Individualized positive end-expiratory pressure reduces driving pressure in obese patients during laparoscopic surgery under pneumoperitoneum: a randomized clinical trial.

Introduction: During pneumoperitoneum (PNP), airway driving pressure (ΔPRS) increases due to the stiffness of the chest wall and cephalic shift of the diaphragm, which favors atelectasis. In addition, depending on the mechanical power (MP) formulas, they may lead to different interpretations. Methods: Patients >18 years of age with body mass index >35 kg/m2 were included in a single-center randomized controlled trial during their admission for bariatric surgery by abdominal laparoscopy. Intra-abdominal pressure was set at 15 mmHg at the pneumoperitoneum time point (PNP). After the recruitment maneuver, the lowest respiratory system elastance (ERS) was detected during the positive end-expiratory pressure (PEEP) step-wise decrement. Patients were randomized to the 1) CTRL group: ventilated with PEEP of 5 cmH2O and 2) PEEPIND group: ventilated with PEEP value associated with ERS that is 5% higher than its lowest level. Respiratory system mechanics and mean arterial pressure (MAP) were assessed at the PNP, 5 min after randomization (T1), and at the end of the ventilation protocol (T2); arterial blood gas was assessed at PNP and T2. ΔPRS was the primary outcome. Three MP formulas were used: MPA, which computes static PEEP × volume, elastic, and resistive components; MPB, which computes only the elastic component; and MPC, which computes static PEEP × volume, elastic, and resistive components without inspiratory holds. Results: Twenty-eight patients were assessed for eligibility: eight were not included and 20 patients were randomized and allocated to CTRL and PEEPIND groups (n = 10/group). The PEEPIND ventilator strategy reduced ΔPRS when compared with the CTRL group (PEEPIND, 13 ± 2 cmH2O; CTRL, 22 ± 4 cmH2O; p < 0.001). Oxygenation improved in the PEEPIND group when compared with the CTRL group (p = 0.029), whereas MAP was comparable between the PEEPIND and CTRL groups. At the end of surgery, MPA and MPB were correlated in both the CTRL (rho = 0.71, p = 0.019) and PEEPIND (rho = 0.84, p = 0.020) groups but showed different bias (CTRL, -1.9 J/min; PEEPIND, +10.0 J/min). At the end of the surgery, MPA and MPC were correlated in both the CTRL (rho = 0.71, p = 0.019) and PEEPIND (rho = 0.84, p = 0.020) groups but showed different bias (CTRL, -1.9 J/min; PEEPIND, +10.0 J/min). Conclusion: Individualized PEEP was associated with a reduction in ΔPRS and an improvement in oxygenation with comparable MAP. The MP, which solely computes the elastic component, better reflected the improvement in ΔPRS observed in the individualized PEEP group. Clinical Trial Registration: The protocol was registered at the Brazilian Registry of Clinical Trials (U1111-1220-7296).

Positive end-expiratory pressure induced changes in airway driving pressure in mechanically ventilated COVID-19 Acute Respiratory Distress Syndrome patients.

BACKGROUND: The profile of changes in airway driving pressure (dPaw) induced by positive-end expiratory pressure (PEEP) might aid for individualized protective ventilation. Our aim was to describe the dPaw versus PEEP curves behavior in ARDS from COVID-19 patients. METHODS: Patients admitted in three hospitals were ventilated with fraction of inspired oxygen (FiO2) and PEEP initially adjusted by oxygenation-based table. Thereafter, PEEP was reduced from 20 until 6 cmH2O while dPaw was stepwise recorded and the lowest PEEP that minimized dPaw (PEEPmin_dPaw) was assessed. Each dPaw vs PEEP curve was classified as J-shaped, inverted-J-shaped, or U-shaped according to the difference between the minimum dPaw and the dPaw at the lowest and highest PEEP. In one hospital, hyperdistention and collapse at each PEEP were assessed by electrical impedance tomography (EIT). RESULTS: 184 patients (41 including EIT) were studied. 126 patients (68%) exhibited a J-shaped dPaw vs PEEP profile (PEEPmin_dPaw of 7.5 ± 1.9 cmH2O). 40 patients (22%) presented a U (PEEPmin_dPaw of 12.2 ± 2.6 cmH2O) and 18 (10%) an inverted-J profile (PEEPmin_dPaw of 14,6 ± 2.3 cmH2O). Patients with inverted-J profiles had significant higher body mass index (BMI) and lower baseline partial pressure of arterial oxygen/FiO2 ratio. PEEPmin_dPaw was associated with lower fractions of both alveolar collapse and hyperinflation. CONCLUSIONS: A PEEP adjustment procedure based on PEEP-induced changes in dPaw is feasible and may aid in individualized PEEP for protective ventilation. The PEEP required to minimize driving pressure was influenced by BMI and was low in the majority of patients.

Increased Lung Immune Metabolic Activity in COVID-19 Survivors.

PURPOSE: We quantified lung glycolytic metabolic activity, clinical symptoms and inflammation, coagulation, and endothelial activation biomarkers in 2019 coronavirus disease (COVID-19) pneumonia survivors. METHODS: Adults previously hospitalized with moderate to severe COVID-19 pneumonia were prospectively included. Subjects filled out a questionnaire on clinical consequences, underwent chest CT and 18 F-FDG PET/CT, and provided blood samples on the same day. Forty-five volunteers served as control subjects. Analysis of CT images and quantitative voxel-based analysis of PET/CT images were performed for both groups. 18 F-FDG uptake in the whole-lung volume and in high- and low-attenuation areas was calculated and normalized to liver values. Quantification of plasma markers of inflammation (interleukin 6), d -dimer, and endothelial cell activation (angiopoietins 1 and 2, vascular cell adhesion molecule 1, and intercellular adhesion molecule 1) was also performed. RESULTS: We enrolled 53 COVID-19 survivors (62.3% were male; median age, 50 years). All survivors reported at least 1 persistent symptom, and 41.5% reported more than 6 symptoms. The mean lung density was greater in survivors than in control subjects, and more metabolic activity was observed in normal and dense lung areas, even months after symptom onset. Plasma proinflammatory, coagulation, and endothelial activation biomarker concentrations were also significantly higher in survivors. CONCLUSION: We observed more metabolic activity in areas of high and normal lung attenuation several months after moderate to severe COVID-19 pneumonia. In addition, plasma markers of thromboinflammation and endothelial activation persisted. These findings may have implications for our understanding of the in vivo pathogenesis and long-lasting effects of COVID-19 pneumonia.

Case Report: Incidental Finding of COVID-19 Infection after Positron Emission Tomography/CT Imaging in a Patient with a Diagnosis of Histoplasmosis and Recurring Fever.

This is a case report of a 37-year-old woman evaluated with 18F-fludeoxyglucose (18F-FDG) positron emission computed tomography/CT with recurrent fever after treatment with itraconazole for 6 weeks for histoplasmosis. The examination demonstrated a decrease in the dimensions of the pulmonary opacities previously identified in the left lower lobe and attributed to histoplasmosis. In addition to these pulmonary opacities, increased FDG uptake was also observed in lymph nodes present in the cervical region, mediastinum, left lung hilum, and hepatic hilum. Notably, other pulmonary opacities with ground-glass pattern that were not present in the previous computed tomography were detected in the right lower lobe, with mild 18F-FDG uptake. Nasal swab performed shortly after the examination was positive for COVID-19. In this case, the 18F-FDG positron emission computed tomography/CT study demonstrated findings consistent with active COVID-19 infection coexisting with inflammatory changes associated with histoplasmosis infection.

Estimating COVID-19 Pneumonia Extent and Severity From Chest Computed Tomography.

BACKGROUND: COVID-19 pneumonia extension is assessed by computed tomography (CT) with the ratio between the volume of abnormal pulmonary opacities (PO) and CT-estimated lung volume (CTLV). CT-estimated lung weight (CTLW) also correlates with pneumonia severity. However, both CTLV and CTLW depend on demographic and anthropometric variables. PURPOSES: To estimate the extent and severity of COVID-19 pneumonia adjusting the volume and weight of abnormal PO to the predicted CTLV (pCTLV) and CTLW (pCTLW), respectively, and to evaluate their possible association with clinical and radiological outcomes. METHODS: Chest CT from 103 COVID-19 and 86 healthy subjects were examined retrospectively. In controls, predictive equations for estimating pCTLV and pCTLW were assessed. COVID-19 pneumonia extent and severity were then defined as the ratio between the volume and the weight of abnormal PO expressed as a percentage of the pCTLV and pCTLW, respectively. A ROC analysis was used to test differential diagnosis ability of the proposed method in COVID-19 and controls. The degree of pneumonia extent and severity was assessed with Z-scores relative to the average volume and weight of PO in controls. Accordingly, COVID-19 patients were classified as with limited, moderate and diffuse pneumonia extent and as with mild, moderate and severe pneumonia severity. RESULTS: In controls, CTLV could be predicted by sex and height (adjusted R 2 = 0.57; P < 0.001) while CTLW by age, sex, and height (adjusted R 2 = 0.6; P < 0.001). The cutoff of 20% (AUC = 0.91, 95%CI 0.88-0.93) for pneumonia extent and of 50% (AUC = 0.91, 95%CI 0.89-0.92) for pneumonia severity were obtained. Pneumonia extent were better correlated when expressed as a percentage of the pCTLV and pCTLW (r = 0.85, P < 0.001), respectively. COVID-19 patients with diffuse and severe pneumonia at admission presented significantly higher CRP concentration, intra-hospital mortality, ICU stay and ventilatory support necessity, than those with moderate and limited/mild pneumonia. Moreover, pneumonia severity, but not extent, was positively and moderately correlated with age (r = 0.46) and CRP concentration (r = 0.44). CONCLUSION: The proposed estimation of COVID-19 pneumonia extent and severity might be useful for clinical and radiological patient stratification.

Pulmonary Densitovolumetry Using Computed Tomography in Patients with Nontuberculous Mycobacteria: Correlation with Pulmonary Function Tests.

BACKGROUND: Since nontuberculous mycobacterial pulmonary disease (NTM-PD) is a condition with increasing morbidity, a more detailed knowledge of radiological aspects and pulmonary function plays a relevant role in the diagnosis and appropriate therapeutic management of these patients. OBJECTIVES: The purpose of this study was to evaluate changes in lung parenchyma through computed tomography (CT) densitometry and, secondarily, to analyze its correlation with pulmonary function testing (PFT) in patients with NTM-PD. METHODS: This is a cross-sectional study in which 31 patients with NTM-PD and 27 controls matched by sex, age, and body mass index underwent CT pulmonary densitovolumetry and pulmonary function tests including spirometry and body plethysmograph. RESULTS: Based on the total lung volume (TLV) and total lung mass (TLM) measurements, the cumulative mass ratios were calculated for 3% (M3), 15% (M15), 85% (M85), and 97% (M97) of the TLV. We also calculated the complement, which is represented by TLM (100%) minus the mass of 15% (C85) or 3% (C97) of the TLV. Patients with NTM-PD presented lower values of M3 and M15 than controls, with greater significant differences in the apical third and middle third measurements. Compared to controls, patients with NTM-PD showed higher values of C85 and C97, although significant differences were observed only in the basal third measurements. There were negative correlations of total lung capacity with M3 and M15 in the middle third and apical third measurements. There were positive correlations of residual volume and airway resistance with M3 at the apical third measurement. CONCLUSIONS: Patients with NTM-PD show reduced lung mass and increased lung mass in the apical and basal regions of the lungs, respectively. Furthermore, there is a relationship between lung mass measurements and pulmonary function parameters.

Association of respiratory integer and fractional-order models with structural abnormalities in silicosis.

BACKGROUND AND OBJECTIVE: Integer and fractional-order models have emerged as powerful methods for obtaining information regarding the anatomical or pathophysiological changes that occur during respiratory diseases. However, the precise interpretation of the model parameters in light of the lung structural changes is not known. This study analyzed the associations of the integer and fractional-order models with structural changes obtained using multidetector computed tomography densitometry (MDCT) and pulmonary function analysis. METHODS: Integer and fractional-order models were adjusted to data obtained using the forced oscillation technique (FOT). The results obtained in controls (n = 20) were compared with those obtained in patients with silicosis (n = 32), who were submitted to spirometry, body plethysmograph, FOT, diffusing capacity of the lungs for carbon monoxide (DLCO), and MDCT. The diagnostic accuracy was also investigated using ROC analysis. RESULTS: The observed changes in the integer and fractional-order models were consistent with the pathophysiology of silicosis. The integer-order model showed association only between inertance and the non-aerated compartment (R = -0.69). This parameter also presented the highest associations with spirometry (R = 0.81), plethysmography (-0.61) and pulmonary diffusion (R = 0.53). Considering the fractional-order model, the increase in the poorly aerated and non-aerated regions presented direct correlations with the fractional inertance (R = 0.48), respiratory damping (R = 0.37) and hysteresivity (R = 0.54) and inverse associations with its fractional exponent (R = -0.62) and elastance (-0.35). Significant associations were also observed with spirometry (R = 0.63), plethysmography (0.37) and pulmonary diffusion (R = 0.51). Receiver operator characteristic analysis showed a higher accuracy in the FrOr model (0.908) than the eRIC model (0.789). CONCLUSIONS: Our study has shown clear associations of the integer and fractional-order parameters with anatomical changes obtained via MDCT and pulmonary function measurements. These findings help to elucidate the physiological interpretation of the integer and fractional-order parameters and provide evidence that these parameters are reflective of the abnormal changes in silicosis. We also observed that the fractional-order model showed smaller curve-fitting errors, which resulted in a higher diagnostic accuracy than that of the eRIC model. Taken together, these results provide strong motivation for further studies exploring the clinical and scientific use of these models in respiratory medicine.

Computed tomography trachea volumetry in patients with scleroderma: Association with clinical and functional findings.

BACKGROUND: In scleroderma, excessive collagen production can alter tracheal geometry, and computed tomography (CT) volumetry of this structure may aid in detecting possible abnormalities. The objectives of this study were to quantify the morphological abnormalities in the tracheas of ​​patients with scleroderma and to correlate these findings with data on clinical and pulmonary function. METHODS: This was a cross-sectional study in which 28 adults with scleroderma and 27 controls matched by age, gender and body mass index underwent chest CT with posterior segmentation and skeletonization of the images. In addition, all participants underwent pulmonary function tests and clinical evaluation, including the modified Rodnan skin score (mRSS). RESULTS: Most patients (71.4%) had interstitial lung disease on CT. Compared to controls, patients with scleroderma showed higher values ​​in the parameters measured by CT trachea volumetry, including area, eccentricity, major diameter, minor diameter, and tortuosity. The tracheal area and equivalent diameter were negatively correlated with the ratio between forced expiratory flow and forced inspiratory flow at 50% of forced vital capacity (FEF50%/FIF50%) (r = -0.44, p = 0.03 and r = -0.46, p = 0.02, respectively). The tracheal tortuosity was negatively correlated with peak expiratory flow (r = -0.51, p = 0.008). The mRSS showed a positive correlation with eccentricity (r = 0.62, p < 0.001) and tracheal tortuosity (r = 0.51, p = 0.007), while the presence of anti-topoisomerase I antibody (ATA) showed a positive correlation with tracheal tortuosity (r = 0.45, p = 0.03). CONCLUSIONS: In a sample composed predominantly of scleroderma patients with associated interstitial lung disease, there were abnormalities in tracheal geometry, including greater eccentricity, diameter and tortuosity. In these patients, abnormalities in the geometry of the trachea were associated with functional markers of obstruction. In addition, tracheal tortuosity was correlated with cutaneous involvement and the presence of ATA.

SinusCor: an advanced tool for heart rate variability analysis.

BACKGROUND: Heart rate variability (HRV) is a widespread non-invasive technique to assess cardiac autonomic function. Time and frequency domain analyses have been used in HRV studies, and their interpretations are linked with both clinical prognostic and diagnostic information. Statistical and geometrical parameters, Fast Fourier Transform and Autoregressive based periodograms are commonly used approaches for the assessment of stationary RR intervals (RRi) signals. However, some conditions result in non-stationary HRV behavior such as the "tilt test" and exercise. This study presents the SinusCor, a new free software for HRV analysis that includes the classical time and frequency domain indices and also techniques for non-stationary data analyses in both time (i.e. root mean squared of successive differences; RMSSD calculated with moving segments) and frequency domains (i.e. time-frequency analysis). RESULTS: An example of RRi was acquired from a young male subject and its time and frequency domain indices were calculated. Time-varying and time-frequency analyses were also presented using the RMSSD and total power, respectively. Validation of the present software against a standard software for HRV analysis (Kubios v 3.0.1) was also performed [SinusCor vs. Kubios: RMSSD-93.96 (41.55) vs. 93.96 (41.55) ms; SDNN-101.29 (29.03) vs. 101.29 (29.03) ms; LF-50.42 (19.76) vs. 50.56 (19.56) n.u.; HF-49.57 (19.76) vs. 49.38 (19.56) n.u.; LF/HF-1.38 (1.08) vs. 1.38 (1.07)]. CONCLUSIONS: SinusCor might be a useful tool for classical stationary and non-stationary HRV analysis.

Computed tomography airway lumen volumetry in patients with acromegaly: Association with growth hormone levels and lung function.

INTRODUCTION: The segmentation and skeletonisation of images via computed tomography (CT) airway lumen volumetry provide a new perspective regarding the incorporation of this technique in medical practice. Our aim was to quantify morphological changes in the large airways of patients with acromegaly through CT and, secondarily, to correlate these findings with hormone levels and pulmonary function testing (PFT) parameters. METHODS: This was a cross-sectional study in which 28 non-smoker patients with acromegaly and 15 control subjects underwent CT analysis of airway lumen volumetry with subsequent image segmentation and skeletonisation. Moreover, all participants were subjected to PFT. RESULTS: Compared with the controls, patients with acromegaly presented higher diameters in the trachea, right main bronchus and left main bronchus. The patients with acromegaly also showed a higher tracheal sinuosity index (the deviation of a line from the shortest path, calculated by dividing total length by shortest possible path) than the controls [1.06 (1.02-1.09) vs. 1.03 (1.02-1.04), P = 0.04], and tracheal stenosis was observed in 25% of these individuals. The tracheal area was correlated with the levels of growth hormone (rs  = 0.45, P = 0.02) and insulin-like growth factor type I (rs  = 0.38, P = 0.04). The ratio between the forced expiratory flow and forced inspiratory flow at 50% of the forced vital capacity was correlated with the tracheal area (rs  = 0.36, P = 0.02) and Δ tracheal diameters (rs  = 0.58, P < 0.0001). CONCLUSION: Patients with acromegaly exhibit tracheobronchomegaly and tracheal sinuosity/stenosis. Moreover, there are associations between the results of CT airway lumen volumetry, hormone levels and functional parameters of large airway obstruction.

The endotracheal tube biases the estimates of pulmonary recruitment and overdistension.

To assess the impact of the endotracheal tube (ETT) and of different flow waveforms on estimates of alveolar cyclic recruitment (CR) and overdistension (AO). Numerical simulation of the respiratory system plus ETT (inertance L plus a flow-dependent resistance, K (1) and K (2)), with the following non-linear equation of motion PAW(t)= ((K1 + K2 x/V(t)/) x V(t) + L x V(t)) + Rrs x V(t) + (E1 + E2 x V(t) x V(t) + P0 (PAW pressure at the airways opening, V volume), under volume-controlled mechanical ventilation. An index %E2 = 100 x (E2 x V(T))/(E1 + E2)x V(T)) can be calculated where %E(2) > 30% represents AO and %E(2) < 0% represents CR. Parameters were estimated by the least-squares method, either with the complete equation or suppressing L, K(2) or both. %E(2) is always underestimated (down to -152 percent points) with incomplete equations of motion. The estimation of %E (2) may be strongly biased in the presence of an ETT excluded from the estimation model.

Effects of filtering and delays on the estimates of a nonlinear respiratory mechanics model.

Estimation of mechanical properties of the respiratory system may be disturbed by instrumentation and physical set-up. The effects of lowpass filtering, filter mismatch and inter-channel delay in the digital converter are assessed on numerically simulated signals from a nonlinear model of the respiratory system. Large biases in model parameter estimates (up to about -300% for some parameters) were caused by these instrumental interferences and were reduced by including an inertance in the retrieved model. The results reinforce the importance of a careful evaluation of the instrumental set-up used in physiological measurements.