Modos controlados por presión versus volumen en la ventilación mecánica invasiva

Pulmonary response prediction through personalized basis functions in a virtual patient model

BACKGROUND AND OBJECTIVE

Recruitment maneuvers with subsequent positive-end-expiratory-pressure (PEEP) have proven effective in recruiting lung volume and preventing alveoli collapse. However, determining a safe, effective, and patient-specific PEEP is not standardized, and this more optimal PEEP level evolves with patient condition, requiring personalised monitoring and care approaches to maintain optimal ventilation settings.

METHODS

This research examines 3 physiologically relevant basis function sets (exponential, parabolic, cumulative) to enable better prediction of elastance evolution for a virtual patient or digital twin model of MV lung mechanics, including novel elements to model and predict distension elastance. Prediction accuracy and robustness are validated against recruitment maneuver data from 18 volume-controlled ventilation (VCV) patients at 7 different baseline PEEP levels (0 to 12 cmH2O) and 14 pressure-controlled ventilation (PCV) patients at 4 different baseline PEEP levels (6 to 12 cmH2O), yielding 623 and 294 prediction cases, respectively. Predictions were made up to 12 cmH2O of added PEEP ahead, covering 6 × 2 cmH2O PEEP steps.

RESULTS

The 3 basis function sets yield median absolute peak inspiratory pressure (PIP) prediction error of 1.63 cmH2O for VCV patients, and median peak inspiratory volume (PIV) prediction error of 0.028 L for PCV patients. The exponential basis function set yields a better trade-off of overall performance across VCV and PCV prediction than parabolic and cumulative basis function sets from other studies. Comparing predicted and clinically measured distension prediction in VCV demonstrated consistent, robust high accuracy with R2 = 0.90-0.95.

CONCLUSIONS

The results demonstrate recruitment mechanics are best captured by an exponential basis function across different mechanical ventilation modes, matching physiological expectations, and accurately capture, for the first time, distension mechanics to within 5-10 % accuracy. Enabling the risk of lung injury to be predicted before changing ventilator settings. The overall outcomes significantly extend and more fully validate this digital twin or virtual mechanical ventilation patient model.

A Comparative Study on Predication of Appropriate Mechanical Ventilation Mode through Machine Learning Approach

Ventilation mode is one of the most crucial ventilator settings, selected and set by knowledgeable critical care therapists in a critical care unit. The application of a particular ventilation mode must be patient-specific and patient-interactive. The main aim of this study is to provide a detailed outline regarding ventilation mode settings and determine the best machine learning method to create a deployable model for the appropriate selection of ventilation mode on a per breath basis. Per-breath patient data is utilized, preprocessed and finally a data frame is created consisting of five feature columns (inspiratory and expiratory tidal volume, minimum pressure, positive end-expiratory pressure, and previous positive end-expiratory pressure) and one output column (output column consisted of modes to be predicted). The data frame has been split into training and testing datasets with a test size of 30%. Six machine learning algorithms were trained and compared for performance, based on the accuracy, F1 score, sensitivity, and precision. The output shows that the Random-Forest Algorithm was the most precise and accurate in predicting all ventilation modes correctly, out of the all the machine learning algorithms trained. Thus, the Random-Forest machine learning technique can be utilized for predicting optimal ventilation mode setting, if it is properly trained with the help of the most relevant data. Aside from ventilation mode, control parameter settings, alarm settings and other settings may also be adjusted for the mechanical ventilation process utilizing appropriate machine learning, particularly deep learning approaches.

Emergency 3-Dimensional-Printed Devices for Splitting Ventilators in Lungs With Different Compliances: An In Vitro Study

Ventilator shortages occurred due to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This in vitro study evaluated the effectiveness of 3-dimensional (3D)-printed splitters and 3D-printed air flow limiters (AFL) in delivering appropriate tidal volumes (TV) to lungs with different compliances. Groups were divided according to the size of the AFL: AFL-4 was a 4-mm device, AFL-5 a 5-mm device, AFL-6 a 6-mm device, and no limiter (control). A ventilator was split to supply TV to 2 artificial lungs with different compliances. The AFL improved TV distribution.

Prediction of lung mechanics throughout recruitment maneuvers in pressure-controlled ventilation

Mechanical ventilation (MV) is a core therapy in the intensive care unit (ICU). Some patients rely on MV to support breathing. However, it is a difficult therapy to optimise, where inter- and intra- patient variability leads to significantly increased risk of lung damage. Excessive volume and/or pressure can cause volutrauma or barotrauma, resulting in increased length of time on ventilation, length of stay, cost and mortality. Virtual patient modelling has changed care in other areas of ICU medicine, enabling more personalized and optimal care, and have emerged for volume-controlled MV. This research extends this MV virtual patient model into the increasingly more commonly used pressure-controlled MV mode. The simulation methods are extended to use pressure, instead of both volume and flow, as the known input, increasing the output variables to be predicted (flow and its integral, volume). The model and methods are validated using data from N = 14 pressure-control ventilated patients during recruitment maneuvers, with n = 558 prediction tests over changes of PEEP ranging from 2 to 16 cmH₂O. Prediction errors for peak inspiratory volume for an increase of 16 cmH₂O were 80 [30 - 140] mL (15.9 [8.4 - 31.0]%), with RMS fitting errors of 0.05 [0.03 - 0.12] L. These results show very good prediction accuracy able to guide personalised MV care.

Ventilation in Trauma Patients: The First 24 h is Different!

INTRODUCTION

Ventilation of major trauma patients is often needed in both the acute (emergency department and early ICU phase) and subsequent phases of trauma care for those who need ICU admission. What is unclear is whether ICU ventilation strategies should be directly extrapolated to the acute phase of treatment.

METHODS

This paper reviews the ARDS.net study, highlights recent developments in ventilation strategies, and provides practical ventilation guidance to the trauma surgeon for acute phase (in the ED or ICU) and the subsequent phase of ICU care.

RESULTS

The acute phase of care in the ED and the ICU is different from the subsequent phases of ICU care as the lung is more recruitable and there are other aspects of resuscitation from metabolic acidosis and traumatic brain injury, which require a different ventilation strategy to the traditional ARDS.net approach.

DISCUSSION AND CONCLUSION

The acute phase is different from the subsequent phase of care and there appears to be some inappropriate extrapolation of ICU practice to the acute phase. Application of the proposed ventilation strategies should ensure an optimal outcome. It is important to treat patients as individuals during assessment and treatment.

Comparison of volume control and pressure control ventilation in patients undergoing single level anterior cervical discectomy and fusion surgery

Background and Aims:

Pressure control and volume control ventilation are the most preferred modes of ventilator techniques available in the intraoperative period. The study compared the intraoperative ventilator and blood gas variables of volume-controlled ventilation (VCV) and pressure-controlled ventilation (PCV) in patients undergoing single level anterior cervical discectomy and fusion (ACDF).

Methods:

After obtaining Institutional Ethical Committee approval and informed consent, sixty patients scheduled for single level ACDF surgery performed in supine position under general anaesthesia were included. Group V (30 patients) received VCV and Group P (30 patients) received PCV. The primary objective was oxygenation variable PaO₂/FiO₂ at different points of time i.e. T1–20 min after the institution of the ventilation, T2–20 min after placement of the retractors and T3–20 min after removal of the retractors. The secondary objectives include other arterial blood gas parameters, respiratory and haemodynamic parameters. NCSS version 9 statistical software was used for statistics. Two-way repeated measures for analysis of variance with post hoc Tukey Kramer test was used to analyse continuous variables for both intra- and inter-group comparisons, paired sample t-test for overall comparison and Chi-square test for categorical data.

Results:

The primary variable PaO₂/FiO₂ was comparable in both groups (P = 0.08). The respiratory variables, PAP and C_dynam were statistically significant in PCV group compared to VCV (P < 0.05), though clinically insignificant. Other secondary variables were comparable. (P > 0.05)

Conclusion:

Clinically, both PCV and VCV group appear to be-equally suited ventilator techniques for anterior cervical spine surgery patients.

Comparison of respiratory and hemodynamic stability in patients with traumatic brain injury ventilated by two ventilator modes: Pressure regulated volume control versus synchronized intermittent mechanical ventilation

Background:

This study aimed to compare pressure regulated volume control (PRVC) and synchronized intermittent mechanical ventilation (SIMV) modes of ventilation according to respiratory and hemodynamic stability in patients with traumatic brain injury (TBI) admitted to Intensive Care Unit (ICU).

Materials and Methods:

In a randomized, single-blinded, clinical trial study, 100 patients who hospitalized in ICU due to TBI were selected and randomly divided into two groups. The first and second groups were ventilated by PRVC and SIMV modes, respectively. During mechanical ventilation, arterial blood gas and respiratory and hemodynamic parameters were also recorded and compared between the two groups.

Results:

According to the t-test, the mean rapid shallow breathing index (RSBI) after the first 8 h of mechanical ventilation was significantly higher in SIMV group compared with PRVC group (107.6 ± 2.75 vs. 102.2 ± 5.2, respectively, P < 0.0001). Further, according to ANOVA with repeated measures, the trend of RSBI changes had a significant difference between the two groups (P < 0.001). The trend of ratio of partial pressure arterial oxygen and fraction of inspired oxygen was different between the two groups according to Mann–Whitney–Wilcoxon test (P < 0.001).

Conclusions:

Using PRVC mode might be more desirable than using SIMV mode in patients with TBI due to better stability of ventilation and oxygenating. To ensure for more advantages of PRVC mode, further studies with longer follow-up and more detailed measurements are recommended.

Effect of Mechanical Ventilation Mode Type on Intra- and Postoperative Blood Loss in Patients Undergoing Posterior Lumbar Interbody Fusion Surgery

Background

The aim of study was to evaluate the effect of mechanical ventilation mode type, pressure-controlled ventilation (PCV), or volume-controlled ventilation (VCV) on intra- and postoperative surgical bleeding in patients undergoing posterior lumbar interbody fusion (PLIF) surgery.

Methods

This was a prospective, randomized, single-blinded, and parallel study that included 56 patients undergoing PLIF and who were mechanically ventilated using PCV or VCV. A permuted block randomization was used with a computer-generated list. The hemodynamic and respiratory parameters were measured after anesthesia induction in supine position, 5 min after patients were changed from supine to prone position, at the time of skin closure, and 5 min after the patients were changed from prone to supine position. The amount of intraoperative surgical bleeding, fluid administration, urine output, and transfusion requirement were measured at the end of surgery. The amount of postoperative bleeding and transfusion requirement were recorded every 24 h for 72 h.

Results

The primary outcome was the amount of intraoperative surgical bleeding, and 56 patients were analyzed. The amount of intraoperative surgical bleeding was significantly less in the PCV group than that in the VCV group (median, 253.0 [interquartile range, 179.0 to 316.5] ml in PCV group vs. 382.5 [328.0 to 489.5] ml in VCV group; P &lt; 0.001). Comparing other parameters between groups, only peak inspiratory pressure at each measurement point in PCV group was significantly lower than that in VCV group. No harmful events were recorded.

Conclusion

Intraoperative PCV decreased intraoperative surgical bleeding in patients undergoing PLIF, which may be related to lower intraoperative peak inspiratory pressure.

Comparison of respiratory mechanics measurements in the volume cycled ventilation (VCV) and pressure controlled ventilation (PCV)

Abstract Introduction Monitoring respiratory mechanics may provide important information for the intensivist, assisting in the early detection of pulmonary function changes of patients hospitalized in ICU. Objective: To compare measurements of respiratory mechanics in VCV and PCV modes, and correlate them with age and oxygenation index. Materials and methods: Cross-sectional study conducted in the adult ICU of the Hospital Nossa Senhora da Conceição, in Tubarão - SC. A hundred and twenty individuals were selected between March and August 2013. The respiratory mechanics measurements were evaluated using compliance and resistance static measures of the respiratory system in PCV and VCV modes between the 1st and 5th day of hospitalization. Simultaneously, the oxygenation index PaO2/FiO2 was collected. Results: The obtained results were: compliance (VCV) = 40.9 ± 12.8 mL/cmH2O, compliance (PCV) = 35.0 ± 10.0 mL/cmH2O, resistance (VCV) = 13.2 ± 4.9 cmH2O/L/s, resistance (PCV) = 27.3 ± 16.2 cmH2O/L/s and PaO2/FiO2 = 236.0 ± 97.6 mmHg. There was statistical difference (p < 0.001) between the compliance and resistance measures in VCV and PCV modes. The correlations between the oxygenation index and compliance in VCV and PCV modes and resistance in VCV and PCV modes were, respectively, r = 0.381 (p < 0.001), r = 0.398 (p < 0.001), r = -0.188 (p = 0.040), r = -0.343 (p < 0.001). Conclusion: Despite the differences between the respiratory mechanics measurements the monitoring using VCV and PCV modes seems to show complementary aspects.

Comparison of intraoperative volume and pressure-controlled ventilation modes in patients who undergo open heart surgery

Respiratory problems occur more frequently in patients who undergo open heart surgery. Intraoperative and postoperative ventilation strategies can prevent these complications and reduce mortality. We hypothesized that PCV would have better effects on gas exchange, lung mechanics and hemodynamics compared to VCV in CABG surgery. Our primary outcome was to compare the PaO₂/FiO₂ ratio. Patients were randomized into two groups, (VCV, PCV) consisting of 30 individuals each. Two patients were excluded from the study. I/E ratio was adjusted to 1:2 and, RR:10/min fresh air gas flow was set at 3L/min in all patients. In the VCV group TV was set at 8 mL/kg of the predicted body weight. In the PCV group, peak inspiratory pressure was adjusted to the same tidal volume with the VCV group. PaO2/FiO2 was found to be higher with PCV at the end of the surgery. Time to extubation and ICU length of stay was shorter with PCV. Ppeak was similar in both groups. Pplateau was lower and Pmean was higher at the and of the surgery with PCV compared to VCV. The hemodynamic effects of both ventilation modes were found to be similar. PVC may be preferable to VCV in patients who undergo open heart surgery. However, it would be convenient if our findings are supported by similar studies.

Pressure-Controlled vs Volume-Controlled Ventilation in Acute Respiratory Failure: A Physiology-Based Narrative and Systematic Review

BACKGROUND

Mechanical ventilation is a cornerstone in the management of acute respiratory failure. Both volume-targeted and pressure-targeted ventilations are used, the latter modes being increasingly used. We provide a narrative review of the physiologic principles of these two types of breath delivery, performed a literature search, and analyzed published comparisons between modes.

METHODS

We performed a systematic review and meta-analysis to determine whether pressure control-continuous mandatory ventilation (PC-CMV) or pressure control-inverse ratio ventilation (PC-IRV) has demonstrated advantages over volume control-continuous mandatory ventilation (VC-CMV). The Cochrane tool for risk of bias was used for methodologic quality. We also introduced physiologic criteria as quality indicators for selecting the studies. Outcomes included compliance, gas exchange, hemodynamics, work of breathing, and clinical outcomes. Analyses were completed with RevMan5 using random effects models.

RESULTS

Thirty-four studies met inclusion criteria, many being at high risk of bias. Comparisons of PC-CMV/PC-IRV and VC-CMV did not show any difference for compliance or gas exchange, even when looking at PC-IRV. Calculating the oxygenation index suggested a poorer effect for PC-IRV. There was no difference between modes in terms of hemodynamics, work of breathing, or clinical outcomes.

CONCLUSIONS

The two modes have different working principles but clinical available data do not suggest any difference in the outcomes. We included all identified trials, enhancing generalizability, and attempted to include only sufficient quality physiologic studies. However, included trials were small and varied considerably in quality. These data should help to open the choice of ventilation of patients with acute respiratory failure.

Pressure dynamic characteristics of pressure controlled ventilation system of a lung simulator

Mechanical ventilation is an important life support treatment of critically ill patients, and air pressure dynamics of human lung affect ventilation treatment effects. In this paper, in order to obtain the influences of seven key parameters of mechanical ventilation system on the pressure dynamics of human lung, firstly, mechanical ventilation system was considered as a pure pneumatic system, and then its mathematical model was set up. Furthermore, to verify the mathematical model, a prototype mechanical ventilation system of a lung simulator was proposed for experimental study. Last, simulation and experimental studies on the air flow dynamic of the mechanical ventilation system were done, and then the pressure dynamic characteristics of the mechanical system were obtained. The study can be referred to in the pulmonary diagnostics, treatment, and design of various medical devices or diagnostic systems.

Pressure and volume controlled mechanical ventilation in anaesthetized pregnant sheep

Optimal mechanical ventilation of the pregnant ewe during anaesthesia is of vital importance for maintaining fetal viability. This study aimed to compare peak inspiratory pressure (PIP), oxygenation and cardiovascular parameters with pressure-control (PCV) or volume-control (VCV) mechanical ventilation of anaesthetized pregnant sheep. Twenty ewes at 110 days gestation underwent general anaesthesia in dorsal recumbency for fetal surgery in a research setting. All the sheep were mechanically ventilated; one group with PCV ( n = 10) and another with VCV ( n = 10) to maintain normocapnia. PIP, direct arterial blood pressure, heart rate, arterial pH and arterial oxygen tension were recorded. PIP was lower in the PCV group ( P < 0.001). Arterial oxygen tension was higher in the PCV group ( P = 0.013). Mean and diastolic pressures were lower in the PCV group ( P = 0.029 and P = 0.047, respectively). Both VCV and PCV provide adequate oxygenation of pregnant sheep anaesthetized in dorsal recumbency, though PCV may provide superior oxygenation at a lower PIP.