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  1. 1781

    Prediction model for cytomegalovirus infection following hematopoietic stem cell transplantation in patients with β-thalassemia major by Lin Pan, Zhenbin Wei, Yanni Xie, Zhaoping Gan, Hongwen Xiao, Lianjin Liu, Lingling Shi, Zhongming Zhang, Meiqing Wu, Yinghua Chen, Yanye Liu, Xuemei Zhou, Chan Li, Chunjie Qin, Yongrong Lai, Rongrong Liu

    Published 2025-07-01
    “…Methods: Clinical data from 291 β-thalassemia major patients undergoing hematopoietic stem cell transplantation were retrospectively analyzed. Independent risk factors identified via univariate and multivariate logistic regression analyses formed the basis of a predictive nomogram. …”
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  2. 1782
  3. 1783

    Associations between red cell distribution width and in-hospital mortality in congestive heart failure patients with chronic obstructive pulmonary disease: a retrospective cohort s... by Mixia Li, Kai Zhang, Yu Shi, Tianyi Cai, Zhao Xuan Gu, Yu Han, Fang Ming Gu, Tian Qi Zhang, Min Gao, Bo Li, Dan Cui, Kexiang Liu

    Published 2025-05-01
    “…The impact of RDW at ICU admission on in-hospital mortality was analyzed through multivariable logistic regression models, generalized additive models, and subgroup analysis.ResultsWe enrolled 6,309 patients with congestive heart failure and concomitant chronic obstructive pulmonary disease, with an in-hospital mortality rate of 12.4% (783/6,309). …”
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  4. 1784

    The Effect of Brand Image, Price, and Marketing Content on Buying Interest of Erigo Products in Surabaya by Bagas Branahda Putra Agung, Maharani Ikaningtyas

    Published 2025-08-01
    “…Data collection was carried out through the distribution of online questionnaires. The data analysis technique used was multiple linear regression to determine the effect of each independent variable on the dependent variable. …”
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  5. 1785

    Evaluating the value of machine learning models for predicting hematoma expansion in acute spontaneous intracerebral hemorrhage based on CT imaging features of hematomas and surrou... by Tianyu Yang, Tianyu Yang, Zhen Zhao, Yan Gu, Shengkai Yang, Yonggang Zhang, Lei Li, Ting Wang, Zhongchang Miao

    Published 2025-06-01
    “…CT images were segmented using United Imaging uAI software and both imaging features and clinical characteristics were extracted. Independent risk factors were identified through univariate analysis and least absolute shrinkage and selection operator (LASSO) regression. …”
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  6. 1786

    Impact of spinal cord anomalies on defecation and quality of life in children with anorectal malformations by FAN Linxiao, FENG Wei, XIANG Chenzhu

    Published 2025-06-01
    “…The relationship between these factors and defecation function as well as quality of life was then analyzed. …”
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  7. 1787
  8. 1788

    The Chain Mediation Role of Self-Efficacy, Health Literacy, and Physical Exercise in the Relationship Between Internet Use and Older Adults’ Health: Cross-Sectional Questionnaire S... by Weizhen Liao, Chengyu Ma, Xiqiao Liu, Ziwei Sun

    Published 2025-07-01
    “…However, the role of individual factors such as self-efficacy, health literacy, and physical exercise in the chain of influence between internet use and the health of older adults is unclear. …”
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  9. 1789

    The predictive value of mean platelet volume to platelet count ratio combined with APACHEⅡs for short-term prognosis of patients with acute kidney injury treated by continuous rena... by TANG Ying-ying, NI Xun, Lv Jian-nong

    Published 2020-01-01
    “…Objective To investigate the predictive value of mean platelet volume(MPV)to platelet count(PLT)ratio(MPR)combined with acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)scoring for the short-term prognosis of patients with acute renal injury(AKI)treated with continuous renal replacement therapy(CRRT).Methods A total of 138 AKI patients who received CRRT in our hospital from January 2016 to October 2019 were retrospectively included.According to their survival conditions at discharge,they were divided into survival group(n=80)and death group(n=58).The value of MPR,APACHE Ⅱ score and their combination for predicting the death of AKI patients was analyzed by ROC curve.The independent risk factors for poor prognosis were evaluated by multivariate logistic regression analysis.Results(1)MPV,MPR and APACHE Ⅱ scores of patients in the death group were significantly higher than those in the survival group[(11.9±1.1)fl vs.(11.0±1.1)fl,P<0.01;0.11(0.09,0.14)vs.0.08(0.06,0.11),P<0.01;(25.0±3.5)score vs.(19.5±3.4)score,P<0.01].PLT count of patients in death group was significantly lower than that of survival group[(108.9±28.0)×10~9/L vs.(146.8±41.4)×10~9/L,P<0.01].(2)The cutoff values of MPR,APACHE Ⅱ score and the combination to predict the death of AKI patients were 0.08,24 points and 0.54,respectively.The AUC of death in AKI patients predicted by MPR combined with APACHE Ⅱ was significantly higher than that of MPR and APACHE Ⅱ alone[0.892(0.828-0.938)vs.0.737(0.656-0.809),P<0.01;0.892(0.828-0.938)vs.0.838(0.766-0.896),P<0.05].(3)APACHE Ⅱ score(≥24),MPR combined with APACHE Ⅱ score(APACHE Ⅱ score≥24,and MPR≥0.08),diuretics administration were the independent risk factors for poor prognosis in AKI patients[HR(95%CI):2.311(1.034-5.166),3.533(1.541-8.098),34.816(7.475-162.149),all P< 0.05].Conclusions MPR combined with APACHE Ⅱ score can well predict the short-term prognosis of AKI patients treated with CRRT.…”
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  10. 1790

    One-step ahead: evaluating the efficacy of single-visit rabies pre-exposure prophylaxis against conventional multi-visit protocol: a randomized non-inferiority clinical trial by Aman Dev Singh, Simmi Oberoi, Rohit Batish, Kanwardeep Singh, Maninder Kaur, Shailpreet Kaur Sidhu, Avneet Kaur, Prabhasees Singh

    Published 2025-08-01
    “…Both groups showed significant increases in antibody seroconversion (OD)titres from baseline (p = 0.0038 for Group A, p < 0.0001 for Group B). Regression analysis indicated no significant influence of demographic factors on antibody levels. …”
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  11. 1791

    Association Between Thyroid Hormone Levels and Disease Prognosis in Guillain–Barré Syndrome: A Retrospective Study by Yangrongzhuo Huang, Yuhan Li, Hailing Zhou, Juan Tang

    Published 2025-05-01
    “…Patients were stratified into two groups: HFGS score < 3 (good prognosis group, n = 66) and ≥ 3 (poor prognosis group, n = 116). Logistic regression identified prognostic risk factors, Receiver operating characteristic (ROC) curves determined cut‐off values for FT4 and T4, and correlation analyses evaluated relationships between thyroid hormone levels and inflammatory markers. …”
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  12. 1792

    Helicobacter pylori infection increases the risk of dyslipidemia in Chinese non-obese and non-diabetic population from the perspective of age category: a retrospective cross-sectio... by Huihui Shang, Jiawei Wang, Xinya Zhang, Dingli Zhang, Kai Yue, Song Xu

    Published 2025-07-01
    “…The correlation between H. pylori infection and blood lipid levels was compared between the two groups according to age category. Binary Logistic regression analysis was used to analyze the factors influencing H. pylori infection. …”
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  13. 1793

    Disparities in disease burden of congenital heart disease among 150,488 individuals in Western China by Jun Wang, Yang Bai, Hongmei Zhou, Jue Liu

    Published 2025-08-01
    “…Probit regression model was also used in sensitivity analysis. …”
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  14. 1794

    A qualitative non-participant observational study of non-prescription counseling in community pharmacies by Helene Marie Haldorsen Gombos, Tonje Krogstad, Marthe Rambøl Bjørknes, Hege Sletvold, Milada Cvancarova Hagen, Karin Svensberg

    Published 2025-06-01
    “…Statistical analysis was performed using Chi-square tests and Logistic regression to evaluate standard compliance and predictive factors. …”
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  15. 1795

    Prognostic significance of FT3 levels in hypertrophic cardiomyopathy patients with HFpEF by Zhen-Yu Yang, Zhi-Yuan Zhang, Wei-Jie Zhang, Da Liu, Fu-Shi Piao, Xiangyu Yan, Fang-Tao Shi, Min Yang, Jing Chen, Sheng-song Zhu, Hong-Hou He, Pei-Hong Wu, Cheng Qian, Min Lin, Jun-Qing Feng, Chun-jin Lai

    Published 2025-08-01
    “…Data on demographic and clinical variables, including FT3, were analyzed using univariate and multivariate Cox regression, Kaplan–Meier (KM) survival analysis, and restricted cubic spline (RCS) analysis to explore prognostic factors and FT3's nonlinear predictive value.ResultsAge, atrial fibrillation, and NT-proBNP levels significantly influenced prognosis, while FT3 emerged as an independent predictor of all-cause mortality and cardiac transplantation (P &lt; 0.001). …”
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  16. 1796

    The novel triglyceride‒glucose-weighted adjusted waist index as a supplementary diagnostic tool for heart failure: evidence of improved reclassification beyond traditional TyG-rela... by Yuqin Fan, Dan Ye, Kebin Zhou, Lu Cai, Longhui Yu

    Published 2025-08-01
    “…The TyG-WWI was calculated, and its association with HF risk was analyzed via multivariable logistic regression (adjusted for demographics, lifestyle factors, disease history, and medication use), restricted cubic splines (with 4 knots), and subgroup analyses. …”
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  17. 1797

    The Impact of Maqashid Syariah on the Human Development Index (HDI): The Case of Indonesia by Muhammad Ahsanul Amal, Dedi Gunawan, Miftakhul Choiri, Akhmad Roja Badrus Zaman

    Published 2024-10-01
    “…This study utilises qualitative research methods and incorporates Eviews-12 software for data analysis, notably using panel data regression techniques with selected Common Effect Model (CEM). …”
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  18. 1798

    Managerial ability and market performance: an investigation of firms listed on B3 by Rubia Frehner Poffo, Nelson Hein

    Published 2025-07-01
    “…The study employed a sample of 206 firms covering the period from 2019 to 2023. The analysis was conducted using ordinary least squares (OLS) regression with fixed effects for industry and year, utilizing the Stata® software. …”
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  19. 1799

    Digital Inclusive Finance and Regional Economic Resilience: Evidence From 279 Cities in China by Ziyun Wang, Hanbin Chen

    Published 2025-01-01
    “…Firstly, the relationship between digital inclusive finance and economic resilience is initially explored through benchmark regression, and regional differences are revealed through heterogeneity analysis. …”
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  20. 1800