Association Between Prebiotic or Probiotic Consumption and Risk of Type 2 Diabetes Mellitus in the General Adult Population by Şefika Tuğba Yangöz, Cansu Koşar Şahin, Hatice Ceylan

“…Univariate analysis, logistic and multiple linear regression analyses were conducted.Results: Of 401 adults, 51.6% were male and 78.80% were under 45 years of age. 89% of the sample stated they consumed prebiotic-probiotics. …”
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Respiratory symptoms after coalmine fire and pandemic: A longitudinal analysis of the Hazelwood Health Study adult cohort. by Tyler J Lane, Matthew Carroll, Brigitte M Borg, Tracy A McCaffrey, Catherine L Smith, Caroline X Gao, David Brown, Amanda Johnson, David Poland, Shantelle Allgood, Jillian Ikin, Michael J Abramson

“…Longitudinal effects of fire-related PM2.5 were examined using a mixed-effects logistic regression model. Exacerbation due to COVID-19 was examined using a logistic regression model. …”
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Effects of Metabolism-Related Indicators on Nonalcoholic Fatty Liver Disease in Nonobese Population Based on the National Health and Nutrition Examination Survey by XingWang Zhu, HaiPing Wang, HongLong Zhang, Guole Nie, Jun Yan, Xun Li

“…Among the 904 participants, 116 (12.83%) had NAFLD. The logistic regression model found that the waist-to-hip ratio (WHR), HDL-c, triglyceride (TG), and HbA1c were positively associated with the outcomes. …”
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Efficiency of Disease and Disease Activity Diagnosis Models of Systemic Lupus Erythematosus Based on Protein Array Analysis by Yafei Zhao, Yuanyuan Qi, Xinran Liu, Yan Cui, Zhanzheng Zhao

“…TNF RII and MIP-1b were included in the SLE diagnosis model with logistic regression analysis, and the value of the area under the ROC curve (AUC) was 0.914 (95% confidence interval (CI), 0.859-0.969). …”
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The Prognostic Significance of TRs in Hepatocellular Carcinoma: Insights from TCGA and GEO Databases by Hao Zhou, Weijie Wang, Ruopeng Liang, Rongtao Zhu, Jiahui Cao, Chenguang Sun, Yuling Sun

“…Both Cox regression and logistic regression identified low THRB expression as an independent risk factor for HCC. …”
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Red blood cell distribution width to albumin ratio is associated with increased depression: the mediating role of atherogenic index of plasma by Tingting Shangguan, Jing Xu, Xiaochun Weng, Hao Lin

“…To examine the correlation between RAR and depression, multivariate logistic regression analyses, subgroup analyses, restricted cubic spline analyses, and interaction tests were conducted. …”
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Design of an iterative method for enhanced early prediction of acute coronary syndrome using XAI analysis by Shital Hajare, Rajendra Rewatkar, K.T.V. Reddy

“…The study harnesses diverse algorithms—Support Vector Machines, Logistic Regression, Gradient Boosting Machines, and Deep Forest—tailored for nuanced ACS detection, balancing simplicity with computational depth to optimize performance metrics. …”
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Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD by Nafeisa Dilixiati, Mengyu Lian, Ziliang Hou, Jie Song, Jingjing Yang, Ruiyan Lin, Jinxiang Wang

“…Variables were initially screened using univariate analysis, and then further selected using a backward stepwise regression. Multivariable logistic regression was performed to establish nomograms. …”
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Anxiety and depression prevalence and associated factors in patients with knee osteoarthritis by Qizhen Feng, Qizhen Feng, Mingjie Weng, Xi Yang, Min Zhang

“…Multivariate logistic regression analysis showed that lower BMI, QOL, and utilization of social support scores are risk factors for anxiety and depression in KOA patients (P<0.05). …”
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Determining the status of small dense low-density lipoprotein cholesterol level in women undergoing menopausal transition by Qingfang He, Yujia Fang, Lixin Wang, Mingbin Liang, Xiangyu Chen, Ruying Hu, Jieming Zhong

“…According to their menopausal status, the eligible women subjects were divided into premenopause, perimenopause, and postmenopause. Logistic regression model by SAS software was used to explore the association with sdLDL-C level and different menopausal status.ResultsA total of 2,062 women subjects were included with a median age of 57 (51, 63) years. …”
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Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis by Xiaobing Liu, Caili Yan, Xiuxiu Niu, Jiechun Zeng

“…They were divided into the occurrence and nonoccurrence groups according to whether CCE occurred. The multivariate logistic regression analysis was used to analyze the influencing factors of CCE, and a predictive nomogram model was established. …”
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Association between serum carotenoids levels and endometriosis risk: evidence from the National Health and Nutrition Examination Survey by Jian Huang

“…Weighted multivariate logistic regression analyses were conducted to evaluate the associations of the serum levels of the major carotenoids with endometriosis risk. …”
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Association of body roundness index with cardiovascular disease in patients with cardiometabolic syndrome: a cross-sectional study based on NHANES 2009-2018 by Xiaohua He, Jingling Zhu, Wenfei Liang, Xiuling Yang, Weimin Ning, Zhan Zhao, Jingyi Chen, Qiuxing He

“…In addition, receiver operating characteristic (ROC) curves were used to assess the ability of BRI to predict CVD.ResultsThe logistic regression model showed a positive association between the BRI and CVD. …”
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Risk factors and preventive measures for abnormal blood pressure during hemodialysis filtration for patients with sepsis by Zhang Chunfang, Lin Tingting, Xia Yu, Zhang Daowei

“…Results. Multivariate logistic regression analysis revealed that age, blood calcium, fasting plasma glucose, intact parathyroid hormone, ultrafiltration volume, and ultrafiltration rate were independent risk factors, whereas albumin was a protective factor for ABP during HDF (p < 0.05). …”
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The relationship between weight-adjusted waist index and peripheral artery disease by Zhe Wu, Yang Liu, Bin Wang

“…The results of multiple logistic regression showed that WWI was significantly positively associated with the risk of PAD after full adjustment for covariates (OR: 1.407, 95% CI: 1.100–1.799). …”
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Peripheral Arterial Disease in Type 2 Diabetes Is Associated with an Increase in Fibrinogen Levels by Qin-Fen Chen, Dan Cao, Ting-Ting Ye, Hui-Hui Deng, Hong Zhu

“…Furthermore, the univariate and multiple logistic analyses were performed to explore the correlation between PAD and fibrinogen levels, individual components in the cross-sectional study. …”
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The feasibility of using liver function indices and FibroScan in combination to predict the occurrence of anti-tuberculosis drug-induced liver injury in Patients with liver disease by Shaoqiang Wu, Qiaohua Yang, Huai Li, Yongzhong Li

“…Patients were monitored for clinical and biochemical signs of DILI throughout treatment. Logistic regression models and Receiver Operating Characteristic (ROC) curves were used for data analysis. …”
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The Association of Joint Power Kinetic Variables with Running Injuries: A Case-Control Study by Matt Dewald, Jennifer Dalland, Josie Stockland

“…Two sample T-tests were used to compare peak power variables at the hips, knees, and ankles between non-injured and injured runners. Logistic regression analyses examined how a combination of demographics and peak power variables were associated with injuries…”
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Association between Monocyte to High-Density Lipoprotein Cholesterol Ratio and Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study by Hangkai Huang, Qinqiu Wang, Xiaoying Shi, Yishu Chen, Chao Shen, Juanwen Zhang, Chengfu Xu

“…Univariate and multivariate logistic regression analyses were conducted to explore whether MHR associated with NAFLD. …”
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Implementing Machine Learning for Smart Farming to Forecast Farmers’ Interest in Hiring Equipment by Manik Rakhra, Sumaya Sanober, Noorulhasan Naveed Quadri, Neha Verma, Samrat Ray, Evans Asenso

“…In this research, three different machine learning models were utilized: nearest neighbors, logistic regression, and decision trees. K-nearest neighbors was the most often used model, followed by logistic regression and decision trees. …”
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