Tidal Volume Challenge to Assess Volume Responsiveness

The purpose of this study is to investigate the ability of changes in PPV and SVV after Tidal Volume Challenge to predict fluid responsiveness in patients undergoing general anesthesia with protective mechanical ventilation.

Intraoperative algorithms and protocols regarding fluid therapy are key factors to prevent perioperative hypovolaemia or hypervolaemia, which are both known to increase morbidity and length of hospital stay. Response to fluid therapy (increase in stroke volume, SV) after a bolus infusion should be based on predictors of fluid responsiveness. It has been shown previously that static indices, such as central venous pressure or pulmonary wedge pressure are unsuitable for this purpose. Conversely dynamic indices such as stroke volume variation (SVV) or pulse pressure variation (PPV), can reliably predict fluid responsiveness during mechanical ventilation with a tidal volume of at least 8 ml/kg. In recent years, the use of lung-protective ventilation strategy with tidal volumes of less than 8 ml/kg (e.g. Vt = 6ml/kg of ideal body weight) has been associated with better outcome of patients9 and has been recommended as the standard intraoperative mechanical ventilation strategy.10 Reduced tidal volumes, however, limit the reliability of dynamic PPV and SVV indicators. In order to overcome this Vt-related limitation to PPV and SVV, functional hemodynamic tests should be applied,11 aimed at increasing right ventricle preload. For example, discontinuation of mechanical ventilation as in the end-expiratory occlusion test (EEOT) has been tested, in intensive care patients, as well as in a surgical polulation with conflicting results.15,16 Recently Myantra and coll tested the tidal volume challenge (VtC) in 20 severely ill patients with acute circulatory failure. They demonstrated that the response to fluid administration can be reliably predicted through changes in PPV and SVV after VtC, defined as an increase in Vt to 8 ml/kg for 1 minute. Tidal volume challenge has also been successfully tested in surgical patients. In neurosurgical patients in both supine and prone position. Messina and coll demonstrated that VtC can predict the response to fluid administration through a change in PPV and SVV with high sensitivity and specificity. In robotic laparoscopic procedures in the Trendelenburg position, Jun and coll20 showed PPV changes after a VtC were more sensitive and specific in predicting fluid responsiveness than SVV changes. The purpose of this study is to investigate the ability of changes in PPV and SVV after VtC to predict fluid responsiveness in patients undergoing general anesthesia with protective mechanical ventilation. Patient population / study design In this prospective study, patients who meet the inclusion criteria will be consecutively enrolled after signing a written informed consent. The protocol is in accordance with the principles outlined in the Declaration of Helsinki; the study is approved by the local institutional ethics committee (557/14-10-2021) and will also be registered in an international database (clinicaltrials.gov) prior to initiation. Anesthetic management Patients will receive general anesthesia according to standard practice. Anesthesia induction will be achieved with propofol (1.5 - 2.5 mg/kg), muscle relaxants (rocuronium 0.6 mg/kg or cisatracurium 2 mg/kg) and opioids (fentanyl, or remifentanil), while maintenance of anesthesia will include fentanyl boluses or remifentanil continuous infusion (0.02-0.2 μg/kg/min) and sevoflurane (1.5-2.5 vol%) at the discretion of the attending physician and according to the patients' need. Patients will be ventilated mechanically with protective lung ventilation (Vt = 6 ml/kg of predicted body weight according to x + 0.91 (height in cm - 152.4), where x = 50 for men and x = 45.5 for women),21 and a positive end expiratory pressure (PEEP) of 5 cm H20. Respiratory rate and inspiration:expiration (I:E) ratio will be adjusted to maintain end expiratory carbon dioxide (EtCO2) levels between 35 and 40 mmHg. Hemodynamic monitoring Radial artery cannulation will be performed in all patients. The catheter will be connected through the Acumen IQ transducer (Edwards Lifesciences, Irvine, CA) to the Hemosphere monitor (Edwards Lifesciences, Irvine, CA) and to the standard anesthesia machine monitor (GE Healthcare, USA). The standard anesthesia monitor measures electrocardiogram, pulse oximetry, temperature, arterial pressure while the Hemosphere monitor registers PPV, SVV, SV index, cardiac output (CO) and index (CI), systemic vascular resistance (SVR), dynamic arterial elastance (Eadyn) and difference of pressure over time (dP/dt). PPV is automatically calculated from the Hemosphere monitor according to the formula PPV (%) = \[(PPmax - Ppmin)/PPmean \] x 100 while SVV is calculated according to the formula SVV(%) = \[(SVmax - Svmin) /SVmean \] x 100.22 Study protocol The protocol will begin one hour after anesthesia induction and the stabilization of hemodynamic parameters (changes in MAP \<10% for 5'). Mean arterial pressure (MAP), stroke volume index (SVI), peak inspiratory pressure (PIP), dynamic compliance (Cdyn), PPV, SVV during mechanical ventilation with Vt = 6 ml/kg PBW will be registered (T1 baseline). Tidal volume will be then increased to Vt = 8 ml/kg PBW without changing the other respiratory parameters for 3 minutes. At the end of the tidal volume challenge MAP, SVI, PIP, Cdyn, PPVT2, SVVT2 (Τ2 VtC) will be registered again. Changes in PPV and SVV values are going to be calculated as follows: ΔPPVT2-T1 = PPVT2 - PPVT1 and ΔSVVT2-T1 = SVVT2 - SVVT1 The percentage changes in PPV and SVV \[ΔPPV T2-T1 (%) and ΔSVV T2-T1 (%), respectively\] will also be calculated. When Vt = 6 ml/kg PBW and the hemodynamic parameters are stabilized, at least 5 minutes after the VtC, a volume challenge (volume expansion, VE) will be administered with gelofusin 6 ml/kg PBW. Parameters such as MAP, SVI, PIP, Cdyn, PPV, SVV before (Τ3) and 5 minutes after the volume challenge (T4) will be registered.23,24 Changes registered in SVI before and after the VE will be used as a response indicator to fluids. Patients will be divided in responders to the VE if SVI ≥ 10% and non responders if SVI \< 10%.4,25 Changes in in PPV and SVV values between T3 and Τ4 will also be calculated. The changes in SVV and PPV values after VE (ΔPPVVE and ΔSVVVE) will be calculated as follows: ΔPPVVE = PPVT4 - PPVT3 and ΔSVVVE = SVVT4 - SVVT3 Sample size calculation Sample size was calculated according to the hypothesis that the PPV8 can predict fluid responsiveness if the AUC (area under curve) = 0.75 in relation to the alternative null hypothesis (ΑUC = 0.5). For this difference it was calculated that at least 44 patients are needed to detect a difference of 0.25 with a type I error = 0.05 and a power of 0.90. Taking into account possible dropouts this number was increased to 50 patients. GPower 3.1.2 for Windows (Germany) software was used for sample size calculation. Statistical Analysis Normal distribution of continuous variables will be assessed with the Shapiro-Wilk test. Variables will be expressed as mean ± standard deviation, median \[interquartile range\] or number (percentage). Student's t-test or Mann-Whitney U test will be used for continuous variables and χ2 test for categorical variables. Correlation between variables will be analyzed with Spearman's correlation test. To calculate the ability of the dynamic indices to predict fluid responsiveness the ROC curve approach will be followed. The area under curve will be calculated and will be compared with the DeLong method. Briefly, curve interpretation will be as follows: AUC = 0.5, non reliable test; AUC = 0.6-0.69, test with poor predictive ability; · AUC = 0,7 - 0,79, moderate test; AUC = 0.8-0.89, a test with good predictive ability; AUC = 0.9-0.99, an excellent test; AUC = 1.0, a test with the best possible predictive ability. An optimal threshold value will be determined for each variable to maximize the Youden index (sensitivity + specificity - 1). Considering the possibility of an overlap between responders and non-responders, a grey zone for dynamic preload indices was determined , considering a low cut-off value including 90% of negative fluid challenge responses, and a high cut-off value predicting positive fluid challenge in 90% of cases.