On some factors determining the pressure drop across tracheal tubes during high-frequency percussive ventilation: a flow-independent model

To provide an in vitro estimation of the pressure drop across tracheal tubes (ΔP_TT) in the face of given pulsatile frequencies and peak pressures (P_work) delivered by a high-frequency percussive ventilator (HFPV) applied to a lung model. Tracheal tubes (TT) 6.5, 7.5 and 8.0 were connected to a test lung simulating the respiratory system resistive (R = 5, 20, 50 cmH₂O/L/s) and elastic (C = 10, 20, and 50 mL/cmH₂O) loads. The model was ventilated by HFPV with a pulse inspiratory peak pressure (work pressure P_work) augmented in 5-cmH₂O steps from 20 to 45 cmH₂O, yielding 6 diverse airflows. The percussive frequency (f) was set to 300, 500 and 700 cycles/min, respectively. Pressure (Paw and Ptr) and flow (V’) measurements were performed for all 162 possible combinations of loads, frequencies, and work pressures for each TT size, thus yielding 486 determinations. For each respiratory cycle ΔP_TT was calculated by subtracting each peak Ptr from its corresponding peak Paw. A non-linear model was constructed to assess the relationships between single parameters. Performance of the produced model was measured in terms of root mean square error (RMSE) and the coefficient of determination (r²). ΔP_TT was predicted by P_work (exponential Gaussian relationship), resistance (quadratic and linear terms), frequency (quadratic and linear terms) and tube diameter (linear term), but not by compliance. RMSE of the model on the testing dataset was 1.17 cmH₂O, r² was 0.79 and estimation error was lower than 1 cmH₂O in 68% of cases. As a result, even without a flow value, the physician would be able to evaluate ΔP_TT pressure. If the present results of our bench study could be clinically confirmed, the use of a nonconventional ventilatory strategy as HFPV, would be safer and easier.

An effective pressure-flow characterization of respiratory asynchronies in mechanical ventilation

Ineffective effort during expiration (IEE) occurs when there is a mismatch between the demand of a mechanically ventilated patient and the support delivered by a Mechanical ventilator during the expiration. This work presents a pressure-flow characterization for respiratory asynchronies and validates a machine-learning method, based on the presented characterization, to identify IEEs. 1500 breaths produced by 8 mechanically-ventilated patients were considered: 500 of them were included into the training set and the remaining 1000 into the test set. Each of them was evaluated by 3 experts and classified as either normal, artefact, or containing inspiratory, expiratory, or cycling-off asynchronies. A software implementing the proposed method was trained by using the experts' evaluations of the training set and used to identify IEEs in the test set. The outcomes were compared with a consensus of three expert evaluations. The software classified IEEs with sensitivity 0.904, specificity 0.995, accuracy 0.983, positive and negative predictive value 0.963 and 0.986, respectively. The Cohen's kappa is 0.983 (with 95% confidence interval (CI): [0.884, 0.962]). The pressure-flow characterization of respiratory cycles and the monitoring technique proposed in this work automatically identified IEEs in real-time in close agreement with the experts.

Dead space in acute respiratory distress syndrome

Dead space is the portion of each tidal volume that does not take part in gas exchange and represents a good global index of the efficiency of the lung function. Dead space is not routinely measured in critical care practice, because the difficulties in in interpreting capnograms and the different methods of calculations. Different dead space indices can provide useful information in acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) patients, where changes in microvasculature are the main determinants for the increase in dead space and consequently a worsening of the outcome. Lung recruitment is a dynamic process that combines recruitment manoeuvres (RMs) with positive end expiratory pressure (PEEP) and low Vt to recruit collapsed alveoli. Dead space guided recruitment allows avoiding regional overdistension or reduction in cardiac output in critical care patients with ALI or ARDS. Different patterns of ventilation affect also CO₂ elimination; in fact, end-inspiratory pause prolongation reduces dead space, increasing respiratory system compliance; plateau pressure and consequently driving pressure increase accordingly. Dead space measurement is a reliable method that provides important clinical and prognostic information. Different capnographic indices can be useful to evaluate therapeutic interventions or setting mechanical ventilation.

Uncommon Occurrences of Air Embolism: Description of Cases and Review of the Literature

Many different risk factors have been associated with the occurrence of gas embolism making this potentially lethal complication easily avoidable. However, this condition can occur in circumstances not commonly reported. Three different and extremely uncommon cases of gas embolism are presented and discussed: the first was caused by the voluntary ingestion of hydrogen peroxide, the second occurred during a retrograde cholangiopancreatography, and the last followed the intrapleural injection of Urokinase. Whereas in the first patient the gas embolism was associated with only relatively mild digestive symptoms, in the remaining two it caused a massive cerebral ischemia and an extended myocardial infarction, respectively. Despite a hyperbaric oxygen therapy performed timely in each case, only the first patient survived. The classical risk factors associated with gas embolism like indwelling central venous catheters, diving accidents, etc. are rather well known and thus somewhat preventable; however, a number of less common and difficult-to-recognize causes can determine this condition, making the correct diagnosis elusive and delaying the hyperbaric oxygen therapy, whose window of opportunity is rather narrow. Thus, a gas embolism should be suspected in the presence of not otherwise explainable sudden neurologic and/or cardiovascular symptoms also in circumstances not typically considered at risk.

In vitro estimation of pressure drop across tracheal tubes during high-frequency percussive ventilation

Tracheal tubes (TT) are used in clinical practice to connect an artificial ventilator to the patient's airways. It is important to know the pressure used to overcome tube impedance to avoid lung injury. Although high-frequency percussive ventilation (HFPV) has been increasingly used, the mechanical behavior of TT under HFPV has not yet been described. Thus, we aimed at characterizing in vitro the pressure drop across TT (ΔPTT) by identifying the model that best fits the measured pressure-flow (P-V̇) relationships during HFPV under different working pressures (PWork), percussive frequencies and mechanical loads. Three simple models relating ΔPTT and flow (V̇) were tested. Model 1 is characterized by linear resistive [Rtube ⋅ V̇(t)] and inertial [I · V̈(t)] terms. Model 2 takes into consideration Rohrer's approach [K1· V̇(t) + K2 ⋅V̇(t)] and inertance [I ·V̈(t)]. In model 3 the pressure drop caused by friction is represented by the non-linear Blasius component [Kb· V̇(1.75)(t)] and the inertial term [I· V̈(t)]. Model 1 presented a significantly higher root mean square error of approximation than models 2 and 3, which were similar. Thus, model 1 was not as accurate as the latter, possibly due to turbulence. Model 3 presented the most robust resistance-related coefficient. Estimated inertances did not vary among the models using the same tube. In conclusion, in HFPV ΔPTT can be easily calculated by the physician using model 3.

Comparison of noninvasive ventilation by sequential use of mask and helmet versus mask in acute exacerbation of chronic obstructive pulmonary disease: a preliminary study

BACKGROUND

Noninvasive positive pressure ventilation (NPPV) using a face mask is the ventilatory mode of choice in selected patients experiencing acute exacerbation of chronic obstructive pulmonary disease (COPD). A high incidence of intolerance limits the use of this approach.

OBJECTIVE

To evaluate the sequential use of mask and helmet during NPPV in patients with severe exacerbation of COPD in order to reduce the intolerance to these devices.

METHODS

Fifty-three patients ventilated for the first 2 h with NPPV by mask were studied. If gas exchange and clinical status improved, they were randomized to continue on NPPV by mask or helmet. Physiological parameters were measured at admission, after the first 2 h on NPPV by mask, 4 h after randomization and at discharge. Need for intubation, ventilatory assistance, length of stay (LOS) and complications were recorded.

RESULTS

After the first 2 h of NPPV, gas exchange and clinical parameters improved in 40 patients. Four hours after randomization, PaCO(2) was lower in the mask group than in the helmet group. Nine patients in the mask group and 2 in the helmet group failed NPPV, 8 and 1, respectively, owing to intolerance. Time of noninvasive ventilation and LOS were lower in the mask than in the helmet group.

CONCLUSIONS

In patients with acute exacerbation of COPD and undergoing NPPV, the sequential use of a mask and helmet diminished the incidence of failure. Under the present experimental conditions, the use of a helmet increased LOS and the duration of artificial ventilation.

Gas distribution in a two-compartment model ventilated in high-frequency percussive and pressure-controlled modes

PURPOSE

To demonstrate in a two-compartment heterogeneous mechanical model of the lung how different loads applied to one compartment, while the other is kept constant, would modify gas distribution between the two pathways under high-frequency percussive ventilation (HFPV). Additionally, these results were compared with those generated in the same model by pressure-controlled ventilation (PCV).

METHODS

Analysis was based on a Siemens lung simulator, representing a fixed branch of the system with an elastance equal to 45 cmH(2)O/L and a resistance of 20 cmH(2)O/L/s, and a single-compartment lung simulator, representing a variable pathway of the model, presenting three elastic loads varying between 35 and 85 cmH(2)O/L and three resistive loads varying between 5 and 50 cmH(2)O/L/s. Each simulator represented one compartment of the model connected to a central airway that was ventilated with either a volumetric diffusive respirator (VDR-4; Percussionaire Corporation, Sandpoint, ID, USA) or a Siemens Servo 900c ventilator. Flow and pressures were measured in each branch of the model under nine conditions representing the combinations of three elastic and three resistive loads (variable branch) while the loads in the other pathway were kept constant.

RESULTS

HFPV was able to avoid hyperinflation and reduce tidal volume in a bicompartmental heterogeneous lung model. Under HFPV, gas distribution between the two compartments was not constrained by their time constants. PCV yielded gas distribution as determined by the time constant of each compartment.

CONCLUSIONS

HFPV accommodated volume distribution without overinflating compartments with low time constants, thus possibly presenting a potential protective behavior in mechanically heterogeneous lungs.

Gas distribution in a two-compartment model during volume or pressure ventilation: role of elastic elements

The results of the studies on pulmonary gas distribution during constant-flow controlled-volume inflation (VCV) and inspiratory constant pressure inflation (PCV) in experimental studies are conflicting. In a mathematical model, with the characteristics of two lung compartments including tissue viscoelastic properties, pulmonary gas distribution was tested by simulating PCV and VCV at same inflation volumes. The compartmental distributions of the tidal volume were compared during CMV and PCV in different configurations obtained by changing the elastic and viscoelastic properties in each compartment, but maintaining the same total values of respiratory mechanics measured in patients. In all instances PCV resulted in a slightly higher air-trapping than in VCV mode. Heterogeneous elastic properties diverted most of the tidal volume towards the less compromised compartment. However, both ventilatory modes provided similar compartmental gas distribution, but during VCV compartmental peak pressures were higher in the sicker compartment respect to PCV. The use of PCV could grant a less remarkable pressure variability able to reduce the potential ventilator-associated lung injury. Moreover, the parameters measured during an end-inspiratory pause could not pinpoint unique characteristics for each configuration.