Pendelluft in hypoxemic patients resuming spontaneous breathing: proportional modes versus pressure support ventilation.

BACKGROUND: Internal redistribution of gas, referred to as pendelluft, is a new potential mechanism of effort-dependent lung injury. Neurally-adjusted ventilatory assist (NAVA) and proportional assist ventilation (PAV +) follow the patient's respiratory effort and improve synchrony compared with pressure support ventilation (PSV). Whether these modes could prevent the development of pendelluft compared with PSV is unknown. We aimed to compare pendelluft magnitude during PAV + and NAVA versus PSV in patients with resolving acute respiratory distress syndrome (ARDS). METHODS: Patients received either NAVA, PAV + , or PSV in a crossover trial for 20-min using comparable assistance levels after controlled ventilation (> 72 h). We assessed pendelluft (the percentage of lost volume from the non-dependent lung region displaced to the dependent region during inspiration), drive (as the delta esophageal swing of the first 100 ms [ΔPes 100 ms]) and inspiratory effort (as the esophageal pressure-time product per minute [PTPmin]). We performed repeated measures analysis with post-hoc tests and mixed-effects models. RESULTS: Twenty patients mechanically ventilated for 9 [5-14] days were monitored. Despite matching for a similar tidal volume, respiratory drive and inspiratory effort were slightly higher with NAVA and PAV + compared with PSV (ΔPes 100 ms of -2.8 [-3.8--1.9] cm H2O, -3.6 [-3.9--2.4] cm H2O and -2.1 [-2.5--1.1] cm H2O, respectively, p < 0.001 for both comparisons; PTPmin of 155 [118-209] cm H2O s/min, 197 [145-269] cm H2O s/min, and 134 [93-169] cm H2O s/min, respectively, p < 0.001 for both comparisons). Pendelluft magnitude was higher in NAVA (12 ± 7%) and PAV + (13 ± 7%) compared with PSV (8 ± 6%), p < 0.001. Pendelluft magnitude was strongly associated with respiratory drive (ß = -2.771, p-value < 0.001) and inspiratory effort (ß = 0.026, p < 0.001), independent of the ventilatory mode. A higher magnitude of pendelluft in proportional modes compared with PSV existed after adjusting for PTPmin (ß = 2.606, p = 0.010 for NAVA, and ß = 3.360, p = 0.004 for PAV +), and only for PAV + when adjusted for respiratory drive (ß = 2.643, p = 0.009 for PAV +). CONCLUSIONS: Pendelluft magnitude is associated with respiratory drive and inspiratory effort. Proportional modes do not prevent its occurrence in resolving ARDS compared with PSV.

Dynamic relative regional lung strain estimated by computed tomography and electrical impedance tomography in ARDS patients.

BACKGROUND: In the acute distress respiratory syndrome (ARDS), specific lung regions can be exposed to excessive strain due to heterogeneous disease, gravity-dependent lung collapse and injurious mechanical ventilation. Computed tomography (CT) is the gold standard for regional strain assessment. An alternative tool could be the electrical impedance tomography (EIT). We aimed to determine whether EIT-based methods can predict the dynamic relative regional strain (DRRS) between two levels of end-expiratory pressure (PEEP) in gravity-non-dependent and dependent lung regions. METHODS: Fourteen ARDS patients underwent CT and EIT acquisitions (at end-inspiratory and end-expiratory) at two levels of PEEP: a low-PEEP based on ARDS-net strategy and a high-PEEP titrated according to EIT. Three EIT-based methods for DRRS were compared to relative CT-based strain: (1) the change of the ratio between EIT ventilation and end-expiratory lung impedance in arbitrary units ([ΔZAU low-PEEP/EELIAU low-PEEP]/[ΔZAU high-PEEP/EELIAU high-PEEP]), (2) the change of ΔZ/EELI ratio calibrated to mL ([ΔZml low-PEEP/EELIml low-PEEP]/[ΔZml high-PEEP/EELIml high-PEEP]) using CT data, and (3) the relative change of ∆ZAU (∆ZAU low-PEEP/∆ZAU high-PEEP). We performed linear regressions analysis and calculated bias and limits of agreement to assess the performance of DRRS by EIT in comparison with CT. RESULTS: The DRRS assessed by (ΔZml low-PEEP/EELIml low-PEEP)/(ΔZml high-PEEP/EELIml high-PEEP) and ∆ZAU low-PEEP/∆ZAU high-PEEP showed good relationship and agreement with the CT method (R2 of 0.9050 and 0.8679, respectively, in non-dependent region; R2 of 0.8373 and 0.6588, respectively, in dependent region; biases ranging from - 0.11 to 0.51 and limits of agreement ranging from - 0.73 to 1.16 for both methods and lung regions). Conversely, DRRS based on EELIAU ([ΔZAU low-PEEP/EELIAU low-PEEP]/[ΔZAU high-PEEP/EELIAU high-PEEP]) exhibited a weak negative relationship and poor agreement with the CT method for both non-dependent and dependent regions (R2 ~ 0.3; bias of 3.11 and 2.08, and limits of agreement of - 2.13 to 8.34 and from - 1.49 to 5.64, respectively). CONCLUSION: Changes in DRRS during a PEEP trial in ARDS patients could be monitored using EIT, based on changes in ΔZmL/EELIml and ∆ZAU. The relative change ∆ZAU offers the advantage of not requiring CT data for calibration.

Inflammatory biomarkers and pendelluft magnitude in ards patients transitioning from controlled to partial support ventilation.

The transition from controlled to partial support ventilation is a challenge in acute respiratory distress syndrome (ARDS) patients due to the risks of patient-self-inflicted lung injury. The magnitude of tidal volume (VT) and intrapulmonary dyssynchrony (pendelluft) are suggested mechanisms of lung injury. We conducted a prospective, observational, physiological study in a tertiary academic intensive care unit. ARDS patients transitioning from controlled to partial support ventilation were included. On these, we evaluated the association between changes in inflammatory biomarkers and esophageal pressure swing (ΔPes), transpulmonary driving pressure (ΔPL), VT, and pendelluft. Pendelluft was defined as the percentage of the tidal volume that moves from the non-dependent to the dependent lung region during inspiration, and its frequency at different thresholds (- 15, - 20 and - 25%) was also registered. Blood concentrations of inflammatory biomarkers (IL-6, IL-8, TNF-α, ANGPT2, RAGE, IL-18, Caspase-1) were measured before (T0) and after 4-h (T4) of partial support ventilation. Pendelluft, ΔPes, ΔPL and VT were recorded. Nine out of twenty-four patients (37.5%) showed a pendelluft mean ≥ 10%. The mean values of ΔPes, ΔPL, and VT were - 8.4 [- 6.7; - 10.2] cmH2O, 15.2 [12.3-16.5] cmH2O and 8.1 [7.3-8.9] m/kg PBW, respectively. Significant associations were observed between the frequency of high-magnitude pendelluft and IL-8, IL-18, and Caspase-1 changes (T0/T4 ratio). These results suggest that the frequency of high magnitude pendelluft may be a potential determinant of inflammatory response related to inspiratory efforts in ARDS patients transitioning to partial support ventilation. Future studies are needed to confirm these results.

Clinical characteristics and in-hospital mortality of patients with COVID-19 in Chile: A prospective cohort study.

AIMS OF THIS STUDY: To describe the Latin American population affected by COVID-19, and to determine relevant risk factors for in-hospital mortality. METHODS: We prospectively registered relevant clinical, laboratory, and radiological data of adult patients with COVID-19, admitted within the first 100 days of the pandemic from a single teaching hospital in Santiago, Chile. The primary outcome was in-hospital mortality. Secondary outcomes included the need for respiratory support and pharmacological treatment, among others. We combined the chronic disease burden and the severity of illness at admission with predefined clinically relevant risk factors. Cox regression models were used to identify risk factors for in-hospital mortality. RESULTS: We enrolled 395 adult patients, their median age was 61 years; 62.8% of patients were male and 40.1% had a Modified Charlson Comorbidity Index (MCCI) ≥5. Their median Sequential Organ Failure Assessment (SOFA) score was 3; 34.9% used a high-flow nasal cannula and 17.5% required invasive mechanical ventilation. The in-hospital mortality rate was 14.7%. In the multivariate analysis, were significant risk factors for in-hospital mortality: MCCI ≥5 (HR 4.39, P < .001), PaO2 /FiO2 ratio ≤200 (HR 1.92, P = .037), and advanced chronic respiratory disease (HR 3.24, P = .001); pre-specified combinations of these risk factors in four categories was associated with the outcome in a graded manner. CONCLUSIONS AND CLINICAL IMPLICATIONS: The relationship between multiple prognostic factors has been scarcely reported in Latin American patients with COVID-19. By combining different clinically relevant risk factors, we can identify COVID-19 patients with high-, medium- and low-risk of in-hospital mortality.