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Background: Ventilation management may differ between COVID–19 ARDS (COVID–ARDS) patients and patients with pre–COVID ARDS (CLASSIC–ARDS); it is uncertain whether associations of ventilation management with outcomes for CLASSIC–ARDS also exist in COVID–ARDS. Methods: Individual patient data analysis of COVID–ARDS and CLASSIC–ARDS patients in six observational studies of ventilation, four in the COVID–19 pandemic and two pre–pandemic. Descriptive statistics were used to compare epidemiology and ventilation characteristics. The primary endpoint were key ventilation parameters; other outcomes included mortality and ventilator–free days and alive (VFD–60) at day 60. Results: This analysis included 6702 COVID–ARDS patients and 1415 CLASSIC–ARDS patients. COVID–ARDS patients received lower median VT (6.6 [6.0 to 7.4] vs 7.3 [6.4 to 8.5] ml/kg PBW; p < 0.001) and higher median PEEP (12.0 [10.0 to 14.0] vs 8.0 [6.0 to 10.0] cm H2O; p < 0.001), at lower median ΔP (13.0 [10.0 to 15.0] vs 16.0 [IQR 12.0 to 20.0] cm H2O; p < 0.001) and higher median Crs (33.5 [26.6 to 42.1] vs 28.1 [21.6 to 38.4] mL/cm H2O; p < 0.001). Following multivariable adjustment, higher ΔP had an independent association with higher 60–day mortality and less VFD–60 in both groups. Higher PEEP had an association with less VFD–60, but only in COVID–ARDS patients. Conclusions: Our findings show important differences in key ventilation parameters and associations thereof with outcomes between COVID–ARDS and CLASSIC–ARDS. Trial registration: Clinicaltrials.gov (identifier NCT05650957), December 14, 2022. [ABSTRACT FROM AUTHOR]

Objective: To assess the effect of atelectasis during mechanical ventilation on the periatelectatic and normal lung regions in a model of atelectasis in rats with acute lung injury induced by lipopolysaccharide. Methods: Twenty-four rats were randomized into the following four groups, each with 6 animals: the Saline-Control Group, Lipopolysaccharide Control Group, Saline-Atelectasis Group, and Lipopolysaccharide Atelectasis Group. Acute lung injury was induced by intraperitoneal injection of lipopolysaccharide. After 24 hours, atelectasis was induced by bronchial blocking. The animals underwent mechanical ventilation for two hours with protective parameters, and respiratory mechanics were monitored during this period. Thereafter, histologic analyses of two regions of interest, periatelectatic areas and the normallyaerated lung contralateral to the atelectatic areas, were performed. Results: The lung injury score was significantly higher in the Lipopolysaccharide Control Group (0.41 ± 0.13) than in the Saline Control Group (0.15 ± 0.51), p < 0.05. Periatelectatic regions showed higher lung injury scores than normally-aerated regions in both the Saline-Atelectasis (0.44 ± 0.06 x 0.27 ± 0.74 p < 0.05) and Lipopolysaccharide Atelectasis (0.56 ± 0.09 x 0.35 ± 0.04 p < 0.05) Groups. The lung injury score in the periatelectatic regions was higher in the Lipopolysaccharide Atelectasis Group (0.56 ± 0.09) than in the periatelectatic region of the Saline-Atelectasis Group (0.44 ± 0.06), p < 0.05. Conclusion: Atelectasis may cause injury to the surrounding tissue after a period of mechanical ventilation with protective parameters. Its effect was more significant in previously injured lungs. [ABSTRACT FROM AUTHOR]

Objective: To identify factors that lead to a positive oxygenation response and predictive factors of mortality after prone positioning. Methods: This was a retrospective, multicenter, cohort study involving seven hospitals in Brazil. Inclusion criteria were being > 18 years of age wi th a suspected or confirmed diagnosis of COVID-19, being on invasive mechanical ventilation, having a PaO2/FIO2 ratio < 150 mmHg, and being submitted to prone positioning. After the first prone positioning session, a 20 mmHg improvement in the PaO2/FIO2 ratio was defined as a positive response. Results: The study involved 574 patients, 412 (72%) of whom responded positively to the first prone positioning session. Multiple logistic regression showed that responders had lower Simplified Acute Physiology Score III (SAPS III)/SOFA scores and lower D-dimer levels (p = 0.01; p = 0.04; and p = 0.04, respectively). It was suggested that initial SAPS III and initial PaO2/FIO2 were predictors of oxygenation response. The mortality rate was 69.3%. Increased risk of mortality was associated with age (OR = 1.04 [95 CI: 1.01-1.06]), time to first prone positioning session (OR = 1.18 [95 CI: 1.06-1.31]), number of sessions (OR = 1.31 [95% CI: 1.00-1.72]), proportion of pulmonary impairment (OR = 1.55 [95% CI: 1.02-2.35]), and immunosuppression (OR = 3.83 [95% CI: 1.35-10.86]). Conclusions: Our results show that most patients in our sample had a positive oxygenation response after the first prone positioning session. However, the mortality rate was high, probably due to the health status and the number of comorbidities of the patients, as well as the severity of their disease. Our results also suggest that SAPS III and the initial PaO2/FIO2 predict the oxygenation response; in addition, age, time to first prone positioning, number of sessions, pulmonary impairment, and immunosuppression can predict mortality. [ABSTRACT FROM AUTHOR]

Background: Coexistence of cancer and COVID-19 is associated with worse outcomes. However, the studies on cancer-related characteristics associated with worse COVID-19 outcomes have shown controversial results. The objective of the study was to evaluate cancer-related characteristics associated with invasive mechanical ventilation use or in-hospital mortality in patients with COVID-19 admitted to intensive care unit (ICU). Methods: We designed a cohort multicenter study including adults with active cancer admitted to ICU due to COVID-19. Seven cancer-related characteristics (cancer status, type of cancer, metastasis occurrence, recent chemotherapy, recent immunotherapy, lung tumor, and performance status) were introduced in a multilevel logistic regression model as first-level variables and hospital was introduced as second-level variable (random effect). Confounders were identified using directed acyclic graphs. Results: We included 274 patients. Required to undergo invasive mechanical ventilation were 176 patients (64.2%) and none of the cancer-related characteristics were associated with mechanical ventilation use. Approximately 155 patients died in hospital (56.6%) and poor performance status, measured with the Eastern Cooperative Oncology Group (ECOG) score was associated with increased in-hospital mortality, with odds ratio = 3.54 (1.60–7.88, 95% CI) for ECOG =2 and odds ratio = 3.40 (1.60–7.22, 95% CI) for ECOG = 3 to 4. Cancer status, cancer type, metastatic tumor, lung cancer, and recent chemotherapy or immunotherapy were not associated with in-hospital mortality. Conclusions: In patients with active cancer and COVID-19 admitted to ICU, poor performance status was associated with in-hospital mortality but not with mechanical ventilation use. Cancer status, cancer type, metastatic tumor, lung cancer, and recent chemotherapy or immunotherapy were not associated with invasive mechanical ventilation use or in-hospital mortality. [ABSTRACT FROM AUTHOR]

BACKGROUND: Noninvasive ventilation (NIV) reduces intubation and mortality in patients with COPD exacerbation who present with respiratory failure, and the type of mask may affect its success. Our objective was to compare the performance of 3 different NIV masks in a lung model. METHODS: We set the lung simulator mechanics and respiratory rate, and tested a small oronasal mask, a total face mask, and a large oronasal mask. We added CO2 at a constant rate into the system and monitored the end-tidal carbon dioxide. We used a mechanical ventilator to deliver NIV in 8 different combinations of inspiratory effort, pressure support, and expiratory positive airway pressure. We measured end-tidal carbon dioxide mask leakage, tidal volume, trigger time, time to achieve 90% of the inspiratory target during inspiration, and excess inspiratory time. RESULTS: We presented the mean ± SD of the 8 simulated conditions for each mask. The mean ± SD leakage was higher for the total face mask (51 ± 6 L/min) than for the small oronasal mask (37 ± 5 L/min) and for the large oronasal mask (21 ± 3 L/min), P < .001; but end-tidal carbon dioxide and tidal volume were similar. The mean ± SD 90% of the inspiratory target during inspiration was faster for the small oronasal mask (585 ± 49 ms) compared with the large oronasal (647 ± 107 ms) and total face mask (851 ± 105 ms), P < .001, all other variables were similar. CONCLUSIONS: In this model, we found that the type of mask had no impact on CO2 washout or on most synchrony variables. [ABSTRACT FROM AUTHOR]

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Background: Neurally Adjusted Ventilatory Assist (NAVA) is a proportional ventilatory mode that uses the electrical activity of the diaphragm (EAdi) to offer ventilatory assistance in proportion to patient effort. NAVA has been increasingly used for critically ill patients, but it has not been evaluated during spontaneous breathing trials (SBT). We designed a pilot trial to assess the feasibility of using NAVA during SBTs, and to compare the breathing pattern and patient-ventilator asynchrony of NAVA with Pressure Support (PSV) during SBTs.Methods: We conducted a crossover trial in the ICU of a university hospital in Brazil and included mechanically ventilated patients considered ready to undergo an SBT on the day of the study. Patients underwent two SBTs in randomized order: 30 min in PSV of 5 cmH2O or NAVA titrated to generate equivalent peak airway pressure (Paw), with a positive end-expiratory pressure of 5 cmH2O. The ICU team, blinded to ventilatory mode, evaluated whether patients passed each SBT. We captured flow, Paw and electrical activity of the diaphragm (EAdi) from the ventilator and used it to calculate respiratory rate (RR), tidal volume (VT), and EAdi. Detection of asynchrony events used waveform analysis and we calculated the asynchrony index as the number of asynchrony events divided by the number of neural cycles.Results: We included 20 patients in the study. All patients passed the SBT in PSV, and three failed the SBT in NAVA. Five patients were reintubated and the extubation failure rate was 25% (95% CI 9-49%). Respiratory parameters were similar in the two modes: VT = 6.1 (5.5-6.5) mL/Kg in NAVA vs. 5.5 (4.8-6.1) mL/Kg in PSV (p = 0.076) and RR = 27 (17-30) rpm in NAVA vs. 26 (20-30) rpm in PSV, p = 0.55. NAVA reduced AI, with a median of 11.5% (4.2-19.7) compared to 24.3% (6.3-34.3) in PSV (p = 0.033).Conclusions: NAVA reduces patient-ventilator asynchrony index and generates a respiratory pattern similar to PSV during SBTs. Patients considered ready for mechanical ventilation liberation may be submitted to an SBT in NAVA using the same objective criteria used for SBTs in PSV.Trial Registration: ClinicalTrials.gov ( NCT01337271 ), registered April 12, 2011. [ABSTRACT FROM AUTHOR]

Background: In patients with post-extubation respiratory distress, delayed reintubation may worsen clinical outcomes. Objective measures of extubation failure at the bedside are lacking, therefore clinical parameters are currently used to guide the need of reintubation. Electrical activity of the diaphragm (EAdi) provides clinicians with valuable, objective information about respiratory drive and could be used to monitor respiratory effort.Case Presentation: We describe the case of a patient with Chronic Obstructive Pulmonary Disease (COPD), from whom we recorded EAdi during four different ventilatory conditions: 1) invasive mechanical ventilation, 2) spontaneous breathing trial (SBT), 3) unassisted spontaneous breathing, and 4) Noninvasive Positive Pressure Ventilation (NPPV). The patient had been intubated due to an exacerbation of COPD, and after four days of mechanical ventilation, she passed the SBT and was extubated. Clinical signs of respiratory distress were present immediately after extubation, and EAdi increased compared to values obtained during mechanical ventilation. As we started NPPV, EAdi decreased substantially, indicating muscle unloading promoted by NPPV, and we used the EAdi signal to monitor respiratory effort during NPPV. Over the next three days, she was on NPPV for most of the time, with short periods of spontaneous breathing. EAdi remained considerably lower during NPPV than during spontaneous breathing, until the third day, when the difference was no longer clinically significant. She was then weaned from NPPV and discharged from the ICU a few days later.Conclusion: EAdi monitoring during NPPV provides an objective parameter of respiratory drive and respiratory muscle unloading and may be a useful tool to guide post-extubation ventilatory support. Clinical studies with continuous EAdi monitoring are necessary to clarify the meaning of its absolute values and changes over time. [ABSTRACT FROM AUTHOR]

BACKGROUND: Pressure support ventilation (PSV) is often associated with patient-ventilator asynchrony. Proportional assist ventilation (PAV) offers inspiratory assistance proportional to patient effort, minimizing patient-ventilator asynchrony. The objective of this study was to evaluate the influence of respiratory mechanics and patient effort on patient-ventilator asynchrony during PSV and PAV plus (PAV+). METHODS: We used a mechanical lung simulator and studied 3 respiratory mechanics profiles (normal, obstructive, and restrictive), with variations in the duration of inspiratory effort: 0.5, 1.0, 1.5, and 2.0 s. The Auto-Trak system was studied in ventilators when available. Outcome measures included inspiratory trigger delay, expiratory trigger asynchrony, and tidal volume (VT). RESULTS: Inspiratory trigger delay was greater in the obstructive respiratory mechanics profile and greatest with a effort of 2.0 s (160 ms); cycling asynchrony, particularly delayed cycling, was common in the obstructive profile, whereas the restrictive profile was associated with premature cycling. In comparison with PSV, PAV+ improved patient-ventilator synchrony, with a shorter triggering delay (28 ms vs 116 ms) and no cycling asynchrony in the restrictive profile. VT was lower with PAV+ than with PSV (630 mL vs 837 mL), as it was with the single-limb circuit ventilator (570 mL vs 837 mL). PAV+ mode was associated with longer cycling delays than were the other ventilation modes, especially for the obstructive profile and higher effort values. Auto-Trak eliminated automatic triggering. CONCLUSIONS: Mechanical ventilation asynchrony was influenced by effort, respiratory mechanics, ventilator type, and ventilation mode. In PSV mode, delayed cycling was associated with shorter effort in obstructive respiratory mechanics profiles, whereas premature cycling was more common with longer effort and a restrictive profile. PAV+ prevented premature cycling but not delayed cycling, especially in obstructive respiratory mechanics profiles, and it was associated with a lower VT. [ABSTRACT FROM AUTHOR]

Purpose: Automated weaning modes are available in some mechanical ventilators, but no studies compared them hitherto. We compared the performance of 3 automated modes under standard and challenging situations. Methods: We used a lung simulator to compare 3 automated modes, adaptive support ventilation (ASV), mandatory rate ventilation (MRV), and Smartcare, in 6 situations, weaning success, weaning failure, weaning success with extreme anxiety, weaning success with Cheyne-Stokes, weaning success with irregular breathing, and weaning failure with ineffective efforts. Results: The 3 modes correctly recognized the situations of weaning success and failure, even when anxiety or irregular breathing were present but incorrectly recognized weaning success with Cheyne- Stokes. MRV incorrectly recognized weaning failure with ineffective efforts. Time to pressure support (PS) stabilization was shorter for ASV (1-2 minutes for all situations) and MRV (1-7 minutes) than for Smartcare (8-78 minutes). ASV had higher rates of PS oscillations per 5 minutes (4-15), compared with Smartcare (0-1) and MRV (0-12), except when extreme anxiety was present. Conclusions: Smartcare, ASV, and MRV were equally able to recognize weaning success and failure, despite the presence of anxiety or irregular breathing but performed incorrectly in the presence of Cheyne-Stokes. PS behavior over the time differs among modes, with ASV showing larger and more frequent PS oscillations over the time. Clinical studies are needed to confirm our results. [ABSTRACT FROM AUTHOR]

Background: The decision to intubate COVID-19 patients receiving non-invasive respiratory support is challenging, requiring a fine balance between early intubation and risks of invasive mechanical ventilation versus the adverse effects of delaying intubation. This present study analyzes the association between intubation day and mortality in COVID-19 patients. Methods: We performed a unicentric retrospective cohort study considering all COVID-19 patients consecutively admitted between March 2020 and August 2020 requiring invasive mechanical ventilation. The primary outcome was all-cause mortality within 28 days after intubation, and a Cox model was used to evaluate the effect of time from onset of symptoms to intubation in mortality. Results: A total of 592 (20%) patients of 3020 admitted with COVID-19 were intubated during study period, and 310 patients who were intubated deceased 28 days after intubation. Each additional day between the onset of symptoms and intubation was significantly associated with higher in-hospital death (adjusted hazard ratio, 1.018; 95% CI, 1.005–1.03). Conclusion: Among patients infected with SARS-CoV-2 who were intubated and mechanically ventilated, delaying intubation in the course of symptoms may be associated with higher mortality. Trial registration: The study protocol was approved by the local Ethics Committee (opinion number 3.990.817; CAAE: 30417520.0.0000.0068). [ABSTRACT FROM AUTHOR]

To compare the triggering performance of mid-level ICU mechanical ventilators with a standard ICU mechanical ventilator. Experimental bench study. The respiratory care laboratory of a university-affiliated teaching hospital. A computerized mechanical lung model, the IngMar ASL5000. Ten mid-level ICU ventilators were compared to an ICU ventilator at two levels of lung model effort, three combinations of respiratory mechanics (normal, COPD and ARDS) and two modes of ventilation, volume and pressure assist/control. A total of 12 conditions were compared. Performance varied widely among ventilators. Mean inspiratory trigger time was <100 ms for only half of the tested ventilators. The mean inspiratory delay time (time from initiation of the breath to return of airway pressure to baseline) was longer than that for the ICU ventilator for all tested ventilators except one. The pressure drop during triggering (Ptrig) was comparable with that of the ICU ventilator for only two ventilators. Expiratory Settling Time (time for pressure to return to baseline) had the greatest variability among ventilators. Triggering differences among these mid-level ICU ventilators and with the ICU ventilator were identified. Some of these ventilators had a much poorer triggering response with high inspiratory effort than the ICU ventilator. These ventilators do not perform as well as ICU ventilators in patients with high ventilatory demand. [ABSTRACT FROM AUTHOR]

Objectives: To measure the impact of clusters of double triggering on clinical outcomes.Design: Prospective cohort study.Setting: Respiratory ICU in Brazil.Patients: Adult patients under recent mechanical ventilation and with expectation of mechanical ventilation for more than 24 hours after enrollment.Interventions: None.Measurements and Main Results: We used a dedicated software to analyze ventilator waveforms throughout the entire period of mechanical ventilation and detect double triggering. We defined a cluster of double triggering as a period of time containing at least six double triggering events in a 3-minute period. Patients were followed until hospital discharge. We addressed the association between the presence and the duration of clusters with clinical outcomes. A total of 103 patients were enrolled in the study and 90 (87%) had at least one cluster of double triggering. The median number of clusters per patient was 19 (interquartile range, 6-41), with a median duration of 8 minutes (6-12 min). Compared with patients who had no clusters, patients with at least one cluster had longer duration of mechanical ventilation (7 d [4-11 d] vs 2 d [2-3 d]) and ICU length of stay (9 d [7-16 d] vs 13 d [2-8 d]). Thirty-three patients had high cumulative duration of clusters of double triggering (≥ 12 hr), and it was associated with longer duration of mechanical ventilation, fewer ventilator-free days, and longer ICU length of stay. Adjusted by duration of mechanical ventilation and severity of illness, high cumulative duration of clusters was associated with shorter survival at 28 days (hazard ratio, 2.09 d; 95% CI, 1.04-4.19 d).Conclusions: Clusters of double triggering are common and were associated with worse clinical outcomes. Patients who had a high cumulative duration of clusters had fewer ventilator-free days, longer duration of mechanical ventilation, longer ICU length of stay, and shorter survival than patients with low cumulative duration of cluster. [ABSTRACT FROM AUTHOR]

Objectives: In 2012, a new acute respiratory distress syndrome definition was proposed for adult patients. It was later validated for infants and toddlers. Our objective was to evaluate the prevalence, outcomes, and risk factors associated with acute respiratory distress syndrome in children up to 15 years according to the Berlin definition. Design: A prospective, multicenter observational study from March to September 2013. Setting: Seventy-seven PICU beds in eight centers: two private hospitals and six public academic hospitals in Brazil. Patients: All children aged 1 month to 15 years admitted to the participating PICUs in the study period. Interventions: None. Measurements and Main Results: All children admitted to the PICUs were daily evaluated for the presence of acute respiratory distress syndrome according to the American-European Consensus Conference and Berlin definitions. Of the 562 patients included, acute respiratory distress syndrome developed in 57 patients (10%) and 58 patients (10.3%) according to the Berlin definition and the American-European Consensus Conference definition, respectively. Among patients with acute respiratory distress syndrome according to the Berlin definition, nine patients (16%) were mild, 21 (37%) were moderate, and 27 (47%) were severe. Compared with patients without acute respiratory distress syndrome, patients with acute respiratory distress syndrome had significantly higher severity scores, longer PICU and hospital length of stay, longer duration of mechanical ventilation, and higher mortality (p < 0.001). The presence of two or more comorbidities and admission for medical reasons were associated with development of acute respiratory distress syndrome. Comparisons across the three the Berlin categories showed significant differences in the number of ventilator-free days (21, 20, and 5 d, p = 0.001) and mortality for severe acute respiratory distress syndrome (41%) in comparison with mild (0) and moderate (15%) acute respiratory distress syndrome(p = 0.02). No differences in PICU or hospital stay were observed across the groups. Conclusions: The Berlin definition can identify a subgroup of patients with distinctly worse outcomes, as shown by the increased mortality and reduced number of ventilator-free days in pediatric patients with severe acute respiratory distress syndrome. [ABSTRACT FROM AUTHOR]