scholarly journals Maximum chest CT score is associated with progression to severe illness in patients with COVID-19: A retrospective study from Wuhan, China

2020 ◽  
Author(s):  
Jianwei Xiao ◽  
Xiang Li ◽  
Yuanliang Xie ◽  
Zengfa Huang ◽  
Yi Ding ◽  
...  
Keyword(s):  
Disease Progression ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
Severe Disease ◽  
Radiological Feature ◽  
Severe Illness ◽  
Chronic Obstructive ◽  
Limited Information ◽  
Obstructive Pulmonary Disease ◽  
Health Crisis

Abstract Background: The Coronavirus Disease 2019 (COVID-19) pandemic is a world-wide health crisis. Limited information is available regarding which patients will experience more severe disease symptoms. We evaluated hospitalized patients who were initially diagnosed with moderate COVID-19 for clinical parameters and radiological feature that showed an association with progression to severe/critical symptoms.Methods: This study, a retrospective single-center study at the Central Hospital of Wuhan, enrolled 243 patients with confirmed COVID­19 pneumonia. Forty of these patients progressed from moderate to severe/critical symptoms during follow up. Demographic, clinical, laboratory, and radiological data were extracted from electronic medical records and compared between moderate- and severe/critical-type symptoms. Univariable and multivariable logistic regressions were used to identify the risk factors associated with symptom progression.Results: Patients with severe/critical symptoms were older (p<0.001) and more often male (p=0.046). A combination of chronic obstructive pulmonary disease (COPD) and high maximum chest computed tomography (CT) score was associated with disease progression. Maximum CT score (>11) had the greatest predictive value for disease progression. The area under the receiver operating characteristic curve was 0.861 (95% confidence interval: 0.811-0.902).Conclusions: Maximum CT score and COPD were associated with patient deterioration. Maximum CT score (>11) was associated with severe illness.

scholarly journals Maximum chest CT score is associated with progression to severe illness in patients with COVID-19: a retrospective study from Wuhan, China

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jianwei Xiao ◽  
Xiang Li ◽  
Yuanliang Xie ◽  
Zengfa Huang ◽  
Yi Ding ◽  
...  
Keyword(s):  
Disease Progression ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
Severe Disease ◽  
Radiological Feature ◽  
Severe Illness ◽  
Chronic Obstructive ◽  
Limited Information ◽  
Obstructive Pulmonary Disease ◽  
Health Crisis

Abstract Background The Coronavirus Disease 2019 (COVID-19) pandemic is a world-wide health crisis. Limited information is available regarding which patients will experience more severe disease symptoms. We evaluated hospitalized patients who were initially diagnosed with moderate COVID-19 for clinical parameters and radiological feature that showed an association with progression to severe/critical symptoms. Methods This study, a retrospective single-center study at the Central Hospital of Wuhan, enrolled 243 patients with confirmed COVID­19 pneumonia. Forty of these patients progressed from moderate to severe/critical symptoms during follow up. Demographic, clinical, laboratory, and radiological data were extracted from electronic medical records and compared between moderate- and severe/critical-type symptoms. Univariable and multivariable logistic regressions were used to identify the risk factors associated with symptom progression. Results Patients with severe/critical symptoms were older (p < 0.001) and more often male (p = 0.046). A combination of chronic obstructive pulmonary disease (COPD) and high maximum chest computed tomography (CT) score was associated with disease progression. Maximum CT score (> 11) had the greatest predictive value for disease progression. The area under the receiver operating characteristic curve was 0.861 (95% confidence interval: 0.811–0.902). Conclusions Maximum CT score and COPD were associated with patient deterioration. Maximum CT score (> 11) was associated with severe illness.

scholarly journals Maximum chest CT score is associated with progression to severe illness in patients with COVID-19: A retrospective study from Wuhan, China

2020 ◽  
Author(s):  
Jianwei Xiao ◽  
Xiang Li ◽  
Yuanliang Xie ◽  
Zengfa Huang ◽  
Yi Ding ◽  
...  
Keyword(s):  
Disease Progression ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
Severe Disease ◽  
Radiological Feature ◽  
Severe Illness ◽  
Chronic Obstructive ◽  
Limited Information ◽  
Obstructive Pulmonary Disease ◽  
Health Crisis

Abstract Background: The Coronavirus Disease 2019 (COVID-19) pandemic is a world-wide health crisis. Limited information is available regarding which patients will experience more severe disease symptoms. We evaluated hospitalized patients who were initially diagnosed with moderate COVID-19 for clinical parameters and radiological feature that showed an association with progression to severe/critical symptoms. Methods: This study, a retrospective single-center study at the Central Hospital of Wuhan, enrolled 243 patients with confirmed COVID­19 pneumonia. Forty of these patients progressed from moderate to severe/critical symptoms during follow up. Demographic, clinical, laboratory, and radiological data were extracted from electronic medical records and compared between moderate- and severe/critical-type symptoms. Univariable and multivariable logistic regressions were used to identify the risk factors associated with symptom progression.Results: Patients with severe/critical symptoms were older (p<0.001) and more often male (p=0.046). A combination of chronic obstructive pulmonary disease (COPD) and high maximum chest computed tomography (CT) score was associated with disease progression. Maximum CT score (>11) had the greatest predictive value for disease progression. The area under the receiver operating characteristic curve was 0.861 (95% confidence interval: 0.811-0.902).Conclusions: Maximum CT score and COPD were associated with patient deterioration. Maximum CT score (>11) was associated with severe illness.

scholarly journals Maximum chest CT score predicts progression to severe illness in patients with COVID-19: a retrospective study from Wuhan, China

2020 ◽  
Author(s):  
Jianwei Xiao ◽  
Xiang Li ◽  
Yuanliang Xie ◽  
Zengfa Huang ◽  
Yi Ding ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Progression ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
Severe Illness ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Factors Associated ◽  
Radiological Data ◽  
Symptom Progression

Abstract Background: We investigated the clinical course and imaging findings of hospitalized patients who were initially diagnosed with moderate COVID-19 symptoms to identify risk factors associated with progression to severe/critical symptoms.Methods: This study was a retrospective single-center study at The Central Hospital of Wuhan. 243 patients with confirmed COVID­19 pneumonia were enrolled in the analysis, of which 40 patients progressed from moderate to severe/critical symptoms during follow up. Demographic, clinical, laboratory and radiological data were extracted from electronic medical records and compared between moderate and severe/critical symptom types. Univariable and multivariable logistic regressions were used to identify the risk factors associated with symptom progression.Results: Patients with severe/critical symptoms were older (p＜0.001) and more often male (p=0.046). We found that the combination of chronic obstructive pulmonary disease and high maximum CT scores was associated with disease progression. Maximum CT scores (≥11) had the greatest predictive value for disease progression. The area under the receiver operating characteristic curve (ROC) was 0.861 (95% CI: 0.811-0.902).Conclusions: Maximum CT scores and COPD are associated with patient deterioration. Maximum CT scores (≥11) are associated with severe illness.

scholarly journals Characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019

2020 ◽  
Vol 41 (22) ◽  
pp. 2070-2079 ◽  
Author(s):  
Shaobo Shi ◽  
Mu Qin ◽  
Yuli Cai ◽  
Tao Liu ◽  
Bo Shen ◽  
...  
Keyword(s):  
Clinical Significance ◽  
Myocardial Injury ◽  
Troponin I ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
Hospital Death ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Cardiovascular Comorbidities ◽  
High Level

Abstract Aims To investigate the characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019 (COVID-19). Methods and results We enrolled 671 eligible hospitalized patients with severe COVID-19 from 1 January to 23 February 2020, with a median age of 63 years. Clinical, laboratory, and treatment data were collected and compared between patients who died and survivors. Risk factors of death and myocardial injury were analysed using multivariable regression models. A total of 62 patients (9.2%) died, who more often had myocardial injury (75.8% vs. 9.7%; P &lt; 0.001) than survivors. The area under the receiver operating characteristic curve of initial cardiac troponin I (cTnI) for predicting in-hospital mortality was 0.92 [95% confidence interval (CI), 0.87–0.96; sensitivity, 0.86; specificity, 0.86; P &lt; 0.001]. The single cut-off point and high level of cTnI predicted risk of in-hospital death, hazard ratio (HR) was 4.56 (95% CI, 1.28–16.28; P = 0.019) and 1.25 (95% CI, 1.07–1.46; P = 0.004), respectively. In multivariable logistic regression, senior age, comorbidities (e.g. hypertension, coronary heart disease, chronic renal failure, and chronic obstructive pulmonary disease), and high level of C-reactive protein were predictors of myocardial injury. Conclusion The risk of in-hospital death among patients with severe COVID-19 can be predicted by markers of myocardial injury, and was significantly associated with senior age, inflammatory response, and cardiovascular comorbidities.

scholarly journals Clinical Determinants of Disease Progression in Amyotrophic Lateral Sclerosis—A Retrospective Cohort Study

2021 ◽  
Vol 10 (8) ◽  
pp. 1623
Author(s):  
Maria Viktoria Requardt ◽  
Dennis Görlich ◽  
Torsten Grehl ◽  
Matthias Boentert
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Motor Neuron ◽  
Disease Progression ◽  
Rating Scale ◽  
Rapid Decline ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Hazard Ratios ◽  
Sum Score ◽  
Lateral Sclerosis

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that is ultimately fatal but characterized by substantial phenotypic heterogeneity, which is known to impact long-term course and survival. This study investigated clinical determinants of disease progression and outcome in a large cohort of patients with ALS. Methods: Retrospective analysis included comprehensive data from 625 patients who attended a tertiary ALS centre at least twice. Patients were stratified according to five distinct clinical phenotypes: classical ALS; bulbar ALS; ALS with frontotemporal dementia (ALS-FTD); upper motor neuron predominant (UMNP); and lower motor neuron predominant (LMNP). Results: This study confirmed higher age at symptom onset, shorter latency to diagnosis and more rapid decline in the revised ALS Functional Rating Scale sum score as predictors of poor prognosis. Hazard ratios for shorter survival were higher in patients with ALS-FTD versus classical ALS, and in patients with versus without chronic obstructive pulmonary disease (COPD). Mean survival was longest in the UMNP phenotype group. Conclusions: This study confirmed established predictors of shorter survival in ALS and showed that concomitant COPD in particular relates to poor outcome.

scholarly journals Airway inflammation in COPD: progress to precision medicine

2019 ◽  
Vol 54 (2) ◽  
pp. 1900651 ◽  
Author(s):  
Christopher Brightling ◽  
Neil Greening
Keyword(s):  
Precision Medicine ◽  
Airway Inflammation ◽  
Severe Disease ◽  
Chronic Obstructive ◽  
Inflammasome Activation ◽  
Eosinophilic Inflammation ◽  
Obstructive Pulmonary Disease ◽  
Interleukin 5 ◽  
Increased Risk ◽  
Anti Inflammatory

Chronic obstructive pulmonary disease (COPD) is a significant cause of morbidity and mortality worldwide, and its prevalence is increasing. Airway inflammation is a consistent feature of COPD and is implicated in the pathogenesis and progression of COPD, but anti-inflammatory therapy is not first-line treatment. The inflammation has many guises and phenotyping this heterogeneity has revealed different patterns. Neutrophil-associated COPD with activation of the inflammasome, T1 and T17 immunity is the most common phenotype with eosinophil-associated T2-mediated immunity in a minority and autoimmunity observed in more severe disease. Biomarkers have enabled targeted anti-inflammatory strategies and revealed that corticosteroids are most effective in those with evidence of eosinophilic inflammation, whereas, in contrast to severe asthma, response to anti-interleukin-5 biologicals in COPD has been disappointing, with smaller benefits for the same intensity of eosinophilic inflammation questioning its role in COPD. Biological therapies beyond T2-mediated inflammation have not demonstrated benefit and in some cases increased risk of infection, suggesting that neutrophilic inflammation and inflammasome activation might be largely driven by bacterial colonisation and dysbiosis. Herein we describe current and future biomarker approaches to assess inflammation in COPD and how this might reveal tractable approaches to precision medicine and unmask important host–environment interactions leading to airway inflammation.

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.

scholarly journals Bronchiectasis and increased mortality in patients with corticosteroid-dependent severe asthma: a nationwide population study

2020 ◽  
Vol 14 ◽  
pp. 175346662096303
Author(s):  
Hayoung Choi ◽  
Hyun Lee ◽  
Jiin Ryu ◽  
Sung Jun Chung ◽  
Dong Won Park ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Respiratory Diseases ◽  
Chronic Obstructive ◽  
Study Cohort ◽  
Limited Information ◽  
Term Survival ◽  
Obstructive Pulmonary Disease ◽  
All Cause Mortality ◽  
The Impact

Background: Long-term corticosteroid (CS) use is associated with increased mortality in patients with asthma, and comorbid bronchiectasis is also associated with frequent asthma exacerbation and increased healthcare use. However, there is limited information on whether bronchiectasis further increases mortality in patients with CS-dependent asthma. This study examined the impact of bronchiectasis on mortality in patients with CS-dependent asthma. Methods: A retrospective cohort of patients with CS-dependent asthma ⩾18 years old was established using records from the Korean National Health Insurance Service database from 2005 to 2015. Patients with CS-dependent asthma with and without bronchiectasis were matched by age, sex, type of insurance, and Charlson comorbidity index. We evaluated the hazard ratio (HR) for all-cause mortality in patients with bronchiectasis compared with those without bronchiectasis. Results: The study cohort included 754 patients with CS-dependent asthma with bronchiectasis and 3016 patients with CS-dependent asthma without bronchiectasis. Patients with CS-dependent asthma with bronchiectasis had a higher all-cause mortality than those without bronchiectasis (8429/100,000 versus 6962/100,000 person-years, p < 0.001). The adjusted HR for mortality in patients with CS-dependent asthma with bronchiectasis relative to those without bronchiectasis was 1.33 (95% confidence interval, 1.18–1.50), and the association was primarily significant for respiratory diseases (subdistribution HR = 1.65, 95% confidence interval, 1.42–1.92). Conclusions: Bronchiectasis further increases all-cause mortality in patients with CS-dependent asthma, a trend that was especially associated with respiratory diseases including chronic obstructive pulmonary disease. Strategies to improve treatment outcomes in patients with CS-dependent asthma with bronchiectasis are urgently needed to improve long-term survival. The reviews of this paper are available via the supplemental material section.

PON1 gene polymorphisms in patients with chronic obstructive pulmonary disease

2018 ◽  
Vol 71 (11) ◽  
pp. 963-970
Author(s):  
Marija Grdić Rajković ◽  
Sanja Popović-Grle ◽  
Andrea Vukić Dugac ◽  
Dunja Rogić ◽  
Ivana Rako ◽  
...  
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Operating Characteristic ◽  
Fragment Length Polymorphism ◽  
Characteristic Curve ◽  
Paraoxonase 1 ◽  
Pon1 Activity ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Pon1 Gene

AimsChronic obstructive pulmonary disease (COPD) is characterised with oxidative stress. Paraoxonase 1 (PON1) is an enzyme, coded by PON1 gene, with distinctive antiatherogenic and antioxidative roles. We aimed to investigate the frequencies of Q192R, L55M and −108C>T polymorphisms and association of those polymorphisms with paraoxonase and arylesterase activities in patients with COPD.MethodsPON1 genotype was determined by PCR–restriction fragment length polymorphism method. PON1 activity was measured by paraoxon and phenylacetate.ResultsOnly −108C>T polymorphism resulted in significantly different distribution of genotypes and alleles, with higher frequency of TT genotype and T allele in patients compared with control subjects. Moreover, T allele (OR 2.29 (95% CI 1.54 to 3.41); p<0.001) as well as TT genotype (OR 5.00 (95% CI 2.19 to 11.43); p<0.001) showed an association with the disease. −108C>T polymorphism was suggested as a significant diagnostic predictor for the disease (OR (95% CI) 2.65 (1.53 to 4.59), p=0.001), with an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84 to 0.93) and with 83.90% of correctly classified cases.ConclusionsHigher frequency of TT genotype and T allele could contribute to the observed reduction of PON1 activity in patients with COPD. T allele and TT genotype are associated with COPD, and the PON1−108C>T polymorphism could be a potential predictor of the disease.

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