Showing 1,081 - 1,100 results of 6,805 for search '"\"((\\"factors AND regression analysis\\") OR (\\"factors AND regression analyzed\\"))~\""', query time: 0.20s Refine Results
  1. 1081

    Factors that contribute to loss to follow-up in the medium term after initiation of anti-vascular endothelial growth factor therapy for neovascular age-related macular degeneration... by Takaaki Sugisawa, Fumi Gomi, Yuri Harada, Hiroko Imaizumi, Shuichiro Aoki, Akiko Miki, Maya Kishi, Tomofusa Yamauchi, Daisuke Nagasato, Yoko Ozawa, Masatoshi Haruta, Nobuhiro Kato, Hisashi Matsubara, Tsutomu Yasukawa, Aki Kato, Hiroto Terasaki, Takao Hirano, Yasuhiro Iesato, Hiroki Tsujinaka, Tomoya Murakami, Yoshinori Mitamura, Makiko Wakuta, Kazuhiro Kimura, Masahiko Shimura, J-CREST (Japan Clinical Retina Study) Group

    Published 2025-01-01
    “…Stepwise regression analysis identified factors that were significantly associated with LTFU at a very early stage to be greater central retinal thickness at baseline and a prior treatment history, those associated with early LTFU to be worse baseline best-corrected visual acuity (BCVA), anti-VEGF treatment combined with photodynamic therapy, and a follow-up period that overlapped with the COVID-19 pandemic, and that associated with medium-term LTFU to be worse BCVA at 3 months. …”
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  2. 1082
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  4. 1084

    Risk factors for multidrug resistance in pulmonary tuberculosis patients with diabetes mellitus by Lianpeng Wu, Lianpeng Wu, Na Chen, Na Chen, Dandan Xia, Dandan Xia, Xiangao Jiang, Xiangao Jiang

    Published 2025-01-01
    “…Multivariate logistic regression analysis was used to identify independent risk factors for MDR, and receiver operating characteristic (ROC) curves were constructed to evaluate the predictive value of these factors.ResultsA total of 318 patients were analyzed, with 253 in the non-MDR group and 65 in the MDR group. …”
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  5. 1085

    Ecological Factors Determining Abundance of Parasitic Mites on Aedes spp. Larvae by Nurhadi Eko Firmansyah, Susi Soviana, Bambang Heru Budianto

    Published 2017-12-01
    “…The influence of ecological factors was analyzed using regression and correlation analysis. …”
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  6. 1086

    Cognitive Disorders Awareness and Associated Risk Factors in Xizang Autonomous Region by HAO Yu, WANG Junshan, ZHUO Ma, SUOLANG Quzhen, JI Shiyong, HU Yaxiong, DING Zhijie, CIDAN Zhuoga, YUAN Jing, ZHAO Yuhua

    Published 2025-01-01
    “…Demographic information and data on awareness of cognitive disorders were collected, and an ordered Logistic regression model was used to analyze influencing factors in the overall population and stratified by occupation.ResultsA total of 327 questionnaires were collected, with 14 excluded (13 for not meeting residency requirements and 1 for self-reported diagnosis of cognitive impairment), leaving 313 valid questionnaires. …”
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  7. 1087

    Clinical Factors Contributing to Age-Related Gait Dysfunction in Older Adults by Yoshihito Sakai MD, PhD, Tsuyoshi Watanabe MD, PhD, Norimitsu Wakao MD, PhD, Hiroki Matsui MD, PhD, Naoaki Osada MD, Yui Adachi MD, Yosuke Takeichi MD, Akira Katsumi MD, PhD, Ken Watanabe PhD

    Published 2025-05-01
    “…Results Among the 2083 participants, 1323 and 760 were included in the independent and assisted groups, respectively. The logistic regression analysis identified five significant factors ( P < 0.01): age, body mass index, red blood cell distribution width, skeletal muscle mass index, and sagittal vertical axis. …”
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  8. 1088
  9. 1089

    Risk Factors for Gout in Taiwan Biobank: A Machine Learning Approach by Liu YR, Nfor ON, Zhong JH, Lin CY, Liaw YP

    Published 2024-11-01
    “…Five machine learning models were used: Bayesian Network (BN), Random Forest (RF), Gradient Boosting (GB), Logistic Regression (LR), and Neural Network (NN). The predictive performance was evaluated using a split dataset (80% training set and 20% test set).Results: Variable importance analysis was performed to identify key variables, with uric acid and gender emerging as the most influential risk factors. …”
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  10. 1090
  11. 1091

    Exploring the optimal method for quantifying the contribution of driving factors of urban floods by Xi Huang, Linhan Yang, GuiCheng Yang, Jiufeng Li, Luo Liu, Yilun Liu, Xianzhe Tang

    Published 2025-06-01
    “…Effective UF management requires two key elements: (1) assessing susceptibility to identify flood-prone hotspots and (2) analyzing factor contributions to pinpoint primary drivers. …”
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  12. 1092

    Influencing factors of intraoperative blood transfusion and prognosis in lung transplant patients by YANG Huaying, QIANG Xinchen, SUN Lingling, SHAO Junliang

    Published 2025-06-01
    “…[Objective] To explore the risk factors of allogeneic blood transfusion during lung transplant surgery and prognostic effects of transfusion by analyzing the basic data, surgical details, laboratory tests results, and intraoperative blood transfusion details during the perioperative period of lung transplant, so as to guide clinical blood use. …”
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  13. 1093
  14. 1094

    Network structure and influencing factors of the quality of inbound tourism flows circulation by MA Lijun, LIANG Xiaoyao

    Published 2024-11-01
    “…Finally, Quadratic Assignment Procedure (QAP) regression was used to explore the influencing factors of inbound tourism flows circulation quality. …”
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  15. 1095

    A Pilot Study on Diabetes Distress, Insulin Growth Factor-I, Insulin-Like Growth Factor Binding Protein-3, and HbA1c in Diabetic Patients by Tahiruddin Tahiruddin, Diah Indriastuti, Syahrul Syahrul, Andi Masyitha Irwan, Satriya Pranata

    Published 2025-04-01
    “…Serum levels of IGF-I and IGFBP-3 were measured using the ELISA (Enzyme-Linked Immunosorbent Assay) kit method. The data were analyzed using regression analysis. Results: Most respondents had moderate distress, with a DDS score of 53.4%, a high IGF-I level of 76.7%, and a low IGFBP-3 level of 76.7%. …”
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  16. 1096

    Heatstroke characteristics and meteorological conditions in Hefei, China: thresholds and driving factors by Xueliang Deng, Liang Zhao, Changchun Xiao, Rui Dai, Qianqian Xu, Yeqing Yao, Caimeng Liang, Lei Yao, Dongyan He

    Published 2025-01-01
    “…The relationship between heatstroke and meteorological conditions was discussed by statistical methods, such as correlation analysis, cluster analysis and linear regression analysis. …”
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  17. 1097

    Investigation on influencing factors and prognosis of complicated infection in patients with maintenance hemodialysis by YU Qian, LI Xiao-ying, WU Xin, MIN Ya-li, CHEN Song, ZHANG Chun, PAN Zhi-yu, HUANG Yun, QU Ling-ling, LUO An-dian

    Published 2019-01-01
    “…Objective To know about influencing factors of complicated infection in patients with maintenance hemodialysis(MHD),and to understand characteristics,prognosis and influencing factors of complicated infection in patients with MHD.Methods Clinical data of MHD patients hospitalized in Guiyang First People’s Hospital from January 2012 to December 2017 were collected,and divided into the infection group and the non-infection group based on presence of complicated infection.General information and laboratory test results of these patients were collected,so as to analyze infectious factors in them and summarize types of pathogens and infections in them.Based on prognosis of these patients with MHD,they were divided into the good prognosis group and the poor prognosis group,so as to analyze influencing factors of their prognosis.Results Through comparison of the data between the infection group and the non-infection group,it was found that the risk for complicated infection increased significantly for those patients with a primary disease of diabetic nephropathy.Kt/V<1.2,and use of a ferric preparation,hemoglobin<110 g/L and albumin<40 g/L in recent 3 months(P<0.05).In the MHD patients hospitalized due to infection,the most common infectious bacteria included Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa and,staphylococcus aureus,and infection of the respiratory system is the most common.Multi-factor regression analysis revealed that the factors influencing prognosis of complicated infection in the patients with MHD included age>65,bed time>10 days,requirement for blood transfusion,multiple drug-resistant bacterial infection,and malnutrition,with statistically significant difference(P<0.05).Conclusions Primary diabetic nephropathy,Kt/V<1.2,and use of a ferric preparation,hemoglobin<110 g/L and albumin<40 g/L in recent 3 months are the risk factors of complicated infection in MHD patients;infection of the respiratory tract is the most common;and,age>65,bed time>10 days,requirement for blood transfusion,multiple drug-resistant bacterial infection and malnutrition are the hazardous factors of prognosis of complicated infection in patients with MHD.…”
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  18. 1098

    Clinical characteristics and risk factors of chronic critical illness in children with sepsis by Lin Yang, Lin Yang, Na Zang, Na Zang, Cong Liu, Cong Liu, Ying Yang, Ying Yang, Kai Bing Pu, Kai Bing Pu, Li Ping Tan, Li Ping Tan, En Mei Liu, En Mei Liu

    Published 2025-05-01
    “…Multivariate logistic regression identified pSOFA score, underlying respiratory diseases, trauma, prolonged mechanical ventilation, surgical interventions, and secondary infections as independent risk factors for the development of CCI in children with sepsis. …”
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  19. 1099

    Correlative factors associated with the recurrence of ovarian endometriosis: a retrospective study by Xi-Wa Zhao, Meng-Meng Zhang, Jian Zhao, Wei Zhao, Shan Kang

    Published 2021-08-01
    “…According to the logistic regression analysis, the significant risk factors that were independently associated with high recurrence of endometriosis were previous medical treatment of endometriosis (odds ratio [OR] = 2.06; 95% confidence interval [95% CI] = 1.27–3.34; P = 0.004), painful nodules in the pouch of Douglas (OR = 2.44; 95% CI = 1.23–4.85; P = 0.011), largest cyst diameter (OR = 1.54; 95% CI = 1.08–2.18; P = 0.016) and bilateral ovarian involvement (OR = 1.69; 95% CI = 1.19–2.39; P = 0.003). …”
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