Individualized positive end-expiratory pressure reduces driving pressure in obese patients during laparoscopic surgery under pneumoperitoneum: a randomized clinical trial.

Introduction: During pneumoperitoneum (PNP), airway driving pressure (ΔPRS) increases due to the stiffness of the chest wall and cephalic shift of the diaphragm, which favors atelectasis. In addition, depending on the mechanical power (MP) formulas, they may lead to different interpretations. Methods: Patients >18 years of age with body mass index >35 kg/m2 were included in a single-center randomized controlled trial during their admission for bariatric surgery by abdominal laparoscopy. Intra-abdominal pressure was set at 15 mmHg at the pneumoperitoneum time point (PNP). After the recruitment maneuver, the lowest respiratory system elastance (ERS) was detected during the positive end-expiratory pressure (PEEP) step-wise decrement. Patients were randomized to the 1) CTRL group: ventilated with PEEP of 5 cmH2O and 2) PEEPIND group: ventilated with PEEP value associated with ERS that is 5% higher than its lowest level. Respiratory system mechanics and mean arterial pressure (MAP) were assessed at the PNP, 5 min after randomization (T1), and at the end of the ventilation protocol (T2); arterial blood gas was assessed at PNP and T2. ΔPRS was the primary outcome. Three MP formulas were used: MPA, which computes static PEEP × volume, elastic, and resistive components; MPB, which computes only the elastic component; and MPC, which computes static PEEP × volume, elastic, and resistive components without inspiratory holds. Results: Twenty-eight patients were assessed for eligibility: eight were not included and 20 patients were randomized and allocated to CTRL and PEEPIND groups (n = 10/group). The PEEPIND ventilator strategy reduced ΔPRS when compared with the CTRL group (PEEPIND, 13 ± 2 cmH2O; CTRL, 22 ± 4 cmH2O; p < 0.001). Oxygenation improved in the PEEPIND group when compared with the CTRL group (p = 0.029), whereas MAP was comparable between the PEEPIND and CTRL groups. At the end of surgery, MPA and MPB were correlated in both the CTRL (rho = 0.71, p = 0.019) and PEEPIND (rho = 0.84, p = 0.020) groups but showed different bias (CTRL, -1.9 J/min; PEEPIND, +10.0 J/min). At the end of the surgery, MPA and MPC were correlated in both the CTRL (rho = 0.71, p = 0.019) and PEEPIND (rho = 0.84, p = 0.020) groups but showed different bias (CTRL, -1.9 J/min; PEEPIND, +10.0 J/min). Conclusion: Individualized PEEP was associated with a reduction in ΔPRS and an improvement in oxygenation with comparable MAP. The MP, which solely computes the elastic component, better reflected the improvement in ΔPRS observed in the individualized PEEP group. Clinical Trial Registration: The protocol was registered at the Brazilian Registry of Clinical Trials (U1111-1220-7296).

Positive end-expiratory pressure induced changes in airway driving pressure in mechanically ventilated COVID-19 Acute Respiratory Distress Syndrome patients.

BACKGROUND: The profile of changes in airway driving pressure (dPaw) induced by positive-end expiratory pressure (PEEP) might aid for individualized protective ventilation. Our aim was to describe the dPaw versus PEEP curves behavior in ARDS from COVID-19 patients. METHODS: Patients admitted in three hospitals were ventilated with fraction of inspired oxygen (FiO2) and PEEP initially adjusted by oxygenation-based table. Thereafter, PEEP was reduced from 20 until 6 cmH2O while dPaw was stepwise recorded and the lowest PEEP that minimized dPaw (PEEPmin_dPaw) was assessed. Each dPaw vs PEEP curve was classified as J-shaped, inverted-J-shaped, or U-shaped according to the difference between the minimum dPaw and the dPaw at the lowest and highest PEEP. In one hospital, hyperdistention and collapse at each PEEP were assessed by electrical impedance tomography (EIT). RESULTS: 184 patients (41 including EIT) were studied. 126 patients (68%) exhibited a J-shaped dPaw vs PEEP profile (PEEPmin_dPaw of 7.5 ± 1.9 cmH2O). 40 patients (22%) presented a U (PEEPmin_dPaw of 12.2 ± 2.6 cmH2O) and 18 (10%) an inverted-J profile (PEEPmin_dPaw of 14,6 ± 2.3 cmH2O). Patients with inverted-J profiles had significant higher body mass index (BMI) and lower baseline partial pressure of arterial oxygen/FiO2 ratio. PEEPmin_dPaw was associated with lower fractions of both alveolar collapse and hyperinflation. CONCLUSIONS: A PEEP adjustment procedure based on PEEP-induced changes in dPaw is feasible and may aid in individualized PEEP for protective ventilation. The PEEP required to minimize driving pressure was influenced by BMI and was low in the majority of patients.

Empirical evidence for safety of mechanical ventilation during simulated cardiopulmonary resuscitation on a physical model.

BACKGROUND: Cardiac arrest is a critical event requiring adequate and timely response in order to increase a patient's chance of survival. In patients mechanically ventilated with advanced airways, cardiopulmonary resuscitation (CPR) maneuver may be simplified by keeping the ventilator on. This work assessed the response of an intensive care mechanical ventilator to CPR using a patient manikin ventilated in three conventional modes. METHODS: Volume-controlled (VCV), pressure-controlled (PCV) and pressure regulated volume-controlled (PRVC) ventilation were applied in a thorax physical model, with or without chest compressions. The mechanical ventilator was set with inspiratory time of 1.0 s, ventilation rate of 10 breaths/min, positive end-expiratory pressure of 0 cmH2O, FiO2 of 1.0, target tidal volume of 600 mL and trigger level of -20 cmH2O. Airway opening pressure and ventilatory flow signals were continuously recorded. RESULTS: Chest compression resulted in increased airway peak pressure in all ventilation modes (p < 0.001), especially with VCV (137% in VCV, 83% in PCV, 80% in PRVC). However, these pressures were limited to levels similar to release valves in manual resuscitators (~60 cmH2O). In pressure-controlled modes tidal/min volumes decreased (PRVC = 11%, p = 0.027 and PCV = 12%, p < 0.001), while still within the variability observed during bag-valve-mask ventilation. During VCV, variation in tidal/min volumes were not significant (p = 0.140). Respiratory rate did not change with chest compression. CONCLUSIONS: Volume and pressure ventilation modes responded differently to chest compressions. Yet, variation in delivered volume and the measured peak pressures were within the reported for the standard bag-valve-mask system.

Variable Ventilation Associated With Recruitment Maneuver Minimizes Tissue Damage and Pulmonary Inflammation in Anesthetized Lung-Healthy Rats.

BACKGROUND: Recruitment maneuver and positive end-expiratory pressure (PEEP) can be used to counteract intraoperative anesthesia-induced atelectasis. Variable ventilation can stabilize lung mechanics by avoiding the monotonic tidal volume and protect lung parenchyma as tidal recruitment is encompassed within the tidal volume variability. METHODS: Forty-nine (7 per group) male Wistar rats were anesthetized, paralyzed, and mechanically ventilated. A recruitment maneuver followed by stepwise decremental PEEP titration was performed while continuously estimating respiratory system mechanics using recursive least squares. After a new recruitment, animals were ventilated for 2 hours in volume-control with monotonic (VCV) or variable (VV) tidal volumes. PEEP was adjusted at a level corresponding to the minimum elastance or 2 cm H2O above or below this level. Lungs were harvested for histologic analysis (left lung) and cytokines measurement (right lung). Seven animals were euthanized before the first recruitment as controls. RESULTS: A time-dependent increase in respiratory system elastance was observed and significantly minimized by PEEP (P < .001). Variable ventilation attenuated the amount of concentrations of proinflammatory mediators in lung homogenate: neutrophil cytokine-induced neutrophil chemoattractant 1 (VV = 40 ± 5 and VCV = 57 ± 8 pg/mg; P < .0001) and interleukin-1ß (VV = 59 ± 25 and VCV = 261 ± 113 pg/mg; P < .0001). Variable ventilation was also associated with lower structural lung parenchyma damage. Significant reductions in air fraction at dorsal and caudal lung regions were observed in all ventilated animals (P < .001). CONCLUSIONS: Variable ventilation was more protective than conventional ventilation within the applied PEEP levels.

Generalized estimation of the ventilatory distribution from the multiple-breath washout: a bench evaluation study.

BACKGROUND: The multiple-breath washout (MBW) is able to provide information about the distribution of ventilation-to-volume (v/V) ratios in the lungs. However, the classical, all-parallel model may return skewed results due to the mixing effect of a common dead space. The aim of this work is to examine whether a novel mathematical model and algorithm is able to estimate v/V of a physical model, and to compare its results with those of the classical model. The novel model takes into account a dead space in series with the parallel ventilated compartments, allows for variable tidal volume (VT) and end-expiratory lung volume (EELV), and does not require a ideal step change of the inert gas concentration. METHODS: Two physical models with preset v/V units and a common series dead space (vd) were built and mechanically ventilated. The models underwent MBW with N2 as inert gas, throughout which flow and N2 concentration signals were acquired. Distribution of v/V was estimated-via nonnegative least squares, with Tikhonov regularization-with the classical, all-parallel model (with and without correction for non-ideal inspiratory N2 step) and with the new, generalized model including breath-by-breath vd estimates given by the Fowler method (with and without constrained VT and EELV). RESULTS: The v/V distributions estimated with constrained EELV and VT by the generalized model were practically coincident with the actual v/V distribution for both physical models. The v/V distributions calculated with the classical model were shifted leftwards and broader as compared to the reference. CONCLUSIONS: The proposed model and algorithm provided better estimates of v/V than the classical model, particularly with constrained VT and EELV.

Generalized estimation of the ventilatory distribution from the multiple-breath nitrogen washout.

BACKGROUND: This work presents a generalized technique to estimate pulmonary ventilation-to-volume (v/V) distributions using the multiple-breath nitrogen washout, in which both tidal volume (V T ) and the end-expiratory lung volume (EELV) are allowed to vary during the maneuver. In addition, the volume of the series dead space (v d ), unlike the classical model, is considered a common series unit connected to a set of parallel alveolar units. METHODS: The numerical solution for simulated data, either error-free or with the N2 measurement contaminated with the addition of Gaussian random noise of 3 or 5 % standard deviation was tested under several conditions in a computational model constituted by 50 alveolar units with unimodal and bimodal distributions of v/V. Non-negative least squares regression with Tikhonov regularization was employed for parameter retrieval. The solution was obtained with either unconstrained or constrained (V T , EELV and v d ) conditions. The Tikhonov gain was fixed or estimated and a weighting matrix (WM) was considered. The quality of estimation was evaluated by the sum of the squared errors (SSE) (between reference and recovered distributions) and by the deviations of the first three moments calculated for both distributions. Additionally, a shape classification method was tested to identify the solution as unimodal or bimodal, by counting the number of shape agreements after 1000 repetitions. RESULTS: The accuracy of the results showed a high dependence on the noise amplitude. The best algorithm for SSE and moments included the constrained and the WM solvers, whereas shape agreement improved without WM, resulting in 97.2 % for unimodal and 90.0 % for bimodal distributions in the highest noise condition. CONCLUSIONS: In conclusion this generalized method was able to identify v/V distributions from a lung model with a common series dead space even with variable V T . Although limitations remain in presence of experimental noise, appropriate combination of processing steps were also found to reduce estimation errors.