Cerebral Gaseous Microemboli are Detectable During Continuous Venovenous Hemodialysis in Critically Ill Patients: An Observational Pilot Study

BACKGROUND Continuous venovenous hemodialysis (CVVHD) may generate microemboli that cross the pulmonary circulation and reach the brain. The aim of the present study was to quantify (load per time interval) and qualify (gaseous vs. solid) cerebral microemboli (CME), detected as high-intensity transient signals, using transcranial Doppler ultrasound. MATERIALS AND METHODS Twenty intensive care unit (ICU group) patients requiring CVVHD were examined. CME were recorded in both middle cerebral arteries for 30 minutes during CVVHD and a CVVHD-free interval. Twenty additional patients, hospitalized for orthopedic surgery, served as a non-ICU control group. Statistical analyses were performed using the Mann-Whitney U test or the Wilcoxon matched-pairs signed-rank test, followed by Bonferroni corrections for multiple comparisons. RESULTS In the non-ICU group, 48 (14.5-169.5) (median [range]) gaseous CME were detected. In the ICU group, the 67.5 (14.5-588.5) gaseous CME detected during the CVVHD-free interval increased 5-fold to 344.5 (59-1019) during CVVHD (P<0.001). The number of solid CME was low in all groups (non-ICU group: 2 [0-5.5]; ICU group CVVHD-free interval: 1.5 [0-14.25]; ICU group during CVVHD: 7 [3-27.75]). CONCLUSIONS This observational pilot study shows that CVVHD was associated with a higher gaseous but not solid CME burden in critically ill patients. Although the differentiation between gaseous and solid CME remains challenging, our finding may support the hypothesis of microbubble generation in the CVVHD circuit and its transpulmonary translocation toward the intracranial circulation. Importantly, the impact of gaseous and solid CME generated during CVVHD on brain integrity of critically ill patients currently remains unknown and is highly debated

Detection of inspiratory recruitment of atelectasis by automated lung sound analysis as compared to four-dimensional computed tomography in a porcine lung injury model

Background: Cyclic recruitment and de-recruitment of atelectasis (c-R/D) is a contributor to ventilator-induced lung injury (VILI). Bedside detection of this dynamic process could improve ventilator management. This study investigated the potential of automated lung sound analysis to detect c-R/D as compared to four-dimensional computed tomography (4DCT). Methods: In ten piglets (25 ± 2 kg), acoustic measurements from 34 thoracic piezoelectric sensors (Meditron ASA, Norway) were performed, time synchronized to 4DCT scans, at positive end-expiratory pressures of 0, 5, 10, and 15 cmH2O during mechanical ventilation, before and after induction of c-R/D by surfactant washout. 4DCT was post-processed for within-breath variation in atelectatic volume (Δ atelectasis) as a measure of c-R/D. Sound waveforms were evaluated for: 1) dynamic crackle energy (dCE): filtered crackle sounds (600–700 Hz); 2) fast Fourier transform area (FFT area): spectral content above 500 Hz in frequency and above −70 dB in amplitude in proportion to the total amount of sound above −70 dB amplitude; and 3) dynamic spectral coherence (dSC): variation in acoustical homogeneity over time. Parameters were analyzed for global, nondependent, central, and dependent lung areas. Results: In healthy lungs, negligible values of Δ atelectasis, dCE, and FFT area occurred. In lavage lung injury, the novel dCE parameter showed the best correlation to Δ atelectasis in dependent lung areas (R2 = 0.88) where c-R/D took place. dCE was superior to FFT area analysis for each lung region examined. The analysis of dSC could predict the lung regions where c-R/D originated. Conclusions: c-R/D is associated with the occurrence of fine crackle sounds as demonstrated by dCE analysis. Standardized computer-assisted analysis of dCE and dSC seems to be a promising method for depicting c-R/D

Gamma-glutamyltransferase is a strong predictor of secondary sclerosing cholangitis after lung transplantation for COVID-19 ARDS

Background: Lung transplantation (LTx) can be considered for selected patients suffering from COVID-19 acute respiratory distress syndrome (ARDS). Secondary sclerosing cholangitis in critically ill (SSC-CIP) patients has been described as a late complication in COVID-19 ARDS survivors, however, rates of SSC-CIP after LTx and factors predicting this detrimental sequela are unknown. Methods: This retrospective analysis included all LTx performed for post-COVID ARDS at 8 European LTx centers between May 2020 and January 2022. Clinical risk factors for SSC-CIP were analyzed over time. Prediction of SSC-CIP was assessed by ROC-analysis. Results: A total of 40 patients were included in the analysis. Fifteen patients (37.5%) developed SSC-CIP. GGT at the time of listing was significantly higher in patients who developed SSC-CIP (median 661 (IQR 324-871) vs 186 (109-346); p = 0.001). Moreover, higher peak values for GGT (585 vs 128.4; p < 0.001) and ALP (325 vs 160.2; p = 0.015) were found in the ‘SSC’ group during the waiting period. Both, GGT at the time of listing and peak GGT during the waiting time, could predict SSC-CIP with an AUC of 0.797 (95% CI: 0.647-0.947) and 0.851 (95% CI: 0.707-0.995). Survival of ‘SSC’ patients was severely impaired compared to ‘no SSC’ patients (1-year: 46.7% vs 90.2%, log-rank p = 0.004). Conclusions: SSC-CIP is a severe late complication after LTx for COVID-19 ARDS leading to significant morbidity and mortality. GGT appears to be a sensitive parameter able to predict SSC-CIP even at the time of listing

Intrapulmonary 3He gas distribution depending on bolus size and temporal bolus placement

OBJECTIVE: Dynamic ventilation (3)He-MRI is a new method to assess pulmonary gas inflow. As differing airway diameters throughout the ventilatory cycle can influence gas inflow this study intends to investigate the influence of volume and timing of a He gas bolus with respect to the beginning of the tidal volume on inspiratory gas distribution. MATERIALS AND METHODS: An ultrafast 2-dimensional spoiled gradient echo sequence (temporal resolution 100 milliseconds) was used for dynamic ventilation (3)He-MRI of 11 anesthetized and mechanically ventilated pigs. The applied (3)He gas bolus was varied in volume between 100 and 200 mL. A 150-mL bolus was varied in its application time after the beginning of the tidal volume between 0 and 1200 milliseconds. Signal kinetics were evaluated using an in-house developed software after definition of parameters for the quantitative description of (3)He gas inflow. RESULTS: The signal rise time (time interval between signal in the parenchyma reaches 10% and 90% of its maximum) was prolonged with increasing bolus volume. The parameter was shortened with increasing delay of (3)He application after the beginning of the tidal volume. Timing variation as well as volume variation showed no clear interrelation to the signal delay time 10 (time interval between signal in the trachea reaches 50% of its maximum and signal in the parenchyma reaches 10% of its maximum). CONCLUSIONS: Dynamic ventilation (3)He-MRI is able to detect differences in bolus geometry performed by volume variation. Pulmonary gas inflow as investigated by dynamic ventilation (3)He-MRI tends to be accelerated by an increasing application delay of a (3)He gas bolus after the beginning of the tidal volume