scholarly journals Prediction of COVID-19 Patients at High Risk of Progression to Severe Disease

2020 ◽  
Vol 8 ◽  
Author(s):  
Zhenyu Dai ◽  
Dong Zeng ◽  
Dawei Cui ◽  
Dawei Wang ◽  
Yanling Feng ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Disease Severity ◽  
Cox Regression ◽  
Clinical Chemistry ◽  
Characteristic Curve ◽  
Severe Disease ◽  
Bootstrap Sampling ◽  
Orthogonal Projections ◽  
High Risk Factors

In order to develop a novel scoring model for the prediction of coronavirus disease-19 (COVID-19) patients at high risk of severe disease, we retrospectively studied 419 patients from five hospitals in Shanghai, Hubei, and Jiangsu Provinces from January 22 to March 30, 2020. Multivariate Cox regression and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were both used to identify high-risk factors for disease severity in COVID-19 patients. The prediction model was developed based on four high-risk factors. Multivariate analysis showed that comorbidity [hazard ratio (HR) 3.17, 95% confidence interval (CI) 1.96–5.11], albumin (ALB) level (HR 3.67, 95% CI 1.91–7.02), C-reactive protein (CRP) level (HR 3.16, 95% CI 1.68–5.96), and age ≥60 years (HR 2.31, 95% CI 1.43–3.73) were independent risk factors for disease severity in COVID-19 patients. OPLS-DA identified that the top five influencing parameters for COVID-19 severity were CRP, ALB, age ≥60 years, comorbidity, and lactate dehydrogenase (LDH) level. When incorporating the above four factors, the nomogram had a good concordance index of 0.86 (95% CI 0.83–0.89) and had an optimal agreement between the predictive nomogram and the actual observation with a slope of 0.95 (R2 = 0.89) in the 7-day prediction and 0.96 (R2 = 0.92) in the 14-day prediction after 1,000 bootstrap sampling. The area under the receiver operating characteristic curve of the COVID-19-American Association for Clinical Chemistry (AACC) model was 0.85 (95% CI 0.81–0.90). According to the probability of severity, the model divided the patients into three groups: low risk, intermediate risk, and high risk. The COVID-19-AACC model is an effective method for clinicians to screen patients at high risk of severe disease.

scholarly journals Cytokines and Exhaled Nitric Oxide Are Risk Factors in Preterm Infants for Bronchopulmonary Dysplasia

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zhenjie Zhang ◽  
Wuchen Wu ◽  
Lian Hou ◽  
Jingjing Jiang ◽  
Weilin Wan ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Risk Factors ◽  
Mechanical Ventilation ◽  
High Risk ◽  
Disease Severity ◽  
Preterm Infants ◽  
Bronchopulmonary Dysplasia ◽  
Exhaled Nitric Oxide ◽  
High Risk Factors ◽  
Tnf Α

Bronchopulmonary dysplasia (BPD) is the most common complication of extremely preterm birth. This study was aimed at detecting cytokine and fractional exhaled nitric oxide (FeNO) levels to evaluate their mechanisms and predicted significance for BPD. Preterm infants born at g e s t a t i o n a l   a g e ≤ 32   w e e k s were recruited, and clinical data were collected. We detected ten cytokines, including IFN-γ, IL-10, IL-12p70, IL-13, IL-1β, IL-2, IL-4, IL-6, IL-8, and TNF-α on Days 1–3, Days 7–14, and Days 21–28 after birth by using the Meso Scale Discovery (MSD) technology. The FeNO levels of infants were measured when they met the discharge criteria. A total of 46 preterm infants were enrolled, consisting of 14 infants in BPD group and 32 infants in the control group. The gestational age ( 27.5 ± 1.3 vs. 29.9 ± 1.3 weeks) and birth weight ( 1021 ± 261  g vs. 1489 ± 357 g) were lower in the BPD group. The following were high-risk factors for BPD, as determined by multivariate logistic regression analysis: g e s t a t i o n a l   a g e < 30   w e e k s , b i r t h   w e i g h t < 1000   g , PDA, longer mechanical ventilation, and higher FeNO. The cytokines of IL-6 and IL-8 on Days 7–14 and IL-4, IL-6, IL-8, and TNF-α on Days 21–28 were also high-risk factors for BPD. IL-6 contributed to BPD disease severity. Conclusion. The preterm infants with PDA and prolonged mechanical ventilation tended to develop BPD. The IL-6 and IL-8 were significantly increased on Days 7–14 and were high-risk factors for BPD. Moreover, the IL-6 level was associated with BPD disease severity. We speculated that NO was related to BPD via Th2 cell-mediated inflammatory responses such as IL-4 and IL-6. Cytokines might predict the occurrence of BPD.

scholarly journals Prediction for Progression Risk in Patients With COVID-19 Pneumonia: The CALL Score

2020 ◽  
Vol 71 (6) ◽  
pp. 1393-1399 ◽  
Author(s):  
Dong Ji ◽  
Dawei Zhang ◽  
Jing Xu ◽  
Zhu Chen ◽  
Tieniu Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Cox Regression ◽  
Medical Center ◽  
Predictive Values ◽  
Scoring Model ◽  
High Risk Factors ◽  
Progressive Group ◽  
Good Concordance ◽  
Score Model

Abstract Background We aimed to clarify high-risk factors for coronavirus disease 2019 (COVID-19) with multivariate analysis and establish a predictive model of disease progression to help clinicians better choose a therapeutic strategy. Methods All consecutive patients with COVID-19 admitted to Fuyang Second People’s Hospital or the Fifth Medical Center of Chinese PLA General Hospital between 20 January and 22 February 2020 were enrolled and their clinical data were retrospectively collected. Multivariate Cox regression was used to identify risk factors associated with progression, which were then were incorporated into a nomogram to establish a novel prediction scoring model. ROC was used to assess the performance of the model. Results Overall, 208 patients were divided into a stable group (n = 168, 80.8%) and a progressive group (n = 40,19.2%) based on whether their conditions worsened during hospitalization. Univariate and multivariate analyses showed that comorbidity, older age, lower lymphocyte count, and higher lactate dehydrogenase at presentation were independent high-risk factors for COVID-19 progression. Incorporating these 4 factors, the nomogram achieved good concordance indexes of .86 (95% confidence interval [CI], .81–.91) and well-fitted calibration curves. A novel scoring model, named as CALL, was established; its area under the ROC was .91 (95% CI, .86–.94). Using a cutoff of 6 points, the positive and negative predictive values were 50.7% (38.9–62.4%) and 98.5% (94.7–99.8%), respectively. Conclusions Using the CALL score model, clinicians can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and efficient use of medical resources.

scholarly journals Impact of Antibody Cocktail Therapy Combined with Casirivimab and Imdevimab on Clinical Outcome for Covid-19 patients in A Real-Life Setting: A Single Institute Analysis

2021 ◽  
Author(s):  
Yasutaka Kakinoki ◽  
Kazuki Yamada ◽  
Yoko Tanino ◽  
Keiko Suzuki ◽  
Takaya Ichikawa ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Severe Disease ◽  
Real Life ◽  
Public Health Care ◽  
Medical Interventions ◽  
High Risk Factors ◽  
Real Life Setting ◽  
Medical Facilities ◽  
Antibody Cocktail

ABSTRACT Background. Recent data from clinical trial suggest that antibody cocktail therapy, a combination of the monoclonal antibodies casirivimab and imdevimab, has been shown to rapidly reduce the viral load and markedly decrease the risk of hospitalization or death among high-risk patients with coronavirus disease 2019 (Covid-19). However, it remains unclear how effective in a real-life clinical setting the therapy is. Methods. We retrospectively analyzed mild to moderate Covid-19 patients with one or more high-risk factors for severe disease who consecutively underwent the antibody cocktail therapy of the disease in our institute in June 2021 through early September 2021, compared to those with high-risk factors who were isolated in non-medical facilities consecutively during the same period, thereby being not given the antibody cocktail therapy there. The key outcome was the percentage of patients with Covid-19-related deterioration which needed additional medical interventions, such as oxygen support or other antiviral therapies. Results. Data from 55 patients with initially receiving antibody cocktail therapy and 53 patients with isolation into non-medical facilities are analyzed. 22 (41.5 %) of 53 patients with isolation facilities were finally hospitalized to receive medical interventions. On the other hand, 13 (23.6 %) of 55 patients with antibody cocktail therapy in our hospital subsequently underwent further medical interventions because of the progression. In multivariate analysis with variables of age, BMI, and high-risk factors, the antibody cocktail therapy significantly reduced 70 % in the need for further medical interventions compared to the initial isolation in the non-medical facilities (odds ratio=0.30, 95%CI [0.10-0.87], p=0.027). Furthermore, patients with 96% or above of SPO2 were significantly more favorable for the therapy than those with 95% or below of SPO2. Conclusion. The treatment of antibody cocktail was closely linked to reduction in the need for further medical interventions. The result indicates that the antibody cocktail therapy is associated with reducing the strain on hospitals, which is related to the improvement of medical management for public health care in Covid-19 pandemic era.

scholarly journals Informing the public health response to COVID-19: a systematic review of risk factors for disease, severity, and mortality

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
M. Flook ◽  
C. Jackson ◽  
E. Vasileiou ◽  
C. R. Simpson ◽  
M. D. Muckian ◽  
...  
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Systematic Review ◽  
At Risk ◽  
Risk Factor ◽  
Disease Severity ◽  
Severe Disease ◽  
Public Health Response ◽  
Wide Range ◽  
Multivariable Analyses

Abstract Background Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) has challenged public health agencies globally. In order to effectively target government responses, it is critical to identify the individuals most at risk of coronavirus disease-19 (COVID-19), developing severe clinical signs, and mortality. We undertook a systematic review of the literature to present the current status of scientific knowledge in these areas and describe the need for unified global approaches, moving forwards, as well as lessons learnt for future pandemics. Methods Medline, Embase and Global Health were searched to the end of April 2020, as well as the Web of Science. Search terms were specific to the SARS-CoV-2 virus and COVID-19. Comparative studies of risk factors from any setting, population group and in any language were included. Titles, abstracts and full texts were screened by two reviewers and extracted in duplicate into a standardised form. Data were extracted on risk factors for COVID-19 disease, severe disease, or death and were narratively and descriptively synthesised. Results One thousand two hundred and thirty-eight papers were identified post-deduplication. Thirty-three met our inclusion criteria, of which 26 were from China. Six assessed the risk of contracting the disease, 20 the risk of having severe disease and ten the risk of dying. Age, gender and co-morbidities were commonly assessed as risk factors. The weight of evidence showed increasing age to be associated with severe disease and mortality, and general comorbidities with mortality. Only seven studies presented multivariable analyses and power was generally limited. A wide range of definitions were used for disease severity. Conclusions The volume of literature generated in the short time since the appearance of SARS-CoV-2 has been considerable. Many studies have sought to document the risk factors for COVID-19 disease, disease severity and mortality; age was the only risk factor based on robust studies and with a consistent body of evidence. Mechanistic studies are required to understand why age is such an important risk factor. At the start of pandemics, large, standardised, studies that use multivariable analyses are urgently needed so that the populations most at risk can be rapidly protected. Registration This review was registered on PROSPERO as CRD42020177714.

Association between maternal high-risk factors and anemia among women in Ethiopia

Nutrition ◽  
2021 ◽  
pp. 111404
Author(s):  
Noha Fadl ◽  
Gillian H Ice ◽  
Zelalem T Haile
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
High Risk Factors
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