Chest
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The purpose of this review was to describe our management approach to patients with treatment-emergent central sleep apnea (TECSA). The emergence of central sleep apnea during positive airway pressure therapy occurs in approximately 8% of titration studies for OSA, and it has been associated with several demographic, clinical, and polysomnographic factors, as well as factors related to the titration study itself. TECSA shares similar pathophysiology with central sleep apnea. ⋯ CPAP therapy remains a standard therapy for TECSA. Expectant management is appropriate given its transient nature in most cases, whereas select patients would benefit from an early switch to an alternative positive airway pressure modality. Other treatment options include supplemental oxygen and pharmacologic therapy.
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Randomized Controlled Trial
Endobronchial Ultrasound Staging of Operable NSCLC: Do Triple Normal Lymph Nodes Require Routine Biopsy?
Staging guidelines for lung cancer recommend endobronchial ultrasound (EBUS) and systematic biopsy of at least three mediastinal lymph node (LN) stations for accurate staging. A four-point ultrasonographic score (Canada Lymph Node Score [CLNS]) was developed to determine the probability of malignancy in each LN. A LN with a CLNS of < 2 is considered low probability for malignancy. We hypothesized that, in patients with cN0 non-small cell lung cancer, LNs with CLNS of < 2 may not require routine biopsy because they represent true node-negative disease. ⋯ At the time of staging for lung cancer, combining CT scanning, PET scanning, and CLNS criteria can identify triple-normal LNs that have a high NPV for malignancy. This raises the question of whether triple-normal LNs require routine sampling during EBUS and transbronchial needle aspiration. A prospective trial is required to confirm these findings.
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COPD is a clinically heterogeneous syndrome characterized by injury to airways, airspaces, and lung vasculature and usually caused by tobacco smoke and/or air pollution exposure. COPD is also independently associated with nonpulmonary comorbidities (eg, cardiovascular disease) and malignancies (eg, GI, bladder), suggesting a role for systemic injury. Since not all those with exposure develop COPD, there has been a search for plasma and lung biomarkers that confer increased cross-sectional and longitudinal risk. ⋯ The prototypic COPD protein biomarker is alpha-1 antitrypsin; however, this biomarker only accounts for 1% to 5% of COPD. This article reviews and summarizes the evidence for other validated biomarkers for each COPD outcome, and discusses their advantages, weaknesses, and required regulatory steps to move the biomarker from the bench into clinic. Although we highlight the emergence of many novel biomarkers (eg, fibrinogen, soluble receptor for advanced glycation, surfactant protein D, club cell secretory protein), there is increasing evidence that individual biomarkers only explain a fraction of the increased COPD risk and that multiple biomarker panels are needed to completely explain clinical variation and risk in individuals and populations.
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Observational Study
Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation.
Objective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation (MV) may aid in delivering timely treatment. ⋯ A transparent deep learning algorithm improves on traditional clinical criteria to predict the need for MV in hospitalized patients, including in those with COVID-19. Such an algorithm may help clinicians to optimize timing of tracheal intubation, to allocate resources and staff better, and to improve patient care.
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To assess airway and lung parenchymal damage noninvasively in cystic fibrosis (CF), chest MRI has been historically out of the scope of routine clinical imaging because of technical difficulties such as low proton density and respiratory and cardiac motion. However, technological breakthroughs have emerged that dramatically improve lung MRI quality (including signal-to-noise ratio, resolution, speed, and contrast). At the same time, novel treatments have changed the landscape of CF clinical care. ⋯ Moreover, functional information from MRI can be used to assess regional, small-airway disease with sensitivity to detect small changes even in patients with mild CF. Finally, automated quantification methods have emerged to support conventional visual analyses for more objective and reproducible assessment of disease severity. This article aims to review the most recent developments of lung MRI, with a focus on practical application and clinical value in CF, and the perspectives on how these modern techniques may converge and impact patient care soon.