Clinical trial NCT03568786: Influence of the End-inspiratory Pause on Mechanical Ventilation.
Official title: Influence of the End-inspiratory Pause on Mechanical Ventilation and Its Correlation With Electrical Impedance Tomography
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Anesthesia
Surgery
Keywords: end-inspiratory pause
lung protection
intraoperative ventilation
lung compliance
Lead sponsor: Fundación Pública Andaluza para la gestión de la Investigación en Sevilla
Sponsor class: OTHER
First posted: 2018-06-26
Enrollment: 32
Sex: ALL
Minimum age (years): 18
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Primary purpose: TREATMENT

Brief summary: This study evaluates the influence of two different end-inspiratory pause (EIP) times on respiratory mechanics and arterial gases of surgical patients when ventilated under an open lung approach (OLA) strategy. The investigators evaluate the impact of using EIP 10% versus 30% of the inspiratory time on a volume control model. The investigators also analyse the potential influence of these EIP on pulmonary gas distribution measured by electric impedance tomography.

Detailed description: Prolonging the EIP while maintaining an adequate expiratory time has shown benefits in terms of improving alveolar effective ventilation and enhancing gas exchange in surgical and intensive care patients. However, there are no published studies addressing the effects of different EIP times on the respiratory mechanics and gas distribution of surgical patients when associated with OLA strategies for ventilation.

Assuming the benefits of OLA, these investigators hypothesized about the potential effects of increasing the EIP when ventilating patients in a volume control mode. In the present study the investigators evaluated the influence of two different EIP (10% and 30% of the inspiratory time) on the respiratory mechanics of patients submitted to scheduled abdominal surgery under general anesthesia and ventilated with a protective lung strategy. The investigators studied the influence of EIP on driving pressure (Pdriv), plateau pressure (Pplat), respiratory static compliance (Crs) and open lung PEEP (OL-PEEP). We also assessed gas distribution by means of electric impedance tomography and studied its influence on gas exchange measured by means of serial gasometries.

Study protocol. A forced spirometry was performed in all patients after accepting their inclusion.

On the day of surgery, standard monitoring was initiated on arrival in the theatre, including electrocardiography, pulse oximetry, and noninvasive blood pressure monitoring. After light sedation with 1-2 mg of midazolam, a thoracic epidural catheter was placed under local anesthesia on anesthesiologist's criteria. A remifentanil infusion 0.03 mcg/kg/min was started before left radial artery catheterization under local anesthesia. After recording basal data during full consciousness on 21% inspired oxygen, all participants were preoxygenated via a facial mask for 5 min on spontaneous ventilation with fraction of inspired oxygen (FiO2) of 0.7 and fresh gas flow of 6 L/min. After induction with propofol ((1-1.5 mg/kg of predicted body weight (PBW)), 0.8 mg/kg of PBW of rocuronium were administered and proceeded with tracheal intubation. Patients were ventilated via a Primus (Drager, Telford, PA, USA) using a tidal volume of 7 ml/kg of PBW; volume control mode comprised an inspiration: expiration ratio of 1:2 and a respiratory rate of 12-14 breaths per minute to maintain the etCO2 at 35-40 mmHg, with an initial PEEP of 5 cmH2O. EIP was programmed according to randomization group. Fresh gas flow of 2 L/min with FiO2 of 0.7 was used throughout the procedure. Anesthesia was maintained with remifentanil 0.03-0.1 mcg/kg/min and sevoflurane, with minimal alveolar concentration (MAC) of 0.7-1 adjusted for patient´s age. Bispectral Index monitoring was used throughout the entire procedure (BIS Quatro, Covidien Ilc, Mansfield, MA, USA). All ventilation parameters remained stable throughout the study except the EIP (diverted in function of study protocol assignation) and the PEEP, which was tailored according the principles of OLA ventilation previously published. A central venous line was inserted in all cases and continuous cardiac output monitoring, systemic vascular resistance and systolic volume variation were monitored throught out all procedure by means of FloTrac sensor (Edwards Lifesciences, Irvine, California, USA). Other monitoring included train of four (TOF) for neuromuscular relaxation.

Dräger Primus (Dräger Medical, Lübeck, Germany) was used for ventilation with continuous monitoring of peak pressure (Ppk), Pplat, PEEP, Crs, FiO2, fraction of expired oxygen (FeO2), end-tidal CO2 (etCO2). For blood gases an ABL90 FLEX PLUS analyzer (Radiometer Medical, Copenhagen, Denmark) was used. If hemodynamic instability occurred during the ARM (fall\> 20% of the cardiac index or mean arterial pressure), maneuver was discontinued and ephedrine or phenylephrine was administered and registered, restoring ARM on haemodynamics recovering.

Ventilatory management Data collection was made in five different moments (moment 0 to 4); moment 0: after endotracheal intubation, on establishing mechanical ventilation and prior to ARM, with the EIP assigned to each group and a standard PEEP of 5 cm H2O. Subsequently an ARM was performed as previously described by Ferrando et al, with calculation of the optimal PEEP by means of a decremental titration trial followed of a new AMR and establishment of a tailored OL-PEEP, 2 cmH2O over optimal PEEP (moment 1). EIP was then crossed between groups (30% in Group 1 and 10% in Group 2), moment 2. Another ARM was then performed with the consequent re-assignation of a different OL-PEEP for each group (moment 3). Finally, EIP was crossed again (moment 4). All data were collected 5 minutes after changes implementation.

Statistic analysis The investigators used the statistical software IBM SPSS Statistics for Windows, version 24 (IBM Corp., Armonk, N.Y., USA) for data analysis. An exploratory analysis of the data was performed using the mean and standard deviation or the median with interquartile ranges for quantitative variables. The investigators used the percentages for analysis of the qualitative variables. The investigators checked the normality of the distribution of data with the Kolmogorov-Smirnov test, or with the Shaphiro-Wilk test for variables with less than 50 records. The Student´s T test for paired samples was used to analyse the difference in the means of quantitative paired variables (intra-group differences), and the Student T test for independent samples to analyse the difference in the means of quantitative variables between both groups (inter-group differences).

Finally, the investigators grouped records corresponding to the EIP applied after recruitment, independently of the original assignation according to Group, In this sense, investigators grouped data corresponding to Group 1 in moment 1 with Group 2 in moment 3 (EIP10% after recruitment) and data of Group 1 in moment 3 with Group 2 in moment 1 (EIP 30% after recruitment), obtaining a sample of 32 registers in comparable paired conditions.

Calculation of the sample size Given the absence of previously published works with an approach similar to the one proposed by investigators, the sample size was calculated based on the data obtained in a pilot sample of 5 patients submitted to surgical and anesthesia management similar to those of the protocol proposed. The investigators estimated the sample size assuming the differences in Crs when changing from an EIP 10 % to 30% in a sequential way (paired sample), determining an average difference 12 ml/cm H2O between both interventions. Sample size was calculated to obtain a power of 80 % to detect differences in the contrast of the null hypothesis h₀: μ₁ = μ₂ by means of a bilateral Student's T test for two related samples, taking into account a level of significance is of 5 %, and assuming a mean of the differences of 12 ± 20 units. Taking into account that the expected percentage of dropouts was 20.00% it would be necessary to recruit 30 pairs of experimental units in the study.

Eligibility criteria: Inclusion Criteria:

* Patients older than 18 years proposed for major abdominal surgery under general anesthesia.
* Written informed consent.

Exclusion Criteria:

* Participation in another interventional study
* American Society of Anesthesiologists (ASA) classification grade = IV
* Patient in dialysis
* Chronic obstructive pulmonary disease (COPD) grade GOLD (Global Initiative for Chronic Obstructive Lung Disease) \> 2
* Functional vital capacity \< 60% or \> 120% of the predicted
* Body mass index (BMI) \> 35 kg/m2
* Relation PaO2/FiO2 \<200 mmHg in the baseline sample
* Presence of mechanical ventilation in the 72 hours prior to enrollment
* New York Heart Association (NYHA) functional class ≥ 3
* Clinically suspected heart failure
* Cardiac Index (IC) \< 2.5 ml/min/m2 and/or inotropics prior to surgery
* Diagnosis or suspicion of intracranial hypertension
* Presence of pneumothorax or giant bullae on preoperative imaging tests
* Use of Continuous Positive Airway Pressure (CPAP).

Primary outcomes:
measure: Changes in Respiratory System Compliance (ml/cmH2O)
timeFrame: Moment 0 (M0): 5 minutes (min) after tracheal intubation, with volume control and PEEP of 5 cmH2O; M1: 5 min after alveolar recruitment maneuver (ARM); M2: 5 min after crossing time of EIP; M3: 5 min after new ARM; M4: 5 min after crossing time EIP
Secondary outcomes:
measure: Changes in Driving Pressure (Pdriv; cmH2O)
timeFrame: Moment 0 (M0): 5 minutes (min) after tracheal intubation, with volume control and PEEP of 5 cmH2O; M1: 5 min after alveolar recruitment maneuver (ARM); M2: 5 min after crossing time of EIP; M3: 5 min after new ARM; M4: 5 min after crossing time EIP
Other outcomes:
Locations:
city: Seville
country: Spain
facility: Fundación Pública Andaluza para la Gestión de Investigación de Salud en Sevilla
Study officials:
affiliation: Fundación Pública Andaluza para la Investigación de Salud en Sevilla (FISEVI)
name: Daniel López-Herrera
role: PRINCIPAL_INVESTIGATOR
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