Microcirculatory resistance index based on a single angiographic view predicts long-term prognosis following rotational atherectomy in patients with acute coronary syndrome by Xinbo Bai, Xiaohua Yu, Yufang Li, Zhe Zhang, Xuemei Guo, Yanan Xue, Luwa Gao, Kun Wang, Zhonghai Wei, Qing Dai, Biao Xu, Lina Kang

“…Abstract Background To explore the long-term predictive value of the angiographic microcirculatory resistance (AMR) index for patients with acute coronary syndrome (ACS) undergoing rotational atherectomy (RA). …”
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Evaluating the potential of phenotypic age to enhance cardiovascular risk prediction over chronological age in the UK Biobank by Kristine J. S. Kwan, Shi-Shuai Xie, Hai-Lei Li, Xue-Guang Lin, Yi-Jie Lu, Bo Chen, Kai-Xin Ge, Shu-Ya Tang, Hui Zhang, Shuai Jiang, Jing-Dong Tang

“…We applied a Cox regression model with time-dependent variables to assess the association between PhenoAgeAccel and incident CVD. The predictive value of PhenoAge and PhenoAgeAccel was evaluated with reference to the Framingham Risk Score (FRS) model using Kaplan-Meier curves, receiver operating characteristic curves (AUC), and Harrel’s C-index. …”
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CPAP modulation of sleep microstructure (N2-SSD and REM-AHI) as predictors of neurological recovery in ischemic stroke patients with moderate-to-severe OSA by Tianyu Jing, Tianyu Jing, Tianyu Jing, Liwen Xu, Liwen Xu, Shutong Sun, Wenyi Yu, Wenyi Yu, Yixi Zheng, Yixi Zheng, Gang Xu, Xinhao Shen, Tieyu Tang, Cheng Chu, Cheng Chu

“…Continuous positive airway pressure (CPAP) therapy is the primary treatment for stroke-related OSA; however, its positive effects on patient prognosis and the underlying mechanisms remain controversial.ObjectiveThis study aimed to investigate the impact of CPAP therapy on the recovery of IS patients with moderate-to-severe OSA and to identify biomarkers significantly associated with prognosis to assess their predictive value for short-term neurological outcomes. …”
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Risk factors of adverse outcome of COVID-19 and experience of Tocilizumab administration in patients on maintenance hemodialysis due to diabetic kidney disease by E. M. Zeltyn-Abramov, M. A. Lysenko, N. F. Frolova, T. N. Markova, N. I. Belavina, N. N. Klochkova, S. V. Kondrashkina, R. T. Iskhakov, A. I. Ushakova

“…For risk identification of upcoming lethal outcome a predictive model was created with the use of discovered RF as variables. The predictive value of this model is 92,45% (positive prognostic value — 96,5%, negative prognostic value — 87,5%).In TCZ treated subgroup the laboratory markers of adverse outcome were detected with application of correlation analysis. …”
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Triglyceride glucose-weight-adjusted waist index as a cardiovascular mortality predictor: incremental value beyond the establishment of TyG-related indices by Jiajun Qiu, Jin’e Li, Shan Xu, Jingqi Yang, Haixia Zeng, Yuying Zhang, Shiqi Yang, Lixuan Fang, Jiadian Huang, Hongtao Zhou, Jiaying Feng, Yujie Zan, Jia Zhan, Jianping Liu

“…Conclusion The current study is the first to validate that the TyG-WWI is a reliable risk prediction tool for cardiovascular death in the general population and has greater predictive value than traditional TyG-related parameters. …”
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Associations of Blood Pressure and Heart Rate and Their Contribution to the Development of Cardiovascular Complications and All-Cause Mortality in the Russian Population of 25-64 Y... by S. A. Shalnova, V. A. Kutsenko, A. V. Kapustina, E. B. Yarovaya, Yu. A. Balanova, S. E. Evstifeeva, A. E. Imaeva, S. A. Maksimov, G. A. Muromtseva, N. V. Kulakova, O. N. Kalachikova, T. M. Chernykh, O. A. Belova, G. V. Artamonova, E. V. Indukaeva, Yu. I. Grinshtein, R. A. Libis, D. V. Duplyakov, O. P. Rotar, I. A. Trubacheva, V. N. Serebryakova, A. Yu. Efanov, A. O. Konradi, S. A. Boytsov, O. M. Drapkina

“…To study the relationship of blood pressure (BP) and heart rate (HR) in a sample of men and women 25-64 years old and their predictive value for the development of fatal and non-fatal cardiovascular diseases (CVD) and mortality from all causes.Material and methods. …”
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A retrospective analysis of 6942 amniocentesis cases by Qingsha An, Yuxiao Huang, Feifei Yu, Yilun Tao, Juan Li, Xiaoze Li

“…The analysis encompassed the detection rate of chromosomal abnormalities via amniocentesis, the proportion and positive predictive value (PPV) of each indication group, the distribution of maternal age and gestational age, and the characteristic patterns of confirmed diagnostic findings. …”
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Multidrug-resistant Klebsiella pneumoniae coinfection with multiple microbes: a retrospective study on its risk factors and clinical outcomes by Xixi Song, Chonghe Xu, Zhongqi Zhu, Chenchen Zhang, Chao Qin, Juan Liu, Xiaoli Kong, Zhijun Zhu, Wei Xu, Mei Zhu

“…This study successfully established a predictive model based on risk factors, which has good predictive value for both patients with coinfections and those with CRKP. …”
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Development and external validation of a nomogram prediction model based on quantitative coronary angiography for predicting ischemic lesions: a multi-centre study by Shuai Yang, Shuai Yang, Shuang Leng, Shuang Leng, Zhouchi Wang, Jiang Ming Fam, Jiang Ming Fam, Adrian Fatt Hoe Low, Adrian Fatt Hoe Low, Ru-San Tan, Ru-San Tan, Ping Chai, Ping Chai, Lynette Teo, Lynette Teo, Chee Yang Chin, Chee Yang Chin, John C. Allen, Mark Yan-Yee Chan, Mark Yan-Yee Chan, Khung Keong Yeo, Khung Keong Yeo, Aaron Sung Lung Wong, Aaron Sung Lung Wong, Soo Teik Lim, Soo Teik Lim, Qinghua Wu, Liang Zhong, Liang Zhong, Liang Zhong

“…For per-patient analysis, the corresponding values were 85.8%, 85.7%, 86.0% in the development cohort and 82.2%, 83.3%, 81.1% in the validation cohort.ConclusionThe nomogram may be useful for predicting ischemic lesions using QCA measurements and the LASSO regression algorithm, with external validation indicating potential predictive value in cardiology care settings.…”
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Triglyceride glucose waist circumference and non alcoholic fatty liver disease: a systematic review and meta analysis by Ziyi Xin, Lanlan Feng, Qingwen Yu, Yongmin Shi, Ting Tang, Xuhan Tong, Siqi Hu, Yao You, Shenghui Zhang, Xingwei Zhang, Mingwei Wang, Jiake Tang

“…The triglyceride glucose-waist circumference (TyG-WC) index, a novel measure for assessing IR, may hold significant predictive value for NAFLD. However, the relationship between TyG-WC and the risk of NAFLD remains elusive. …”
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Serum LCAT as a Gender-Neutral Biomarker for Early Osteoporosis: A Multicenter Cohort Validation Study by Wen Y, Cheng S, Gou L, Zhou W, Li Y, Wang R, Wu J, Dai X, Gao M, Wang L, Xue B, Wang Y

“…Moreover, serum LCAT levels exhibited significantly higher predictive value for osteoporosis than that of conventional serum 25-hydroxyvitamin D (25OHD) levels.Conclusion: We demonstrate for the first time that reduced serum LCAT concentrations predict osteoporosis risk independently of confounding factors, qualifying it as a promising early-stage diagnostic biomarker. …”
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Predictive multigenic scale. Analysis of own results in metastatic breast cancer by R. M. Paltuev, S. N. Aleksakhina, A. S. Artemyeva, E. A. Baychorov, S. Yu. Bakharev, A. A. Bozhok, V. A. Vasin, V. I. Vladimirov, O. A. Volynshchikova, A. Yu. Vorontsov, E. A. Gaysina, A. A. Hoffman, E. N. Imyanitov, V. V. Klimenko, A. V. Komyakhov, M. M. Konstantinovа, M. V. Kopp, A. G. Kudaybergenova, I. A. Lalak, D. L. Matevosyan, N. M. Mudzhiri, O. V. Poltareva, O. I. Sevryukova, V. F. Semiglazov, T. Yu. Semiglazova, M. M. Urezkova, L. A. Churilova

“…We analyzed the expression of 28 genes with a high predictive value that have been substantially studied (including ESR1, PGR, PIK3CA, BCAR4, BCAS2, CCND1, CCND2, CCND3, FOXA1, Erb2, EGFR, CDH3, FOXC1, KRT14, KRT5, CD274, CDK4, CDK6, P53, PTEN, BRCA1, BRCA2, CHEK2, CLDN3, CLDN7, AR, TOP2a, TUBBIII). …”
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Elevated FDG uptake in non-tumorous lung regions does not predict immune checkpoint inhibitor–related pneumonitis in lung cancer patients by Friederike Völter, Friederike Völter, Friederike Völter, Lukas Wehlte, Blerina Resuli, Blerina Resuli, Blerina Resuli, Julia Walter, Julia Walter, Julia Walter, Lea Daisenberger, Maria Ingenerf, Maurice Heimer, Matthias Brendel, Matthias Brendel, Matthias Brendel, Gabriel T. Sheikh, Lena M. Unterrainer, Lena M. Unterrainer, Lena M. Unterrainer, Diego Kauffmann-Guerrero, Diego Kauffmann-Guerrero, Diego Kauffmann-Guerrero, Thomas Pfluger, Lucie Heinzerling, Lucie Heinzerling, Amanda Tufman, Amanda Tufman, Amanda Tufman

“…Logistic regression analyses were performed to identify the predictive value of pretreatment SUV for the development of cinrPneumonitis.ResultsA total of 239 patients were included, of whom 41 (17.2%) developed cinrPneumonitis. …”
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Development of a predictive model for metachronous liver metastasis in gastric cancer by Siyuan Wang, Siyuan Wang, Gaozan Zheng, Fengsu Wu, Ye Tian, Xinyu Qiao, Xinyu Dou, Hanjun Dan, Hanjun Dan, Guangming Ren, Liaoran Niu, Pengfei Wang, Lili Duan, Yumao Yang, Jianyong Zheng, Fan Feng

“…Besides conventional parameters, we identified and incorporated peripheral blood monocyte and lymphocyte counts as novel predictors, demonstrating their independent predictive value. Integrating these factors into nomogram could enhance predictive accuracy of MLM.…”
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Skin rash in metastatic hormone sensitive prostate cancer patients treated with apalutamide: a retrospective multicenter study in Korea by Won Tae Kim, Hyun Ho Han, Seok Joong Yun, Seong Hyeon Yu, Taek Won Kang, Yun-Sok Ha, Jun Nyung Lee, Tae Gyun Kwon, Byung Hoon Kim, Won Ik Seo, Chan Ho Lee, Jae Il Chung, Jung Ki Jo, U-Syn Ha, Ji Youl Lee, Hwang Gyun Jeon, Seong Il Seo, Kyo Chul Koo, Byung Ha Chung, Jong Wook Kim, Joongwon Choi, Jong Wook Park, Hongzoo Park, Sungchan Park, Soo Dong Kim, Hak Min Lee, Sung Kyu Hong, Jae Young Joung

“…This study aims to investigate the incidence rate of skin rash and the predictive value of inflammation markers for skin rash in real-world Korean patients. …”
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Projection selection and rapid atrial pacing improves early outcomes after self-expanding transcatheter aortic valves by María Tamargo, Enrique Gutiérrez, Jorge García Carreño, María Eugenia Vázquez Álvarez, Ricardo Sanz-Ruiz, Mike Huanca, Erika Ludeña, Javier Soriano, Jaime Elí, Francisco Fernández-Avilés, Javier Bermejo

“…The absence of the Wenckebach phenomenon during RAP had a negative predictive value of 97% (95%CI, 91-99) for pacemaker implantation at the follow-up, which significantly decreased the need for 24-hour temporary pacemaker monitoring in the COP + RAP group (91.8% vs 28.1%; P < .0001) and the median [IQR] length of stay (5.0 [4-8] days vs 2.0 [1-4] days; P < .0001). …”
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An App model that utilizes a logistic regression algorithm for predicting choledocholithiasis: A prospective clinical trial by F. García-Villarreal, L.M. Torres-Treviño, C. Herrera-Figueroa, J.O. Jáquez-Quintana, A.A. Garza-Galindo, C.A. Cortez-Hernández, D. García-Compeán, R.A. Jiménez-Castillo, H.J. Maldonado-Garza, J.A. González-González

“…In patients with an intermediate risk for CL, the AUC value was 0.72 and the positive predictive value (PPV) was 70%. In patients with a high risk for CL, the AUC value was 0.78 and the PPV was 89%. …”
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An Exosomal mRNA Urine Test for Detection and Risk Stratification of Human Kidney Transplant Rejection by Rania El Fekih, Kurt Franzen, James Hurley, Brian C. Haynes, Tamara Merhej, Areej Alghamdi, Elliot Hallmark, Shuran Xing, Sonia Kumar, John Choi, Zhabiz Solhjou, Christa Deban, Anis Saad, Ahmad Halawi, Nour Younis, Katherine Cashman, Maribel Dagher, Siawosh K. Eskandari, Soltan Al Chaar, Helmut Rennke, Astrid Weins, Reza Abdi, Anil Chandraker, James F. Markmann, Kassem Safa, Leonardo V. Riella, Matt McFaul, Chris Ventura, Alexandre V. Vlassov, Richard Formica, Camila Macedo, Johan Skog, Jamil R. Azzi

“…Results: Four mRNAs (IL32, B2M, CXCL11, and PGK1) performed well in distinguishing biopsies with rejection or significant inflammation from those without inflammation, achieving 94% sensitivity, 62% positive predictive value, and 52% specificity. Patients who tested positive by the signature but negative by biopsy were nearly twice as likely to experience adverse outcomes in the 5-year follow-up period, including subsequent rejection, thereby showing the limitations of kidney biopsies and the prognostic potential of molecular signatures. …”
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Flower lose, a cell fitness marker, predicts COVID‐19 prognosis by Michail Yekelchyk, Esha Madan, Jochen Wilhelm, Kirsty R Short, António M Palma, Linbu Liao, Denise Camacho, Everlyne Nkadori, Michael T Winters, Emily S Rice, Inês Rolim, Raquel Cruz‐Duarte, Christopher J Pelham, Masaki Nagane, Kartik Gupta, Sahil Chaudhary, Thomas Braun, Raghavendra Pillappa, Mark S Parker, Thomas Menter, Matthias Matter, Jasmin Dionne Haslbauer, Markus Tolnay, Kornelia D Galior, Kristina A Matkwoskyj, Stephanie M McGregor, Laura K Muller, Emad A Rakha, Antonio Lopez‐Beltran, Ronny Drapkin, Maximilian Ackermann, Paul B Fisher, Steven R Grossman, Andrew K Godwin, Arutha Kulasinghe, Ivan Martinez, Clay B Marsh, Benjamin Tang, Max S Wicha, Kyoung Jae Won, Alexandar Tzankov, Eduardo Moreno, Rajan Gogna

“…In patients presenting in the early phase of COVID‐19 illness, hFwe‐Lose expression accurately predicts subsequent hospitalization or death with positive predictive values of 87.8–100% and a negative predictive value of 64.1–93.2%. hFwe‐Lose outperforms conventional inflammatory biomarkers and patient age and comorbidities, with an area under the receiver operating characteristic curve (AUROC) 0.93–0.97 in predicting hospitalization/death. …”
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A protein-based classifier for differentiating follicular thyroid adenoma and carcinoma by Yaoting Sun, He Wang, Lu Li, Jianbiao Wang, Wanyuan Chen, Li Peng, Pingping Hu, Jing Yu, Xue Cai, Nan Yao, Yan Zhou, Jiatong Wang, Yingrui Wang, Liqin Qian, Weigang Ge, Mengni Chen, Feng Yang, Zhiqiang Gui, Wei Sun, Zhihong Wang, Minghua Ge, Yi He, Guangzhi Wang, Yongfu Zhao, Huanjie Chen, Xiaohong Wu, Yuxin Du, Wenjun Wei, Fan Wu, Dingcun Luo, Xiangfeng Lin, Haitao Zheng, Xin Zhu, Bei Wei, Jiafei Shen, Jincao Yao, Zhennan Yuan, Tong Liu, Jun Pan, Yifeng Zhang, Yangfan Lv, Qiaonan Guo, Qijun Wu, Tingting Gong, Ting Chen, Shu Zheng, Jingqiang Zhu, Hanqing Liu, Chuang Chen, Hong Han, Sathiyamoorthy Selvarajan, Michael Mingzhao Xing, Kennichi Kakudo, Erik K Alexander, Yijun Wu, Yu Wang, Dong Xu, Hao Zhang, Xiu Nie, Oi Lian Kon, N Gopalakrishna Iyer, Zhiyan Liu, Yi Zhu, Haixia Guan, Tiannan Guo, We-TEC Investigators

“…It exhibited a 95.7% negative predictive value for ruling out malignancy. This study presents a promising protein-based approach for the differential diagnosis of FTA and FTC, potentially enhancing diagnostic accuracy and clinical decision-making.…”
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