index (SVI). OBJECTIVES The aim of this study was to evaluate echocardiographic parameters during simulated mild to moderate central hypovolaemia. DESIGN This was a prospective preclinical study. SETTING Laboratory trial performed in Charité-Universitätsmedizin Berlin, Germany. PATIENTS AND METHODS Thirty healthy male volunteers underwent graded central hypovolaemia using a lower body negative pressure (LBNP) chamber with a stepwise decrease to simulate a mild (−15 mmHg), mild-to-moderate (−30 mmHg), and moderate state of hypovolaemic shock (−45 mmHg). During every stage, a transthoracic echocardiography examination (TTE) was performed by a certified examiner. MAIN OUTCOME MEASURES Systolic and diastolic myocardial performance markers, as well as cardiac volumes were recorded during simulated hypovolaemia and compared to baseline values. RESULTS During simulated hypovolaemia via LBNP, SVI decreased progressively at all stages, whereas MAP and HR did not consistently change. Left ventricular (LV) ejection fraction decreased at −30 and −45 mmHg. Simultaneously with SVI decline, LV global longitudinal strain (LV GLS), tricuspid annular plain systolic excursion (TAPSE), and right ventricular RV S’ and left-atrial end-systolic volume (LA ESV) decreased compared to baseline at all stages. CONCLUSIONS In this study, simulated central hypovolaemia using LBNP did not induce consistent changes in MAP and HR. SVI decreased and was associated with deteriorated right- and left-ventricular function, observed with echocardiography. The decreased filling status was characterised by decreased LA ESV. CLINICAL TRIAL NUMBER ClinicalTrials.gov Identifier: NCT03481855.

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Evaluation of Pulse Arrival Times during Lower Body Negative Pressure Test for the Non-Invasive Detection of Hypovolemia

Cited by 4 publications

References 14 publications

Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia

Detection of a Stroke Volume Decrease by Machine-Learning Algorithms Based on Thoracic Bioimpedance in Experimental Hypovolaemia

Perioperative advanced haemodynamic monitoring of patients undergoing multivisceral debulking surgery: an observational pilot study

A comprehensive echocardiographic analysis during simulated hypovolaemia

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