BACKGROUND: Mechanical power of ventilation, a summary parameter reflecting the energy transferred from the ventilator to the respiratory system, has associations with outcomes. INTELLiVENT-Adaptive Support Ventilation is an automated ventilation mode that changes ventilator settings according to algorithms that target a low work-and force of breathing. The study aims to compare mechanical power between automated ventilation by means of INTELLiVENT-Adaptive Support Ventilation and conventional ventilation in critically ill patients.
METHODS: International, multicenter, randomized crossover clinical trial in patients that were expected to need invasive ventilation > 24 hours. Patients were randomly assigned to start with a 3-hour period of automated ventilation or conventional ventilation after which the alternate ventilation mode was selected. The primary outcome was mechanical power in passive and active patients; secondary outcomes included key ventilator settings and ventilatory parameters that affect mechanical power.
RESULTS: A total of 96 patients were randomized. Median mechanical power was not different between automated and conventional ventilation (15.8 [11.5-21.0] versus 16.1 [10.9-22.6] J/min; mean difference -0.44 (95%-CI -1.17 to 0.29) J/min; P = 0.24). Subgroup analyses showed that mechanical power was lower with automated ventilation in passive patients, 16.9 [12.5-22.1] versus 19.0 [14.1-25.0] J/min; mean difference -1.76 (95%-CI -2.47 to -10.34J/min; P < 0.01), and not in active patients (14.6 [11.0-20.3] vs 14.1 [10.1-21.3] J/min; mean difference 0.81 (95%-CI -2.13 to 0.49) J/min; P = 0.23).
CONCLUSIONS: In this cohort of unselected critically ill invasively ventilated patients, automated ventilation by means of INTELLiVENT-Adaptive Support Ventilation did not reduce mechanical power. A reduction in mechanical power was only seen in passive patients.
BACKGROUND: Clinicaltrials.gov (study identifier NCT04827927), April 1, 2021.
UNASSIGNED: https://clinicaltrials.gov/study/NCT04827927?term=intellipower&rank=1.

BACKGROUND: Tracheostomy-related acquired pressure injuries (TRPIs) are one of the hospital-acquired conditions. We hypothesize that an uneven ventilator circuit load, leading to non-neutral tracheostomy tube positioning in the immediate post-tracheostomy period, leads to an increased incidence of TRPIs. Does switching the ventilator circuit load daily, in addition to standard post-tracheostomy care, lead to a decreased incidence of TRPIs?
METHODS: This is a prospective quality improvement study. Study was conducted at two academic hospital sites within tertiary care hospitals at Emory University in different ICUs. Consecutive patients undergoing bedside percutaneous tracheostomy by the interventional pulmonary service were included. The flip the ventilator circuit (FLIC) protocol was designed and implemented in selected ICUs, with other ICUs as controls.
RESULTS: Incidence of TRPI in intervention and control group were recorded at post-tracheostomy day 5. A total of 99 patients were included from October 22, 2019, to May 22, 2020. Overall, the total incidence of any TRPI was 23% at post-tracheostomy day 5. Incidence of stage I, stage II, and stages III-IV TRPIs at postoperative day 5 was 11%, 12%, and 0%, respectively. There was a decrease in the rate of skin breakdown in patients following the FLIC protocol when compared with standard of care (13% vs. 36%; p = 0.01). In a multivariable analysis, interventional group had decreased odds of developing TRPI (odds ratio, 0.32; 95% CI, 0.11-0.92; p = 0.03) after adjusting for age, albumin, body mass index, diabetes mellitus, and days in hospital before tracheostomy.
CONCLUSIONS: The incidence of TRPIs within the first week following percutaneous tracheostomy is high. Switching the side of the ventilator circuit to evenly distribute load, in addition to standard bundled tracheostomy care, may decrease the overall incidence of TRPIs.

OBJECTIVE: We analysed the relationship between oscillatory volume (VOSC) and pressure amplitude (ΔP) in six neonatal high-frequency oscillatory (HFO) ventilators and related it to (1) the accuracy of VOSC and ΔP measurements and (2) the maximal delivered ΔP.
METHODS: In vitro study.
METHODS: Neonatal intensive care unit.
METHODS: Ventilators tested were VN800 (Dräger), Servo-n (Maquet Getinge), SensorMedics 3100A (Vyaire Medical), Fabian HFOi (Vyaire Medical), SLE6000 (SLE UK) and Humming Vue (Metran). We changed various settings and mechanical characteristics of the test lung to mimic preterm and term conditions.
METHODS: For each condition, we measured VOSC and ΔP. We assessed the accuracy of the VOSC and ΔP measurements versus a reference measurement system using linear regression and Bland-Altman analysis. We evaluated the maximum delivered ΔP at different oscillatory frequencies.
RESULTS: We observed large variability between machines in the ΔP displayed at any target VOSC. Most ventilators over-read ΔP with errors up to 30 cmH2O or 60%. The error in the measurement of VOSC was up to ±2 mL or ±30%. We observed high variability in the accuracy of ΔP and VOSC measurements; the SLE6000 committed the lowest errors in ΔP measurements and the Fabian HFOi in VOSC. The maximum delivered ΔP varied depending on the ventilator, being maximal for the Humming Vue, followed by the SLE6000 and SensorMedics 3100A.
CONCLUSIONS: The variability in the relationship between VOSC and ΔP among HFO ventilators is largely explained by the variable accuracy in ΔP and VOSC measurement. Different ventilators also exhibit important differences in the maximal generated ΔP.

OBJECTIVE: To explore a simple method for measuring the dynamic intrinsic positive end-expiratory pressure (PEEPi) during invasive mechanical ventilation.
METHODS: A 60-year-old male patient was admitted to the critical care medicine department of Dongying People\'s Hospital in September 2020. He underwent invasive mechanical ventilation treatment for respiratory failure due to head and chest trauma, and incomplete expiratory flow occurred during the treatment. The expiratory flow-time curve of this patient was served as the research object. The expiratory flow-time curve of the patient was observed, the start time of exhalation was taken as T0, the time before the initiation of inspiratory action (inspiratory force) was taken as T1, and the time when expiratory flow was reduced to zero by inspiratory drive (inspiratory force continued) was taken as T2. Taking T1 as the starting point, the follow-up tracing line was drawn according to the evolution trending of the natural expiratory curve before the T1 point, until the expiratory flow reached to 0, which was called T3 point. According to the time phase, the intrapulmonary pressure at the time just from expiratory to inspiratory (T1 point) was called PEEPi1. When the expiratory flow was reduced to 0 (T2 point), the intrapulmonary pressure with the inhaling power being removed hypothetically was called PEEPi2. And it was equal to positive end-expiratory pressure (PEEP) set in the ventilator at T3 point. The area under the expiratory flow-time curve (expiratory volume) between T0 and T1 was called S1. And it was S2 between T0 and T2, S3 between T0 and T3. After sedation, in the volume controlled ventilation mode, approximately one-third of the tidal volume was selected, and the static compliance of patient\'s respiratory system called \"C\" was measured using the inspiratory pause method. PEEPi1 and PEEP2 were calculated according to the formula \"C = ΔV/ΔP\". Here, ΔV was the change in alveolar volume during a certain period of time, and ΔP represented the change in intrapulmonary pressure during the same time period. This estimation method had obtained a National Invention Patent of China (ZL 2020 1 0391736.1).
RESULTS: (1) PEEPi1: according to the formula \"C = ΔV/ΔP\", the expiratory volume span from T1 to T3 was \"S3-S1\", and the intrapulmonary pressure decreased span was \"PEEPi1-PEEP\". So, C = (S3-S1)/(PEEPi1-PEEP), PEEPi1 = PEEP+(S3-S1)/C. (2)PEEPi2: the expiratory volume span from T2 to T3 was \"S3-S2\", and the intrapulmonary pressure decreased span was \"PEEPi2-PEEP\". So, C = (S3-S2)/(PEEPi2-PEEP), PEEPi2 = PEEP+(S3-S2)/C.
CONCLUSIONS: For patients with incomplete expiratory during invasive mechanical ventilation, the expiratory flow-time curve extension method can theoretically be used to estimate the dynamic PEEPi in real time.

OBJECTIVE: The prognosis of patients with idiopathic pulmonary fibrosis (IPF) and respiratory failure requiring mechanical ventilation is poor. Therefore, mechanical ventilation is not recommended. Recently, outcomes of mechanical ventilation, including those for patients with IPF, have improved. The aim of this study was to investigate changes in the use of mechanical ventilation in patients with IPF and their outcomes over time.
METHODS: This retrospective, observational cohort study used data from the National Health Insurance Service database. Patients diagnosed with IPF between January 2011 and December 2019 who were placed on mechanical ventilation were included. We analyzed changes in the use of mechanical ventilation in patients with IPF and their mortality using the Cochran- Armitage trend test.
RESULTS: Between 2011 and 2019, 1,227 patients with IPF were placed on mechanical ventilation. The annual number of patients with IPF with and without mechanical ventilation increased over time. However, the ratio was relatively stable at approximately 3.5%. The overall hospital mortality rate was 69.4%. There was no improvement in annual hospital mortality rate. The overall 30-day mortality rate was 68.7%, which did not change significantly. The overall 90-day mortality rate was 85.3%. The annual 90-day mortality rate was decreased from 90.9% in 2011 to 83.1% in 2019 (p = 0.028).
CONCLUSIONS: Despite improvements in intensive care and ventilator management, the prognosis of patients with IPF receiving mechanical ventilation has not improved significantly.

BACKGROUND: Tidal volume (Vt) delivery during mechanical ventilation is influenced by gas compression, humidity, and temperature.
OBJECTIVE: This bench study aimed at assessing the accuracy of Vt delivery by paediatric intensive care ventilators according to the humidification system. Secondary objectives were to assess the following: (i) the accuracy of Vt delivery in ventilators with an integrated Y-piece pneumotachograph and (ii) the ability of ventilators to deliver and maintain a preset positive end-expiratory pressure.
METHODS: Six latest-generation intensive care ventilators equipped with a paediatric mode were tested on the ASL5000 test lung in four simulated paediatric bench models (full-term neonate, infant, preschool-age chile, and school-age child), under volume-controlled mode with a heated humidifier (HH) or a heat moisture exchanger, with various loading conditions. Three ventilators equipped with a Y-piece pneumotachograph were tested with or without the pneumotachograph in the neonatal and infant models. \"Accurate Vt\" delivery was defined as a volume error (percentage of the preset Vt under body temperature and pressure and saturated water vapour conditions) being ≤10 % of the absolute preset value.
RESULTS: Vt accuracy varied significantly across ventilators but was acceptable in almost all the ventilators and all the models, except the neonatal model. The humidification system had an impact on Vt delivery in the majority of the tested conditions (p < 0.05). The use of an HH was associated with a better Vt accuracy in four ventilators (V500, V800, R860, and ServoU) and allowed to achieve an acceptable level of volume error in the neonatal model as compared to the use of heat moisture exchanger. The use of an integrated pneumotachograph was associated with lower volume error in only one ventilator (p < 0.01). All the tested ventilators were able to maintain adequate positive end-expiratory pressure levels.
CONCLUSIONS: The humidification system affects Vt accuracy of paediatric intensive care ventilators, especially in the youngest patients for whom the HH should be preferred.

During low-flow oxygen therapy, the true value of inspired oxygen fraction (FiO2) is generally unknown. Knowledge of delivered FiO2 values may be useful as well as to adjust oxygen therapy, as well as to predict patient deterioration. This study proposes a New FiO2 Prediction Formula (NFiO2) for low-flow oxygenation and compares its predictive value to precedent formulas. In a bench study, the O2 Flow rate was delivered through a T-piece connected to a dual-compartment artificial lung controlled by a mechanical ventilator. To test the NFiO2 formula, a set of ventilatory parameters were tested: Tidal Volume was set from 400 to 600 ml, Respiratory Rate (RR) was set from 18 to 30 CPM, Ti/Ttot was set at 0.33 and 0.25, and O2 flow rates from 3 to 10 L/min. A data acquisition system measured all parameters. To quantify the accuracy of the NFiO2 compared to other FiO2 prediction formulas, Bland and Altman agreement analyses were performed. To make use of the Duprez Formula 2018 in clinical practice, we simplified the formula to estimate the FiO2 during oxygenation at low flow. This NFiO2 formula makes use of only O2 Flow Rate and RR. Bias and limits of agreement between predicted FiO2 and benchtop FiO2 highlighted consistent differences between different FiO2 prediction formulas. The NFiO2 and the Duprez Formula 2018 seemed to be the most accurate formulas, followed by the Vincent Formula, and lastly the Shapiro Formula. A New FiO2 Prediction Formula was developed using clinical readily available variables (RR and O2 Flow rate) which showed good accuracy in predicting FiO2 during oxygenation at low flow.

BACKGROUND: The high resistance of pediatric endotracheal tubes (ETTs) exposes mechanically ventilated children to a particular risk of developing intrinsic positive end-expiratory pressure (iPEEP). To date, determining iPEEP at the bedside requires the execution of special maneuvers, interruption of ventilation, or additional invasive measurements. Outside such interventions, iPEEP may be unrecognized.
OBJECTIVE: To develop a new approach for continuous calculation of iPEEP based on routinely measured end-expiratory flow and ETT resistance.
METHODS: First, the resistance of pediatric ETTs with inner diameter from 2.0 to 4.5 mm were empirically determined. Second, during simulated ventilation, iPEEP was either calculated from the measured end-expiratory flow and ETT\'s resistance (iPEEPcalc ) or determined with a hold-maneuver available at the ventilator (iPEEPhold ). Both estimates were compared with the end-expiratory pressure measured at the ETT\'s tip (iPEEPdirect ) by means of absolute deviations.
RESULTS: End-expiratory flow and iPEEP increased with decreasing ETT inner diameter and with higher respiratory rates. iPEEPcalc and iPEEPhold were comparable and indicated good correspondence with iPEEPdirect . The largest absolute mean deviation was 1.0 cm H2 O for iPEEPcalc and 1.1 cm H2 O for iPEEPhold .
CONCLUSIONS: We conclude that iPEEP can be determined from routinely measured variables and predetermined ETT resistance, which has to be confirmed in the clinical settings. As long as this algorithm is not available in pediatric ICU ventilators, nomograms are provided for estimating the prevailing iPEEP from end-expiratory flow.

Emergency mechanical ventilators developed during the pandemic were used to meet the high demand in intensive care units to care for COVID-19 patients. An example of such ventilators is Masi, developed in Peru and installed in more than 15 hospitals around the country. This study aimed to compare Masi\'s performance with other emergency mechanical ventilators manufactured during the covid-19 pandemic such as Neyün, Spiro Wave and a prototype developed by the Faculty of Engineering of the National University of Asuncion (FIUNA). Three configurations of a test lung were used, combining different values of resistance and compliance (C1, C2 and C3). Ventilators were set to volume-controlled ventilation with tidal volume = 400 mL, respiratory rate = 12 breaths/minute, and positive end-expiratory pressure (PEEP) = 8 cm H2O. These parameters were measured in a series of ten two-minute tests which then were evaluated through a two-way analysis of variance, considering the type of ventilator and test lung configuration as the two independent variables. For target values, MASI delivered VT that ranged from 319 to 432 ml (-20 to +8%), respiratory rate of 12 bpm, and PEEP from 8.4 to 9.5 cm H2O (+5 to +20%). In contrast, for instance, Neyün delivered VT that ranged from 199 to 543 ml (-50 to +35%) and PEEP from 7.05 to 9.21 cm H2O (--11 to +15%), with p<0.05. The analysis of variance showed that he differences between preset and delivered parameters were influenced by the type of ventilator and, significantly, by the test lung configuration.Clinical Relevance- This establishes the most advantageous conditions in which three emergency mechanical ventilators work and a quantitative perspective in this topic.

Certain criteria for ventilator-associated events (VAE) definition might influence the type of an event, its detection rate and consequently the resource expenditure in intensive care unit. The Impact of Infections by Antimicrobial-Resistant Microorganisms - Ventilator-Associated Pneumonia (IMPACTO MR-PAV) aims to evaluate the incidence and diagnostic accuracy of ventilator-associated pneumonia (VAP) using the current criteria for VAP surveillance in Brazil versus the VAE criteria defined by the US National Healthcare Safety Network-Center for Diseases Control and Prevention (CDC) criteria.
The study will be conducted in around 15 centres across Brazil from October 2022 to December 2023. Trained healthcare professionals will collect data and compare the incidence of VAP using both the current criteria for VAP surveillance in Brazil and the VAE criteria defined by the CDC. The accuracy of the two criteria for identifying VAP will also be analysed. It will also characterise other events associated with mechanical ventilation (ventilator-associated condition, infection-related ventilator-associated complication) and adjudicate VAP reported to the Brazilian Health Regulatory Agency (ANVISA) using current epidemiological diagnostic criteria.
This study was approved by the Institutional Review Board under the number 52354721.0.1001.0070. The study\'s primary outcome measure will be the incidence of VAP using the two different surveillance criteria, and the secondary outcome measures will be the accuracy of the two criteria for identifying VAP and the adjudication of VAP reported to ANVISA. The results will contribute to the improvement of VAP surveillance in Brazil and may have implications for other countries that use similar criteria.
NCT05589727; Clinicaltrials.gov.