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1.
Intensive Care Med Exp ; 11(1): 61, 2023 Sep 08.
Article in English | MEDLINE | ID: mdl-37682496

ABSTRACT

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.

2.
Eur J Anaesthesiol ; 40(8): 578-586, 2023 08 01.
Article in English | MEDLINE | ID: mdl-37265333

ABSTRACT

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.


Subject(s)
Echocardiography , Hypovolemia , Humans , Male , Hypovolemia/diagnostic imaging , Prospective Studies , Ventricular Function, Left/physiology , Stroke Volume/physiology , Ventricular Function, Right/physiology
3.
Sensors (Basel) ; 22(14)2022 Jul 06.
Article in English | MEDLINE | ID: mdl-35890746

ABSTRACT

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.


Subject(s)
Hypovolemia , Lower Body Negative Pressure , Algorithms , Humans , Hypovolemia/diagnosis , Lower Body Negative Pressure/adverse effects , Machine Learning , Male , Stroke Volume/physiology
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