scholarly journals Erratum: Automated CT Staging of Chronic Obstructive Pulmonary Disease Severity for Predicting Disease Progression and Mortality with a Deep Learning Convolutional Neural Network

2022 ◽  
Vol 4 (1) ◽  
Author(s):  
Kyle A. Hasenstab ◽  
Nancy Yuan ◽  
Tara Retson ◽  
Douglas J. Conrad ◽  
Seth Kligerman ◽  
...  
Keyword(s):  
Neural Network ◽  
Chronic Obstructive Pulmonary Disease ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Disease Progression ◽  
Pulmonary Disease ◽  
Disease Severity ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease

scholarly journals A temporal visualization of chronic obstructive pulmonary disease progression using deep learning and unstructured clinical notes

2019 ◽  
Vol 19 (S8) ◽  
Author(s):  
Chunlei Tang ◽  
Joseph M. Plasek ◽  
Haohan Zhang ◽  
Min-Jeoung Kang ◽  
Haokai Sheng ◽  
...  
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Deep Learning ◽  
Disease Progression ◽  
Pulmonary Disease ◽  
Time Lapse ◽  
Chronic Obstructive ◽  
Allocation Model ◽  
Obstructive Pulmonary Disease ◽  
Clinical Notes ◽  
Copd Patients

Abstract Background Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients with COPD and to generate a temporal visualization that describes signs and symptoms during different stages of COPD progression. Methods We present a two-step approach for visualizing COPD progression at the level of unstructured clinical notes. We included 15,500 COPD patients who both received care within Partners Healthcare’s network and died between 2011 and 2017. We first propose a four-layer deep learning model that utilizes a specially configured recurrent neural network to capture irregular time lapse segments. Using those irregular time lapse segments, we created a temporal visualization (the COPD atlas) to demonstrate COPD progression, which consisted of representative sentences at each time window prior to death based on a fraction of theme words produced by a latent Dirichlet allocation model. We evaluated our approach on an annotated corpus of COPD patients’ unstructured pulmonary, radiology, and cardiology notes. Results Experiments compared to the baselines showed that our proposed approach improved interpretability as well as the accuracy of estimating COPD progression. Conclusions Our experiments demonstrated that the proposed deep-learning approach to handling temporal variation in COPD progression is feasible and can be used to generate a graphical representation of disease progression using information extracted from clinical notes.

Inspiratory muscle strength in chronic obstructive pulmonary disease depending on disease severity

2007 ◽  
Vol 113 (5) ◽  
pp. 243-249 ◽  
Author(s):  
Hans-Joachim Kabitz ◽  
Stephan Walterspacher ◽  
David Walker ◽  
Wolfram Windisch
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Muscle Strength ◽  
Pulmonary Disease ◽  
Disease Severity ◽  
Inspiratory Muscle ◽  
Walking Distance ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Copd Patients ◽  
Inspiratory Muscle Strength

Staging criteria for COPD (chronic obstructive pulmonary disease) include symptoms and lung function parameters, but the role of reduced inspiratory muscle strength related to disease severity remains unclear. Therefore the present study tested whether inspiratory muscle strength is reduced in COPD and is related to disease severity according to GOLD (Global Initiative for Chronic Obstructive Lung Disease) criteria and assessed its clinical impact. PImax (maximal inspiratory mouth occlusion pressure), SnPna (sniff nasal pressure) and TwPmo (twitch mouth pressure) following bilateral anterior magnetic phrenic nerve stimulation were assessed in 33 COPD patients (8 GOLD0, 6 GOLDI, 6 GOLDII, 7 GOLDIII and 6 GOLDIV) and in 28 matched controls. Furthermore, all participants performed a standardized 6 min walking test. In comparison with controls, PImax (11.6±2.5 compared with 7.3±3.0 kPa; P<0.001), SnPna (9.7±2.5 compared with 6.9±3.3 kPa; P<0.001) and TwPmo (1.6±0.6 compared with 0.8±0.4 kPa; P<0.001) were markedly lower in COPD patients. TwPmo decreased with increasing COPD stage. TwPmo was correlated with walking distance (r=0.75; P<0.001), dyspnoea (r=−0.61; P<0.001) and blood gas values following exercise (r>0.57; P<0.001). Inspiratory muscle strength, as reliably assessed by TwPmo, decreased with increasing severity of COPD and should be considered as an important factor in rating disease severity and to reflect burden in COPD.

A Correlational study on quality of life and disease severity among Chronic Obstructive Pulmonary Disease (COPD) clients attending a pulmonary Medicine OPD of a Tertiary care hospital, Kolkata

2021 ◽  
pp. 528-532
Author(s):  
Uma Rani Adhikari ◽  
Soma Roy
Keyword(s):  
Quality Of Life ◽  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Disease Severity ◽  
Tertiary Care ◽  
Chronic Obstructive ◽  
Pulmonary Medicine ◽  
Care Hospital ◽  
Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is recently the most common chronic lung disease and presents a serious medical, economic, and social problem for people. A correlational survey research was adopted to identify relationship between quality of life and disease severity among Chronic Obstructive Pulmonary Disease (COPD) clients attending Pulmonary Medicine OPD in a selected hospital, Kolkata with the objectives to assess the quality of life of Chronic Obstructive Pulmonary Disease (COPD) clients and to find out correlation between disease severity and quality of life among Chronic Obstructive Pulmonary Disease (COPD) clients. Purposive sampling technique was adapted to select 138 Chronic Obstructive Pulmonary Disease (COPD) clients attending Pulmonary Medicine OPD in a tertiary care hospital, Kolkata. The structured interview schedule was used to collect on demographic data and standardized WHO QOL BREF tool was used to assess Quality of Life. Standardized GOLD criteria were used to assess disease severity of COPD clients. Reliability of the demographic data collection tool was established by inter- rater method and r was 0.77. All the tools were tried out before final data collection. The finding of the study revealed statistically non-significant relationship between all the domain of QOL and disease severity of COPD patients. Total Quality of Life score is also not significantly related with COPD Disease severity score. The study results also showed that QOL is not associated with sociodemographic characteristics. The study concluded that, there is no correlation between quality of life and disease severity.

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