scholarly journals Plasma miRNA profiles associated with stable warfarin dosage in Chinese patients

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9995
Author(s):  
Li Zhao ◽  
Jin Wang ◽  
Shaoxin Shi ◽  
Yuan Wu ◽  
Jumei Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Prediction Models ◽  
Comprehensive Evaluation ◽  
Warfarin Dose ◽  
Chinese Patients ◽  
Warfarin Dosage ◽  
Multivariate Logistic Regression ◽  
Chinese Han ◽  
Expression Levels ◽  
Plasma Mirnas

Background We used bioinformatic analysis and quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays to investigate the association between plasma microRNAs (miRNAs) and stable warfarin dosage in a Chinese Han population. Methods Bioinformatics analysis was used to screen out potential warfarin dose-associated miRNAs. Three plasma miRNAs were validated in 99 samples by RT-qPCR. Kruskal–Wallis test and multivariate logistic regression were used to compare differences in plasma miRNAs expression levels between three warfarin dosage groups. Results There were significant between-group differences among the three dose groups for hsa-miR-133b expression (p = 0.005), but we observed an “n-shaped” dose-dependent curve rather than a linear relationship. Expression levels of hsa-miR-24-3p (p = 0.475) and hsa-miR-1276 (p = 0.558) were not significantly different in the multivariate logistic regression. Conclusion miRNAs have received extensive attention as ideal biomarkers and possible therapeutic targets for various diseases. However, they are not yet widely used in precision medicine. Our results indicate that hsa-miR-133b may be a possible reference factor for the warfarin dosage algorithm. These findings emphasize the importance of a comprehensive evaluation of complex relationships in warfarin dose prediction models and provide new avenues for future pharmacogenomics studies.

scholarly journals Serum Long Non-Coding RNAs PVT1, HOTAIR, and NEAT1 as Potential Biomarkers in Egyptian Women with Breast Cancer

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 301
Author(s):  
Amal Ahmed Abd El-Fattah ◽  
Nermin Abdel Hamid Sadik ◽  
Olfat Gamil Shaker ◽  
Amal Mohamed Kamal ◽  
Nancy Nabil Shahin
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Cancer Patients ◽  
Breast Cancer Diagnosis ◽  
Serum Levels ◽  
Breast Cancer Patients ◽  
Multivariate Logistic Regression ◽  
Expression Levels ◽  
Non Coding Rnas ◽  
Pai 1

Long non-coding RNAs play an important role in tumor growth, angiogenesis, and metastasis in several types of cancer. However, the clinical significance of using lncRNAs as biomarkers for breast cancer diagnosis and prognosis is still poorly investigated. In this study, we analyzed the serum expression levels of lncRNAs PVT1, HOTAIR, NEAT1, and MALAT1, and their associated proteins, PAI-1, and OPN, in breast cancer patients compared to fibroadenoma patients and healthy subjects. Using quantitative real-time PCR (qRT-PCR), we compared the serum expression levels of the four circulating lncRNAs in patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The serum levels of PAI-1 and OPN were measured using ELISA. Receiveroperating-characteristic (ROC) analysis and multivariate logistic regression were used to evaluate the diagnostic value of the selected parameters. The serum levels of HOTAIR, PAI-1, and OPN were significantly higher in breast cancer patients compared to controls and fibroadenoma patients. The serum level of PVT1 was significantly higher in breast cancer patients than in the controls, while that of NEAT1 was significantly lower in breast cancer patients compared to controls and fibroadenoma patients. Both ROC and multivariate logistic regression analyses revealed that PAI-1 has the greatest power in discriminating breast cancer from the control, whereas HOTAIR, PAI-1, and OPN have the greatest power in discriminating breast cancer from fibroadenoma patients. In conclusion, our data suggest that the serum levels of PVT1, HOTAIR, NEAT1, PAI-1, and OPN could serve as promising diagnostic biomarkers for breast cancer.

scholarly journals The rs13347 Polymorphism of the CD44 Gene Is Associated with the Risk of Kidney Stones Disease in the Chinese Han Population of Northeast Sichuan, China

2022 ◽  
Vol 2022 ◽  
pp. 1-6
Author(s):  
Qiao Ying ◽  
Guixi Liu ◽  
Wenjun Zhou ◽  
Jianhua Lan ◽  
Jianhui Du ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Stone Disease ◽  
Multivariate Logistic Regression ◽  
Chinese Han ◽  
Han Population ◽  
Increased Risk ◽  
Hardy Weinberg Equilibrium

Objective. To investigate the association between the rs13347 polymorphism of the CD44 gene and the risk of kidney stone disease (KSD) in the Han population of northeast Sichuan, China, so as to provide a theoretical basis for the treatment of KSD. Methods. We used PCR-restriction fragment length polymorphism (RFLP) technique to perform genotyping at rs13347 locus of the CD44 gene in the KSD group and the gontrol group. SNP Hardy-Weinberg equilibrium (HWE) testing was used to confirm the balance of genetic inheritance. Multivariate logistic regression analysis was used for the assessment of rs13347 polymorphism and the risk of developing KSD and to compare the relationship between the polymorphism of rs13347 and clinical characteristics of patients with KSD. Results. Genotypic results of rs13347 locus of the CD44 gene in the two groups were consistent with the SNP-HWE test, indicating the genetic balance. At the same time, multivariate logistic regression analysis indicated that subjects with CT and TT genotypes at rs13347 in the CD44 gene were more likely to have KSD, and there was a higher prevalence rate in males. Furthermore, carrying allele T at rs13347 was also a risk factor for KSD. In addition, people carrying CT and TT genotypes at rs13347 also have a significantly increased risk of relapsing KSD. Conclusion. The rs13347 polymorphism of the CD44 gene may be associated with the risk of KSD in the Han population of northeast Sichuan in China, and the recurrence rate of KSD in the carriers of CT and TT genotypes is higher.

scholarly journals Serum albumin was negatively associated with diabetic peripheral neuropathy in Chinese population: a cross-sectional study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Pijun Yan ◽  
Qian Tang ◽  
Yuru Wu ◽  
Qin Wan ◽  
Zhihong Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Peripheral Neuropathy ◽  
Serum Albumin ◽  
Multivariate Logistic Regression Analysis ◽  
Cross Sectional Study ◽  
Chinese Patients ◽  
Sectional Study ◽  
Multivariate Logistic Regression ◽  
Cross Sectional

Abstract Background Previous studies that explored the relationship of serum albumin with diabetic peripheral neuropathy (DPN) have indicated inconsistent results. Thus, the present study aimed to evaluated the association between serum albumin and DPN, defined as vibration perception threshold (VPT) values ≥ 25 V and/or inability to feel the monofilament, in Chinese patients with type 2 diabetes mellitus (T2DM). Methods 1465 T2DM patients aged ≥ 16 years, who completed the measurement of serum albumin and DPN screening between 2012 and 2015, were included in the cross-sectional study. Correlation and multivariate logistic regression analysis models were used to evaluate the possible relationship between serum albumin and DPN. Results Patients with higher quartiles of serum albumin had significantly lower VPT values and prevalence of DPN compared with those with lower quartiles (P for trend < 0.01), and there was an inverse relationship between serum albumin and VPT values and prevalence of DPN (all P < 0.01). Multivariate logistic regression analysis demonstrated that the risk of DPN was progressively decreased across serum albumin quartiles (P for trend < 0.01), and participants in the highest quartile of serum albumin were at a significantly decreased risk of DPN compared to those in the lowest quartile (odds rate: 0.311, 95% confidence intervals 0.134–0.724, P < 0.01). ROC analysis revealed that the optimal cutoff point of serum albumin for the prevalence of DPN was 39.95 g/L in patients with T2DM, with a sensitivity of 65.88% and a specificity of 66.7%. Conclusions Decreased levels of serum albumin might be correlated with increased risk of DPN in Chinese patients with T2DM. Future longitudinal studies with large samples are warranted to confirm our findings, and elucidate putative mechanisms for the association.

scholarly journals Predicting COVID-19 malignant progression with AI techniques

2020 ◽  
Author(s):  
Xiang Bai ◽  
Cong Fang ◽  
Yu Zhou ◽  
Song Bai ◽  
Zaiyi Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Deep Learning ◽  
Treatment Strategy ◽  
Protective Factor ◽  
Prediction Models ◽  
Laboratory Data ◽  
Malignant Progression ◽  
Medical Systems ◽  
Multivariate Logistic Regression ◽  
Critical Stage

AbstractBackground and purposeThe worldwide pandemic of coronavirus disease 2019 (COVID-19) greatly challenges public medical systems. With limited medical resources, the treatment priority is determined by the severity of patients. However, many mild outpatients quickly deteriorate into severe/critical stage. It is crucial to early identify them and give timely treatment for optimizing treatment strategy and reducing mortality. This study aims to establish an AI model to predict mild patients with potential malignant progression.MethodsA total of 133 consecutively mild COVID-19 patients at admission who was hospitalized in Wuhan Pulmonary Hospital from January 3 to February 13, 2020, were selected in this retrospective IRB-approved study. All mild patients were categorized into groups with or without malignant progression. The clinical and laboratory data at admission, the first CT, and the follow-up CT at the severe/critical stage of the two groups were compared. Both multivariate logistic regression and deep learning-based methods were used to build the prediction models, with their area under ROC curves (AUC) compared.ResultsMultivariate logistic regression depicted 6 risk factors for malignant progression: age >55years (OR 5.334, 95%CI 1.8-15.803), comorbid with hypertension (OR 5.093, 95%CI 1.236-20.986), a decrease of albumin (OR 4.01, 95%CI 1.216-13.223), a decrease of lymphocyte (OR 3.459, 95%CI 1.067-11.209), the progressive consolidation from CT1 to CTsevere (OR 1.235, 95%CI 1.018-1.498), and elevated HCRP (OR 1.015, 95%CI 1.002-1.029); and one protective factor: the presence of fibrosis at CT1 (OR 0.656, 95%CI 0.473-0.91). By combining the clinical data and the temporal information of the CT data, our deep learning-based models achieved the best AUC of 0.954, which outperformed logistic regression (AUC: 0.893),ConclusionsOur deep learning-based methods can identify the mild patients who are easy to deteriorate into severe/critical cases efficiently and accurately, which undoubtedly helps to optimize the treatment strategy, reduce mortality, and relieve the medical pressure.

Effects of rare CYP2C9 alleles on stable warfarin doses in Chinese Han patients with atrial fibrillation

2020 ◽  
Vol 21 (14) ◽  
pp. 1021-1031
Author(s):  
Dongxu Wang ◽  
Da-Peng Dai ◽  
Hualan Wu ◽  
Jia Chong ◽  
You Lü ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Predictive Power ◽  
Warfarin Dose ◽  
Multivariate Regression Analysis ◽  
Chinese Patients ◽  
Chinese Han ◽  
Dosing Algorithm ◽  
Warfarin Dosing ◽  
Univariate Analyses

Aim: Gene polymorphisms are critical in warfarin dosing variation. Here, the role of rare CYP2C9 alleles on warfarin doses in Chinese Han patients was investigated. Methods: A retrospective study recruited 681 warfarin treated atrial fibrillation patients. The genetic and clinical data were collected. Dose-related variables were selected by univariate analyses and the warfarin-dosing algorithm was derived by multivariate regression analysis. Results: Three rare CYP2C9 alleles ( CYP2C9*13, *16 and *60) were associated with lower stable doses. Inclusion of the rare CYP2C9 alleles in the prediction model added an extra 3.7% warfarin dose predictive power. Conclusion: CYP2C9*13, *16 and *60 was associated with lower stable warfarin doses in Chinese patients. The algorithm including rare CYP2C9 alleles tends to more accurately predict stable warfarin doses.

Estimation of the warfarin dose with a pharmacogenetic refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation

2012 ◽  
Vol 108 (12) ◽  
pp. 1132-1140 ◽  
Author(s):  
Jie Yang ◽  
Lei Gao ◽  
Yan Zhang ◽  
Hongjuan Wang ◽  
Caiyi Lu ◽  
...  
Keyword(s):  
Validation Cohort ◽  
Warfarin Dose ◽  
Chinese Patients ◽  
Fixed Dose ◽  
Dose Requirement ◽  
Chinese Han ◽  
Derivation Cohort ◽  
Dose Prediction ◽  
Low Intensity ◽  
Refinement Algorithm

SummaryPharmacogenetic (PG) dosing algorithms have been confirmed to predict warfarin therapeutic dose more accurately;however, most of them are based on standard intensity of warfarin anticoagulation, and their utility outside this range is limited. This study was designed to develop and validate a PG refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation. Consented Chinese-Han patients (n=310) under stable warfarin treatment were randomly divided into a derivation (n=207) and a validation cohort (n=103), with 83% and 80% of the patients under low-intensity anticoagulation, respectively. In the derivation cohort, a PG algorithm was constructed on the basis of genotypes (CYP2C9*3 and VKORC1–1639A/G) and clinical data. After integrating additional covariates of international normalised ratio (INR) values (INR on day 4 of therapy and target INR) and genotype of CYP4F2 (rs2108622), a PG refinement algorithm was established and explained 54% of warfarin dose variability. In the validation cohort, warfarin dose prediction was more accurate (p <0.01) with the PG refinement algorithm than with the PG algorithm and the fixed dose approach (3 mg/day). In the entire cohort, the PG refinement algorithm could accurately identify larger proportions of patients with lower dose requirement (≤2 mg/day) and higher dose requirement (≥4 mg/day) than did the PG algorithm. In conclusion, PG refinement algorithm integrating early INR response and three genotypes CYP2C9*3, VKORC1–1639A/G, CYP4F2 rs2108622) improves the accuracy of warfarin dose prediction in Chinese patients mainly under low-intensity anticoagulation.

scholarly journals Risk factors and prediction model construction of post-operative atrial fibrillation after thoracic surgery in Chinese patients

2021 ◽  
Author(s):  
Yunling Lin ◽  
Jianmin Sun ◽  
Xun Yuan ◽  
Hui Liu
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Thoracic Surgery ◽  
Prediction Model ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Chinese Patients ◽  
Multivariate Logistic Regression ◽  
Post Operative Atrial Fibrillation

IntroductionThe purpose of this study was to analyze the risk factors of post-operative atrial fibrillation (POAF) after thoracic surgery, and to build a predictive model for accurate preoperative identification of high-risk patients.Material and methodsIn this study, data of 2072 patients with pulmonary masses and esophageal cancer who attended our hospital in the period from January 1, 2017 to December 31, 2018 were analyzed retrospectively. According to whether AF occurred after the operation, the patients were divided into atrial fibrillation (AF) and non-AF (NAF) groups. The general information (age, sex, height, etc.), previous medical history (chronic lung disease, hypertension, etc.), medication history, preoperative ultrasound and cardiogram results, and preoperative and postoperative electrocardiogram (ECG) were collected. The operation mode, resection scope, histopathology and hospitalization were recorded. Univariate and multivariate logistic regression were used to screen out the risk factors of AF and establish a prediction model.ResultsThe incidence of POAF was 5.98%. Univariate analysis showed that sex, age, body mass index, left atrial diameter and operation organ were the risk factors of POAF. The above factors were included in the multivariate logistic regression analysis, and the results showed that male sex, age, anteroposterior diameter of left atrium and surgical organs were related to POAF. On this basis, a POAF prediction model was constructed, which had good discrimination and calibration. The area under the curve (AUC) is 0.784 with 95% CI: 0.746–0.822.ConclusionsThe prediction model of POAF based on the risk factors selected in this study can accurately predict the occurrence of AF after thoracic surgery.

scholarly journals Prevalence of and Risk Factors for Anxiety and Depression in Chinese Patients With Unruptured Intracranial Aneurysms Treated by Endovascular Intervention

2020 ◽  
Author(s):  
Xiao-Dong Zhai ◽  
Jia-Xing Yu ◽  
Yong-Jie Ma ◽  
Si-Shi Xiang ◽  
Gui-Lin Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Household Income ◽  
Multivariate Logistic Regression Analysis ◽  
Endovascular Intervention ◽  
Chinese Patients ◽  
Anxiety And Depression ◽  
Multivariate Logistic Regression ◽  
Annual Household Income

Abstract Background: Studies on anxiety and depression in unruptured intracranial aneurysm (UIA) patients after treatment via endovascular intervention are rare and controversial. We aimed to explore the prevalence of anxiety and depression among Chinese patients with UIAs treated by endovascular intervention and to identify which factors contribute to the development of these symptoms.Methods: We performed a cross-sectional study on anxiety and depression in patients who underwent endovascular treatment for UIAs using the Hospital Anxiety and Depression Scale (HADS). The demographic, clinical and radiological data for all patients were retrospectively collected from the aneurysm database and medical records. Moreover, we utilized data from a large sample of 200 UIA patients and multivariate logistic regression analysis to investigate the risk factors for anxiety and depression in these patients. Candidate variables with P values less than 0.20 in univariate analysis were included in the multivariate logistic regression analysis.Results: Two hundred patients returned completed questionnaires in this study. Of these 200 patients, 34 (17.0%) suffered from anxiety and 31 (15.5%) suffered from depression 30.67±8.6 months after being discharged. The multivariate analysis results indicated that treatment costs exceeding the annual household income was significantly associated with anxiety (AOR = 2.42, 95% CI: 1.08~5.41, P= 0.03). Shorter sleep times were significantly associated with anxiety (AOR= 1.51, 95% CI: 1.06~2.14, P= 0.02) and depression (AOR = 1.62, 95% CI: 1.14~2.29, P= 0.007).Conclusion: The prevalences of anxiety and depression in UIA patients treated by endovascular intervention were 17.0% and 15.5%, respectively. Treatment costs exceeding the annual household income was significantly associated with anxiety. Shorter sleep times were significantly associated with anxiety and depression. Our findings provide valuable evidence for the clinical and psychological management of these patients.

scholarly journals Serum Homocysteine as One of the Risk Factors of Cerebral Small Vessel Disease in Chinese Patients

2019 ◽  
pp. 1-7
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Logistic Regression ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Chinese Patients ◽  
Multivariate Logistic Regression ◽  
Vessel Disease ◽  
Serum Homocysteine

Objective: This study aimed to determine the risk factors of cerebral small vessel disease (CSVD) from different variables including serum homocysteine (Hcy) in a group of Chinese patients. Methods: A total of 139 patients with CSVD admitted to the affiliated hospital of Xuzhou Medical University from July 2017 to July 2018 were enrolled. Fifty healthy individuals were selected as controls. According to the diagnostic criteria, the CSVD patients were divided into three groups, namely, lacunar infarction (LI) group (n=59), white matter lesion (WML) group (n=46), and LI+WML group (n=34). The serum Hcy levels of the three groups were observed and compared. Multivariate logistic regression was performed to determine whether a number of variables including serum Hcy level are the risk factors of CSVD. Results: Hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), fasting blood glucose (FBG), and Hcy were significantly higher in CSVD group than the control group (P < 0.05). The age, gender, SBP, platelet, TG, and Hcy were significantly different between the LI group, WML group, and LI+WML groups (P<0.05). The age and Hcy level of patients in LI+WML group were higher than those of the LI group and WML group, and the difference was statistically significant (P < 0.05). The level of SBP was higher in the LI group than the WML group (P < 0.05). The Hcy level of patients in the LI group was higher than that in the WML group, but there was no significant difference (P > 0.05). The platelet and TG were significantly higher in WML group than LI group and LI+WML group (P < 0.05). Controlling the influence of sex and age, multivariate logistic regression analysis revealed that the Hcy levels were correlated with the incidence of the CSVD. Conclusion: Serum Hcy level is a risk factor for CSVD. Regular detection of serum Hcy level and timely intervention may effectively prevent and control the occurrence and development of CSVD.

scholarly journals Superoxide dismutase gene polymorphism is associated with ischemic stroke risk in the Chinese Han population

2019 ◽  
Author(s):  
Yang Xitong ◽  
Yang Sulian ◽  
Xu Hongyang ◽  
Zhang Yuanyuan ◽  
wang guangming
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Blood Cell ◽  
Chinese Han Population ◽  
Blood Cell Count ◽  
Multivariate Logistic Regression ◽  
Chinese Han ◽  
Han Population ◽  
Increased Risk

Abstract Background:Stroke is a serious cardiovascular disease and a major cause of disability and death in both developed and developing countries. Superoxide dismutases (SODs ) are enzymes that catalyze the breakdown of superoxide into oxygen and hydrogen peroxide and play a key role in the antioxidant response. This study explored the relationship between single nucleotide polymorphisms (SNPs) in SOD genes and the risk of ischemic stroke (IS) in the Chinese Han population of Dali city.Methods: For this case-control study, we enrolled 144 IS patients and 128 healthy controls. The SNPs rs17880487 and rs80265967 of the SOD1 gene, rs4880 and rs284296 of the SOD2 gene, rs2695232 and rs7655372 of the SOD3 gene were detected via Taqman-polymerase chain reaction (PCR). Genotypes and allele frequencies of the two groups were compared. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated by unconditional logistic regression, and environmental factors were corrected with multivariate logistic regression analysis.Results: Rs7655372 of SOD3 was associated with a significantly increased risk of IS. Moreover, this the G and GA genotypes of SNP rs7655372 were associated with an increased risk of IS, whereas the A and GA genotypes were risk factors for IS. Furthermore, multivariate logistic regression analysis showed that fasting blood glucose level, red blood cell count, white blood cell count, low-density lipoprotein level, systolic pressure, diastolic pressure, and rs7655372 GA/GG were independent risk factors for IS.Conclusions: The SOD3 gene rs7655372 locus polymorphism is a risk factor for IS, and its frequency in the Chinese Han population of Dali City denotes that this population is at increased risk of IS.

Sign in / Sign up

Export Citation Format

Share Document