Respiratory monitoring during mechanical ventilation

Development of a Novel Infant Volumetric Capnography Simulator: Making the Invisible Visible Improves Understanding and Safety

INTRODUCTION

Volumetric capnography depicts volumetric capnograms [ie, the plot of expired carbon dioxide (CO 2 ) over the tidal volume]. This bench study aimed to determine the reliability, accuracy, and precision of a novel infant simulator for volumetric capnography. This simulator would be clinically valuable for teaching purposes because it reflects the entire cardiopulmonary physiology within 1 breath.

METHODS

An infant lung simulator was fed with CO 2 supplied by a mass flow controller (VCO 2-IN ) and ventilated using standard settings. A volumetric capnograph was placed between the endotracheal tube and the ventilatory circuit. We simulated ventilated babies of different body weights (2, 2.5, 3, and 5 kg) with a VCO 2 ranging from 12 to 30 mL/min. The correlation coefficient ( r2 ), bias, coefficient of variation (CV = SD/ x × 100), and precision (2 × CV) between the VCO 2-IN and the elimination of CO 2 recorded by the capnograph (VCO 2-OUT ) were calculated. The quality of the capnogram's waveforms was compared with real ones belonging to anesthetized infants using an 8-point scoring system, where 6 points or greater meant that the simulated capnogram showed good, 5 to 3 points acceptable, and less than 3 points an unacceptable shape.

RESULTS

The correlation between VCO 2-IN and VCO 2-OUT was r2 = 0.9953 ( P < 0.001), with a bias of 0.16 (95% confidence intervals from 0.12 to 0.20) mL/min. The CV was 5% or less and the precision was 10% or less. All simulated capnograms showed similar shapes compared with real babies, scoring 6 points for 3 kg and 6.5 points for 2-, 2.5-, and 5-kg babies.

CONCLUSIONS

The simulator of volumetric capnograms was reliable, accurate, and precise for simulating the CO 2 kinetics of ventilated infants.

Non-invasive over-distension measurements: data driven vs model-based

Clinical measurements offer bedside monitoring aiming to minimise unintended over-distension, but have limitations and cannot be predicted for changes in mechanical ventilation (MV) settings and are only available in certain MV modes. This study introduces a non-invasive, real-time over-distension measurement, which is robust, predictable, and more intuitive than current methods. The proposed over-distension measurement, denoted as OD, is compared with the clinically proven stress index (SI). Correlation is analysed via R² and Spearman r_s. The OD safe range corresponding to the unit-less SI safe range (0.95-1.05) is calibrated by sensitivity and specificity test. Validation is fulfilled with 19 acute respiratory distress syndrome (ARDS) patients data (196 cases), including assessment across ARDS severity. Overall correlation between OD and SI yielded R² = 0.76 and Spearman r_s = 0.89. Correlation is higher considering only moderate and severe ARDS patients. Calibration of OD to SI yields a safe range defined: 0 ≤ OD ≤ 0.8 cmH₂O. The proposed OD offers an efficient, general, real-time measurement of patient-specific lung mechanics, which is more intuitive and robust than SI. OD eliminates the limitations of SI in MV mode and its less intuitive lung status value. Finally, OD can be accurately predicted for new ventilator settings via its foundation in a validated predictive personalized lung mechanics model. Therefore, OD offers potential clinical value over current clinical methods.

Over-distension prediction via hysteresis loop analysis and patient-specific basis functions in a virtual patient model

BACKGROUND AND OBJECTIVE

Recruitment maneuvers (RMs) with subsequent positive-end-expiratory-pressure (PEEP) have proven effective in recruiting lung volume and preventing alveolar collapse. However, a suboptimal PEEP could induce undesired injury in lungs by insufficient or excessive breath support. Thus, a predictive model for patient response under PEEP changes could improve clinical care and lower risks.

METHODS

This research adds novel elements to a virtual patient model to identify and predict patient-specific lung distension to optimise and personalise care. Model validity and accuracy are validated using data from 18 volume-controlled ventilation (VCV) patients at 7 different baseline PEEP levels (0-12cmH₂O), yielding 623 prediction cases. Predictions were made up to ΔPEEP = 12cmH₂O ahead covering 6x2cmH₂O PEEP steps.

RESULTS

Using the proposed lung distension model, 90% of absolute peak inspiratory pressure (PIP) prediction errors compared to clinical measurement are within 3.95cmH₂O, compared with 4.76cmH₂O without this distension term. Comparing model-predicted and clinically measured distension had high correlation increasing to R² = 0.93-0.95 if maximum ΔPEEP ≤ 6cmH₂O. Predicted dynamic functional residual capacity (V_frc) changes as PEEP rises yield 0.013L median prediction error for both prediction groups and overall R² of 0.84.

CONCLUSIONS

Overall results demonstrate nonlinear distension mechanics are accurately captured in virtual lung mechanics patients for mechanical ventilation, for the first time. This result can minimise the risk of lung injury by predicting its potential occurrence of distension before changing ventilator settings. The overall outcomes significantly extend and more fully validate this virtual mechanical ventilation patient model.

Is the asynchronous phase of thoracoabdominal movement a novel feature of successful extubation? A preliminary result

Mechanical ventilation is necessary to maintain patients' life in intensive care units. However, too early or too late extubation may injure the muscles or lead to respiratory failure. Therefore, the spontaneous breathing trial (SBT) is applied for testing whether the patients can spontaneously breathe or not. However, previous evidence still reported 15%~20% of the rate of extubation fail. The monitor only considers the ventilation variables during SBT. Therefore, this study measures the asynchronization between thoracic and abdomen wall movement (TWM and AWM) by using instantaneous phase difference method (IPD) during SBT for 120 minutes. The respiratory inductive plethysmography were used for TWM and AWM measurement. The preliminary result recruited 31 signals for further analysis. The result showed that in successful extubation group can be classified into two groups, IPD increase group, and IPD decrease group; but in extubation fail group, the IPD value only increase. Therefore, the IPD decrease group can almost perfectly be discriminated with extubation fail group, especially after 70 minutes (Area under curve of operating characteristic curve was 1). These results showed IPD is an important key factor to find whether the patient is suitable for extubation or not. These finding suggest that the asynchronization between TWM and AWM should be considered as a predictor of extubation outcome. In future work, we plan to recruit 150 subjects to validate the result of this preliminary result. In addition, advanced machine learning method is considered to apply for building effective models to discriminate the IPD increase group and extubation fail group.Clinical Relevance- The finding of this study is that the patients whose average IPD of 95 to 100 minutes was smaller than average IPD of first 5 minutes of SBT could be 100% successful extubation. In addition, ability of discrimination of average IPD after 70 minutes presents AUC 1.

Acute respiratory failure

Acute respiratory failure is common in critically ill children, who are at increased risk of respiratory embarrassment because of the developmental variations in the respiratory system. Although multiple etiologies exist, pneumonia and bronchiolitis are most common. Respiratory system monitoring has evolved, with the clinical examination remaining paramount. Invasive tests are commonly replaced with noninvasive monitors. Children with ALI/ARDS have better overall outcomes than adults, although data regarding specific therapies are still lacking. Most children will have some degree of long-term physiologic respiratory compromise after recovery from ALI/ARDS. The physiologic basis for respiratory failure and its therapeutic options are reviewed here.

Effect of tidal volume in children with acute hypoxemic respiratory failure

OBJECTIVES

To determine if tidal volume (VT) between 6 and 10 ml/kg body weight using pressure control ventilation affects outcome for children with acute hypoxemic respiratory failure (AHRF) or acute lung injury (ALI). To validate lung injury severity markers such as oxygenation index (OI), PaO2/FiO2 (PF) ratio, and lung injury score (LIS).

DESIGN

Retrospective, January 2000-July 2007.

SETTING

Tertiary care, 20-bed PICU.

PATIENTS

Three hundred and ninety-eight endotracheally intubated and mechanically ventilated children with PF ratio <300. Outcomes were mortality and 28-day ventilator free days.

MEASUREMENTS AND MAIN RESULTS

Three hundred and ninety-eight children met study criteria, with 20% mortality. 192 children had ALI. Using >90% pressure control ventilation, 85% of patients achieved VT less than 10 ml/kg. Median VT was not significantly different between survivors and non-survivors during the first 3 days of mechanical ventilation. After controlling for diagnostic category, age, delta P (PIP-PEEP), PEEP, and severity of lung disease, VT was not associated with mortality (P > 0.1), but higher VT at baseline and on day 1 of mechanical ventilation was associated with more ventilator free days (P < 0.05). This was particularly seen in patients with better respiratory system compliance [Crs > 0.5 ml/cmH2O/kg, OR = 0.70 (0.52, 0.95)]. OI, PF ratio, and LIS were all associated with mortality (P < 0.05).

CONCLUSIONS

When ventilating children using lung protective strategies with pressure control ventilation, observed VT is between 6 and 10 ml/kg and is not associated with increased mortality. Moreover, higher VT within this range is associated with more ventilator free days, particularly for patients with less severe disease.