Machine learning-assisted assessment of extracellular vesicles can monitor cellular rejection after heart transplant by Jacopo Burrello, Stefano Panella, Ilaria Barison, Chiara Castellani, Alessio Burrello, Lorenzo Airale, Jessica Goi, Veronica Dusi, Roberto Frigerio, Gino Gerosa, Chiara Tessari, Nicola Pradegan, Giuseppe Toscano, Giovanni Pedrazzini, Mattia Corianò, Francesco Tona, Sara Bolis, Alessandro Gori, Marina Cretich, Marny Fedrigo, Annalisa Angelini, Lucio Barile

“…The AI model achieves an accuracy of 93.3% at leave-one-out testing (AUC 0.968), and 78.9% at validation in an independent cohort (AUC 0.832), with high specificity and negative predictive value. EV profiling outperforms conventional biochemical markers and provides anticipatory insight into rejection dynamics. …”
Get full text

Prognostic significance of severe mitral annular calcification in aortic stenosis: implications for aortic valve replacement outcome by Valeria Pergola, Dan-Alexandru Cozac, Maria Teresa Savo, Saima Mushtaq, Raffaella Motta, Roberto Pedrinelli, Pasquale Perrone-Filardi, Gianfranco Sinagra, Morena De Amicis, Maria Vittoria Chiaruttini, Gabriele Cordoni, Giulia Lorenzoni, Giuseppe Tarantini, Gino Gerosa, Dario Gregori, Giorgio De Conti, Domenico Corrado, Gianluca Pontone

“…Multivariate Cox models evaluated the predictive value of severe MAC alongside other significant variables. …”
Get full text

The Anti-Nucleocapsid IgG Antibody as a Marker of SARS-CoV-2 Infection for Hemodialysis Patients by Akemi Hara, Shun Watanabe, Toyoaki Sawano, Yuki Sonoda, Hiroaki Saito, Akihiko Ozaki, Masatoshi Wakui, Tianchen Zhao, Chika Yamamoto, Yurie Kobashi, Toshiki Abe, Takeshi Kawamura, Akira Sugiyama, Aya Nakayama, Yudai Kaneko, Hiroaki Shimmura, Masaharu Tsubokura

“…Adjusted models had lower predictive value. <i><b>Conclusions:</b></i> Anti-IgG N antibodies showed high diagnostic accuracy for detecting prior SARS-CoV-2 infection in hemodialysis patients, though performance declined over time. …”
Get full text

Redefining the role of IL-18 in post-surgical recovery and sepsis: a key mediator of inflammation resolution by Ioanna Papatheodorou, Gabriela Blažková, Veronika Bosáková, Zuzana Tomášiková, Erin Spearing, Robin Klieber, Pavel Ostašov, Julie Štíchová, Martina Dvončová, Alexandra Mýtniková, Jan Emmer, Kamila Bendíčková, Tomáš Tomáš, Vladimír Šrámek, Petros Kolovos, Monika Holubová, Martin Helán, Marcela Vlková, Jan Frič, Marcela Hortová-Kohoutková

“…Finally, TNF-α/IL-18 ratio showed a high predictive value of clinical severity in septic patients. …”
Get full text

Integrated machine learning identifies disulfidptosis-related and ferroptosis-related genes to evaluate survival prognosis and treatment efficacy in kidney renal clear cell carcino... by Yuan Xiang, Zijian Zhou, Tong Mu, Shunyao Zhang, Lei Xie, Yajie Zhou, Wenxiong Zhang, Liuxiang Fu

“…The nomogram with risk score demonstrated significant predictive value than nomogram without the risk score. …”
Get full text

Comprehensive analysis of single-cell and bulk RNA sequencing data unveils antigen-presenting and processing fibroblasts and establishes a predictive model in gastric cancer by Chenggang Zhang, Fangqi Chen, Jie Li, Yixuan He, Juan Sun, Zicheng Zheng, Guanmo Liu, Yihua Wang, Weiming Kang, Xin Ye

“…Abstract Background Antigen-presenting and processing fibroblasts (APPFs) have emerged as pivotal regulators of antitumor immunity. However, the predictive value of APPF-related genes (APPFRGs) in the prognosis and tumor immune status of gastric cancer (GC) remains largely unexplored. …”
Get full text

CARDIAC TRANSPLANT REJECTION AND NON-INVASIVE COMON CAROTID ARTERY WALL FUNCTIONAL INDICES by A. O. Shevchenko, I. U. Tunjaieva, A. A. Nasyrova, B. L. Mironkov, I. M. Ilinsky, N. P. Mozhejko, I. I. Muminov, O. P. Shevchenko

“…Analysis showed that iRIG values above estimated treshold 7172 cm/sec2 suggested relative risk of any type of rejection 17.7 (95%CI = 6.3–49.9) sensitivity 80.5%, specificity – 81.1%, negative predictive value – 84.3%. Conclusions. Increased carotid wall stiffness is found in patients with both antibody-mediated and cellular car- diac allograft rejection. …”
Get full text

Development and validation of a multidisciplinary risk assessment scale for immune checkpoint inhibitor-associated myocarditis by Yanan DAI, Yuan LIU, Yuchen XU, Qingqing CAI, Yan WANG, Yuhong ZHOU, Leilei CHENG, Junbo GE

“…The association between pretictive risk stratifications and actual assessment results was assessed using the Cox proportional hazards regression model. The predictive value of the scale for ICI-associated myocarditis was evaluated using receiver operating characteristic (ROC) curve. …”
Get full text

Prognostic impact of type 2 diabetes mellitus and coronary microvascular dysfunction in patients undergoing rotational atherectomy during PCI by Lijun Feng, Yuxuan Zhang, Chenyun Zhang, Zining Chen, Jingnan Pan, Zhiling Gao, Delong Chen, Abuduwufuer Yidilisi, Jiacheng Fang, Yiyue Zheng, Tingting Mei, Jiantao Liu, Jianping Xiang, Jinlong Zhang, Changling Li, Jifang Cheng, Jian’an Wang, Jun jiang, Jian’an Wang

“…Abstract Background The combined predictive value of type 2 diabetes mellitus (T2DM) and coronary microvascular dysfunction (CMD) in rotational atherectomy (RA) patients during the PCI remains unclear. …”
Get full text

Improved epigenetic age prediction models by combining sex chromosome and autosomal markers by Zhong Wan, Peter Henneman, Huub C. J. Hoefsloot, Ate D. Kloosterman, Pernette J. Verschure

“…Our data indicated no added predictive value of Y chromosomal DNAm markers in our best-performing prediction model, even though we acknowledged the potential of applying Y chromosomal markers for age prediction. …”
Get full text

Integrating Dynamic Red Blood Cell Distribution Width Monitoring and β-Blocker Therapy for Mortality Prediction in Intensive Care Unit Cardiomyopathy Patients: A Bayesian Multivari... by Si Chen, Rui Nie, Yi Wang, Haoran Guo, Yan Wang, Haixia Luan, Xiaoli Zeng, Hui Yuan

“…Comparative analysis demonstrated that RDW exhibited greater predictive value over the aggregate index of systemic inflammation (AISI), systemic inflammation response index (SIRI), and SII. …”
Get full text

A Multi-Algorithm Machine Learning Model for Predicting the Risk of Preterm Birth in Patients with Early-Onset Preeclampsia by Xu Y, Zu Y, Zhang Y, Liang Z, Xu X, Yan J

“…Yanhong Xu,1,&amp;ast; Yizheng Zu,2,&amp;ast; Ying Zhang,1,&amp;ast; Zewei Liang,1 Xia Xu,1,3– 5 Jianying Yan1,3– 5 1College of Clinical Medicine for Obstetrics &amp; Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, People’s Republic of China; 2The Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, People’s Republic of China; 3Fujian Clinical Research Center for Maternal-Fetal Medicine, Fuzhou, Fujian, People’s Republic of China; 4Laboratory of Maternal-Fetal Medicine, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, People’s Republic of China; 5National Key Obstetric Clinical Specialty Construction Institution of China, Fuzhou, Fujian, People’s Republic of China&amp;ast;These authors contributed equally to this workCorrespondence: Xia Xu, College of Clinical Medicine for Obstetrics &amp; Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, People’s Republic of China, Email xuxia0623@fjmu.edu.cn Jianying Yan, College of Clinical Medicine for Obstetrics &amp; Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, People’s Republic of China, Email yanjy2019@fjmu.edu.cnPurpose: To analyze the risk factors for preterm birth in patients with early-onset preeclampsia (EOPE) based on multi-algorithm machine learning and to construct a predictive model to explore the predictive value of the model.Methods: A retrospective analysis was conducted on 442 EOPE patients from a single tertiary center, divided into preterm birth (&lt; 37 weeks, n=358) and term-born (≥ 37 weeks, n=84) groups. …”
Get full text

Comparison of [99mTc]Tc-FAPI SPECT/CT and [18F]FDG PET/CT as predictive biomarkers for immunotherapy response in gastrointestinal cancer by Yu Zhang, Hong Chen, Dajia Lin, Zhiyi Lin, Jiyun Shi, Hannan Gao, Chenshen Huang, Fangqing Xue, Fan Wang, Wenxin Chen

“…For diagnostic accuracy in a total of 253 lesions in 78 patients, compared with [18F]FDG PET/CT, [99mTc]Tc-FAPI SPECT/CT demonstrated a higher sensitivity (100% [15 of 15 lesions] vs. 20% [3 of 15]; P < 0.001), accuracy (100% [48 of 48 lesions] vs. 75% [36 of 48];P < 0.001), and negative predictive value (100% [33 of 33 lesions] vs. 69% [36 of 48 lesions]; P = 0 0.001) in detecting peritoneal spread, and a higher sensitivity (85% [17 of 20 lesions] vs. 50% [10 of 20]; P = 0.041) in detecting liver metastases. …”
Get full text

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

“…However, further validation in large-scale prospective cohorts is warranted to confirm its long-term predictive value and generalizability across diverse populations. …”
Get full text

PLAGL2 as a prognostic biomarker and an EMT-promoting factor in PDAC by Yan-Hui Yang, Hao Wang, Zhe-Hua Xing, Qian-Qian Bai, Wei-Feng Liu, Da-Huan Li, Chi Zhang, Shu-Min Zhang, Fang-Fei Liu, Yu-Bo Liu, Hua Fan

“…We subsequently examined the expression of PLAGL2 via immunohistochemistry and PCR in PDAC tumor tissue samples from our hospital, explored the relationships between PLAGL2 expression and clinical features, and evaluated the predictive value of PLAGL2 for the survival of PDAC patients. we investigated the effect of PLAGL2 on the epithelial‒mesenchymal transition (EMT) process by examining its association with the expression of EMT-related proteins. …”
Get full text

Define a good prognosis of RNF43 codon 659-mutated and concomitant genomic signatures in CRC: an analysis of the cBioPortal database by Feng Wang, Li Lin, Zhongkang Li, Lei Qin, Shuai Zhang, Xueqing Hu, Yunbo Zhao, Yingying Huang

“…All mutation data were filtered by the 1021-panel (Geneplus-Beijing, China), and the processed data were used to analyze the predictive value of RNF43-mutated to OS and concomitant co-mutations. …”
Get full text

Right ventricular dysfunction for prediction of long‐term recovery in de novo HFrEF : a PROLONG‐II substudy by Aiste Monika Jakstaite, Johanna Mueller‐Leisse, Henrike A.K. Hillmann, Stephan Hohmann, Jörg Eiringhaus, Udo Bavendiek, Tibor Kempf, Christian Veltmann, Johann Bauersachs, David Duncker, D. Berliner

“…Abstract Aims To analyse the predictive value of advanced markers of right ventricular (RV) function and RV‐pulmonary arterial (PA) coupling in forecasting long‐term left ventricular (LV) improvement in de novo heart failure with reduced ejection fraction (HFrEF). …”
Get full text

Altered albumin/neutrophil to lymphocyte ratio are associated with all-cause and cardiovascular mortality for advanced cardiovascular-kidney-metabolic syndrome by Xiaoshuang Yin, Jinmei Zou, Jing Yang

“…RCS analysis indicated an L-shaped link between ANLR and both ACM and CVM, both before and after PSM (all Pnon-linearity &lt; 0.001). The predictive value of ANLR, NLR, and ALB for CVM and ACM in individuals with advanced CKM syndrome demonstrated that ANLR and NLR exhibited comparable predictive capabilities for both ACM and CVM, outperforming ALB. …”
Get full text

Optimasi Convolutional Neural Network Untuk Deteksi Covid-19 pada X-ray Thorax Berbasis Dropout by I Gede Totok Suryawan, I Putu Agus Eka Darma Udayana

“…It proved that when this system was tested with COVID-19 thorax x-ray public database data, the classifier that used this architecture could achieve an accuracy rate of 95.20% followed by precision and recall value reaching 94.80% and 94.80%. respectively and last but not least F-score of 95.18% and Negative Predictive value of 95.60%  It could also save training time up to 62% compared to other deep learning architectures. …”
Get full text

Genetic scores to stratify risk of developing multiple islet autoantibodies and type 1 diabetes: A prospective study in children. by Ezio Bonifacio, Andreas Beyerlein, Markus Hippich, Christiane Winkler, Kendra Vehik, Michael N Weedon, Michael Laimighofer, Andrew T Hattersley, Jan Krumsiek, Brigitte I Frohnert, Andrea K Steck, William A Hagopian, Jeffrey P Krischer, Åke Lernmark, Marian J Rewers, Jin-Xiong She, Jorma Toppari, Beena Akolkar, Richard A Oram, Stephen S Rich, Anette-G Ziegler, TEDDY Study Group

“…The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. …”
Get full text