The validity of monitoring the control of diabetes with random blood glucose testing by O.F. Daramola, B. Mash

“…Retrospective data from a district hospital setting were used to analyse the correlation between glycated haemoglobin (HbA1c) and RBG, the best predictive value of RBG, and its predictive properties. …”
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Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank by Heli Julkunen, Juho Rousu

“…In a clinical cardiovascular risk prediction scenario using the established QRISK3 model, the method adds predictive value by identifying interactions beyond the age interaction effects currently included. …”
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Improving  the  Financial  Reporting of  Organizations  in the Digital Economy by T. Yu. Druzhilovskaya, E. S. Druzhilovskaya

“…The article analyzes the problem of the relationship between the development of the digital economy and ensuring the qualitative characteristics of financial statements, such as relevance, predictive value, confirming value, materiality, fair representation, completeness, neutrality, comparability, verifiability, timeliness, clarity and being error-free. …”
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Predictors for Gangrene and Perforation of Gallbladder Wall in Patients with Acute Cholecystitis by Polina Marinova

“…The total possible score was 11 points. The positive predictive value of the scale was 96% and identified the cases with micro-perforation and perivesical abbesses among the group with the highest total score.…”
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Diagnostic Utility of Endocan and Interleukins for Late-Onset Neonatal Sepsis by Preslava Gatseva, Alexander Blazhev, Zarko Yordanov, Victoria Atanasova

“…The best sensitivity (78%) and negative predictive value (84%) was found for IL-6. The introduction into routine practice of indicators such as PCT and IL-6 may provide an opportunity to promptly optimize the diagnostic and therapeutic approach to LOS.…”
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Relevance of telemonitoring algorithms for the management of home noninvasive ventilation by Clara Bianquis, Kinan El Husseini, Léa Razakamanantsoa, Adrien Kerfourn, Emeline Fresnel, Jean-Christian Borel, Antoine Cuvelier, Johan Dupuis, Frédéric Gagnadoux, Capucine Morélot-Panzini, Jesus Gonzalez-Bermejo, Jean-François Muir, Arnaud Prigent, Claudio Rabec, Wojciech Trzepizur, Joao Winck, Patrick Brian Murphy, Maxime Patout

“…They had a global sensitivity of 78% (95% CI 37–95%), a specificity of 40% (95% CI 19–78%), a positive predictive value of 72% (95% CI 65–77%) and a negative predictive value of 45% (95% CI 37–51%). …”
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The contributions of brain structural and functional variance in predicting age, sex and treatment by Ning-Xuan Chen, Gui Fu, Xiao Chen, Le Li, Michael P. Milham, Su Lui, Chao-Gan Yan

“…We found that voxel-based structural indices had stronger predictive value for age and sex, while voxel-based functional metrics showed stronger predictive value for treatment. …”
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Assessing the performance of the Iceland screens, treats, or prevents multiple myeloma (iStopMM) model in a multicultural Bronx cohort: implications for monoclonal gammopathy of un... by Rajvi Gor, Jeevan Shivakumar, Pallavi Surana, John Wei, Irina Murakhovskaya, Mendel Goldfinger, Noah Kornblum, Lauren Shapiro, Aditi Shastri, Ridhi Gupta, David Levitz, Marina Konopleva, Eric Feldman, Kira Gritsman, R. Alejandro Sica, Ioannis Mantzaris, Amit Verma, Dennis Cooper, Murali Janakiram, Nishi Shah

“…The area under the receiver operating characteristic (AUROC) curve assessed the iStopMM model’s performance in predicting ≥10% plasma cells, and sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. …”
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Personalised prediction of maintenance dialysis initiation in patients with chronic kidney disease stages 3–5: a multicentre study using the machine learning approach by Usman Iqbal, Tzu-Hao Chang, Chu-Lin Chou, Mai-Szu Wu, Yung-Ho Hsu, Chih-Wei Huang, Anh Trung Hoang, Phung-Anh Nguyen, Thanh Phuc Phan, Gia Tuyen Do, Huu Dung Nguyen, I-Jen Chiu, Yu-Chen Ko, Chia-Te Liao

“…Model evaluation metrics, including area under the curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value and F1 score, were employed.Results A total of 6123 and 5279 patients were included for 1 year and 3 years of the model development. …”
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AI-based staging, causal hypothesis and progression of subjects at risk of Alzheimer’s disease: a multicenter study by Simona Aresta, Raffaello Nemni, Moreno Zanardo, Graziella Sirabian, Dario Capelli, Marco Alì, Paolo Vitali, Paolo Vitali, Enrico Giuseppe Bertoldo, Valentina Fiolo, Lilla Bonanno, Giuseppa Maresca, Petronilla Battista, Francesco Sardanelli, Francesco Sardanelli, Francesca Benedetta Pizzini, Isabella Castiglioni, Christian Salvatore, Christian Salvatore

“…For the three-class classification of causal hypotheses (n = 112), the AI performance vs. biomarker-based diagnosis was: positive predictive value 91% [95% CI: 84–96%]; negative predictive value 100%, and accuracy 91% [84–96%]. …”
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Diagnostic Efficacy of Cervical Elastography in Predicting Spontaneous Preterm Birth in Pregnancies with Threatened Preterm Labor by Hayan Kwon, Ji-Hee Sung, Hyun Soo Park, Ja-Young Kwon, Yun Ji Jung, Hyun-Joo Seol, Hyun Mi Kim, Won Joon Seong, Han Sung Hwang, Soo-Young Oh, on behalf of The Korean Consortium for the Study of Cervical Elastography in Prediction of Preterm Delivery

“…This study aimed to determine the predictive value of cervical elastography for preterm delivery before 37 weeks of gestation in patients with threatened PTL and a cervical length greater than 15 mm. …”
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Early Neonatal Mortality (< 24 h) in Ecuador: A Population-Based Study on the Impact of Apgar Score, Gestational Age, Birth Weight, Delivery Type, and Healthcare Level by Iván Dueñas-Espín, María Alejandra Montaluisa, Andrea Aguilar-Molina, Fernando Aguinaga, Luciana Armijos-Acurio, Ruth Jimbo-Sotomayor, Ángela León Cáceres, María F. Rivadeneira, Silvana Rivera-Guerra, Xavier Sánchez, Betzabé Tello

“…These findings underscore the importance of Apgar evaluation in neonates and suggest a predictive value of the score for early neonatal mortality.…”
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Evaluating the diagnostic accuracy of 99mTc-labeled somatostatin receptor imaging for suspected pheochromocytomas and paragangliomas by Bo Li, Xintao Ding, Jie Zhang, Minmin Tang, Huimin Liu, Xinyu Wu, Yongju Gao

“…The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy of the imaging modality were calculated. …”
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The diagnostic utility of lung ultrasound in the assessment of interstitial lung disease associated with rheumatoid arthritis by Shaoyu Zheng, Zexuan Zhou, Guangzhou Du, Qingzi Chen, Shaoqi Chen, Jianqun Lin, Shijian Hu, Weijin Zhang, Kedi Zheng, Jinghua Zhuang, Meigan Huang, Barbara Ruaro, Cosimo Bruni, Anna-Maria Hoffmann-Vold, Marco Matucci-Cerinic, Daniel E. Furst, Yukai Wang

“…The diagnostic sensitivity and specificity of LUS were 86.84% and 77.27%, respectively. The positive predictive value, negative predictive value, a positive likelihood ratio and a negative likelihood ratio were 86.84%, 77.27%, 3.82, and 0.17, respectively. …”
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Predicting the Risk of Preterm Birth Throughout Pregnancy Based on a Novel Transcriptomic Signature by Yang Pan, Yuxin Ran, Dongni Huang, Nanlin Yin, Yanqing Wen, Yan Jiang, Yamin Liu, Hongbo Qi

“…It aimed to identify the transcriptomic signature essential for the occurrence of PTB and evaluate its predictive value in early, mid, and late pregnancy and in women with threatened preterm labor (TPTL). …”
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Diagnostic Effectiveness of Transforming Growth Factor Beta 1 in Assessing the Risk of Developing Graft Dysfunction in Liver Recipient Children by R. M. Kurabekova, O. M. Tsiroulnikova, I. E. Pashkova, A. G. Olefirenko, O. E. Gichkun, L. V. Makarova, R. A. Monakhov, P. O. Shevchenko

“…The accuracy of the method, the positive predictive value and the negative predictive value of the results were 78, 83 and 77 %, respectively. …”
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Development and validation of a clinical-friendly model for predicting 180-day mortality in the older with community-acquired pneumonia by Bingxuan Weng, Lixue Huang, Wenshu Jiao, Yuanqi Wang, Mengyuan Wang, Xuefeng Zhong, Xunliang Tong, Jin Jin, Yanming Li

“…The performance of model in predicting both short- and long-term mortality was compared with CURB-65 using AUC, sensitivity, specificity, negative predictive value and positive predictive value. Results A total of 619 patients, with a median age of 78 years (IQR: 70.5–85.0), were included in the analysis. …”
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Serum sFlt-1/PlGF ratio combined with ANXA2 correlates with adverse pregnancy outcomes in women with suspected preeclampsia by YaNuan Chen, LiYing Huang, JingWen Zhang, Ning Guo

“…The combination of the two indicators had a high predictive value for adverse pregnancy outcomes in women with suspected PE (AUC 0.858, 95CI% 0.785–0.931).Conclusion An sFlt-1/PlGF ratio ≥ 85 combined with circulating ANXA2 < 6.13 ng/mL accurately identifies those at high risk for PE-related adverse outcomes, and its early warning efficacy is significantly superior to current single-biomarker strategies. …”
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Application of continuous renal replacement therapy (CRRT) in patients with severe acute pancreatitis: an analytical study by Yiru Weng, Zhouzhou Dong, Gongjie Ye, Linhui Shi, Panpan Liu, Tingting Zhou, Honghua Ye

“…Using logistic regression, we identified CRRT failure predictors, evaluated their predictive value via ROC analysis, and developed/validated a nomogram prediction model. …”
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Association between relative fat mass and risk of gallstones in adults by Jianjun Wang, Wei He, Ruizi Shi, Yu Huang, Chuan Qin, Xi Chen, Xintao Zeng, Yongwei Huang, Decai Wang

“…The results of the ROC curves suggested that the predictive value of RFM for GS prevalence was superior to that of BMI. …”
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