Clinical impact of combined assessment of myocardial inflammation and fibrosis using myocardial biopsy in patients with dilated cardiomyopathy: a multicentre, retrospective cohort... by Toshihisa Anzai, Yasuo Sugano, Tetsuro Yokokawa, Yoshihiko Ikeda, Hatsue Ishibashi-Ueda, Kazufumi Nakamura, Hiromitsu Kanamori, Michiaki Hiroe, Kaoru Dohi, Takafumi Nakayama, Keiko Ohta Ogo, Kinta Hatakeyama, Yoshihiro Seo, Kyoko Imanaka-Yoshida

“…Here, we investigated the combined prognostic value of these two factors, as evaluated using myocardial biopsy samples.Methods This retrospective and multicentre study included patients with DCM—defined as LVEF of ≤45% and left diastolic diameter of >112% of predicted value, without evidence of secondary or ischaemic cardiomyopathy. …”
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Optimization of Eugenol, Camphor, and Terpineol Mixture Using Simplex-Centroid Design for Targeted Inhibition of Key Antidiabetic Enzymes by Amine Elbouzidi, Mohamed Jeddi, Abdellah Baraich, Mohamed Taibi, Mounir Haddou, Naoufal El Hachlafi, Meryem Idrissi Yahyaoui, Reda Bellaouchi, Bouchra El Guerrouj, Khalid Chaabane, Mohamed Addi

“…Experimental validation of the optimal mixture resulted in IC₅₀ values of 11.02 µg/mL (AAI), 60.85 µg/mL (AGI), 3.75 µg/mL (LIP), and 50.12 µg/mL (ALR), showing less than 10% deviation from predicted values, indicating high model accuracy. This study confirms the combined potential of eugenol, camphor, and terpineol, with eugenol and terpineol significantly enhancing bioactivity. …”
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Performance of Current Chronic Kidney Disease Screening Criteria in Women and Men Across Ethnic Groups: The HELIUS Study by Taryn G. Vosters, MSc, Vianda S. Stel, PhD, Kitty J. Jager, MD, PhD, Bart Ferwerda, PhD, Roos F. Marsman, MD, PhD, Frans J. van Ittersum, MD, PhD, Bert-Jan H. van den Born, MD, PhD, Henrike Galenkamp, PhD, Liffert Vogt, MD, PhD, Irene G.M. van Valkengoed, PhD

“…Area under the curve (AUC), sensitivity, specificity, and positive and negative predictive values were calculated by sex and ethnicity. …”
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Primary care patients presenting with unexpected weight loss in Australian general practices: replication of a diagnostic accuracy study by Brian D Nicholson, Jo-Anne Manski-Nankervis, Alex Lee, Meena Rafiq, Jon Emery, Barbara Hunter, Craig Nelson, Damien McCarthy, Brent Venning, George Fishman, Lucas de Mendonça, Sophie Chima, Deborah Daly, Chris Kearney, Fong Seng Lim, Javiera Martinez-Gutierrez

“…Objective We calculate positive predictive values (PPVs) of patients presenting with unexpected weight loss (UWL) being diagnosed with cancer within 6 months, using data from a population of Australian primary care patients to replicate results from a previous UK study.Design A diagnostic accuracy study involving calculation of the PPV for any cancer using retrospective data from routinely collected electronic healthcare records. …”
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The accuracy of an electronic-Surprise-Question defining end-of-life cohorts in a whole adult population by algorithmic digital risk stratification: the Proactive Risk-Based and Da... by Baldev M. Singh, Nisha Kumari-Dewat, Vijay Klaire, Jonathan Lampitt, Amy Palmer, Adam Ryder, Kamran Ahmed, Mona Sidhu, Hannah Jennens, Ananth Viswanath, Emma Parry

“…The model's ROC c-statistic for 1-year mortality was 0.73 (0.72–0.74) (p < 0.001) and sensitivity, specificity, positive and negative predictive values 50.0%, 95.1%, 11.0%, and 99.4% respectively. …”
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Developing an electronic surprise question to predict end-of-life prognosis in a prospective cohort study of acute hospital admissions by Baldev Singh, Nisha Kumari-Dewat, Adam Ryder, Vijay Klaire, Hannah Jennens, Kamran Ahmed, Mona Sidhu, Ananth Viswanath, Emma Parry

“…For the GSFSQ-No classification, the mortality odds ratio was 12.4 (11.4–13.5) (p<0.001) vs GSFSQ-Yes (c-statistic 0.72 (0.70–0.73), p<0.001; accuracy, positive and negative predictive values 81.2%, 83.6%, 83.6%, respectively). Had the tool been utilised at the time of admission, the potential to reduce possibly avoidable subsequent hospital admissions, death-in-hospital and bed days was significant (p<0.001). …”
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Systematic elucidation of the effective constituents and potential mechanisms of Scrophulariae Radix against neoplasm based on LC-MS, network pharmacology, and molecular docking ap... by Shu-jie Yu, Xiao-bin Kong, Xin Jin, Meng-yi Shan, Gang Cheng, Pei-lu Wang, Wen-long Li, Pei-yuan Zhao, Yun-jie Sheng, Bing-qian He, Qi Shi, Hua-qiang Li, Qi-ming Zhao, Lu-ping Qin, Lu-ping Qin, Xiong-yu Meng, Xiong-yu Meng

“…As a result, the material–liquid ratio was significantly reduced from 100 g/mL to 32 g/mL, and the extraction efficiency was 1.332%, which was close to the predicted value of 1.346% in the response surface method, indicating that the algorithm model had a good fit. …”
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Segmental multi-frequency bioelectrical impedance analysis indicates dehydration status after exercise by Shuang Wang, Pengfei Zhang, Yang Hu, Yao Zheng, Hongyan Yang, Jiaheng Zhou, Xuyun Liu, Jie Xu, Hui Li, Yang Liu, Jia Li, Xing Zhang, Jing Lou, Ling Dong, Guiling Wu

“…Multivariate regression and machine learning analysis showed that predicted values of dehydration were correlated with true values of dehydration (ΔBW: R2 = 0.4471, R2 = 0.5502; ΔBW%: R2 = 0.4469, R2 = 0.5073). …”
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Does syndromic surveillance assist public health practice in early detecting respiratory epidemics? Evidence from a wide Italian retrospective experience by Giovanni Corrao, Andrea Stella Bonaugurio, Giorgio Bagarella, Mauro Maistrello, Olivia Leoni, Danilo Cereda, Andrea Gori

“…Signals that occurred during periods labelled as free from epidemics were used to measure positive predictive values (PPV) and false negative values (FNV) in anticipating the epidemic wave. …”
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Assessment of synthetic post-therapeutic OCT images using the generative adversarial network in patients with macular edema secondary to retinal vein occlusion by Shi Feng, Jingyuan Yang, Xinyu Zhao, Jianchun Zhao, Yunfeng Du, Weihong Yu, Dayong Ding, Xirong Li, Youxin Chen

“…After verifying their accuracy, supporting models were used to detect the CRT, the maximal retinal thickness, IRC area, and SRF area of synthetic OCT images. The output predictive values are compared with real data according to the annotation on the real post-therapeutic OCT images.ResultsA total of 1,140 pairs of pre- and post-therapeutic OCT images obtained from 95 RVO eyes were included in the study, and 374 images were annotated. …”
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Prediction of growth and feed efficiency in mink using machine learning algorithms by A. Shirzadifar, G. Manafiazar, P. Davoudi, D. Do, G. Hu, Y. Miar

“…By comparing the calculated ADG, FCR, and RFI values with the predicted values, it was determined that the most accurate combination of features was to include all features such as sex, color, age, BW and body length on August 1st (at the beginning of the P1). …”
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The characteristics and prognosis of bronchiectasis patients with airflow limitation: a prospective longitudinal study by Yuanting Cai, Linbin Xv, Zili Zhu, Shiyi He, Tianyu Sun, Chao Cao

“…High-resolution computed tomography (HRCT) was used for diagnosing bronchiectasis, whereas postbronchodilator forced expiratory volume in one second of the predicted value (post-FEV1%) was employed for grading airflow limitation. …”
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Response Surface Methodology Optimization of Time-Resolved Fluorescence Immunoassay for Rapid Detection of AflatoxinB₁ in Yellow Rice Wine by Mengjie Zhu, Dun Wang, Du Wang, Jing Dong, Xue Wang, Qi Zhang, Man Xiao

“…The predicted results showed that the maximum recovery rate of AFB₁ (97.35%) could be obtained under the optimum conditions of a methanol-water volume fraction of 78%, a sample to extraction solvent ratio of 1:3.2, a heating temperature of 34 °C, and a heating time of 6.4 min. These predicted values were further verified by validation experiments. …”
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Association between different hemoglobin glycation index and prognosis in patients with a first diagnosis of acute myocardial infarction: a retrospective study based on the MIMIC-I... by Dong Chen, Dong Chen, Ben Hu, Xing-hua Chen, Xing Wei, Jun Feng, Ze-ping Hu

“…BackgroundThe hemoglobin glycation index (HGI) is defined as the difference between the observed and predicted values of glycosylated hemoglobin (HbA1c), which is closely associated with a variety of poor prognoses. …”
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Quantitative genetic analysis reveals potential to genetically improve fruit yield through selection in Solanum lycopersicum × Solanum pimpinellifolium crosses under humid conditio... by Chikezie Onuora Ene, Wosene Gebreselassie Abtew, Happiness Ogba Oselebe, Temesgen Matiwos Menamo, Friday Ugadu Ozi, Chibueze Kelechi Ene, Nnamdi Ogwo

“…The genetic effects were estimated using the Hayman model using the best linear unbiased prediction values. Significant differences in traits were observed among parental lines and their crosses. …”
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Risk factors and risk‐indicating model for early‐onset neonatal sepsis after preterm prelabor rupture of membranes: A historical cohort study by Brynhildur Tinna Birgisdottir, Tomas Andersson, Ingela Hulthén Varli, Sissel Saltvedt, Farhad Abtahi, Ulrika Åden, Malin Holzmann

“…We combined variables associated with high risk into a risk‐indicating model and estimated its performance by calculating its sensitivity, specificity, accuracy, positive and negative predictive values, positive likelihood ratio, and area under the ROC curve. …”
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Glycylglycine promotes the solubility and antigenic utility of recombinant HCV structural proteins in a point-of-care immunoassay for detection of active viremia by Heba Shawky, Ashraf A. Tabll, Reem M. Elshenawy, Naiera M. Helmy, Rehab I. Moustafa, Yasser K. Elesnawy, Marwa M. Abdelghany, Yasmine S. El-Abd

“…The ideal S/Co threshold predicting active viremia (> 2.75) showed an AUC value of 0.9362 (95% CI: 0.9132 to 0.9593), with 87.64, 91.23% sensitivity and specificity, and 94.14, 82.11% positive and negative predictive values, respectively. The different panels of samples assayed with our EIA showed a good concordance with the viral loads and also significant correlations with the golden standards of HCV diagnosis in viremic patients. …”
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DYNAMICS OF INCIDENCE WITH MYOCARDIAL INFARCTION IN THE POPULATION OF KUZBASS AND THE RUSSIAN FEDERATION FOR THE PERIOD 2011-2019 by Андрей Георгиевич Петров, Николай Владимирович Абрамов, Сергей Анатольевич Макаров, Сергей Николаевич Филимонов, Виктор Андреевич Семенихин, Наталья Степановна Черных

“…In order to establish a trend and identify the dynamics of the studied number of indicators as it would be outside the influence of «random» factors, the method of alignment by the method of least squares was applied. The predicted values of the incidence of myocardial infarction in Kuzbass and the Russian Federation have been calculated. …”
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Differential synovial fluid white blood cell count for the diagnosis of chronic peri-prosthetic joint infection – a systematic review and meta-analysis by M. Sabater-Martos, M. Clauss, M. Clauss, A. Ribau, R. Sousa

“…Thresholds of WBC count <span class="inline-formula">&lt;</span> 1500 and <span class="inline-formula">&gt;3000</span> cells per microlitre and PMN <span class="inline-formula">&lt;</span> 65 % and <span class="inline-formula">&gt;75</span> % provide reliable negative and positive predictive values. A standardized diagnostic framework is essential for addressing remaining controversies and ensuring consistent interpretation across clinical settings.…”
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The correlation of circulating pro‐angiogenic miRNAs’ expressions with disease risk, clinicopathological features, and survival profiles in gastric cancer by Wei Peng, Ya‐Nan Liu, Si‐Qiang Zhu, Wen‐Qiang Li, Feng‐Cheng Guo

“…MiR‐18a, miR‐20a, and miR‐210 disclosed good predictive values of GC risk. Six pro‐angiogenic miRNAs including miR‐17‐5p, miR‐92a, miR‐210, miR‐20a, miR‐18a, and miR‐296 expressions were positively while 1 pro‐angiogenic miRNA (miR‐130a) was negatively correlated with tumor malignancy degree in GC patients. …”
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