Search

The process of weaning from mechanical ventilation is one of the challenges in intensive care. 149 patients under extubation process (T-tube test) were studied: 88 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 23 patients with successful test but that had to be reintubated before 48 hours (group R). Each patient was characterized using 8 time series and 6 statistics extracted from respiratory and cardiac signals. A moving window statistical analysis was applied obtaining for each patient a sequence of patterns of 48 features. Applying a cluster analysis two groups with the majority dataset were obtained. Neural networks were applied to discriminate between patients from groups S, F and R. The best performance obtained was 84.0% of well classified patients using a linear perceptron trained with a feature selection procedure (that selected 19 of the 48 features) and taking as input the main cluster centroid. However, the classification baseline 69.8% could not be improved when using the original set of patterns instead of the centroids to classify the patients.

The static pressure volume (PV) curve of the total respiratory system is a well established method to assess pulmonary mechanics during respiratory failure. We have tested the impact of auto-PEEP on the PV curve determination in 16 COPD patients. An isovolumic pressure increment (IPI) was found at the beginning of the curve and a close correlation between IPI and auto-PEEP level (r = 0.962) p less than 0.001) was observed. The regression equation was not significantly different from the identity line. We conclude that the appearance of IPI in PV curves is largely determined by auto-PEEP and it is a good estimate of the existing auto PEEP level.

During the early phase of the acute respiratory distress syndrome in adults (ARDS), pulmonary pressure-volume (P-V) curves exhibit a peculiar pattern, with increased hysteresis and an inflection in the ascending limb (Matamis et al, Chest 86:58-661984). End-expiratory lung volume is also markedly reduced. We traced P-V curves using a 2-L syringe in six patients with ARDS (group 2) and five patients without ARDS (group 1). End-expiratory lung volume, measured using the closed circuit helium dilution technique, was markedly reduced in both groups (39% ± 7% predicted in group 1, and 27% ± 7% in group 2). In the ARDS group, P-V curve was grossly abnormal, with an inflection at low lung volume and increased hysteresis: lung volume difference during inflation and deflation at a pressure 10 cm H2O higher than end-expiratory pressure was 803 ± 127 mL in group 2 and was only 450 ± 189 mL in group 1. Compliance measured during deflation was only slightly reduced in group 2. Application of first positive end-expiratory pressure 10, then 20 cm H2O, restored end-expiratory lung volume in all patients, and, in group 2 (ARDS), suppressed the inflection of the ascending limb, reduced hysteresis, and shifted the P-V trace upward and to the left. We conclude that, in ARDS patients, an abnormal pattern of P-V curve is explained by loss of volume, and by increased surface tension, since lung volume was similarly reduced in both groups. Increasing the level of end-expiratory pressure restores the normal pulmonary P-V relationship by suppressing the airway closure.

We studied airway occlusion pressure (P 0.1) and maximal inspiratory pressure (PIMax) in 10 healthy volunteers (Group A), 10 early postsurgical cardiac patients on spontaneous breathing (Group B), 10 patients mechanically ventilated for ARF (Group C), 10 patients weaning from mechanical ventilation after ARF (Group D) and 10 patients extubated after post-ARF (Group E). We calculated the index P 0.1/PIMax in an attempt to link the ventilatory demands and muscle ventilatory reserve. We found that the sensitivity and specificity in diagnosing the need for either full (C), partial (D) or no ventilatory support (A, B, E) by means of the P 0.1 were C = (50%, 95%), D = (70%, 72%) and A + B + E = (83%, 90%) respectively. When the index P 0.1/PIMax was used they were C = (90%, 100%), D = (80%, 87%) and A + B + E = (86%, 90%). We conclude that the index P 0.1/PIMax increases the reliability of P 0.1 alone to correctly classify the patients that will need either full, partial or no ventilatory support in ARF.

One of the challenges in intensive care is the process of weaning from mechanical ventilation. We studied the differences in respiratory pattern variability between patients capable of maintaining spontaneous breathing during weaning trials and patients that fail to maintain spontaneous breathing. In this work, neural networks were applied to study these differences. 64 patients from mechanical ventilation are studied: Group S with 32 patients with Successful trials and Group F with 32 patients that Failed to maintain spontaneous breathing and were reconnected. A performance of 64.56% of well classified patients was obtained using a neural network trained with the whole set of 35 features. After the application of a feature selection procedure (backward selection) 84.56% was obtained using only 8 of the 35 features.

Nonlinear processes of the autonomic nervous system (ANS) can produce breath-to-breath variability in the pattern of breathing. In order to provide assess to these nonlinear processes, nonlinear statistical dependencies between heart rate variability and respiratory pattern variability are analyzed. In this way, auto-mutual information and cross-mutual information concepts are applied. This information flow analysis is presented as a short-term non linear analysis method to investigate the information flow interactions in patients on weaning trials. 78 patients from mechanical ventilation were studied: Group A of 28 patients that failed to maintain spontaneous breathing and were reconnected; Group B of 50 patients with successful trials. The results show lower complexity with an increase of information flow in group A than in group B. Furthermore, a more (weakly) coupled nonlinear oscillator behavior is observed in the series of group A than in B.

Traditional time domain techniques of data analysis are often not sufficient to characterize the nonlinear dynamics of respiration. In this study, the respiratory pattern variability was analyzed using auto mutual information measures. These provide access to nonlinear statistical autodependencies of respiratory pattern variability. A group of 20 patients on weaning trials from mechanical ventilation were studied at two different pressure support ventilation levels, in order to obtain respiratory volume signals with different variability. Time series of breathing duration, inspiratory time, fractional inspiratory time, tidal volume and mean inspiratory flow were analyzed. Different measures based on auto-mutual information were studied to characterize the respiratory pattern variability with regard to its complex organization.

Assessing autonomic control provides information about patho-physiological imbalances. Measures of variability of the cardiac interbeat duration RR(n) and the variability of the breath duration TinfTot/inf(n) are sensitive to those changes. The interactions between RR(n) and TinfTot/inf(n) are complex and strongly non-linear. A study of joint symbolic dynamics is presented as a new short-term non-linear analysis method to investigate these interactions in patients on weaning trials. 78 patients from mechanical ventilation are studied: Group A (patients that failed to maintain spontaneous breathing and were reconnected) and Group B (patients with successful trials). Using the concept of joint symbolic dynamics, cardiac and respiratory changes were transformed into a word series, and the probability of occurrence of each word type was calculated and compared between both groups. Significant differences were found in 13 words, and the most significant pinfn/inf(Winfc010, r010/inf): 0.0041#177; 0.0036 (group A) against 0.0012#177; 0.0024 (group B), p-value = 0.00001. The number of seldom occurring word types (forbidden words) also presents significant differences fwinfcr/inf: 6.9#177; 6.6 against 13.5#177; 5.3, p-value = 0.00004. Joint symbolic dynamics provides an efficient non-linear representation of cardiorespiratory interactions that offers simple physiological interpretations.

To determine the incidence, risk factors, and outcome of barotrauma in a cohort of mechanically ventilated patients where limited tidal volumes and airway pressures were used.Prospective cohort of 361 intensive care units from 20 countries.A total of 5183 patients mechanically ventilated for more than 12 h.Baseline demographic data, primary indication for mechanical ventilation, daily ventilator settings, multiple-organ failure over the course of mechanical ventilation and outcome were collected. Barotrauma was present in 154 patients (2.9%). The incidence varied according to the reason for mechanical ventilation: 2.9% of patients with chronic obstructive pulmonary disease; 6.3% of patients with asthma; 10.0% of patients with chronic interstitial lung disease (ILD); 6.5% of patients with acute respiratory distress syndrome (ARDS); and 4.2% of patients with pneumonia. Patients with and without barotrauma did not differ in any ventilator parameter. Logistic regression analysis identified as factors independently associated with barotrauma: asthma [RR 2.58 (1.05-6.50)], ILD [RR 4.23 (95%CI 1.78-10.03)]; ARDS as primary reason for mechanical ventilation [RR 2.70 (95%CI 1.55-4.70)]; and ARDS as a complication during the course of mechanical ventilation [RR 2.53 (95%CI 1.40-4.57)]. Case-control analysis showed increased mortality in patients with barotrauma (51.4 vs 39.2%; p=0.04) and prolonged ICU stay.In a cohort of patients in whom airway pressures and tidal volume are limited, barotrauma is more likely in patients ventilated due to underlying lung disease (acute or chronic). Barotrauma was also associated with a significant increase in the ICU length of stay and mortality.

The Simplified Acute Physiology Score III Outcomes Research Group is developing an international multidimensional instrument for the global evaluation of intensive care unit performance. Among its specific objectives are the update of a severity of illness index (Simplified Acute Physiology Score) with a mortality prediction equation, with the hindsight of recent years, and the creation or application of novel instruments in the areas of infections and cost-effectiveness. Some important measurements such as the quality of life and the satisfaction of patients and professionals are not included. A further aim is the achievement of international validation.

The outcome of patients receiving mechanical ventilation for particular indications has been studied, but the outcome in a large number of unselected, heterogeneous patients has not been reported.To determine the survival of patients receiving mechanical ventilation and the relative importance of factors influencing survival.Prospective cohort of consecutive adult patients admitted to 361 intensive care units who received mechanical ventilation for more than 12 hours between March 1, 1998, and March 31, 1998. Data were collected on each patient at initiation of mechanical ventilation and daily throughout the course of mechanical ventilation for up to 28 days.All-cause mortality during intensive care unit stay.Of the 15 757 patients admitted, a total of 5183 (33%) received mechanical ventilation for a mean (SD) duration of 5.9 (7.2) days. The mean (SD) length of stay in the intensive care unit was 11.2 (13.7) days. Overall mortality rate in the intensive care unit was 30.7% (1590 patients) for the entire population, 52% (120) in patients who received ventilation because of acute respiratory distress syndrome, and 22% (115) in patients who received ventilation for an exacerbation of chronic obstructive pulmonary disease. Survival of unselected patients receiving mechanical ventilation for more than 12 hours was 69%. The main conditions independently associated with increased mortality were (1) factors present at the start of mechanical ventilation (odds ratio [OR], 2.98; 95% confidence interval [CI], 2.44-3.63; P.001 for coma), (2) factors related to patient management (OR, 3.67; 95% CI, 2.02-6.66; P.001 for plateau airway pressure35 cm H(2)O), and (3) developments occurring over the course of mechanical ventilation (OR, 8.71; 95% CI, 5.44-13.94; P.001 for ratio of PaO(2) to fraction of inspired oxygen100).Survival among mechanically ventilated patients depends not only on the factors present at the start of mechanical ventilation, but also on the development of complications and patient management in the intensive care unit.

The discrepancy in results from different studies regarding outcome of weaning from mechanical ventilation may be due to several factors such as the differences in patient populations and weaning indexes used. In order to analyze the clinical characteristics and weaning indexes in patients undergoing a 2-h T-piece weaning trial and the relationship between the etiology of acute respiratory failure (ARF) and the outcome of this weaning trial, we prospectively studied 217 patients receiving mechanical ventilation who met standard weaning criteria. Successful weaning occurred in 57.6% (125 of 217) of patients: 13 of 33 (39.4%) patients with chronic obstructive pulmonary disease (COPD), 27 of 46 (58.7%) neurologic patients, and 85 of 138 (61.6%) patients with ARF. Ventilatory support was reinstituted in 31.8% (69 of 217) patients: 20 of 33 (60.6%) of patients with COPD, four of 46 (8.7%) neurologic patients, and 45 of 138 (32.6%) patients with ARF (p , 0.001). Reintubation was required in 23 of 148 (15.5%) patients: 15 of 42 (35.7%) neurologic patients, and eight of 93 (8.6%) patients with ARF, whereas no patient with COPD was reintubated (p , 0.001). Using a discriminant analysis, the following variables were selected as the best predictors of outcome: ( 1 ) in the whole population, days of mechanical ventilation before weaning trial (DMV), frequency-to-tidal volume ratio (f/V T ), maximal inspiratory pressure (MIP), airway occlusion pressure (P 0.1 ), maximal expiratory pressure (MEP), and vital capacity (VC); ( 2 ) in patients with ARF, DMV, P 0.1 /MIP, MIP, f/V T , and age; ( 3 ) in patients with COPD, f/V T , P 0.1 , P 0.1 /MIP, MIP, age, and DMV; ( 4 ) in neurologic patients, MIP, MEP, and f/V T ? P 0.1 . Using these predictors, 74.6% of the whole population, 76.1% of patients with ARF, 93.9% of patients with COPD, and 73.9% of neurologic patients were accurately classified as weaning successes or failures. The highest rate of reintubation occurred in neurologic patients. In this group, the ability to cough and clear respiratory secretions, objectively reflected by MEP, may help in clinical decision-making. Vallverdu I, Calaf N, Subirana M, Net A, Benito S, Mancebo J. Clinical characteristics, respiratory functional parameters, and outcome of a two-hour T-piece trial in patients weaning from mechanical ventilation. AM J RESPIR CRIT CARE MED 1998;158:1855‐1862.

Purpose :The purpose of this article is to analyze the effect of a pressure-regulated volume-controlled ventilation mode on lung mechanics and gas exchange in patients with acute respiratory failure. Materials and Methods :We ventilated 10 patients with two pressure-limited modes: pressure-controlled ventilation (PC) and pressure-regulated volume-controlled ventilation (PRVC) in random order, for 1 hour each. Patients were stabilized on volume-controlled ventilation (VC) for 30 minutes before, between, and at the end of PC and PRVC to reach baseline conditions. At the end of every VC period and at 30 and 60 minutes of PC and PRVC, respiratory mechanics, gasometrics, and hemodynamic parameters were collected. Results :We found no significant differences between the three VC periods. Comparing VC with the two pressure-limited ventilation modes, peak pressure decreased from 29.4 ± 9.1 cm H2O (VC) to 25.9 ± 8.4 (PC 60 minutes) and 26.1 ± 8.2 (PRVC 60 minutes), and PaCO2 decreased significantly from 38.6 ± 3.1 mm Hg (VC) to 36.7 ± 2.8 (PC 60 minutes) and 36.8 ± 2.9 (PRVC 60 minutes). Conclusions :Pressure-limited ventilation allows mechanical ventilation for the same tidal volume as VC but results in a lower peak inspiratory pressure and a slightly lower Paco2. The mechanism responsible for this gas exchange effect is unknown but is probably related to a better air distribution of the decelerated flow. The clinical relevance of this phenomenon remains to be established.

In patients with acute exacerbations of chronic obstructive pulmonary disease, noninvasive ventilation may be used in an attempt to avoid endotracheal intubation and complications associated with mechanical ventilation.We conducted a prospective, randomized study comparing noninvasive pressure-support ventilation delivered through a face mask with standard treatment in patients admitted to five intensive care units over a 15-month period.A total of 85 patients were recruited from a larger group of 275 patients with chronic obstructive pulmonary disease admitted to the intensive care units in the same period. A total of 42 were randomly assigned to standard therapy and 43 to noninvasive ventilation. The two groups had similar clinical characteristics on admission to the hospital. The use of noninvasive ventilation significantly reduced the need for endotracheal intubation (which was dictated by objective criteria): 11 of 43 patients (26 percent) in the noninvasive-ventilation group were intubated, as compared with 31 of 42 (74 percent) in the standard-treatment group (P0.001). In addition, the frequency of complications was significantly lower in the noninvasive-ventilation group (16 percent vs. 48 percent, P = 0.001), and the mean (+/- SD) hospital stay was significantly shorter for patients receiving noninvasive ventilation (23 +/- 17 days vs. 35 +/- 33 days, P = 0.005). The in-hospital mortality rate was also significantly reduced with noninvasive ventilation (4 of 43 patients, or 9 percent, in the noninvasive-ventilation group died in the hospital, as compared with 12 of 42, or 29 percent, in the standard-treatment group; P = 0.02).In selected patients with acute exacerbations of chronic obstructive pulmonary disease, noninvasive ventilation can reduce the need for endotracheal intubation, the length of the hospital stay, and the in-hospital mortality rate.

with Special Reference to Ventilator-associated Barotrauma.- Pneumotachographic Recording of Ventilatory Pattern.- Spirometry.- Inspiratory Occluded Airway Pressure.- Transdiaphragmatic Pressure.- Assessment of the Breathing Workload During Mechanical Ventilation.- Assessment of Diaphragmatic Function.- Pulmonary Compliance.- Respiratory Impedance.- Elastance and Resistance of Respiratory System.- Respiratory Inductive Plethysmography.- Closing Volume.- Functional Residual Capacity in Acute Respiratory Failure. Methods of Measurement in the Ventilated Patients and Their Clinical Utility.- FRC and Efficiency of Gas Mixing in the Lung. SF6.- Determination of Lung-Ventilation and Perfusion by Isotope Technique.- Multiple Inert Gas Elimination Technique.- Pulmonary Diffusion Capacity.- Blood Gases.- Pulse Oximetry in the Intensive Therapy Unit.- Transcutaneous Monitoring of Oxygen and Carbon Dioxide.- Mixed Venous Oxygen Saturation Monitoring in Mechanically Ventilated Patients.- Capnography.- Measurement of Oxygen Consumption and Carbon Dioxide Production in Artificially Ventilated Patients.- Bronchoalveolar Lavage.- Measurement of Extrapulmonary Lung Water.- Interactions Between Convective and Diffusive Components of O2 Transport to the Tissues.- Energy Metabolism and Diaphragmatic Function: Applications of Magnetic Resonance Spectroscopy.- The Oxygen Consumption of the Respiratory Muscles.- Clinical Applications of Balloon Occlusion Pulmonary Angiography (BOPA).- Computerized Axial Tomography of the Lung During Acute Respiratory Failure.

Background Ventilator-associated pneumonia is a common complication in ventilated patients. Endotracheal suctioning is a procedure that may constitute a risk factor for ventilator-associated pneumonia. It can be performed with an open system or with a closed system. In view of suggested advantages being reported for the closed system, a systematic review comparing both techniques was warranted. Objectives To compare the closed tracheal suction system and the open tracheal suction system in adults receiving mechanical ventilation for more than 24 hours. Search methods We searched CENTRAL (The Cochrane Library 2006, Issue 1) MEDLINE, CINAHL, EMBASE and LILACS from their inception to July 2006. We handsearched the bibliographies of relevant identified studies, and contacted authors and manufacturers. Selection criteria The review included randomized controlled trials comparing closed and open tracheal suction systems in adult patients who were ventilated for more than 24 hours. Data collection and analysis We included the relevant trials fitting the selection criteria. We assessed methodological quality using method of randomization, concealment of allocation, blinding of outcome assessment and completeness of follow up. Effect measures used for pooled analyses were relative risk (RR) for dichotomous data and weighted mean differences (WMD) for continuous data. We assessed heterogeneity prior to meta-analysis. Main results Of the 51 potentially eligible references, the review included 16 trials (1684 patients), many with methodological weaknesses. The two tracheal suction systems showed no differences in risk of ventilator-associated pneumonia (11 trials; RR 0.88; 95% CI 0.70 to 1.12), mortality (five trials; RR 1.02; 95% CI 0.84 to 1.23) or length of stay in intensive care units (two trials; WMD 0.44; 95% CI -0.92 to 1.80). The closed tracheal suction system produced higher bacterial colonization rates (five trials; RR 1.49; 95% CI 1.09 to 2.03). Authors' conclusions Results from 16 trials showed that suctioning with either closed or open tracheal suction systems did not have an effect on the risk of ventilator-associated pneumonia or mortality. More studies of high methodological quality are required, particularly to clarify the benefits and hazards of the closed tracheal suction system for different modes of ventilation and in different types of patients.

Gentamicin intrapatient pharmacokinetics variations were studied in 40 critically ill medical patients, suffering gram-negative sepsis. These patients were studied in two phases throughout gentamicin treatment: firstly, on the second day of treatment, when aggressive fluid therapy was required, and secondly, five days later, when patients had achieved a more stable clinical condition. Pharmacokinetic parameters were determined using least squares linear regression analysis assuming a one-compartment model using the Sawchuk-Zaske method. The apparent volume of distribution (Vd) in the first phase of the study was 0.43 +/- 0.12 L/kg, while on the seventh day of treatment it was 0.29 +/- 0.17 L/kg (p less than 0.001). Statistically significant differences were also observed for peak serum concentration (p less than 0.001), total dosage recommended (p less than 0.001) and half-life (p less than 0.05), whilst differences were not found for trough levels. From the analysis of the results obtained, we recommend increasing the initial dosage and monitoring plasma levels within the first days of therapy in critically ill patients treated with gentamicin, since important variations in aminoglycoside Vd related to disease, fluid balance and renal function, commonly occur in these patients.

The Simplified Acute Physiology Score III Outcomes Research Group is developing an international multidimensional instrument for the global evaluation of intensive care unit performance. Among its specific objectives are the update of a severity of illness index (Simplified Acute Physiology Score) with a mortality prediction equation, with the hindsight of recent years, and the creation or application of novel instruments in the areas of infections and cost-effectiveness. Some important measurements such as the quality of life and the satisfaction of patients and professionals are not included. A further aim is the achievement of international validation.

ContextThe outcome of patients receiving mechanical ventilation for particular indications has been studied, but the outcome in a large number of unselected, heterogeneous patients has not been reported.ObjectiveTo determine the survival of patients receiving mechanical ventilation and the relative importance of factors influencing survival.Design, Setting, and SubjectsProspective cohort of consecutive adult patients admitted to 361 intensive care units who received mechanical ventilation for more than 12 hours between March 1, 1998, and March 31, 1998. Data were collected on each patient at initiation of mechanical ventilation and daily throughout the course of mechanical ventilation for up to 28 days.Main Outcome MeasureAll-cause mortality during intensive care unit stay.ResultsOf the 15 757 patients admitted, a total of 5183 (33%) received mechanical ventilation for a mean (SD) duration of 5.9 (7.2) days. The mean (SD) length of stay in the intensive care unit was 11.2 (13.7) days. Overall mortality rate in the intensive care unit was 30.7% (1590 patients) for the entire population, 52% (120) in patients who received ventilation because of acute respiratory distress syndrome, and 22% (115) in patients who received ventilation for an exacerbation of chronic obstructive pulmonary disease. Survival of unselected patients receiving mechanical ventilation for more than 12 hours was 69%. The main conditions independently associated with increased mortality were (1) factors present at the start of mechanical ventilation (odds ratio [OR], 2.98; 95% confidence interval [CI], 2.44-3.63; P35 cm H2O), and (3) developments occurring over the course of mechanical ventilation (OR, 8.71; 95% CI, 5.44-13.94; P

We have studied eleven patients ventilated in the assisted mode during recovery from acute respiratory failure. We have measured the effort required to trigger the pressure demand valve for 3 different ventilators, and have measured the occulusion pressure as an index of neuromuscular inspiratory drive. We found a delay in the opening of the demand valve, as previously described by other authors. We also found a close correlation between the effort required to open the demand valve and the occlusion pressure. We conclude that the inspiratory effort required to open the demand valve, in the assist mode, is greater than the preset trigger level and that it is well correlated with the neuromuscular inspiratory drive. This inspiratory effort against the closed demand valve, allows the measurement of the occlusion pressure.

We studied different gas dilution techniques in order to validate an easy method for the measurement of functional residual capacity (FRC) in patients with acute respiratory failure (ARF) undergoing mechanical ventilation (MV). FRC was measured in duplicate using four different techniques in 22 adult patients. The reference technique was the bag-in-a-box (BB) with helium (BB He) which was compared with a BB with nitrogen (BB NO, with helium syringe (He S), and with N 2 syringe N 2 S) techniques. The mean values of FRC (in BTPS units) obtained with the different techniques were 1,108 mL ± 398 mL (BB He), 1,061 mL ± 418 mL (BB N 2 , 1,170 mL ± 431 mL (He S), and 1,050 mL ± 429 mL N 2 S), the differences not being statistically significant. The linear regression equations were BB N 2 = −42 + 0.99 BB He, He S=54 +1.00 BB He, and N 2 S= −66 + 1.00 BB He. The mean difference between duplicate determinations ranged between −1.8 mL and 14 mL. The techniques studied are useful and practical bedside procedures for the estimation of FRC in ARF patients undergoing MV.

The effect of PEEP on the arterial minus end-tidal carbon dioxide gradient (FaCO 2 – PetCO 2 ) was evaluated in 13 adult patients with acute respiratory failure. The morphologic study of the pressure-volume (P-V) curves allowed separation of the patients into two groups: group 1 (n = 7) with initial inflection point in the (P-V) curve, and group 2 without inflection point. We hypothesized that the profile of the PaCO 2 – PetCO 2 gradient would indicate an appropriate PEEP level only in patients with recruitable air spaces. We ventilated group 1 patients with zero end expiratory pressure (ZEEP), PEEP corresponding to inflection point pressure (PEEP Pi ) and PEEP 5 cm H 2 O above PEEP Pi , and group 2 patients with ZEEP, 6 cm H 2 O PEEP and 12 cm H 2 O PEEP. The PaCO 2 – PetCO 2 gradient changed significantly in group 1 (ZEEP: 13.59 mm Hg; PEEP Pi : 8.33 mm Hg; PEEP Pi + 5 cm H 2 O: 10.54 mm Hg), but not in group 2 (ZEEP: 14.15 mm Hg; PEEP 6 cm H 2 O:14.20 mm Hg; PEEP 12 cm H 2 O: 16.53 mm Hg). Our results show that the PaCO 2 – PetCO 2 gradient may be useful in selecting a PEEP level which produces alveolar recruitment, but only in those patients with initial inflection point in the P-V curve.

The measurement of static pulmonary compliance by means of pressure-volume curves is an useful tool in the management of patients with acute respiratory failure. On admission to our Intensive Care Unit, we calculated the static pulmonary compliance values from the pressure-volume curve in 55 severe acute respiratory failure patients under mechanical ventilation. A predictive model, based on static pulmonary compliance measured on the deflation of the pressure-volume curve and patients' age, was developed using a function derived by stepwise discriminant analysis. Thirty-six of the 40 patients (90%) in the learning sample and 12 of the 15 patients (80%) in the test sample were correctly classified into survivors or non-survivors. The overall classification demonstrated an accuracy of 88% (48 of 55 patients). We conclude that the value of static pulmonary compliance can be an useful prognostic factor in patients with severe acute respiratory failure.

We evaluated the influence of intrinsic positive end-expiratory pressure (PEEPi) on the measurement of static respiratory compliance in 15 adult patients with acute respiratory failure under mechanical ventilation. Modifying the inspiratory/expiratory ratio from 1:2 to 2:1, and the respiratory frequency from 15 to 20 and 25 breath/min significantly changed compliance values. Because PEEPi can increase the work of breathing, we suggest adjusting ventilatory variables to minimize PEEPi.

One of the most frequent reasons for instituting mechanical ventilation is to decrease patient's work of breathing. Many attempts have been made to increase the effectiveness of the evaluation of the respiratory pattern with the analysis of the respiratory signals. This work proposes a method for the study of the differences in respiratory pattern variability in patients on weaning trials. The proposed method is based on a support vector machine using 35 features extracted from the respiratory flow signal. In this paper, a group of 146 patients with mechanical ventilation were studied: group S of 79 patients with successful weaning trials and group F of 67 patients that failed to maintain spontaneous breathing and were reconnected. Applying a feature selection procedure based on the use of the support vector machine with a leave-one-out cross-validation, it was obtained 86.67% of well classified patients on group S and 73.34% on group F, using only 8 of the 35 features. Therefore, support vector machine can be a classification method of the respiratory pattern variability useful in the study of patients on weaning trials.

Breathing pattern as periodic breathing (PB) in chronic heart failure (CHF) is associated with poor prognosis and high mortality risk. This work investigates the significance of a number of time domain parameters for characterizing respiratory flow cycle morphology in patients with CHF. Thus, our primary goal is to detect PB pattern and identify patients at higher risk. In addition, differences in respiratory flow cycle morphology between CHF patients (with and without PB) and healthy subjects are studied. Differences between these parameters are assessed by investigating the following three classification issues: CHF patients with PB versus with non-periodic breathing (nPB), CHF patients (both PB and nPB) versus healthy subjects, and nPB patients versus healthy subjects. Twenty-six CHF patients (8/18 with PB/nPB) and 35 healthy subjects are studied. The results show that the maximal expiratory flow interval is shorter and with lower dispersion in CHF patients than in healthy subjects. The flow slopes are much steeper in CHF patients, especially for PB. Both inspiration and expiration durations are reduced in CHF patients, mostly for PB. Using the classification and regression tree technique, the most discriminant parameters are selected. For signals shorter than 1 min, the time domain parameters produce better results than the spectral parameters, with accuracies for each classification of 82/78, 89/85, and 91/89 %, respectively. It is concluded that morphologic analysis in the time domain is useful, especially when short signals are analyzed.

Mechanical ventilators are used to provide life support in patients with respiratory failure. Assessing autonomic control during the ventilator weaning provides information about physiopathological imbalances. Autonomic parameters can be derived and used to predict success in discontinuing from the mechanical support. Time-frequency analysis is used to derive cardiac and respiratory parameters, as well as their evolution in time, during ventilator weaning in 130 patients. Statistically significant differences have been observed in autonomic parameters between patients who are considered ready for spontaneous breathing and patients who are not. A classification based on respiratory frequency, heart rate and heart rate variability spectral components has been proposed and has been able to correctly classify more than 80% of the cases.

Mechanical ventilators are used to provide life support in patients with respiratory failure. We studied the effect of pressure support ventilation (PSV) on the variational activity of the respiratory pattern in 20 patients on weaning trials from mechanical ventilation. The patients were each placed under two different levels of pressure support ventilation. The respiratory pattern was characterized by the following time series: inspiratory time (T/sub j/), breath duration (T/sub TOT/), and tidal volume (V/sub T/). The variational activity of breathing was partitioned into autoregressive, periodic and white noise fractions. High pressure support ventilation increased the gross variability of the inspiratory time and the breath duration. High PSV also caused a significant increase on the power of the oscillations for T/sub j/ and T/sub TOT/ time series. During both low and high PSV uncorrelated random behavior constituted > 80% of the variance of each breath component.

Understanding the respiratory control system and the ventilatory pattern under hypercapnic stimulus is important to interpret the acute exacerbation of COPD and the condition of patients connected to mechanical ventilation. The purpose of this study is the analysis of respiratory and muscle parameters in order to obtain the most sensitive and characteristic of different levels of hypercapnic stimulus. Parameters defined and calculated from pressure signals show the highest variations with the increment of stimulus. Other ones like exhaled ventilation or ratios between respiratory parameters are more influenced by hypercapnia than tidal volume, respiratory frequency or even end tidal CO/sub 2/. Muscle parameters from electromyographic signals of three respiratory muscles are calculated in time and frequency domain. In spite of greater variability between subjects, the most interesting muscles because of their activation with higher stimulus are in the following order: diaphragm, sternomastoid and genioglossus. Moreover, a model of respiratory control system is evaluated in order to predict and simulate appropriately this ventilatory stimulus. In spite of scattered real data, they are compared with simulation results obtained by the model and predicted by means of a specific respiratory optimization.

The purpose of this work is to evaluate characteristics of five respiratory models under different levels of exercise, hypercapnia and hypoxia. Two of them, RS1 and RS2, have permitted the implementation of a respiratory control system much more complex than the other ones. RS1 considers the integration of cardiorespiratory and mechanical systems. The most important difference in RS2 is the presence of respiratory frequency (f) that changes depending on the level of stimulus as it happens in fact. Tidal volume (V/sub T/) vs. f plots which are very interesting for the physiologists are obtained. A comparative study of the steady-state and transient responses between the five models is performed by simulation analyzing some interesting respiratory variables: expired ventilation, V/sub T/, f and arterial CO/sub 2/ and O/sub 2/ pressures. Finally, the influence of f and the ratio between inspiration and expiration intervals is evaluated.

Aging population is a major concern that is reflected in the increase of chronic diseases. Heart Failure (HF) is one of the most common chronic diseases of elderly people that is punctuated with acute episodes, which result in hospitalization. The periodic modulation of the amplitude of the breathing pattern is proved to be one of the multiple symptoms of an acute episode, and thus, the features extracted from its characterization contribute in the improvement of the first diagnosis of the clinical practice. The main objective of this study is to evaluate if the features extracted from the breathing pattern along with common clinical variables are reliable enough to detect Periodic Breathing (PB). A dataset of 44 elderly patients containing clinical information and a short record of electrocardiogram and respiratory flow signal was used to train two machine learning classification methods: Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA). All the available clinical parameters within the dataset along with the parameters characterizing the respiratory pattern were used to classify the observations into two groups. SVM classification was optimized and performed using a = -8 and C = 10.04 giving an accuracy of 88.2 % sensitivity of 90 % and specificity of 85.7 % Similar results were achieved with LDA classifying with an accuracy of 82.4 %, a sensitivity of 81.8% and specificity of 83.3 % PB has been accurately detected using both classifiers.

Many automatic devices to measure effective compliance can now be incorporated in mechanical ventilators. We compared measurements from these devices against those obtained from a pressure-volume curve made with a super-syringe. The methods produced closely correlating results (r = 0.854; p less than .001) in 20 adult patients with acute respiratory failure. Both techniques provide useful information about the elastic properties of the lung and can be used to adjust mechanical ventilation.

Summary Objectives: The traditional techniques of data analysis are often not sufficient to characterize the complex dynamics of respiration. In this study the respiratory pattern variability was analyzed using symbolic dynamics. Methods: A group of 20 patients on weaning trials from mechanical ventilation were studied at two different pressure support ventilation levels. Breath duration (TTOT) time series and the relation TI/TTOT, that contains the influence of inspiratory time (TI), were considered. Length-3 words and 3 different symbols were proposed. The incidence of the overlapping τ and the parameter α were analyzed. Results: From the breath duration time series, the distribution of words with probability of occurrence higher than 6% was concentrated on one word for low respiratory variability, whereas high variability was characterized by 4 words, presenting a statistically significant difference (p ≤ 0.0005). The probability occurrence of words “110” and “111” was also significantly different (p ≤ .0005) when comparing both variabilities. Conclusion: The analysis carried out obtained discriminant functions able to correctly classify all the testing set series. These results permit the consideration of symbolic dynamics as a promising methodology to study the respiratory pattern variability.

Periodic breathing (PB) has a high prevalence in chronic heart failure (CHF) patients with mild to moderate symptoms and poor ventricular function. This work proposes the analysis and characterization of the respiratory pattern to identify periodic breathing pattern (PB) and non-periodic breathing pattern (nPB) through the respiratory flow signal. The respiratory pattern analysis is based on the extraction and the study of the flow envelope signal. The flow envelope signal is modelled by an autoregressive model (AR) whose coefficients would characterize the respiratory pattern of each group. The goodness of the characterization is evaluated through a linear and non linear classifier applied to the AR coefficients. An adaptive feature selection is used before the linear and non linear classification, employing leave-one-out cross validation technique. With linear classification the percentage of well classified patients (8 PB and 18 nPB patients) is 84.6% using the statistically significant coefficients whereas with non linear classification, the percentage of well classified patients increase to more than 92% applying the best subset of coefficients extracted by a forward selection algorithm.

Some of the most common clinical problems in elderly patients are related to diseases of the cardiac and respiratory systems. Elderly patients often have altered breathing patterns, such as periodic breathing (PB) and Cheyne-Stokes respiration (CSR), which may coincide with chronic heart failure. In this study, we used the envelope of the respiratory flow signal to characterize respiratory patterns in elderly patients. To study different breathing patterns in the same patient, the signals were segmented into windows of 5 min. In oscillatory breathing patterns, frequency and time-frequency parameters that characterize the discriminant band were evaluated to identify periodic and non-periodic breathing (PB and nPB). In order to evaluate the accuracy of this characterization, we used a feature selection process, followed by linear discriminant analysis. 22 elderly patients (7 patients with PB and 15 with nPB pattern) were studied. The following classification problems were analyzed: patients with either PB (with and without apnea) or nPB patterns, and patients with CSR versus PB, CSR versus nPB and PB versus nPB patterns. The results showed 81.8% accuracy in the comparisons of nPB and PB patients, using the power of the modulation peak. For the segmented signal, the power of the modulation peak, the frequency variability and the interquartile ranges provided the best results with 84.8% accuracy, for classifying nPB and PB patients.

The traditional techniques of data analysis are often not sufficient to characterize the complex dynamics of respiration. In this study the respiratory pattern variability at different levels of pressure support ventilation (PSV) has been analyzed using nonlinear prediction methods. These methods use the volume signals generated by the respiratory system in order to construct a model of its dynamics, and then to estimate the deterministic level of the system from the quality of the predictions made with the model. Different methods of prediction evaluation and neighborhood definition have been considered. The incidence of different prediction depths and embedding dimensions have been analyzed. A group of 12 patients on weaning trials from mechanical ventilation have been studied at two different PSV levels. High statistically significant differences have been obtained when comparing the mean prediction error at two different PSV levels (p

Mechanical ventilators are used to provide life support in patients with respiratory failure. One of the challenges in intensive care is the process of weaning from mechanical ventilation. We studied the differences in respiratory pattern variability between patients capable of maintaining spontaneous breathing during weaning trials and patients that fail to maintain spontaneous breathing. The respiratory pattern was characterized by the following time series: inspiratory time (T/sub I/), expiratory time (T/sub E/), breath duration (T/sub Tot/), tidal volume (V/sub T/), fractional inspiratory time (T/sub I//T/sub Tot/), mean inspiratory flow (V/sub T//T/sub I/), respiratory frequency (f), and rapid shallow breathing index (f/V/sub T/). The variational activity of breathing was partitioned into autoregressive, periodic and white noise fractions. Patients with unsuccessful trial presented a tendency to higher values of gross variability of V/sub T//T/sub I/ and f/V/sub T/, and lower values of T/sub I/. The autocorrelation coefficients tended to present higher values for T/sub I/, T/sub I//T/sub Tot/ and V/sub T//T/sub I/. During both successful and unsuccessful T-tube test uncorrelated random behavior constituted > 75% of the variance of each time breath components and represented 50 to 70% in the breath component related to V/sub T/. Correlated behavior represented 6 to 21% in time components and 28 to 50% in component related to V/sub T/.