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BACKGROUND This study aims to correlate nodule, patient, and technical risk factors less commonly investigated in the literature with pneumothorax development during computed tomography-guided core needle lung nodule biopsy. PATIENTS AND METHODS Retrospective data on 671 computed tomography-guided percutaneous core needle lung biopsies from 671 patients at a tertiary care center between March 2014 and August 2016. Univariate and multivariable logistic regression analyses were used to identify pneumothorax risk factors. RESULTS The overall incidence of pneumothorax was 26.7% (n=179). Risk factors identified on univariate analysis include anterior [odds ratio (OR)=1.98; P

Pulmonary alveolar proteinosis (PAP) is a rare pulmonary surfactant homeostasis disorder resulting in buildup of lipo-proteinaceous material within the alveoli. PAP is classified as primary (autoimmune and hereditary), secondary, congenital and unclassifiable type based on the underlying pathogenesis. PAP has an insidious onset and can, in some cases, progress to severe respiratory failure. Diagnosis is often secured with bronchoalveolar lavage in the setting of classic imaging findings. Recent insights into genetic alterations and autoimmune mechanisms have provided newer diagnostics and treatment options. In this review, we discuss the etiopathogenesis, diagnosis and treatment options available and emerging for PAP.

PURPOSE Computed tomography (CT)-derived ventilation methods compute respiratory induced volume changes as a surrogate for pulmonary ventilation. Currently, there are no known methods to derive perfusion information from noncontrast CT. We introduce a novel CT-Perfusion (CT-P) method for computing the magnitude mass changes apparent on dynamic noncontrast CT as a surrogate for pulmonary perfusion. METHODS CT-Perfusion is based on a mass conservation model which describes the unknown mass change as a linear combination of spatially corresponding inhale and exhale HU estimated voxel densities. CT-P requires a deformable image registration (DIR) between the inhale/exhale lung CT pair, a preprocessing lung volume segmentation, and an estimate for the Jacobian of the DIR transformation. Given this information, the CT-P image, which provides the magnitude mass change for each voxel within the lung volume, is formulated as the solution to a constrained linear least squares problem defined by a series of subregional mean magnitude mass change measurements. Similar to previous robust CT-ventilation methods, the amount of uncertainty in a subregional sample mean measurement is related to measurement resolution and can be characterized with respect to a tolerance parameter τ . Spatial Spearman correlation between single photon emission CT perfusion (SPECT-P) and the proposed CT-P method was assessed in two patient cohorts via a parameter sweep of τ . The first cohort was comprised of 15 patients diagnosed with pulmonary embolism (PE) who had SPECT-P and 4DCT imaging acquired within 24 h of PE diagnosis. The second cohort was comprised of 15 nonsmall cell lung cancer patients who had SPECT-P and 4DCT images acquired prior to radiotherapy. For each test case, CT-P images were computed for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.125], and the Spearman correlation between the SPECT-P and the resulting CT-P images were computed. RESULTS The median correlations between CT-P and SPECT-P taken over all 30 test cases ranged between 0.49 and 0.57 across the parameter sweep. For the optimal tolerance τ = 0.0385, the CT-P and SPECT-P correlations across all 30 test cases ranged between 0.02 and 0.82. A one-sample sign test was applied separately to the PE and lung cancer cohorts. A low Spearmen correlation of 15% was set as the null median value and two-sided alternative was tested. The PE patients showed a median correlation of 0.57 (IQR = 0.305). One-sample sign test was statistically significant with 96.5 % confidence interval: 0.20-0.63, P

Background Hypercoagulability may contribute to COVID‐19 pathogenicity. The role of anticoagulation (AC) at therapeutic (tAC) or prophylactic doses (pAC) is unclear. Objectives We evaluated the impact on survival of different AC doses in COVID‐19 patients. Methods Retrospective, multi‐center cohort study of consecutive COVID‐19 patients hospitalized between March 13 and May 5, 2020. Results A total of 3480 patients were included (mean age, 64.5 years [17.0]; 51.5% female; 52.1% black and 40.6% white). 18.5% (n = 642) required intensive care unit (ICU) stay. 60.9% received pAC (n = 2121), 28.7% received ≥3 days of tAC (n = 998), and 10.4% (n = 361) received no AC. Propensity score (PS) weighted Kaplan‐Meier plot demonstrated different 25‐day survival probability in the tAC and pAC groups (57.5% vs 50.7%). In a PS–weighted multivariate proportional hazards model, AC was associated with reduced risk of death at prophylactic (hazard ratio [HR] 0.35 [95% confidence interval {CI} 0.22‐0.54]) and therapeutic doses (HR 0.14 [95% CI 0.05‐0.23]) compared to no AC. Major bleeding occurred more frequently in tAC patients (81 [8.1%]) compared to no AC (20 [5.5%]) or pAC (46 [2.2%]) subjects. Conclusions Higher doses of AC were associated with lower mortality in hospitalized COVID‐19 patients. Prospective evaluation of efficacy and risk of AC in COVID‐19 is warranted.

PURPOSE. The computed tomography (CT) derived ventilation imaging methodology employs deformable image registration (DIR) to recover respiratory motion-induced volume changes from an inhale/exhale CT image pair, as a surrogate for ventilation. The Integrated Jacobian Formulation (IJF) and Mass Conserving Volume Change (MCVC) numerical methods for volume change estimation represent two classes of ventilation methods, namely transformation-based and intensity (Hounsfield Unit) based, respectively. Both the IJF and MCVC methods utilize subregional volume change measurements that satisfy a specified uncertainty tolerance. In previous publications, the ventilation images resulting from this numerical strategy demonstrated robustness to DIR variations. However, the reduced measurement uncertainty comes at the expense of measurement resolution. The purpose of this study is to examine the spatial correlation between robust CT ventilation images and single photon emission CT ventilation (SPECT-V). METHODS: Previously described implementations of IJF and MCVC require the solution of a large scale, constrained linear least squares problem defined by a series of robust subregional volume change measurements. We introduce a simpler parameterized implementation that reduces the number of unknowns while increasing the number of data points in the resulting least squares problem. A parameter sweep of the measurement uncertainty tolerance, τ, was conducted using the 4DCT and SPECT-V images acquired for fifteen non-small cell lung cancer patients prior to radiotherapy. For each test case, MCVC and IJF CT-ventilation images were created for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.25]. Voxel-wise Spearman correlation between the SPECT-V and the resulting CT-ventilation images were computed. RESULTS: The median correlations between MCVC and SPECT-V ranged from 0.20 to 0.48 across the parameter sweep, while the median correlations for IJF and SPECT-V ranged between 0.79 and 0.82. For the optimal IJF tolerance τ = 0.07, the IJF and SPECT-V correlations across all fifteen test cases ranged between 0.12 and 0.90. For the optimal MCVC tolerance τ = 0.03, the MCVC and SPECT-V correlations across all fifteen test cases ranged between −0.06 and 0.84. CONCLUSION: The reported correlations indicate that robust methods generate ventilation images that are spatially consistent with SPECT-V, with the transformation-based IJF method yielding higher correlations than those previously reported in the literature. For both methods, overall correlations were found to marginally vary for τ ∈ [0.03, 0.15], indicating that the clinical utility of both methods is robust to both uncertainty tolerance and DIR solution.

Purpose Conflicting data exist with regard to the effect of needle gauge on outcomes of computed tomography (CT)-guided lung nodule biopsies. The purpose of this study was to compare the complication and diagnostic adequacy rates between 2 needle sizes: 18 G and 20 G in CT-guided lung nodule biopsies. Materials and methods This retrospective cohort study examined CT-guided lung biopsies performed between March 2014 and August 2016 with a total of 550 patients between the ages of 30 and 94. Biopsies were performed using an 18-G or a 20-G needle. Procedure-associated pneumothorax and other complication rates were compared between the 2 groups. Univariate and multiple logistic regression analyses were performed. Results There was no significant difference in pneumothorax rate between 18 G (n=125) versus 20 G (n=425) (rates: 25.6% vs. 28.7%; P=0.50; odds ratio [OR]=0.86; 95% confidence interval [CI]=0.54-1.35), chest tube insertion rate (4.8% vs. 5.6%; P=0.71; OR=0.84; 95% CI=0.34-2.11), or diagnostic adequacy (95% vs. 93%; P=0.36; OR=1.51; 95% CI=0.61-3.72). Multiple logistic regression analysis demonstrated emphysema along the biopsy path (OR=3.12; 95% CI=1.63-5.98) and nodule distance from the pleural surface ≥4 cm (OR=1.85; 95% CI=1.05-3.28) to be independent risk factors for pneumothorax. Conclusion No statistically significant difference in pneumothorax rate or diagnostic adequacy was found between 18-G versus 20-G core biopsy needles. Independent risk factors for pneumothorax include emphysema along the biopsy path and nodule distance from the pleural surface.

Background QT prolongation increases the risk of ventricular arrhythmia and is common among critically ill patients. The gold standard for QT measurement is electrocardiography. Automated measurement of corrected QT (QTc) by cardiac telemetry has been developed, but this method has not been compared with electrocardiography in critically ill patients. Objective To compare the diagnostic performance of QTc values obtained with cardiac telemetry versus electrocardiography. Methods This prospective observational study included patients admitted to intensive care who had an electrocardiogram ordered simultaneously with cardiac telemetry. Demographic data and QTc determined by electrocardiography and telemetry were recorded. Bland-Altman analysis was done, and correlation coefficient and receiver operating characteristic (ROC) coefficient were calculated. Results Fifty-one data points were obtained from 43 patients (65% men). Bland-Altman analysis revealed poor agreement between telemetry and electrocardiography and evidence of fixed and proportional bias. Area under the ROC curve for QTc determined by telemetry was 0.9 (P < .001) for a definition of prolonged QT as QTc ≥ 450 milliseconds in electrocardiography (sensitivity, 88.89%; specificity, 83.33%; cutoff of 464 milliseconds used). Correlation between the 2 methods was only moderate (r = 0.6, P < .001). Conclusions QTc determination by telemetry has poor agreement and moderate correlation with electrocardiography. However, telemetry has an acceptable area under the curve in ROC analysis with tolerable sensitivity and specificity depending on the cutoff used to define prolonged QT. Cardiac telemetry should be used with caution in critically ill patients.

Sepsis is a common consequence of infection, associated with a mortality rate > 25%. Although community-acquired sepsis is more common, hospital-acquired infection is more lethal. The most common site of infection is the lung, followed by abdominal infection, catheter-associated blood steam infection and urinary tract infection. Gram-negative sepsis is more common than gram-positive infection, but sepsis can also be due to fungal and viral pathogens. To reduce mortality, it is necessary to give immediate, empiric, broad-spectrum therapy to those with severe sepsis and/or shock, but this approach can drive antimicrobial overuse and resistance and should be accompanied by a commitment to de-escalation and antimicrobial stewardship. Biomarkers such a procalcitonin can provide decision support for antibiotic use, and may identify patients with a low likelihood of infection, and in some settings, can guide duration of antibiotic therapy. Sepsis can involve drug-resistant pathogens, and this often necessitates consideration of newer antimicrobial agents.

Computed tomography (CT) derived ventilation algorithms estimate the apparent voxel volume changes within an inhale/exhale CT image pair. Transformation‐based methods compute these estimates solely from the spatial transformation acquired by applying a deformable image registration (DIR) algorithm to the image pair. However, approaches based on finite difference approximations of the transformation's Jacobian have been shown to be numerically unstable. As a result, transformation‐based CT ventilation is poorly reproducible with respect to both DIR algorithm and CT acquisition method. Purpose We introduce a novel Integrated Jacobian Formulation (IJF) method for estimating voxel volume changes under a DIR‐recovered spatial transformation. The method is based on computing volume estimates of DIR mapped subregions using the hit‐or‐miss sampling algorithm for integral approximation. The novel approach allows for regional volume change estimates that (a) respect the resolution of the digital grid and (b) are based on approximations with quantitatively characterized and controllable levels of uncertainty. As such, the IJF method is designed to be robust to variations in DIR solutions and thus overall more reproducible. Methods Numerically, Jacobian estimates are recovered by solving a simple constrained linear least squares problem that guarantees the recovered global volume change is equal to the global volume change obtained from the inhale and exhale lung segmentation masks. Reproducibility of the IJF method with respect to DIR solution was assessed using the expert‐determined landmark point pairs and inhale/exhale phases from 10 four‐dimensional computed tomographies (4DCTs) available on http://www.dir-lab.com. Reproducibility with respect to CT acquisition was assessed on the 4DCT and 4D cone beam CT (4DCBCT) images acquired for five lung cancer patients prior to radiotherapy. Results The ten Dir‐Lab 4DCT cases were registered twice with the same DIR algorithm, but with different smoothing parameter. Finite difference Jacobian (FDJ) and IFJ images were computed for both solutions. The average spatial errors (300 landmarks per case) for the two DIR solution methods were 0.98 (1.10) and 1.02 (1.11). The average Pearson correlation between the FDJ images computed from the two DIR solutions was 0.83 (0.03), while for the IJF images it was 1.00 (0.00). For intermodality assessment, the IJF and FDJ images were computed from the 4DCT and 4DCBCT of five patients. The average Pearson correlation of the spatially aligned FDJ images was 0.27 (0.11), while it was 0.77 (0.13) for the IFJ method. Conclusion The mathematical theory underpinning the IJF method allows for the generation of ventilation images that are (a) computed with respect to DIR spatial accuracy on the digital voxel grid and (b) based on DIR‐measured subregional volume change estimates acquired with quantifiable and controllable levels of uncertainty. Analyses of the experiments are consistent with the mathematical theory and indicate that IJF ventilation imaging has a higher reproducibility with respect to both DIR algorithm and CT acquisition method, in comparison to the standard finite difference approach.

Purpose: We sought to identify clinical factors that predict extubation failure (reintubation) and its prognostic implications in critically ill COVID-19 patients. Materials and Methods: Retrospective, multi-center cohort study of hospitalized COVID-19 patients. Multivariate competing risk models were employed to explore the rate of reintubation and its determining factors. Results: Two hundred eighty-one extubated patients were included (mean age, 61.0 years [±13.9]; 54.8% male). Reintubation occurred in 93 (33.1%). In multivariate analysis accounting for death, reintubation risk increased with age (hazard ratio [HR] 1.04 per 1-year increase, 95% confidence interval [CI] 1.02 -1.06), vasopressors (HR 1.84, 95% CI 1.04-3.60), renal replacement (HR 2.01, 95% CI 1.22-3.29), maximum PEEP (HR 1.07 per 1-unit increase, 95% CI 1.02 -1.12), paralytics (HR 1.48, 95% CI 1.08-2.25) and requiring more than nasal cannula immediately post-extubation (HR 2.19, 95% CI 1.37-3.50). Reintubation was associated with higher mortality (36.6% vs 2.1%; P < 0.0001) and risk of inpatient death after adjusting for multiple factors (HR 23.2, 95% CI 6.45-83.33). Prone ventilation, corticosteroids, anticoagulation, remdesivir and tocilizumab did not impact the risk of reintubation or death. Conclusions: Up to 1 in 3 critically ill COVID-19 patients required reintubation. Older age, paralytics, high PEEP, need for greater respiratory support following extubation and non-pulmonary organ failure predicted reintubation. Extubation failure strongly predicted adverse outcomes.

Background: Lung compliance is the ability of the lung to expand with changes in pressure and is one of the earliest physiological measurements to be altered in patients with parenchymal lung disease. Therefore, compliance monitoring could potentially identify patients at risk for disease progression. However, in clinical practice, compliance measurements are prohibitively invasive for use as a routine monitoring tool. Purpose: We propose a novel method for computing dynamic lung compliance imaging (LCI) from non-contrast computed tomography (CT) scans. LCI applies image processing methods to free-breathing 4DCT images, acquired under two different continuous positive airway pressures (CPAP) applied using a full-face mask, in order to compute the lung volume change induced by the pressure change. LCI provides a quantitative volumetric map of lung stiffness. Methods: We compared mean LCI values computed for 10 patients with idiopathic pulmonary fibrosis (IPF) and 7 non-IPF patients who were screened for lung nodules. 4DCTs were acquired for each patient at 5cm and 10 cm H20 CPAP, as the patients were free breathing at functional residual capacity. LCI was computed from the two 4DCTs. Mean LCI intensities, which represent relative voxel volume change induced by the change in CPAP pressure, were computed. Results: The mean LCI values for patients with IPF ranged between [0.0309, 0.1165], whereas the values ranged between [0.0704, 0.2185] for the lung nodule cohort. Two-sided Wilcoxon rank sum test indicated that the difference in medians is statistically significant (p value = 0.009) and that LCI -measured compliance is overall lower in the IPF patient cohort. Conclusion: There is considerable difference in lung compliance scores between patients with IPF compared to controls. Future longitudinal studies should look for LC alterations in areas of lung prior to radiographic detection of fibrosis to further characterize LCI's potential utility as an image marker for disease progression.

Background The Coronavirus disease 2019 (COVID-19) pandemic has affected millions of people across the globe. It is associated with a high mortality rate and has created a global crisis by straining medical resources worldwide. Objectives To develop and validate machine-learning models for prediction of mechanical ventilation (MV) for patients presenting to emergency room and for prediction of in-hospital mortality once a patient is admitted. Methods Two cohorts were used for the two different aims. 1980 COVID-19 patients were enrolled for the aim of prediction ofMV. 1036 patients’ data, including demographics, past smoking and drinking history, past medical history and vital signs at emergency room (ER), laboratory values, and treatments were collected for training and 674 patients were enrolled for validation using XGBoost algorithm. For the second aim to predict in-hospital mortality, 3491 hospitalized patients via ER were enrolled. CatBoost, a new gradient-boosting algorithm was applied for training and validation of the cohort. Results Older age, higher temperature, increased respiratory rate (RR) and a lower oxygen saturation (SpO2) from the first set of vital signs were associated with an increased risk of MV amongst the 1980 patients in the ER. The model had a high accuracy of 86.2% and a negative predictive value (NPV) of 87.8%. While, patients who required MV, had a higher RR, Body mass index (BMI) and longer length of stay in the hospital were the major features associated with in-hospital mortality. The second model had a high accuracy of 80% with NPV of 81.6%. Conclusion Machine learning models using XGBoost and catBoost algorithms can predict need for mechanical ventilation and mortality with a very high accuracy in COVID-19 patients.

Hypercoagulability is a recognized feature in SARS-CoV-2 infection. There exists a need for a dedicated risk assessment model (RAM) that can risk-stratify hospitalized COVID-19 patients for venous thromboembolism (VTE) and guide anticoagulation. We aimed to build a simple clinical model to predict VTE in COVID-19 patients. This large-cohort, retrospective study included adult patients admitted to four hospitals with PCR-confirmed SARS-CoV-2 infection. Model training was performed on 3531 patients hospitalized between March and December 2020 and validated on 2508 patients hospitalized between January and September 2021. Diagnosis of VTE was defined as acute deep vein thrombosis (DVT) or pulmonary embolism (PE). The novel RAM was based on commonly available parameters at hospital admission. LASSO regression and logistic regression were performed, risk scores were assigned to the significant variables, and cutoffs were derived. Seven variables with assigned scores were delineated as: DVT History = 2; High D-Dimer (>500–2000 ng/mL) = 2; Very High D-Dimer (>2000 ng/mL) = 5; PE History = 2; Low Albumin (100 bpm) = 1. The model had a sensitivity of 83% and specificity of 53%. This simple, robust clinical tool can help individualize thromboprophylaxis for COVID-19 patients based on their VTE risk category.

Objective: To evaluate CT-ventilation imaging (CTVI) within a well-characterized, healthy cohort with no respiratory symptoms and examine the correlation between CTVI and concurrent pulmonary function test (PFT). Methods: CT scans and PFTs from 77 Caucasian participants in the NORM dataset (clinicaltrials.gov NCT00848406) were analyzed. CTVI was generated using the robust Integrated Jacobian Formulation (IJF) method. IJF estimated total lung capacity (TLC) was computed from CTVI. Bias-adjusted Pearson’s correlation between PFT and IJF-based TLC was computed. Results: IJF- and PFT-measured TLC showed a good correlation for both males and females [males: 0.657, 95% CI (0.438–0.797); females: 0.667, 95% CI (0.416–0.817)]. When adjusting for age, height, smoking, and abnormal CT scan, correlation moderated [males: 0.432, 95% CI (0.129–0.655); females: 0.540, 95% CI (0.207–0.753)]. Visual inspection of CTVI revealed participants who had functional defects, despite the fact that all participant had normal high-resolution CT scan. Conclusion: In this study, we demonstrate that IJF computed CTVI has good correlation with concurrent PFT in a well-validated patient cohort with no respiratory symptoms. Advances in knowledge: IJF-computed CTVI’s overall numerical robustness and consistency with PFT support its potential as a method for providing spatiotemporal assessment of high and low function areas on volumetric non-contrast CT scan.

Background: Aspiration community-acquired pneumonia (ACAP) and community-acquired pneumonia (CAP) in patients with aspiration risk factors (AspRFs) are infections associated with anaerobes, but limited evidence suggests their pathogenic role. Research Question: What are the aspiration risk factors, microbiology patterns, and empiric anti-anaerobic use in patients hospitalized with CAP? Study Design and Methods: This is a secondary analysis of GLIMP, an international, multicenter, point-prevalence study of adults hospitalized with CAP. Patients were stratified into three groups: (1) ACAP, (2) CAP/AspRF+ (CAP with AspRF), and (3) CAP/AspRF- (CAP without AspRF). Data on demographics, comorbidities, microbiological results, and anti-anaerobic antibiotics were analyzed in all groups. Patients were further stratified in severe and nonsevere CAP groups. Results: We enrolled 2,606 patients with CAP, of which 193 (7.4%) had ACAP. Risk factors independently associated with ACAP were male, bedridden, underweight, a nursing home resident, and having a history of stroke, dementia, mental illness, and enteral tube feeding. Among non-ACAP patients, 1,709 (70.8%) had CAP/AspRF+ and 704 (29.2%) had CAP/AspRF-. Microbiology patterns including anaerobes were similar between CAP/AspRF-, CAP/AspRF+ and ACAP (0.0% vs 1.03% vs 1.64%). Patients with severe ACAP had higher rates of total gram-negative bacteria (64.3% vs 44.3% vs 33.3%, P =.021) and lower rates of total gram-positive bacteria (7.1% vs 38.1% vs 50.0%, P 50% in all groups) independent of AspRFs or ACAP received specific or broad-spectrum anti-anaerobic coverage antibiotics. Interpretation: Hospitalized patients with ACAP or CAP/AspRF+ had similar anaerobic flora compared with patients without aspiration risk factors. Gram-negative bacteria were more prevalent in patients with severe ACAP. Despite having similar microbiological flora between groups, a large proportion of CAP patients received anti-anaerobic antibiotic coverage.

SESSION TITLE: Respiratory Infections: What have We Learned About COVID-19 and New Trial Data for Management of Aspergilloma SESSION TYPE: Original Investigations PRESENTED ON: October 18-21, 2020 PURPOSE: Early clinical observations of novel coronavirus-associated Acute Respiratory Distress Syndrome (C-ARDS) reported a higher than expected compliance discordant to the degree of hypoxemia Our goal was to evaluate survival of patients with C-ARDS according to different lung mechanical parameters METHODS: We conducted a prospective, observational study of C-ARDS patients admitted to the ICU at a tertiary care hospital in Michigan (March 1st to May 1st, 2020) Subjects were enrolled at the time of intubation and followed until death or discharge The average lung compliance (AvC) measured in ml/cm H2O and the ratio of arterial oxygen partial pressure to fractional inspired oxygen (P/F ratio) were calculated daily over the first 7 days post-intubation Median differences in AvC and P/F ratio between alive and deceased participants were calculated using Wilcoxon Rank Sum Pearson correlation was used to describe the relationship between AvC and P/F ratio Multivariate logistic regression was performed to explain co-variate effect after adjustment Survival function was performed using the Kaplan-Meier estimator for different levels of AvC RESULTS: 135 patients were included;mortality was 41 4% (n=56) Baseline demographics were similar between the survivor and deceased groups, except for hypertension and coronary artery disease (CAD) trending towards significance in the latter Survivors had longer length of stay (34 7 days vs 17 6 days;p = 0 001) There was no significant correlation between AvC and P/F ratio (Pearson's r 0 09;p=0 31) Surviving and deceased patients had different median P/F values (185 [IQR 242 to 135] vs 150 [IQR 196 to 109];p=0 01), but did not differ significantly in terms of median AvC (29 [IQR 35 to 26] vs 31 [IQR 37 to 24];p 0 69) There was no difference in survival curves between AvC levels of 35, 40 and 45 A multivariate logistic regression analysis was done to adjust for gender, BMI, hypertension, coronary artery disease and ventilator length of stay Only age [OR =1 05, 95% CI: 1 02, 1 08, p 0 003] and PF value [OR = 0 98, 95% CI: 0 98, 0 99, p 0 001] were significant risk factors for mortality CONCLUSIONS: Our results suggest that low P/F ratio and advanced age are the most significant independent predictors of mortality in C-ARDS The severity of hypoxemia did not correlate significantly with lung elasticity, and lung compliance was not predictive of mortality Our findings are consistent with other reports on lung mechanics in C-ARDS (Schenck et al) CLINICAL IMPLICATIONS: As with typical ARDS, degree of hypoxemia at the onset of respiratory failure may have prognostic implications in patients with C-ARDS Pulmonary compliance by itself does not predict risk of mortality DISCLOSURES: No relevant relationships by Abdulgadir Adam, source=Web Response No relevant relationships by Paul Bozyk, source=Web Response No relevant relationships by Enrique Calvo Ayala, source=Web Response No relevant relationships by Edward Castillo, source=Web Response No relevant relationships by christopher Dado, source=Web Response No relevant relationships by Bhavinkumar Dalal, source=Web Response Removed 04/27/2020 by Bhavinkumar Dalal, source=Web Response No relevant relationships by Bhavinkumar Dalal, source=Web Response Removed 04/27/2020 by Bhavinkumar Dalal, source=Web Response No relevant relationships by Bhavinkumar Dalal, source=Web Response Removed 04/27/2020 by Bhavinkumar Dalal, source=Web Response No relevant relationships by Bhavinkumar Dalal, source=Web Response Removed 04/27/2020 by Bhavinkumar Dalal, source=Web Response No relevant relationships by Sanjay Dogra, source=Web Response No relevant relationships by Giovi Grasso-Knight, source=Web Response No relevant relationships by Zaid Imam, source=Web Response No relevant relationships by Filip Ionescu, source=Web Response No relevan relationships by Daniel Keena, source=Web Response No relevant relationships by Nader Mina, source=Web Response No relevant relationships by Ehsun Naeem, source=Web Response Speaker/Speaker's Bureau relationship with Boehringer Ingelheim Please note: $5001 - $20000 by Girish Nair, source=Web Response, value=Honoraria Speaker/Speaker's Bureau relationship with GlaxoSmithKline Please note: $20001 - $100000 Added 05/31/2020 by Vishal Patel, source=Web Response, value=Consulting fee

While the world is grappling with the consequences of a global pandemic related to SARS-CoV-2 causing severe pneumonia, available evidence points to bacterial infection with Streptococcus pneumoniae as the most common cause of severe community acquired pneumonia (SCAP). Rapid diagnostics and molecular testing have improved the identification of co-existent pathogens. However, mortality in patients admitted to ICU remains staggeringly high. The American Thoracic Society and Infectious Diseases Society of America have updated CAP guidelines to help streamline disease management. The common theme is use of timely, appropriate and adequate antibiotic coverage to decrease mortality and avoid drug resistance. Novel antibiotics have been studied for CAP and extend the choice of therapy, particularly for those who are intolerant of, or not responding to standard treatment, including those who harbor drug resistant pathogens. In this review, we focus on the risk factors, microbiology, site of care decisions and treatment of patients with SCAP.

A hypercoagulable state has been described in coronavirus disease 2019 (COVID-19) patients. Others have reported a survival advantage with prophylactic anticoagulation (pAC) and therapeutic anticoagulation (tAC), but these retrospective analyses have important limitations such as confounding by indication. We studied the impact of tAC and pAC compared with no anticoagulation (AC) on time to death in COVID-19. We performed a cross-sectional analysis of 127 deceased COVID-19 patients and compared time to death in those who received tAC (n = 67), pAC (n = 47), and no AC (n = 13). Median time to death was longer with higher doses of AC (11 days for tAC, 8 days for pAC, and 4 days for no AC, p

Purpose Limited diagnostic options exist for patients with suspected pulmonary embolism (PE) who cannot undergo CT-angiogram (CTA). CT-ventilation methods recover respiratory motion-induced lung volume changes as a surrogate for ventilation. We recently demonstrated that pulmonary blood mass change, induced by tidal respiratory motion, is a potential surrogate for pulmonary perfusion. In this study, we examine blood mass and volume change in patients with PE and parenchymal lung abnormalities (PLA). Methods A cross-sectional analysis was conducted on a prospective, cohort-study with 129 consecutive PE suspected patients. Patients received 4DCT within 48 h of CTA and were classified as having PLA and/or PE. Global volume change (VC) and percent global pulmonary blood mass change (PBM) were calculated for each patient. Associations with disease type were evaluated using quantile regression. Results 68 of 129 patients were PE positive on CTA. Median change in PBM for PE-positive patients (0.056; 95% CI: 0.045, 0.068; IQR: 0.051) was smaller than that of PE-negative patients (0.077; 95% CI: 0.064, 0.089; IQR: 0.056), with an estimated difference of 0.021 (95% CI: 0.003, 0.038; p = 0.0190). PLA was detected in 57 (44.2%) patients. Median VC for PLA-positive patients (1.26; 95% CI: 1.22, 1.30; IQR: 0.15) showed no significant difference from PLA-negative VC (1.25; 95% CI: 1.21, 1.28; IQR: 0.15). Conclusions We demonstrate that pulmonary blood mass change is significantly lower in PE-positive patients compared to PE-negative patients, indicating that PBM derived from dynamic non-contrast CT is a potentially useful surrogate for pulmonary perfusion.

Introduction: Arterial and venous thromboembolism are common complications in COVID-19. Micro-macro thrombosis-related organ dysfunction can confer an increased risk for mortality. The optimal dosage of anticoagulation (AC) in COVID-19 patients remains unclear. Interim data from adaptive randomized control trials (ATTACC, REMAP-CAP, and ACTIV-4a) showed divergent results of therapeutic AC (TAC) versus usual care AC for the primary outcome of organ support free days in hospitalized COVID-19 patients. Components of CHA 2DS 2-VASc, a model originally built for predicting ischemic stroke in atrial fibrillation, are consistent with independent risk factors for COVID-19 severity and mortality. Herein, we analyzed the performance of the CHA 2DS 2-VASc model in hospitalized COVID-19 patients for predicting arterial and venous thromboembolic events, which could potentially aid in risk stratification of hospitalized patients and guide AC dosing. Methods: This is a large, retrospective, multicenter cohort study that included all adult patients from one tertiary care and five community hospitals with PCR-proven SARS-CoV-2 infection between 3/1/2020 and 12/1/2020. The primary composite outcome was acute arterial thromboembolism (ATE) and venous thromboembolism (VTE). We identified patients with ATE [cerebrovascular accident (CVA), myocardial infarction (MI) including both ST-segment elevation MI and non-ST-segment elevation MI], and VTE [deep vein thrombosis (DVT) and pulmonary embolism (PE)] using ICD -10 codes. Mean and standard deviation were reported for continuous variables; proportions were reported for categorical variables. To compare the groups, the Chi-square test was used for categorical variables, and the t-test was used for continuous variables. CHA 2DS 2-VASc scores were calculated on admission and were used as a measure of the predictive accuracy of the scoring system. Sensitivity and specificity with different cut-offs of CHA 2DS 2-VASc scores were calculated. All statistical tests were 2-sided with an α (significance) level of 0.05. All data were analyzed using R version 4.0.5. Results: Among 3526 patients, a total of 619 patients had thromboembolic events: 383 had ATE and 236 had VTE. Of 383 patients who had ATE, 350 patients were found to have acute MI, 48 had CVA, and 15 had both MI and CVA. In patients with VTE, 134 had DVT, 168 had PE, and 66 had both DVT and PE (Figure 1). We analyzed the primary composite outcome of ATE and VTE (group 1) vs no ATE and VTE (group 2). Baseline characteristics are included in Table 1. The in-patient all-cause mortality rate was 28.4% in group 1 vs 12.6% in group 2 (p Conclusion: Our results suggest that the CHA 2DS 2-VASc model for arterial and venous thromboembolism has a moderate performance. The CHA 2DS 2-VASc score of 5 has a high specificity, though low sensitivity, for predicting thromboembolism. The CHA 2DS 2-VASc score can be used as an adjunct risk stratification tool to initiate TAC. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Background: Hypercoagulability may contribute to COVID-19 pathogenicity. Evidence comparing clinical outcomes among patients with COVID-19 receiving therapeutic compared to prophylactic dose anticoagulation is limited. We evaluated whether therapeutic anticoagulation (tAC) is associated with improved survival compared to prophylactic (pAC) and no anticoagulation (AC) in hospitalized COVID-19 patients. Methods: This was a retrospective, multi-center cohort study of consecutive COVID-19 patients admitted between March 13th, 2020 and May 5th, 2020 to eight hospitals within a large academic system in Southeast Michigan, USA. Participants were assigned to three groups based on whether they received no AC, pAC throughout most of their hospitalization, or at least 3 days of tAC. Major bleeding was defined as transfusion of five or more units of packed red blood cells within 48 hours regardless of hemoglobin level, hemoglobin < 7g/dL and any red blood cell transfusion or a diagnosis code for major bleeding during the hospitalization or radiological evidence of intracranial hemorrhage Results: A total of 3480 patients were included (mean age, 64.5 years [17.0]; 51.5% female; 52.1% black and 40.6% white). 18.5% (n=642) were treated in the intensive care unit (ICU). 60.9% received pAC (n=2121), 28.7% received at least 3 days of tAC (n=998), and 10.4% (n=361) did not receive AC. Propensity score (PS) weighted Kaplan-Meier plot demonstrated a statistical difference in the 25-day survival probability in the tAC group compared to the pAC group (57.5% vs 50.7%, Figure). In a PS weighted multivariate proportional hazards model adjusting for age, body mass index and ICU status, AC was associated with a reduced risk of death at both prophylactic (hazard ratio [HR] 0.35 [95% confidence interval {CI} 0.22-0.54]) and therapeutic doses (HR 0.14 [95% CI 0.05-0.23]) compared to no AC. Major bleeding occurred more frequently among tAC patients (81 [8.1%]) compared to those who received no AC (20 [5.5%]) or pAC (46 [2.2%]). Conclusions : Higher doses of AC are associated with lower mortality in hospitalized COVID-19 patients. The lowest hazard ratio was observed in ICU patients, but risk was also significantly lower in non-ICU hospitalized patients. Bleeding occurred more frequently with higher doses of anticoagulation. Ongoing randomized trials are warranted to prospectively evaluate efficacy and risk of tAC in patients with COVID-19. Figure Disclosures No relevant conflicts of interest to declare.

Pneumonia is a leading cause of hospital-acquired infections, although reported rates of ventilator-associated pneumonia (VAP) have been declining in recent years. A multifaceted infection prevention approach, using a “ventilator bundle,” has been shown to reduce the frequency of VAP, while improving other patient outcomes. Because of difficulties in defining VAP, the Center for Medicare and Medicaid Service introduced a new streamlined ventilator-associated event (VAE) definition in 2013 for the surveillance of complications in mechanically ventilated patients. VAE measures are increasingly being measured by institutions in the United States in place of VAP rates and as a potential measure of the quality of intensive care unit (ICU) care. However, there is increased recognition that the streamlined definitions identify a different subset of patients than those identified by traditional VAP surveillance and that VAP prevention strategies may not impact all the causes of VAE. Also, VAP and VAE rates may not always reflect the quality of care in a given ICU, especially since patient factors, beyond the control of the hospital, may impact the rates of VAP and VAE. In this review, we discuss the issues related to VAP as a quality measure and the areas of uncertainty related to the new VAE definitions.

Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease with a fatal prognosis. Over the last decade, the concepts in pathobiology of pulmonary fibrosis have shifted from a model of chronic inflammation to dysregulated fibroproliferative repair in genetically predisposed patients. Although new breakthrough treatments are now available that slow the progression of the disease, several newer anti-inflammatory and anti-fibrotic drugs are under investigation. Patients with IPF often have coexistent conditions; prompt detection and interventions of which may improve the overall outcome of patients with IPF. Here, we summarize the present understanding of pathogenesis of IPF and treatment options for IPF in the current landscape of new anti-fibrotic treatment options.

We previously reported that apparent lung mass varies across the phases of 4D computed tomography (4DCT) images. We hypothesize that these variations correspond to the physiologic changes in pulmonary perfusion induced during normal tidal breathing, and should therefore be present in every breathing patient. In this study, we characterize and quantify the respiratory induced variation in pulmonary blood mass (▵PBM) on 89 patients treated with stereotactic body radiotherapy. ▵PBM was computed from the treatment planning helical 4DCT images of each patient. Conversion from Hounsfield Units (HU) to density and mass per voxel was made using the density calibration curve, applied to the lung parenchyma volume within each phase. A difference in the lung mass with breathing was found for all cases, as was a substantial individual variation in lung volume. We found that the ▵PBM increased during inhalation, and decreased during exhalation. A significant correlation between the individual ▵PBM and tidal volume was observed; ▵PBM increased with tidal volume. We further evaluated the anatomic distribution of ▵PBM variation comparing the central versus peripheral lung, cranial versus caudal, dependent versus non-dependent lung. Our observations regarding spatial distribution of the ▵PBM agree with previously reported differences among similar regions for the supine patient. These results show that a variation in pulmonary mass during respiration is apparent on 4DCT and suggest that these variations reflect respiratory induced changes in the pulmonary perfusion. Therefore, the 4DCT derived respiratory induced ▵PBM signal can provide further insight into the pulmonary circulation and advance the overall understanding and diagnosis of human health and disease.