Showing 21 - 28 results of 28 for search '(("factors and regression analysis") OR ("factor and regression analyzed"))*', query time: 0.12s Refine Results
  1. 21

    Predictive values of neck circumference and TyG index on polycystic ovary syndrome with metabolic syndrome by Yixuan Liu, Aihong Liu, Xiangyu Xu, Huali Wang, Qinghai Wang, Xianwei Huang, Ping Liu

    Published 2025-07-01
    “…ANOVA, multi-factor logistic regression analysis and ROC curve prediction analysis were performed. …”
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    Article
  2. 22

    Prevalence and factors associated with anxiety and depression among the older people in ethnic minority areas in southern China: a cross-sectional study by Suyi Wu, Liu Yang, Haini Mo, Li Li, Zirong Li, Yanping Ying

    Published 2025-06-01
    “…Descriptive analysis, univariate analysis, and two-factor logistic regression analysis were employed to explore the influencing factors of depression and anxiety among the older people in ethnic minority areas.ResultsThe prevalence rates of anxiety and depression were 11.42 and 15.94%, respectively. …”
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  3. 23

    RISK FACTORS FOR THE EARLY NEONATAL MORTALITY IN NEWBORNS WITH VERY LOW AND EXTREMELY LOW BIRTH WEIGHT by О. V. Lebedeva, Т. А. Chikina

    Published 2014-12-01
    “…The association of risk factors with the early neonatal mortality was assessed by means of a multiple-factor logistic regression analysis. A critical p error level was set equal to 0.05. …”
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  4. 24

    Predictive value of hemoglobin, serum PAF, and IL-17 in patients with radiation enteritis complicated with intestinal obstruction and construction and validation of predictive mode... by Meng Wang, Yang Zhao, Wenqiang Ren

    Published 2025-08-01
    “…The decision curve analysis (DCA) was used to evaluate the value of clinical application.ResultsMulti-factor Logistic regression analysis showed that diabetes, decreased hemoglobin level, increased serum PAF and IL-17 levels, CRP, were the independent risk factors for intestinal obstruction in patients with radiation enteritis (p < 0.05). …”
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  5. 25

    Relevancy Prediction of the Emerging Pathogens with Porcine Diarrhea by Logistic Regression Model by Benqiang Li, Jie Tao, Xin Li, Jinghua Cheng, Ying Shi, Pan Tang, Huili Liu

    Published 2025-02-01
    “…Furthermore, multiple-factor logistic regression analysis confirmed that PAstV, PKoV, bovine viral diarrhea virus (BVDV), and PEDV were closely related to porcine diarrhea. …”
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  6. 26

    Clinicopathological Features and Prognostic Factors of Renal Cell Carcinoma in Young Patients Under 45 Years: A Single-Center Retrospective Study by Gao Y, Yan H, Zhang T, Lu G, Ma L

    Published 2025-06-01
    “…Single - factor Cox regression analysis revealed that symptoms, hypertension, clinical stage, pathological grade, and pathological type were independent risk factors for overall survival in young renal cancer patients.Conclusion: Young RCC patients present with unique clinicopathological characteristics and prognostic factors. …”
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  7. 27

    The Current Status and Influencing Factors of Multiple Chronic Conditions among the Elderly Aged 60 and above in Gansu Province by ZHU Xianshang, ZENG Hongyu, LYU Fengli, WANG Jiancheng

    Published 2025-04-01
    “…The results of multi-factor Logistic regression analysis showed that gender, age, ethnicity, pre-retirement occupation, spouse, number of children, relationship with children, self-rated health status, self-rated life satisfaction, and loneliness are influencing factors for the occurrence of multiple chronic conditions in the elderly (P<0.05) . …”
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  8. 28

    Analysis of the inflammatory storm response and heparin binding protein levels for the diagnosis and prognosis of sepsis-associated encephalopathy by Dian Yu, Jun Liu, Xiaoyun Song, Yongfeng Ao, Xiaomin Li, Yi Han

    Published 2025-02-01
    “…Subsequently, Multi-factor logistic regression analysis revealed that ultra-high IL-6 (> 5000 pg/ml), IL-10 (> 1000 pg/ml), and HBP (> 300 ng/ml) levels and elevated SOFA and APACHE-II scores were risk cytokines for the development of SAE (P < 0.05). 28-day mortality was significantly higher in patients in the SAE group and in the IL-6 > 5000 pg/ml group compared to patients in the USAE and IL-6 < 5000 pg/ml groups(P < 0.001).The four screened predictors of HBP > 300 ng/ml, IL-6 > 5000 pg/ml, decreased GCS score, and decreased APACHEII score were combined into a new predictive data model (risk score).In the SAE group, patients with high risk scores had a higher 28-day mortality rate compared with the low risk score group (P < 0.001). …”
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