Hospitalizations, emergency medical care utilization, and contacts with the regional on-call medical services among nursing home residents in Germany: a cross-sectional study in 44... by Paula Lienesch, Heinz Rothgang, Ansgar Gerhardus, Karin Wolf-Ostermann, Falk Hoffmann, Jonas Czwikla

“…Associations between individual characteristics and the utilization of the three medical care types were examined using multivariable logistic regressions. Results Of the analyzed residents, 45.8% were hospitalized, 23.2% utilized emergency medical care, and 12.1% had contact with an on-call medical service at least once in the previous 12 months. …”
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Pornography-Watching Disorder and Its Risk Factors Among Young Adults: Cross-Sectional Survey by Csaba Erdős, Oguz Kelemen, Dávid Pócs, Edit Paulik, András Papp, Edina Horváth, Arbel Golan, Krisztián Széll

“…Multivariable binary logistic regression was used to identify significant predictors of PWD. …”
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初次产检孕妇对HBV感染和母婴传播防治知识知晓率的横断面调查 by 韩振艳, 白小艺, 尹玉竹, 侯红瑛

“…调查这些孕妇对乙肝病毒感染和 母婴传播相关知识的知晓率，及对HBV母婴传播防治措施的态度，并分析知识和态度的影响因素。采用方差分 析、Logistic 回归方法进行统计学分析。【结果】①共发放调查问卷500份，有效问卷的回收率为91.8%（459/500）。 …”
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Associations of health literacy with metabolic status and quality of life among comunity patients with type 2 diabetes in Shanghai by YANG Liping, SONG Haihong, SHEN Jue, GAO Jinli, ZHANG Zhiping, QIAN Liuyu, GONG Huan

“…Pearson correlation coefficients were employed to assess the relationship between health literacy levels and metabolic indicators as well as QoL. Logistic regression models were used to estimate the odds ratios (OR) and 95% confidence intervals (CI) for the associations between patients’ health literacy levels, metabolic status, and QoL.ResultsAmong the 932 diabetic patients surveyed, the health literacy level was low, with an average score of (65.2±13.4) points of which (62.6±13.8) points for males and (67.9±12.5) points for females. …”
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Determinants of Dropout From a Virtual Agent–Based App for Insomnia Management in a Self-Selected Sample of Users With Insomnia Symptoms: Longitudinal Study by María Montserrat Sanchez Ortuño, Florian Pecune, Julien Coelho, Jean Arthur Micoulaud-Franchi, Nathalie Salles, Marc Auriacombe, Fuschia Serre, Yannick Levavasseur, Etienne De Sevin, Patricia Sagaspe, Pierre Philip

“…The primary outcome was a binary variable: having dropped out after completing the screening assessment (early dropout) or having completed all the treatment phases (n=551). Multivariable logistic regression analysis was used to identify predictors of dropout among a set of sociodemographic, clinical, and sleep diary variables, and users’ perceptions of the treatment program, collected during the screening interview. …”
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Inflammatory Markers and Severity in COVID-19 Patients with Clostridioides Difficile Co-Infection: A Retrospective Analysis Including Subgroups with Diabetes, Cancer, and Elderly by Teodor Cerbulescu, Flavia Ignuta, Uma Shailendri Rayudu, Maliha Afra, Ovidiu Rosca, Adrian Vlad, Stana Loredana

“…Statistical comparisons employed <i>t</i>-tests, chi-square tests, and logistic regression models. Results: Patients with CDI demonstrated significantly higher CRP, IL-6, SII, and CAR, coupled with lower albumin and PNI (<i>p</i> < 0.05). …”
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中国汉族人群CAV1/CAV2基因多态性与2型糖尿病的关系 by 邹丽媛, 林可意, 谢莉萍, 曾龙驿

“…【结果】CAV1基因rs926198、CAV2基因rs2270188、rs1052990位点的低频等位基因频率（MAF）在T2DM组和对照 组存在统计学差异（P=0.008、0.021、0.045）。Logistic回归分析校正年龄、性别、BMI因素，CAV1 rs926198位点CC/ CT基因型个体T2DM患病风险比TT型显著增加（OR=2.240，95%CI=1.415-3.544，P=0.001）；CAV1 rs3807986位点 GG/GA基因型比AA型患T2DM风险降低（OR=0.640，95%CI=0.449-0.913，P=0.014）；CAV2 rs2270188位点GG/GT 基因型携带者较之TT基因型T2DM患病风险明显降低（OR=0.616，95%CI=0.432-0.878，P=0.007）；CAV2 rs1052990 位点GG/GT基因型比TT型患T2DM风险亦降低（OR=0.658，95%CI=0.453-0.956，P=0.028）。…”
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Cigarette Smoking Patterns Among Racial and Ethnic Groups With Chronic Lung Diseases During the COVID-19 Pandemic by Vijaya L. Seegulam, MPH, Caretia J. Washington, BS, Parvathy P. Surendran, BPT, Alyssa M. Falise, PhD, MSPH, Diana Gomez-Manjarres, MD, Catalina Lopez-Quintero, MD, MPH, PhD

“…The authors estimated predicted probabilities derived from multiple logistic regression and negative binomial regression models to examine changes in (1) the prevalence of current cigarette smoking in the target population, (2) the mean number of days of cigarette smoking in the past 30 days, and (3) the mean number of cigarettes smoked in the past 30 days across racial/ethnic subgroups and prepandemic, pandemic, and postpandemic periods. …”
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Assessment of Types, Factors Contributing to Violence Against Women and its Effects on the Health Seeking Behaviour of Women in Rubanda Town Council Rubanda District. by Byumvuhore, Stephen

“…Frequencies, percentages, and logistic regression were used to achieve the objectives. …”
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Individual and community level factors associated with household level food insecurity of Ethiopia: multilevel mixed effects analysis of 2021 Performance Monitoring for Action Ethi... by Eyob Ketema Bogale, Tadele Fentabel Anagaw, Misganaw Guadie Tiruneh, Eneyew Talie Fenta, Destaw Endeshaw, Ousman Adal, Abiyu Abadi Tareke, Natnael Kebede, Amare Mebrat Delie

“…A multi-level mixed-effects logistic regression analysis was used to assess the individual and community-level factors associated with household-level food insecurity. …”
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Current Enzooticity of <i>Dirofilaria immitis</i> and <i>Angiostrongylus vasorum</i> in Central and Southern Italy by Donato Traversa, Simone Morelli, Angela Di Cesare, Chiara Astuti, Alessandra Barlaam, Mariasole Colombo, Fabrizia Veronesi, Barbara Paoletti, Raffaella Iorio, Raffaella Maggi, Alessandra Passarelli, Alessia Pede, Linda Rossi, Manuela Diaferia

“…., Baermann’s and fecal flotation tests), respectively. Binomial logistic regression was performed to evaluate statistically significant associations between positivity for <i>D. immitis</i> and/or <i>A. vasorum</i> and potential risk factors. …”
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Machine learning based models for predicting presentation delay risk among gastric cancer patients by Huali Zhou, Huali Zhou, Qiong Gu, Rong Bao, Liping Qiu, Yuhan Zhang, Fang Wang, Wenlian Liu, Lingling Wu, Li Li, Yihua Ren, Lei Qiu, Qian Wang, Gaomin Zhang, Xiaoqing Qiao, Wenjie Yuan, Juan Ren, Min Luo, Rong Huang, Qing Yang, Qing Yang

“…Prediction models were developed based on six machine learning algorithms, which are logistic regression (LR), support vector machine (SVM), random forest (RF), gradient boosted trees (GBDT), extremely gradient boosting (XGBoost) and muti-layer perceptron (MLP). …”
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Circulating Isthmin-1 Levels and Their Relationship with Diabetes and Metabolic Diseases in Kuwaiti Adults by Eman Alshawaf, Sulaiman K. Marafie, Mohamed Abu-Farha, Ahmed N. Albatineh, Tahani Alramah, Aldana Albuhairi, Yafa Al Qassar, Reem Zinoun, Rawan Shalabi, Sarah Behbehani, Dalal Mohammed, Fahad Alajmi, Mohammed A. Abdalla, Ebaa Al-Ozairi, Mohammad Shehab, Muhammad Abdul-Ghani, Fahd Al-Mulla, Jehad Abubaker

“…Additionally, individuals with higher CAP scores demonstrated significantly lower Ism1 levels, and the Spearman’s rank correlation revealed a negative association between Ism1 and both CAP scores (r = −0.109, <i>p</i>-value = 0.025) and insulin resistance (r = −0.141, <i>p</i>-value = 0.004). Logistic regression analysis further supported Ism1 as an independent significant protective factor against obesity-related metabolic dysfunction. …”
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Association between interpregnancy interval and adverse perinatal outcomes according to maternal age in the context of China’s two-child policy by SiQin Xiu, Li Tang, Chengjie Qin, Di Tian, Yuhong Chen, Lingling Gu, Liu Yang, Yuhao Sun, Xinghui Liu, Yonghong Lin, Yumei Wang

“…Their relationships with clinical characteristics and pregnancy outcomes were analyzed using chi-square tests and Cochran-Armitage test for trend. Logistic regression modeling, incorporating restricted cubic spline (RCS), was used to assess association between IPI and adverse perinatal outcomes, including full-term low birthweight (LBW), preterm birth (PTB), small-for-gestational age (SGA) and adverse neonatal composite (very low birthweight, very preterm birth, severe neonatal asphyxia or death). …”
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Renin–angiotensin–aldosterone system activation in plasma as marker for prognosis in critically ill patients with COVID-19: a prospective exploratory study by Katharina Krenn, Felix Kraft, Luana Mandroiu, Verena Tretter, Roman Reindl-Schwaighofer, Theresa Clement, Oliver Domenig, Matthias G. Vossen, Gregor Riemann, Marko Poglitsch, Roman Ullrich

“…All RAS parameters were evaluated as predictors of 28-day and 60-day survival using receiver operating characteristic and multivariate logistic regression analysis. Results AA2R at inclusion was a predictor of 60-day survival for ICU patients with an AUROC of 0.73. …”
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Prevalence of post-acute sequelae of SARS-CoV-2 infection in people living with HIV: a systematic review with meta-analysisResearch in context by Dimitra V. Pouliopoulou, Nicole Billias, Joy C. MacDermid, Erin Miller, Kelly K. O'Brien, Kieran L. Quinn, Monali S. Malvankar-Mehta, Tiago V. Pereira, Angela M. Cheung, Fahad Razak, Saverio Stranges, Pavlos Bobos

“…We performed meta-analysis of proportions to synthesise prevalence estimates using logit transformation and a sensitivity analysis using mixed-effects logistic regression. We used random-effects meta-analyses to summarize the odds ratio (OR) of developing Long COVID in adults living with HIV compared to adults living without HIV and conducted a sensitivity analysis including only studies with covariate-adjusted estimates that was planned a-priori. …”
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Protocol for a multisite randomised controlled trial assessing the effect of the Telehealth for Early Developmental Intervention in babies born very preterm (TEDI-Prem) programme o... by Alicia J Spittle, Peter J Anderson, Angela T Morgan, Rachel Schembri, Li Huang, Kim Dalziel, Rod W Hunt, Katherine Lee, Anne E Holland, Karli Treyvaud, Abbey L Eeles, Stacey Dusing, Shaaron Brown, Susan M Fehring, Gillian Henty, Elizabeth Kozaris

“…Secondary outcomes address other neurodevelopmental domains (Bayley-4 cognitive and language composite score; Infant Toddler Social Emotional Assessment), parental mental health (Depression Anxiety and Stress Scale 21), parent–child interaction (Emotional Availability Scale) and programme cost-effectiveness which encompasses parent quality of life (Short-Form Six-Dimension Quality of Life) and child quality of life (EuroQol Toddler and Infant Populations measure) at 12 and 24 months’ CA.Mean differences between groups will be examined using linear regression for continuous outcomes and logistic regression for binary outcomes. All models will be fitted via generalised estimating equations to account for multiple births and adjusted for the hospital sites.Ethics and dissemination This trial has Royal Children’s Hospital Human Research and Ethics Committee approval (HREC/67604/RCHM-2020) with specific site approval for all participating sites. …”
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Mental health and well-being in adolescent and young adult refugees in Sweden: A cross-sectional study of accompanied and unaccompanied individuals by Erica Mattelin, Amal R. Khanolkar, Johan Andersson, Hania Kutabi, Laura Korhonen

“…Associations between accompanied status and well-being/depression/suicidal thoughts, generalized anxiety disorder/panic disorder/PTSD symptoms, and functional ability were analyzed using linear and logistic regression, adjusted for age, gender, parental education, asylum status, and region of origin. …”
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Association between METTL14 gene polymorphisms and risk of ovarian endometriosis by Zijun Zhou, Zijun Zhou, Youkun Jie, Xianyue Hu, Xianyue Hu, Guange Chen, Yanjing Bao, Yanjing Bao, Zhenbo OuYang, Liangzhi Wu, Tianyang Gao, Qiushi Zhang, Qiushi Zhang, Wenfeng Hua, Wenfeng Hua

“…We employed unconditional logistic regression and stratified analyses to evaluate their genotypic associations with the risk of ovarian endometriosis.ResultsAmong the five SNPs examined, we found that the rs298982 A allele was significantly associated with increased risk, whereas the rs62328061 G allele was linked to a decreased risk of ovarian endometriosis. …”
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Elevated D-dimer on admission may predict poor prognosis in childhood influenza associated encephalopathy by Huizhen Wang, Lingkong Zeng, Xingfeng Cheng, Hui Li, Hong Zhang, Yuanmei Shi, Yong Zhang, Changjian Li

“…In the univariate analysis, the poor prognosis group compared with the clinically cured group showed a significant increase in the number of days of hospitalization (3.0 vs. 9.5 days, P < 0.001), high-sensitivity C-reactive protein (6.80 vs. 1.88 mg/L, P = 0.003), interleukin-6 (20.26 vs. 8.24 pg/mL, P = 0.001), interleukin-10 (11.75 vs. 4.72 pg/mL, P = 0.003), alanine aminotransferase (104.0 vs. 20.0 U/L, P = 0.011), aspartate azelotransferase (186.5 vs. 37.0 U/L, P = 0.003), serum albumin (37.99 vs. 40.76 g/L, P = 0.042), prothrombin time (13.2 vs. 11.4 s, P = 0.017), D-dimer (4.34 vs. 0.44 mg/L FEU, P < 0.001), peripheral blood CD19 B-cell count (35.11 vs. 32.75 cells/µL, P = 0.018), and cerebrospinal fluid chloride (126.82 vs. 125.50 mmol/L, P = 0.027) were statistically different in the above 11 indicators. After binary logistic regression analysis, it was concluded that D-dimer was an independent risk factor for poor prognosis (odds ratio = 1.440, 95% confidence interval 1.052–1.972, P = 0.023), and the area under the curve (95% confidence interval) was 0.802 (0.680–0.924), P < 0.001. …”
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