AIMC Topic: Forced Expiratory Volume

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Efficacy and safety of lebrikizumab in adult patients with mild-to-moderate asthma not receiving inhaled corticosteroids.

Respiratory medicine Dec 13, 2017
BACKGROUND: Asthma is a heterogeneous and complex disease in both its clinical course and response to treatment. IL-13 is central to Type 2 inflammation and contributes to many features of asthma. In a previous Phase 2 study, lebrikizumab, an anti-IL...
Quinolines Acetates Female Administration, Inhalation Sulfides Adult Anti-Asthmatic Agents Treatment Failure Asthma Antibodies, Monoclonal Humans Double-Blind Method Forced Expiratory Volume Severity of Illness Index Injections, Subcutaneous Male Treatment Outcome Middle Aged Cyclopropanes Glucocorticoids
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A randomised, phase III trial of once-daily fluticasone furoate/vilanterol 100/25 μg versus once-daily vilanterol 25 μg to evaluate the contribution on lung function of fluticasone furoate in the combination in patients with COPD.

Respiratory medicine Dec 2, 2016
BACKGROUND: The contribution of fluticasone furoate (FF) on lung function in the FF/vilanterol (VI) 100/25 μg combination has been demonstrated numerically, but not statistically.
Benzyl Alcohols Chlorobenzenes Aged Adult Humans Female Double-Blind Method Forced Expiratory Volume Drug Administration Schedule Androstadienes Adrenergic beta-2 Receptor Agonists Kaplan-Meier Estimate Administration, Inhalation Glucocorticoids Quality of Life Drug Combinations Pulmonary Disease, Chronic Obstructive Male Middle Aged
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Reductions in pulmonary function detected in patients with lymphangioleiomyomatosis: An analysis of the Japanese National Research Project on Intractable Diseases database.

Respiratory investigation Dec 22, 2015
BACKGROUND: In lymphangioleiomyomatosis (LAM), predicting lung disease progression is essential for treatment planning. However, no previous Japanese studies have attempted to predict the reductions in pulmonary function that occur in LAM patients.
Lymphangioleiomyomatosis Male Middle Aged Lung Neoplasms Databases as Topic Statistics as Topic Forced Expiratory Volume Japan Pregnancy Female Adult Humans
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Deep Learning-Based Chronic Obstructive Pulmonary Disease Exacerbation Prediction Using Flow-Volume and Volume-Time Curve Imaging: Retrospective Cohort Study.

Journal of medical Internet research May 15, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common and progressive respiratory condition characterized by persistent airflow limitation and symptoms such as dyspnea, cough, and sputum production. Acute exacerbations (AE) of COPD (AE...
Retrospective Studies Female Aged Humans Disease Progression Deep Learning Forced Expiratory Volume Spirometry Pulmonary Disease, Chronic Obstructive Male Middle Aged
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Sputum Neutrophil Gelatinase-Associated Lipocalin as a Biomarker in Asthma-COPD Overlap.

The Journal of the Association of Physicians of India Sep 1, 2023
BACKGROUND: Asthma COPD overlap (ACO) is a consensus-based phenotype having characteristics of both COPD and asthma. Distinguishing ACO from other diseases is even more important as it is related to low health-related quality of life, augmented exace...
Asthma-Chronic Obstructive Pulmonary Disease Overlap Syndrome Forced Expiratory Volume Asthma Male Middle Aged Aged Humans Case-Control Studies Lipocalin-2 Adult Biomarkers Neutrophils Sputum Pulmonary Disease, Chronic Obstructive Female
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Area under the expiratory flow-volume curve: predicted values by regression and deep learning methods and recommendations for clinical practice.

BMJ open respiratory research Apr 1, 2021
BACKGROUND: In spirometry, the area under expiratory flow-volume curve (AEX-FV) was found to perform well in diagnosing and stratifying physiologic impairments, potentially lessening the need for complex lung volume testing. Expanding on prior work, ...
Spirometry Vital Capacity Area Under Curve Humans Forced Expiratory Volume Deep Learning
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Unsupervised learning technique identifies bronchiectasis phenotypes with distinct clinical characteristics.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease Mar 1, 2016
BACKGROUND: Unsupervised learning technique allows researchers to identify different phenotypes of diseases with complex manifestations.
Phenotype Prospective Studies Female Humans Anti-Bacterial Agents Male Middle Aged Quality of Life Cohort Studies Risk Factors Aged Adult Forced Expiratory Volume Pseudomonas aeruginosa Bronchiectasis Unsupervised Machine Learning Cough Sputum Body Mass Index Follow-Up Studies Cluster Analysis
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