Analysis of risk factors for hyperlipidemia in 1233 maintenance hemodialysis patients by LUO Deng-gui, QI Ai-rong, XU Yuan-zhao, FU Bo, YANG Jun, YANG Dong

“…For basic kidney diseases,there were 630 cases of primary glomerular disease( 51. 3%),281 cases of diabetic nephropathy( 22. 9%),71 cases of hypertensive renal injury( 5. 8%),17 cases of chronic renal tubular interstitial disease( 1. 4%),88 cases of obstructive nephropathy( 7. 2%),7 cases of lupus nephritis( 0. 6%),51 cases of polycystic kidney cases( 4. 2%),15 cases of gouty nephropathy( 1. 2%),15 cases of hepatitis B related nephropathy( 1. 2%),and 60 cases of other kidney diseases( 4. 9%). Multiple factor Logistic regression analysis revealed that sex and blood calcium were closely related to hyperlipidemia in patients with MHD,and HP was an importantly protective factor for hyperlipidemia in MHD patients( P < 0. 05). …”
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Back to the basics–risk factor identification of pediatric malignant lymphadenopathy proven by pathological studies by Wei-Hsiang Su, Cheng-Che Wu, Chia-Man Chou, Sheng-Yang Huang, Hou-Chuan Chen

“…Weight loss, fixed LAP, firm consistency, and serum lactate dehydrogenase (LDH) exceeding 240 U/L were more related to malignant LAP than other risk factors. Multiple regression analysis revealed two independent risk factors. …”
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Unveiling Patient Satisfaction: Analysis of Factor Influencing Patient-Centered Care At Bunda Margonda Hospital by Putu Agus Sujana Putra, NLP Dina Susanti, Made Rismawan, Made Dian Shanti Kusuma

“…In the non-BPJS group, age (p = 0.029) and marital status (p = 0.024) were significant factors. Logistic regression analysis revealed that length of stay was the most influential factor for BPJS patients (aOR = 2.3; p = 0.023), whereas marital status was the primary factor for non-BPJS patients (aOR = 1.3; p = 0.024). …”
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Changes of serum tumor marker levels and analysis of risk factors in patients with chronic kidney disease by YU Jun-nan, LIU Cai-xia, ZHAO Nan, SUN Dong

“…Objective To investigate whether the expression of serum tumor markers in patients with chronic kidney disease(CKD)has changed,and to analyze the risk factors influencing the changes.Methods The serum tumor markers[including α-fetoprotein(AFP),carcinoembryonic antigen(CEA),CA125,CA199,CA153,TPSA],albumin(Alb),serum creatinine,hemoglobin levels,age and glomerular filtration rate(GFR)of 427 CKD patients and 420 healthy medical examiners from the Affiliated Hospital of Xuzhou Medical University were collected and compared for differences between the two groups.The relevant factors that lead to changes in tumor markers in patients with CKD were screened out by univariate analysis,and multi-factor logistic regression analysis were used to identify risk factors for elevated tumor indicators.Results There was no significant difference in serum TPSA between the CKD group and the healthy control group(P<0.05).The AFP level was lower than that of the healthy control group,and the difference was statistically significant(P<0.01).The levels of CEA,CA125,CA199,and CA153 were higher than those in the healthy control group,with statistically significantdifferences(P<0.01).Logistic regression analysis showed that decreased glomerular filtration rate was a risk factor for CEA elevation,serum albumin and hemoglobin decline were risk factors for CA125 elevation,serum albumin decrease was a risk factor for CA199 and CA153 elevation,and age was a risk factor for elevated TPSA.Conclusions The application value of TPSA in CKD patients is the same as that in the normal population.In the diagnosis of related tumors based on serum tumor indicators,a comprehensive analysis must be done in conjunction with factors such as patients’ age,renal function,serum albumin,and hemoglobin levels.…”
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Predictive modeling of the development height of water-conducting fracture zones in mines in Shandong mining area by XU Dongjing, DOU Xuan, LI Ye, XIA Zhicun

“…Taking 36 sets of data measuring the development height of hydraulic fracture zones under similar geological conditions in Shandong mining area as example for analysis, we selected coal seam thickness, mining depth, sloping length of working face, and hard rock lithology ratio coefficient as the main control factors for the prediction model. We analyzed their correlation with the development height of hydraulic fracture zones, and established a multifactorial prediction model with highly-correlated factors via regression analysis and deep learning calculation. …”
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Effects of Scrambler Therapy in Patients with Failed Back Surgery Syndromes and Factors Associated with Depression Affecting Pain before and after the Therapy by Hayoung Byun, Min-Kyun Oh, Chang Han Lee

“…The changes in the ODI, BPI, and residual pain before and after the therapy were analyzed using the Wilcoxon signed rank test. Spearman correlation analysis and Fisher’s exact test were used to confirm the correlation between BDI and other factors. …”
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Internet addiction and its influencing factors among middle school students in Hunan province: a cross-sectional study by Fei WANG, Lixi QIN, Zhuoga NIMA, Yaqing TAN, Miyang LUO, Yanhua CHEN, Jiayou LUO

“…The chi-square test was used to compare the differences in internet addiction detection rates between groups, and multi-factor logistic regression analysis was used to analyze the influencing factors of internet addiction. …”
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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

“…The 3 - year and 5 - year survival rates for the asymptomatic group were 100% and 97%, respectively, while for the symptomatic group, they were 94% and 83%, respectively. 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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Association of Robson Ten Group Classification System with neonatal/postneonatal mortality: an analysis for the effect of the mass migrationAJOG Global Reports at a Glance by Damla Çarkçı Yıldız, MD, Elif Gül Yapar Eyi, MD

“…Robson Group Distribution: The distribution of cesarean births across Robson groups was varied, with the highest mortality rates observed in groups R8, R9, R10, R6, and R7 (p=.001). Risk Factors: Logistic regression analysis identified Robson groups, fetal presentation, gestational age, Apgar scores, and newborn weight/height as significant risk factors for neonatal /postneonatal mortality. …”
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Association of pregnancy outcomes with neonatal TSH levels in euthyroid singleton pregnancies by Weiwei Feng, Weiwei Feng, Mengfan Song, Mengfan Song, Yu Meng, Yu Meng

“…Univariate and multivariate logistic regression analyses were conducted to adjust for confounding factors and further analyze the relationship between pregnancy outcomes and elevated neonatal TSH levels.ResultsA total of 24079 pregnant women were included in this study. …”
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Predictive Value of AIP and AGR for Non-alcoholic Fatty Liver Disease and Significant Liver Fibrosis by Zhang Simin, Zhou Changyu, Shi Xianquan, Huang Lizhen

“…SPSS 27.0 and R 4.4.0 were used to analyze the data, single-factor Logistic regression analysis was applied to screen the influencing factors of NAFLD, stepwise regression was applied to screen the variables, and multi-factor Logistic regression was performed to construct the prediction model and draw the column graph. …”
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Association of restless legs syndrome with malnutrition,inflammation and sleep quality in hemodialysis patients by HUANG Hua-xing, SHEN Liang-lan, ZHANG Fen, WANG Chen, FANG Xing-xing, CHEN Dong-mei

“…Malnutrition-inflammation( MIS) and Pittsburgh Sleep Quality Index( PSQI) were evaluated. Single factor Logistic regression analysis was used to analyze the related factors. …”
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Comparison of differences in hematogenous metastasis among cervical cancer patients by CT-guided three-tube intracavitary brachytherapy and hybrid intracavitary and interstitial br... by Bo Yang, Yinping Hu, Shuhui Yu, Chunfang Zhao, Zhongyan Dou, Lan Li, Kangming Li, Meiping Jiang, Lan Zhang, Xingrao Wu

“…By propensity score matching (PSM) between the two groups according to 1:1 matching, single factor logistic regression analysis revealed that there was no significant difference in the incidence of hematogenous metastasis between the two groups (OR = 0.382, 95% CI = 0.071–2.040; P = 0.260). …”
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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

“…In addition, the GCS score and serum cholinesterase levels in the SAE group were lower than in the non-SAE group (P < 0.05). 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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