Predictive value of the simplified pulmonary embolism severity index combined with serum uric acid and neutrophil percentage in the short-term prognosis of lung cancer patients with acute pulmonary embolism by YAN Qiumei, ZHANG Xing, LI Yuying

“…Conclusion： sPESI combined with SUA and neutrophil percentage has a good predictive value for short-term prognosis in lung cancer patients combined with APE. …”
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Predictive Value of Individual Gastric Secretion Indices and Their Constellations for Predicting the Response of Gastric Mucosal Parietal Cells to Pentagastrin Stimulation and Famotidine Blocking Effect in Patients with Gastric and Duodenal Ulcers by M. Pliatsko, O. Faiura, N. Grechkivska, O. Voloshyna, Y. Leshchuk, A. Maksymuk

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Diagnostic value of breast ultrasound in mammography BI-RADS 0 and clinically indeterminate or suspicious of malignancy breast lesions by Dobrosavljević Aleksandar, Rakić Snežana, Nikolić Branka, Janković-Ražnatović Svetlana, Dragojević-Dikić Svetlana, Milošević Zorica, Jurisić Aleksandar, Skrobić Milica

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Predictive role of quantification of myocardial fibrosis using delayed contrast-enhanced magnetic resonance imaging in nonischemic dilated cardiomyopathies: a systematic review and... by E Z Golukhova, S A Aleksandrova, B Sh Berdibekov

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Influencing factors of lower extremity deep venous thrombosis after lumbar fusion in elderly patients by Chen Jing, Zhuge Hengyan, Huang Zhihui, Wu Lin

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The relationship between serum uric acid level and concentration of proangiogenic endothelial progenitor cells in chronic heart failure patients by A. A. Kremzer

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Heart rate variability and increased risk for developing type 2 diabetes mellitus by Penčić-Popović Biljana, Ćelić Vera, Ćosić Zoran, Pavlović-Kleut Milena, Čaparević Zorica, Kostić Nada, Milovanović Branislav, Šljivić Aleksandra, Stojčevski Biljana

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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 renal replacement therapy by TANG Ying-ying, NI Xun, Lv Jian-nong

“…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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The value of hematological parameters measured at first presentation in patients diagnosed with pregnancy in predicting early pregnancy loss; can NLPR be a new predictive value? A case-control study by Oguzhan Gunenc, Sevcan Sarikaya, Muslu Kazim Korez

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Relationship between peripheral blood miR-146b-5p levels and lymphocyte subsets in patients with sepsis and its predictive value for prognosis: a single-center study by Sha Cheng, Jiaojiao Wang, Pengfei Wang, Xianli Long, Huiling Liu, Xueyin Li, Xiaowei Zhang, Xuemei Zhao, Hang Sun, Chuanxin Wu

“…In this study, we investigated the expression of miR-146b-5p and lymphocyte subsets in sepsis patients and analyzed their correlation with the aim of establishing their combined predictive value for clinical outcomes and advancing personalized treatment strategies.MethodsFrom January 2020 to July 2024, we enrolled 191 patients diagnosed with sepsis at the ICU of the Second Affiliated Hospital of Chongqing Medical University and collected basic clinical data. …”
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Comment on &amp;ldquo;Predictive Value of Advanced Lung Cancer Inflammation Index and Development of a Nomogram for Prognosis in Patients with Cervical Cancer Treated with Radiotherapy&amp;rdquo; [Response to Letter] by Yu Q, Jin X

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Multi-omics analysis unveils the predictive value of IGF2BP3/SPHK1 signaling in cancer stem cells for prognosis and immunotherapeutic response in muscle-invasive bladder cancer by Yaobang Wang, Wuyue Song, Chao Feng, Shulin Wu, Zezu Qin, Tao Liu, Yu Ye, Rong Huang, Yuanliang Xie, Zhong Tang, Qiuyan Wang, Tianyu Li

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Predictive Value of Age, Creatinine, and Ejection Fraction I and II Scores for Postoperative Atrial Fibrillation in Isolated On-Pump Coronary Artery Bypass Grafting Surgery: A Multicenter Retrospective Study by Sameh Alagha, Serkan Mola, Mehmet Çeber, Alp Yıldırım

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COMPARATIVE ANALYSIS OF ACTUAL AND PREDICTED CANCER MORTALITY IN THE RUSSIAN FEDERATION REGIONS AFFECTED BY RADIOACTIVE CONTAMINATION DUE TO THE CHERNOBYL ACCIDENT by V. V. Kuchumov, A. A. Lyapkalo, M. S. Nikolaevich

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Combining echocardiography with carotid ultrasound parameters in predicting major adverse cardiovascular events among older individuals with coronary artery disease by Tianli Jia, Xiaoxiao Li, Qianqian Xie

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Intra-operative blink reflex neurophysiological monitoring in posterior skull base neurosurgery by Michael W. Y. Lee, Shu-wah Chau

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Predictive value of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) for all-cause and cardiovascular mortality with non-hyperhomocysteinemia: evidence from NHANES 1999 to 2006 by Liang Deng, Haicheng Zhong, Sheng Zhou, Ziming Wang, Jingjing Sun, Chang Liu, Xinghui Li, Quankai Cheng, Jie Deng

“…Lastly, the NHHR's predictive value for mortality as well as its potential mediating effects were evaluated.ResultsA total of 13,847 participants were included in our study. …”
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Combined Predictive Value of GLIM-Defined Malnutrition and Preoperative Adipose Tissue ¹⁸F-FDG Uptake for Recurrence-Free Survival After Radical Gastrectomy in Patients with Gastric Cancer by Xuan Zhou, Kailai Yin, Huanhuan Hong, Heqing Yi, Linfa Li

“…Background: The Global Leadership Initiative on Malnutrition (GLIM) criteria provide a standardized approach for assessing the nutritional status of patients and demonstrate strong predictive value for the prognosis of patients with gastric cancer. …”
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Comparison of robotic-assisted and laparoscopic partial nephrectomy based on the PADUA score and the predictive value of the PADUA score and the Mayo Adhesive Probability score for postoperative complications: a single-center retrospective study by Shuo Liu, Bowen Zhang, Bowen Weng, Xiangqiang Liu, Sichuan Hou

“…Abstract Purpose This study compared perioperative outcomes of robot-assisted partial nephrectomy (RAPN) and laparoscopic partial nephrectomy (LPN) through the PADUA score as well as assessed the predictive value of the PADUA score and the Mayo Adhesive Probability (MAP) score for postoperative complications. …”
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Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes by Xueli Zhang, Yu Huang, Shunming Liu, Shuo Ma, Min Li, Zhuoting Zhu, Wei Wang, Xiayin Zhang, Jiahao Liu, Shulin Tang, Yijun Hu, Zongyuan Ge, Honghua Yu, Mingguang He, Xianwen Shang

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