4.6 Article

Standardisation and application of the single-breath determination of nitric oxide uptake in the lung

Journal

EUROPEAN RESPIRATORY JOURNAL
Volume 49, Issue 2, Pages -

Publisher

EUROPEAN RESPIRATORY SOC JOURNALS LTD
DOI: 10.1183/13993003.00962-2016

Keywords

-

Funding

  1. European Respiratory Society [TF-2014-24]

Ask authors/readers for more resources

Diffusing capacity of the lung for nitric oxide (DLNO), otherwise known as the transfer factor, was first measured in 1983. This document standardises the technique and application of single-breath DLNO. This panel agrees that 1) pulmonary function systems should allow for mixing and measurement of both nitric oxide (NO) and carbon monoxide (CO) gases directly from an inspiratory reservoir just before use, with expired concentrations measured from an alveolar collection or continuously sampled via rapid gas analysers; 2) breath-hold time should be 10 s with chemiluminescence NO analysers, or 4-6 s to accommodate the smaller detection range of the NO electrochemical cell; 3) inspired NO and oxygen concentrations should be 40-60 ppm and close to 21%, respectively; 4) the alveolar oxygen tension (PAO(2)) should be measured by sampling the expired gas; 5) a finite specific conductance in the blood for NO (theta NO) should be assumed as 4.5 mL.min(-1) . mmHg(-1) . mL(-1) of blood; 6) the equation for 1/theta CO should be (0.0062 . PAO(2)+1.16) . (ideal haemoglobin/measured haemoglobin) based on breath-holding PAO(2) and adjusted to an average haemoglobin concentration (male 14.6 g.dL(-1), female 13.4 g.dL(-1)); 7) a membrane diffusing capacity ratio (DMNO/DMCO) should be 1.97, based on tissue diffusivity.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Mathematical & Computational Biology

Predicting the onset of breast cancer using mammogram imaging data with irregular boundary

Shu Jiang, Jiguo Cao, Graham A. Colditz, Bernard Rosner

Summary: With mammography as the primary screening strategy for breast cancer, it is important to utilize mammogram imaging data to identify women at different risk levels. This study proposes a supervised functional principal component analysis method for extracting features from mammogram images, which improves prediction accuracy. The method effectively addresses the irregular boundary issue and shows better performance compared to unsupervised methods in simulation studies.

BIOSTATISTICS (2023)

Article Statistics & Probability

A Dynamic Interaction Semiparametric Function-on-Scalar Model

Hua Liu, Jinhong You, Jiguo Cao

Summary: Motivated by recent work on massive functional data, this study proposes a new dynamic interaction semiparametric function-on-scalar (DISeF) model, which is useful to explore the dynamic interaction among a set of covariates and their effects on the functional response. The study develops an efficient estimation procedure to iteratively estimate the bivariate varying-coefficient functions, the index parameters, and the covariance functions of random effects. It also establishes the asymptotic properties of the estimators and develops a test statistic to check the variability of the dynamic interaction.

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2023)

Article Biology

Supervised two-dimensional functional principal component analysis with time-to-event outcomes and mammogram imaging data

Shu Jiang, Jiguo Cao, Bernard Rosner, Graham A. Colditz

Summary: Screening mammography is a method to detect breast cancer early, and it measures breast density to predict future cancer risk. This article introduces flexible methods, supervised FPCA and functional partial least squares, to extract image-based features associated with failure time while considering right censoring. The proposed methods outperform benchmark models in terms of prediction performance and reveal different risk patterns within mammograms.

BIOMETRICS (2023)

Article Statistics & Probability

Deep Learning With Functional Inputs

Barinder Thind, Kevin Multani, Jiguo Cao

Summary: This article presents a methodology for integrating functional data into deep neural networks. The method not only accurately predicts new data, but also recovers the true underlying relationship between functional covariates and scalar responses. The authors have also developed an R package that enables easy implementation of the approach.

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2023)

Article Biology

Computational Efficiency and Precision for Replicated-Count and Batch-Marked Hidden Population Models

Matthew R. P. Parker, Laura L. E. Cowen, Jiguo Cao, Lloyd T. Elliott

Summary: This research addresses computational issues in open-population N-mixture models and proposes methods using fast Fourier transform and improved numerical stability. By comparing with standard methods, it demonstrates the advantages of these methods in terms of computational efficiency and precision.

JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS (2023)

Article Respiratory System

Respiratory recovery trajectories after severe-to-critical COVID-19: a 1-year prospective multicentre study

Frederic Schlemmer, Simon Valentin, Laurent Boyer, Anne Guillaumot, Francois Chabot, Clairelyne Dupin, Pierre Le Guen, Gwenael Lorillon, Anne Bergeron, Damien Basille, Julia Delomez, Claire Andrejak, Valentine Bonnefoy, Helene Goussault, Jean-Baptiste Assie, Pascaline Choinier, Anne-Marie Ruppert, Jacques Cadranel, Maria Chiara Mennitti, Mehdi Roumila, Charlotte Colin, Sven Gunther, Olivier Sanchez, Thomas Gille, Lucile Sese, Yurdagul Uzunhan, Morgane Faure, Maxime Patout, Capucine Morelot-Panzini, Pierantonio Laveneziana, Maeva Zysman, Elodie Blanchard, Chantal Raherison-Semjen, Violaine Giraud, Etienne Giroux-Leprieur, Stefanie Habib, Nicolas Roche, Anh Tuan Dinh-Xuan, Islem Sifaoui, Pierre-Yves Brillet, Camille Jung, Emmanuelle Boutin, Richard Layese, Florence Canoui-Poitrine, Bernard Maitre

Summary: This pragmatic study aimed to describe the clinical follow-up and respiratory recovery trajectories of survivors of severe-to-critical COVID-19, as well as identify factors influencing their health-related quality of life. The results showed that although pulmonary function and radiological abnormalities improved up to 1 year post-acute COVID-19, a high percentage of severe-to-critical disease survivors had significant lung sequelae and residual symptoms, warranting prolonged follow-up.

EUROPEAN RESPIRATORY JOURNAL (2023)

Article Respiratory System

Outcome prediction model and prognostic biomarkers for COVID-19 patients in Vietnam

Hien Thi Thu Nguyen, Vang Le-Quy, Son Van Ho, Jakob Holm Dalsgaard Thomsen, Malene Pontoppidan Stoico, Hoang Van Tong, Nhat-Linh Nguyen, Henrik Bygum Krarup, Son Hong Nguyen, Viet Quoc Tran, Linh Toan Nguyen, Anh Tuan Dinh-Xuan

Summary: This study aims to predict the severity of COVID-19 based on clinical and biological indicators, and identify biomarkers for prognostic assessment. The most important indicators were IL-6, ferritin, and D-dimer. Two different sets of biomarkers can be used for disease severity assessment and prognosis.

ERJ OPEN RESEARCH (2023)

Article Medical Laboratory Technology

The stability of blood gases and CO-oximetry under slushed ice and room temperature conditions

Gerald S. Zavorsky, Xander M. R. van Wijk

Summary: The objective of this study was to determine the stability of blood gases under different storage conditions using survival analyses. The results showed that pCO(2) and pH in blood samples remained stable for 60 minutes at room temperature and 3 hours in slushed ice. However, storing samples in slushed ice reduced the stability time for pO(2), especially when the baseline pO(2) was ≥60 mmHg. In conclusion, according to RCPA guidelines, blood gas and CO-oximetry panels can be stored for up to 40 minutes at room temperature.

CLINICAL CHEMISTRY AND LABORATORY MEDICINE (2023)

Letter Respiratory System

Implications of the new ERS/ATS standards on the interpretation of lung function tests

Paul Desbordes, Maarten De Vos, Julie Maes, Frans de Jongh, Karl Sylvester, Claus Franz Vogelmeier, Anh Tuan Dinh-Xuan, Jann Mortensen, Wim Janssens, Marko Topalovic

EUROPEAN RESPIRATORY JOURNAL (2023)

Article Respiratory System

Collaboration between explainable artificial intelligence and pulmonologists improves the accuracy of pulmonary function test interpretation

Nilakash Das, Sofie Happaerts, Iwein Gyselinck, Michael Staes, Eric Derom, Guy Brusselle, Felip Burgos, Marco Contoli, Anh Tuan Dinh-Xuan, Frits M. E. Franssen, Sherif Gonem, Neil Greening, Christel Haenebalcke, William D-C. Man, Jorge Moises, Rudi Peche, Vitalii Poberezhets, Jennifer K. Quint, Michael C. Steiner, Eef Vanderhelst, Mustafa Abdo, Marko Topalovic, Wim Janssens

Summary: Collaboration between pulmonologists and explainable AI (XAI) is superior in diagnosing pulmonary function tests (PFTs) compared to individual pulmonologists or XAI alone. XAI's suggestions improve accuracy, confidence, and inter-rater agreement of pulmonologists. Therefore, the collaboration between pulmonologists and XAI is crucial for interpreting PFTs.

EUROPEAN RESPIRATORY JOURNAL (2023)

Article Rheumatology

Prognostic value of automated assessment of interstitial lung disease on CT in systemic sclerosis

Aelle Le Gall, Trieu-Nghi Hoang-Thi, Raphael Porcher, Bertrand Dunogue, Alice Berezne, Loic Guillevin, Veronique Le Guern, Pascal Cohen, Benjamin Chaigne, Jonathan London, Matthieu Groh, Romain Paule, Guillaume Chassagnon, Maria Vakalopoulou, Anh-Tuan Dinh-Xuan, Marie Pierre Revel, Luc Mouthon, Alexis Regent

Summary: A deep-learning-based algorithm for automated quantification of ILD on HRCT can effectively assess the extent of ILD and predict the risk of death in SSc patients.

RHEUMATOLOGY (2023)

Article Health Care Sciences & Services

GINA Implementation Improves Asthma Symptoms Control and Lung Function: A Five-Year Real-World Follow-Up Study

Nguyen Van Tho, Vu Tran Thien Quan, Do Van Dung, Nguyen Hoang Phu, Anh Tuan Dinh-Xuan, Le Thi Tuyet Lan

Summary: This study evaluated the level of asthma symptoms control and lung function over 5 years of GINA implementation. The results showed that asthma symptoms control and lung function improved after 3 months and the improvement was sustained over 5 years in patients managed according to GINA recommendations.

JOURNAL OF PERSONALIZED MEDICINE (2023)

Article Health Care Sciences & Services

COPD Patients with Asthma Features in Vietnam: Prevalence and Suitability for Personalized Medicine

Nguyen Van Tho, Thu Phuong Phan, Anh Tuan Dinh-Xuan, Quy Chau Ngo, Le Thi Tuyet Lan

Summary: The study aimed to estimate the proportion of COPD patients with asthma features and compare the clinical characteristics and medication use between COPD patients with asthma features and those with COPD alone. A cross-sectional study conducted in Vietnam found that 27.3% of COPD patients had asthma features. These patients were younger, had higher FEV1 values, a higher proportion of positive bronchodilator reversibility tests, higher blood eosinophil count, and were more often treated with ICS/LABA.

JOURNAL OF PERSONALIZED MEDICINE (2023)

Review Respiratory System

Holistic management of patients with progressive pulmonary fibrosis

Ana Oliveira, Gaia Fabbri, Thomas Gille, Elena Bargagli, Boris Duchemann, Rachel Evans, Hilary Pinnock, Anne E. Holland, Elisabetta Renzoni, Magnus Ekstrom, Steve Jones, Marlies Wijsenbeek, Anh Tuan Dinh-Xuan, Guido Vagheggini

Summary: This article summarizes the main needs of patients with progressive pulmonary fibrosis (PF) and their caregivers and proposes a supportive care approach. Personalized care, education, emotional and psychological support, specialized treatments, and better access to information and resources are necessary. Treatment should start at diagnosis and be tailored to the patient's needs, including individualized pharmacological and non-pharmacological interventions such as oxygen therapy and pulmonary rehabilitation.

BREATHE (2023)

Article Statistics & Probability

Jointly modelling multiple transplant outcomes by a competing risk model via functional principal component analysis

Jianghu (James) Dong, Haolun Shi, Liangliang Wang, Ying Zhang, Jiguo Cao

Summary: Longitudinal biomarkers are commonly used in clinical studies to monitor disease progression. This study develops a joint model that utilizes functional principal component analysis to extract features from longitudinal trajectories and employs a competing risk model to handle multiple time-to-event outcomes.

JOURNAL OF APPLIED STATISTICS (2023)

No Data Available