Publications by authors named "Lixia Deng"

8 Publications

  • Page 1 of 1

Acceptance of a COVID-19 vaccine and associated factors among pregnant women in China: a multi-center cross-sectional study based on health belief model.

Hum Vaccin Immunother 2021 May 14:1-10. Epub 2021 May 14.

Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.

: Vaccine hesitancy has been recognized as an urgent public health issue. We aimed to explore the acceptance of a COVID-19 vaccine and related factors among pregnant women, a vulnerable population for vaccine-preventable diseases. A multi-center cross-sectional study among pregnant women was conducted in five provinces of mainland China from November 13 to 27, 2020. We collected sociodemographic characteristics, attitude, knowledge, and health beliefs on COVID-19 vaccination. Locally weighted scatterplot smoothing regression analysis was used to assess the trends of vaccination acceptance. Multivariable logistic regression was performed to identify factors related to vaccination acceptance. Among the 1392 pregnant women, the acceptance rate of a COVID-19 vaccine were 77.4% (95%CI 75.1-79.5%). In the multivariable regression model, the acceptance rate was associated with young age (aOR = 1.87, 95% CI: 1.20-2.93), western region (aOR = 2.73, 95% CI: 1.72-4.32), low level of education (aOR = 2.49, 95% CI: 1.13-5.51), late pregnancy (aOR = 1.49, 95% CI: 1.03-2.16), high knowledge score on COVID-19 (aOR = 1.05, 95% CI: 1.01-1.10), high level of perceived susceptibility (aOR = 2.18, 95% CI: 1.36-3.49), low level of perceived barriers (aOR = 4.76, 95% CI: 2.23-10.18), high level of perceived benefit (aOR = 2.18, 95% CI: 1.36-3.49), and high level of perceived cues to action (aOR = 15.70, 95% CI: 8.28-29.80). About one quarters of pregnant women have vaccine hesitancy. Our findings highlight that targeted and multipronged efforts are needed to build vaccine literacy and confidence to increase the acceptance of a COVID-19 vaccine during the COVID-19 pandemic, especially for vulnerable populations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1080/21645515.2021.1892432DOI Listing
May 2021

[Correlation between gut microbiota and liver biochemical indicators in patients with chronic hepatitis B].

Sheng Wu Gong Cheng Xue Bao 2021 Jan;37(1):301-311

Yantai City Hospital for infectious Diseases, Yantai 264001, Shandong, China.

Chronic hepatitis B (CHB) is a global epidemic disease caused by hepatitis B virus that can lead to hepatic failure, even liver cirrhosis and hepatocellular carcinoma. The occurrence and development of CHB are closely related to the changes in the gut microbiota communities. To explore the relationship between the structure of gut microbiota and liver biochemical indicators, 14 CHB patients (the CHB group) and 11 healthy people (the CN group) were randomly enrolled in this study. Our results demonstrate that CHB caused changes in the gut microbiota communities and biochemical indicators, such as alanine transaminase, total bilirubin and gamma glutamyl transferase. Furthermore, CHB induced imbalance of the gut microbiota. Prevotella, Blautia, Ruminococcus, Eubacterium eligens group, Bacteroides uniformis and Ruminococcus sp. 5_1_39BFAA were associated with the critical biochemical indicators and liver injury, suggesting a new approach to CHB treatment.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.13345/j.cjb.200279DOI Listing
January 2021

Image Stitching Based on Nonrigid Warping for Urban Scene.

Sensors (Basel) 2020 Dec 9;20(24). Epub 2020 Dec 9.

School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China.

Image stitching based on a global alignment model is widely used in computer vision. However, the resulting stitched image may look blurry or ghosted due to parallax. To solve this problem, we propose a parallax-tolerant image stitching method based on nonrigid warping in this paper. Given a group of putative feature correspondences between overlapping images, we first use a semiparametric function fitting, which introduces a motion coherence constraint to remove outliers. Then, the input images are warped according to a nonrigid warp model based on Gaussian radial basis functions. The nonrigid warping is a kind of elastic deformation that is flexible and smooth enough to eliminate moderate parallax errors. This leads to high-precision alignment in the overlapped region. For the nonoverlapping region, we use a rigid similarity model to reduce distortion. Through effective transition, the nonrigid warping of the overlapped region and the rigid warping of the nonoverlapping region can be used jointly. Our method can obtain more accurate local alignment while maintaining the overall shape of the image. Experimental results on several challenging data sets for urban scene show that the proposed approach is better than state-of-the-art approaches in both qualitative and quantitative indicators.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/s20247050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763989PMC
December 2020

Detecting Matching Blunders of Multi-Source Remote Sensing Images via Graph Theory.

Sensors (Basel) 2020 Jul 2;20(13). Epub 2020 Jul 2.

School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China.

Large radiometric and geometric distortion in multi-source images leads to fewer matching points with high matching blunder ratios, and global geometric relationship models between multi-sensor images are inexplicit. Thus, traditional matching blunder detection methods cannot work effectively. To address this problem, we propose two matching blunder detection methods based on graph theory. The proposed methods can build statistically significant clusters in the case of few matching points with high matching blunder ratios, and use local geometric similarity constraints to detect matching blunders when the global geometric relationship is not explicit. The first method (named the complete graph-based method) uses clusters constructed by matched triangles in complete graphs to encode the local geometric similarity of images, and it can detect matching blunders effectively without considering the global geometric relationship. The second method uses the triangular irregular network (TIN) graph to approximate a complete graph to reduce to computational complexity of the first method. We name this the TIN graph-based method. Experiments show that the two graph-based methods outperform the classical random sample consensus (RANSAC)-based method in recognition rate, false rate, number of remaining matching point pairs, dispersion, positional accuracy in simulated and real data (image pairs from Gaofen1, near infrared ray of Gaofen1, Gaofen2, panchromatic Landsat, Ziyuan3, Jilin1and unmanned aerial vehicle). Notably, in most cases, the mean false rates of RANSAC, the complete graph-based method and the TIN graph-based method in simulated data experiments are 0.50, 0.26 and 0.14, respectively. In addition, the mean positional accuracy (RMSE measured in units of pixels) of the three methods is 2.6, 1.4 and 1.5 in real data experiments, respectively. Furthermore, when matching blunder ratio is no higher than 50%, the computation time of the TIN graph-based method is nearly equal to that of the RANSAC-based method, and roughly 2 to 40 times less than that of the complete graph-based method.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/s20133712DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374350PMC
July 2020

Significance of the thrombo-inflammatory status-based novel prognostic score as a useful predictor for in-hospital mortality of patients with type B acute aortic dissection.

Oncotarget 2017 Oct 23;8(45):79315-79322. Epub 2017 May 23.

Department of Emergency Medicine, West China Hospital, Sichuan University, Chengdu, China.

Background: Inflammation and thrombosis are associated with development and progression of acute aortic dissection (AAD). The aim of this study was to assess the prognostic significance of Simplified Thrombo-Inflammatory Prognostic Score (sTIPS), in patients with early phase type B AAD.

Methods: We retrospectively reviewed 491 patients with type B AAD between November 2012 and September 2015. sTIPS was calculated from the white blood cell count (WBC) and mean platelet volume to platelet count (MPV/PC) ratio, at the time of admission. Patients with both, WBC > 10 (10/L) and MPV/PC ratio > 7.5 (10fL/10L) were assigned a score of 2, while patients with high levels of either one or none of the above markers, were assigned scores of 1 and 0 respectively. Multivariable Cox regression analyses were used to investigate the associations between the score and hospital survival.

Results: Of the 491 type B AAD patients included in this analysis, 24 patients (4.9%) died during hospitalization. Kaplan-Meier analysis revealed that the cumulative mortality was significantly higher in patients with higher sTIPS ( = 0.001). Multivariable Cox regression analysis further indicated that higher sTIPS was a strong predictor of in-hospital mortality after eliminating all confounding factors (sTIPS 2: hazard ratio 4.704, 95%; confidence interval [CI] 1.184-18.685; = 0.028; sTIPS 1: hazard ratio 1.918, 95%; CI 1.134-3.537; = 0.045).

Conclusions: sTIPS at admission was a useful tool for stratifying the risk in type B AAD patients, for outcomes such as in-hospital mortality in the early phase.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.18632/oncotarget.18105DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668043PMC
October 2017

Management and outcomes in acute aortic dissection patients with shock.

Am Heart J 2016 11 29;181:e1-e2. Epub 2016 Aug 29.

Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ahj.2016.08.014DOI Listing
November 2016

Hypoalbuminemia predicts clinical outcome in patients with type B acute aortic dissection after endovascular therapy.

Am J Emerg Med 2016 Aug 4;34(8):1369-72. Epub 2016 Apr 4.

Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China; Department of Emergency Medicine, West China Hospital, Sichuan University, Chengdu, China.

Background: Few studies have reported that serum albumin (SA) levels on admission were associated with increased risk of long-term outcomes in patients with type B acute aortic dissection (AAD). The aim of this study was to investigate the effect of admission levels of SA on survival among patients with type B AAD undergoing endovascular therapy (EVT).

Methods: A total of 131 patients with type B AAD undergoing EVT were retrospectively enrolled and followed up for 2.1years. They were divided into hypoalbuminemia and nonhypoalbuminemia groups. We analyzed the incidence of inhospital complications and long-term mortality. Kaplan-Meier curves and multivariable Cox regression analyses were used to investigate the associations between SA levels and survival.

Results: Among 131 type B AAD patients, hypoalbuminemia was detected in 61 (46.6%) at admission. Compared to those without hypoalbuminemia, patients with hypoalbuminemia did not have higher inhospital complications; however, Kaplan-Meier analysis showed that they did have a significantly lower survival rate (73.8% vs 92.5%; log-rank χ(2)=9.8; P=.002). Multivariable Cox regression analysis further revealed that hypoalbuminemia was an independent predictor of long-term mortality among patients with type B AAD (hazard ratio, 4.28; 95% confidence interval, 1.36-13.47; P=.013), over 2.1years.

Conclusions: Hypoalbuminemia is common in type B AAD patients and is independently associated with increased risk of long-term death. Renal dysfunction may be the main pathophysiological mechanism underlying hypoalbuminemia in patients with type B AAD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajem.2016.03.067DOI Listing
August 2016