IL‐2Rα is a potential biomarker for heart failure diagnosis of patients with end‐stage renal disease and haemodialysis by Bingya Lv, Zhe Wang, Ya Suo, Shuai Shao, Meng Yuan, Yue Zhang, Lihua Wang, Guangping Li, Qiankun Bao

“…Results In the HF with reduced ejection fraction (HFrEF) group, the levels of several cytokines, including stem cell growth factor‐β (SCGF‐β), C–X–C motif chemokine 10 (CXCL10), interleukin‐1α (IL‐1α), interleukin‐6 (IL‐6), interleukin‐8 (IL‐8), interleukin‐16 (IL‐16), interleukin‐1 receptor antagonist protein (IL‐1Ra), interferon‐γ (IFN‐γ), tumour necrosis factor‐α (TNF‐α), leukaemia inhibitory factor (LIF), C–C motif chemokine 3 (CCL3), interleukin‐10 (IL‐10), interleukin‐2 receptor subunit alpha (IL‐2Rα), tumour necrosis factor ligand superfamily member 10 (TNFSF10), macrophage colony‐stimulating factor (M‐CSF), granulocyte colony‐stimulating factor (G‐CSF) and stem cell factor (SCF), were significantly increased, while C–C motif chemokine 11 (CCL11)/eotaxin levels were decreased compared with those in the control group (P < 0.05). Receiver operating characteristic (ROC) curve analysis highlighted TNF‐α [area under the ROC curve (AUC) = 0.85, odds ratio (OR) = 1.080, 95% confidence interval (CI): 1.033–1.128, P = 0.001], IFN‐γ (AUC = 0.84, OR = 1.836, 95% CI: 1.289–2.615, P = 0.003) and IL‐2Rα (AUC = 0.82, OR = 1.022, 95% CI: 1.009–1.035, P = 0.001) as excellent predictors for HFrEF in haemodialysis patients with ESRD, and they outperformed soluble suppression of tumourigenicity‐2 (sST2) but slightly underperformed N‐terminal pro‐brain natriuretic peptide (NT‐proBNP). …”
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Development, validation, and clinical application of a machine learning model for risk stratification and management of cervical cancer screening based on full-genotyping hrHPV tes... by Binhua Dong, Zhen Lu, Tianjie Yang, Junfeng Wang, Yan Zhang, Xunyuan Tuo, Juntao Wang, Shaomei Lin, Hongning Cai, Huan Cheng, Xiaoli Cao, Xinxin Huang, Zheng Zheng, Chong Miao, Yue Wang, Huifeng Xue, Shuxia Xu, Xianhua Liu, Huachun Zou, Pengming Sun

“…Calibration and clinical utility were assessed with brier score, calibration curve and decision curve analysis (DCA). Findings: 1,112,846 women were recruited, of whom 599,043 were included in the analysis based on hrHPV full genotyping. …”
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Quality of Care of Adult Patients With Allergic Diseases in Urban, Rural, and Remote Primary Care Sites in the Philippines by Carol Stephanie C. Tan-Lim, Robbi Miguel G. Falcon, Jeremiah F. Feliciano, Michael B. Fong MD, Mark Anthony U. Javelosa, Leonila F. Dans, Iris Thiele C. Isip-Tan, Josephine T. Sanchez, Mia P. Rey, Antonio Miguel L. Dans

“…Methods: This was a retrospective review of electronic health records of all adult patients who consulted in the 3 sites from May 2019 to April 2022. Data of adult patients with allergic diseases was extracted from the 3 EHR systems operating across the participating sites using standardized Structured Query Language queries across the 3 systems. …”
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An auxiliary diagnostic strategy for distinguishing Guillain–Barré syndrome and chronic inflammatory demyelinating polyneuropathy: combining platelet-to-lymphocyte ratio and cerebr... by Simin Song, Yunfei Bai, Haoran Mu, Jianru Xiao, Wei Li, Yuying Zhao, Chuanzhu Yan, Jinfan Zheng, Caijing Wang, Qinzhou Wang

“…Methods For 65 patients with GBS, 38 with typical CIDP, and 65 healthy controls (HCs), clinical, serological, and CSF data were collected. Inflammatory markers were analyzed. …”
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Predicting hypoglycemia risk after gastrointestinal surgery in type 2 diabetes mellitus: a retrospective cohort study by Huilan Yao, Shijin Yuan, Hongying Pan, Sisi Hong, Chen Huang, Linfang Zhao, Hongdi Yuan, Lei Mei, Yinghong Zheng, Xiaolong Liu, Weina Lu

“…ObjectiveTo identify factors influencing hypoglycemia in patients with type 2 diabetes mellitus (T2DM) following gastrointestinal tumor surgery and construct a predictive model for assessing hypoglycemia risk.MethodsWe retrospectively collected data on 1280 patients with T2DM who underwent gastrointestinal tumor surgery and divided them into two groups—one for model building (n = 982) and another for validation (n = 298). …”
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Experimental study on metallic impurity behavior with boronization wall conditioning in EAST tokamak by Yunxin Cheng, Ling Zhang, Ailan Hu, Shigeru Morita, Wenmin Zhang, Chengxi Zhou, Darío Mitnik, Fengling Zhang, Jiuyang Ma, Zhengwei Li, Yiming Cao, Haiqing Liu

“…In this work, the impurity spectra at extreme ultraviolet (EUV) wavelength range measured by sets of fast-time-response and space-resolved EUV spectrometers are widely used in the data analysis. The variation in the boron content in plasma after boronization are investigated by monitoring the 2nd order of B V line at 48.59 Å. …”
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Seismic noise characterization for the Buddusò–Ala dei Sardi wind park (Sardinia, Italy) and its impact on the Einstein Telescope candidate site by G. Diaferia, I. Molinari, I. Molinari, M. Olivieri, M. Olivieri, F. Di Felice, A. Contu, D. D'Urso, D. D'Urso, D. D'Urso, L. Naticchioni, L. Naticchioni, D. Rozza, D. Rozza, J. Harms, J. Harms, A. Cardini, R. De Rosa, R. De Rosa, M. Di Giovanni, M. Di Giovanni, V. Mangano, V. Mangano, F. Ricci, F. Ricci, L. Trozzo, C. Murineddu, C. Giunchi, C. Giunchi

“…We run a passive seismic experiment, “Wind turbIne Noise assEsSment in the Italian site candidate for Einstein Telescope” (WINES), using a linear array of nine broadband stations, installed at increasing distances from the wind farm. Spectral analysis, based on the retrieval of spectrograms and power spectral densities at all stations, shows a significant increase in noise amplitude when the wind farm is in operation. …”
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Defining criteria for disease activity states in juvenile dermatomyositis based on the Juvenile Dermatomyositis Activity Index by Carine Wouters, Nicolino Ruperto, Maria Trachana, Angelo Ravelli, Veronika Vargová, Troels Herlin, Angela Pistorio, Pavla Dolezalova, Claudia Bracaglia, Alessandro Consolaro, Silvia Rosina, Ana Rebollo-Giménez, Ana Guilaisne Bernard-Medina, Laura Carenini

“…Optimal cut-offs were determined against external criteria by calculating different percentiles of score distribution and through receiver operating characteristic curve analysis. External criteria included the modified Pediatric Rheumatology International Trials Organization (PRINTO) criteria for clinically ID in JDM (for ID) and PRINTO levels of improvement in the clinical trial (for LDA and HDA). …”
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Revealing key regulatory factors in lung adenocarcinoma: the role of epigenetic regulation of autophagy-related genes from transcriptomics, scRNA-seq, and machine learning by Xianchang Zeng, Lingyun Wei, Lu Lv, Di Wu, Yingying Shen, Xinliang Lu, Xianghui Kong, Zhijian Cai, Jianli Wang, Jianli Wang

“…Machine learning algorithms were utilized to construct and identify diagnostic markers for LUAD, which were then validated by receiver operating characteristic (ROC) curve analysis. Cell experiments, real-time PCR, and Western blot were conducted to verify the expression of KDM6B and KANSL1 and their effects on T-cell differentiation.ResultsBased on single-cell and transcriptome analyses, we screened 19 A-ERGs that were significantly differentially expressed in lung cancer tissues. …”
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Multicentre external validation of the Neonatal Healthcare-associated infectiOn Prediction (NeoHoP) score: a retrospective case–control study by Andrew Whitelaw, Michael Sharland, Cecilia Ferreyra, Angela Dramowski, Adrie Bekker, Sithembiso Christopher Velaphi, Daynia Elizabeth Ballot, Trusha Nana, Lizel G Lloyd, Mirjam Maria van Weissenbruch, Birgitta Gleeson, Jeannette Wadula

“…This study aims to validate the Neonatal Healthcare-associated infectiOn Prediction (NeoHoP) score, designed for LMICs, across diverse neonatal populations.Methods Prospective data from three South African neonatal units in the Neonatal Sepsis Observational (NeoOBS) study were analysed. …”
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Correlation and Agreement of Quantitative Flow Ratio With Fractional Flow Reserve in Saphenous Vein Grafts by Ruben W. de Winter, Yvemarie B. O. Somsen, Roel Hoek, Pepijn A. van Diemen, Ruurt A. Jukema, Mathé P. Jonker, Albert C. van Rossum, Jos W. R. Twisk, Rolf A. Kooistra, Jasper Janssen, Sina Porouchani, Adriaan Wilgenhof, Niels J. Verouden, Ibrahim Danad, Johan H. C. Reiber, Alexander Nap, Paul Knaapen

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Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018 by Xiangling Deng, Lifei Ma, Pin Li, Mengyang He, Ruyue Jin, Yuandong Tao, Hualin Cao, Hengyu Gao, Wenquan Zhou, Kuan Lu, Xiaoye Chen, Wenchao Li, Huixia Zhou

“…The model’s area under the receiver operator curve (AUC) and F1 score were 0.938 and 0.889, respectively. …”
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Global glucose metabolism rate as diagnostic marker for disorder of consciousness of patients: quantitative FDG-PET study by Dongsheng Liu, Dongsheng Liu, Dongsheng Liu, Nan Wang, Nan Wang, Nan Wang, Ming Song, Ming Song, Ming Song, Xiaoke Chai, Xiaoke Chai, Qiheng He, Tianqing Cao, Dawei Kong, Zhuhuan Song, Guangming Zhang, Lei Liu, Xiaosong Wang, Guoqiang Chen, Shaoya Yin, Shaoya Yin, Shaoya Yin, Yi Yang, Yi Yang, Yi Yang, Yi Yang, Yi Yang, Yi Yang, Yi Yang, Yi Yang, Jizong Zhao, Jizong Zhao

“…Mean cortical metabolism of the overall sample was utilized for distinguishing between UWS and MCS, as well as for predicting the outcome at a 1-year follow-up through the application of receiver operating characteristic (ROC) analysis.ResultsWe used Global Glucose Metabolism as the Diagnostic Marker. …”
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Design and development of the Pediatric Urology Recovery After Surgery Endeavor (PURSUE) multicentre pilot and exploratory study by Kyle O Rove, Andrew C Strine, Duncan T Wilcox, Gino J Vricella, Timothy P Welch, Brian VanderBrink, David I Chu, Rajeev Chaudhry, Rebecca S Zee, Megan A Brockel, Douglas E. Coplen, Paul F. Austin, Erica J. Traxel, Jacob AuBuchon, Robert P. Moore, Vijaya M. Vemulakonda, Brian T. Caldwell, Carter J. Sevick, Nicholas Burjek, Elizabeth B. Yerkes, Yvonne Y. Chan, C.D. Anthony Herndon

“…Early paediatric urology data demonstrated ERAS reduced complications in this population.Methods and analysis In 2016, a working group of paediatric urologists and anaesthesiologists convened to develop an ERAS protocol suitable for patients undergoing lower urinary tract reconstruction and define study process measures, patient-reported outcomes and clinically relevant outcomes in paediatric and adolescent/young adult patients. …”
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Comparative study of robotic-assisted vs. laparoscopic surgery for colorectal cancer: a single-center experience by Wenpeng Wang, Jia Liu, Jiefu Wang, Li Li, Dalu Kong, Junfeng Wang

“…This study aimed to compare clinical and surgical outcomes between RACS and LCS for CRC patients.MethodsWe included 225 patients from Tianjin Medical University Cancer Institute &amp; Hospital (TJMUCH) between January 2021 and June 2024, divided into RACS (n=82) and LCS (n=143) groups. Data on demographics, clinicopathological variables, surgical parameters, and perioperative outcomes were analyzed. …”
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Efficacy of prehospital National Early Warning Score to predict outpatient disposition at an emergency department of a Japanese tertiary hospital: a retrospective study by Jumpei Tsukuda, Shigeki Fujitani, Kenichiro Morisawa, Nobuhiko Shimozawa, Yasuhiko Taira, Tomohiro Shinozaki, Takuro Endo, Toru Yoshida, Takako Motohashi, Hsiang-Chin Hsu, Shunsuke Fukuda, Takaki Naito

“…The predictive performance of NEWS for patient disposition was assessed using receiver operating characteristic curve analysis. Patient dispositions were compared among NEWS-based categories after adjusting for age, sex and presence of traumatic injury.Setting A tertiary hospital in Japan.Participants Overall, 2847 patients transported by ambulance between April 2017 and March 2018 were included.Results The mean (±SD) NEWS differed significantly among patients discharged from the ED (n=1330, 3.7±2.9), admitted to the ward (n=1263, 6.3±3.8), admitted to the ICU (n=232, 9.4±4.0) and died in the ED (n=22, 11.7±2.9) (p&lt;0.001). …”
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Construction and validation of a predictive model for the serum phosphorus reduction after total parathyroidectomy in patients with secondary hyperparathyroidism by Yingnan Feng, Yingnan Feng, Yinghui Zhou, Xiaodong Feng, Qila Sa, Qila Sa, Ningyuan Zhang, Ningyuan Zhang, Wantao Xie, Wantao Xie, Bailiang Liu, Fengyang Chen, Guangming Cheng, Wei Zhang

“…ObjectiveWe aimed to construct a predictive scoring model for the factors influencing serum phosphorus reduction following total parathyroidectomy (tPTX) in secondary hyperparathyroidism (SHPT) and provide a reference for identifying patients who can successfully correct hyperphosphatemia before surgery.MethodsThe clinical data of 529 patients with SHPT who underwent tPTX were retrospectively analyzed according to the inclusion and exclusion criteria. …”
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Development and validation of the VAE-NT index: a novel biomechanical parameter for distinguishing subclinical corneal abnormalities by Lanting Yang, Lanting Yang, Lanting Yang, Hui Xu, Hui Xu, Honghu Jiang, Jingyin Zhu, Shihao Chen, Shihao Chen

“…The VAE-NT index was compared with the tomographic and biomechanical index (TBI) in both the training and validation datasets.ResultsIn the training dataset, the optimal parameter combination forming the VAE-NT index included the following DCRs: SP A1, SP HC, A1 Time, DA Ratio Max (2 mm), DA Ratio Max (1 mm), Integrated Radius, and stress–strain index version 2 (SSI2). The receiver operating characteristic (ROC) curve analysis showed an AUC value of 0.971, with a cut-off value of 0.425, an accuracy of 95.283%, a specificity of 94.340%, and a sensitivity of 96.230%. …”
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The blood lactate/serum albumin ratio might represent a good prognostic indicator of 28-day mortality in patients with acute respiratory distress syndrome: a retrospective observat... by Jiahao Chen, Chang Gao, Ling Yang, Lijuan Yang, Ying He, Shiqi Guo, Yuanxiao Sun, Siyu He, Qiang Guo

“…The risk factors for 28-day mortality were determined using conditional logistic regression analysis. The receiver operating characteristic curve was used to evaluate the area under the curve (AUC). …”
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Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects by Maryam Yeganegi, Mahsa Danaei, Sepideh Azizi, Fatemeh Jayervand, Reza Bahrami, Seyed Alireza Dastgheib, Heewa Rashnavadi, Ali Masoudi, Amirmasoud Shiri, Kazem Aghili, Mahood Noorishadkam, Hossein Neamatzadeh

“…Recent studies highlight the effectiveness of AI techniques, such as convolutional neural networks (CNNs) and support vector machines (SVMs), achieving detection accuracy rates of up to 95% across various datasets, including fetal ultrasound images, genetic data, and maternal health records. SVM models have demonstrated 71.50% accuracy on training datasets and 68.57% on testing datasets for NTD classification, while advanced deep learning (DL) methods report patient-level prediction accuracy of 94.5% and an area under the receiver operating characteristic curve (AUROC) of 99.3%. …”
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