Incidence, Risk Factors, and Modified Risk Assessment Model of Venous Thromboembolism in Non‐Hodgkin Lymphoma Patients by Wen Li, Rui Liu, Ying Shen, GongZhizi Gao, Rui Yang, Yiwen Wang, Ruoyu Yang, Zujie Lin, Ruijun Dong, Wanhong Zhao, Aili He, Ju Bai

“…Sequential testing of TM and TAT achieved a sensitivity of 66.7%, specificity of 100%, positive predictive value (PPV) of 100%, and negative predictive value (NPV) of 96.7%. …”
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Prevalence and influencing factors of the dyadic psychological stress among patients with lung cancer and their family caregivers: a cross-sectional study by Juan Li, Chan Li, Jie Zou, Fang-Qun Cheng, Li Peng, Li-Hong Deng, Pei-Pei Wu, Sai-Yu Gao, Zhi-Yao Xiong, Ying Zuo, Yan Luo, Xiao-Hua Rao, Bo Yuan, Ou-Ying Chen, Jing-Ping Zhang

“…For lung cancer patients, patients’ illness perception positively predicted their depression scores and patients’ level of mindfulness and level of self-compassion negatively predicted their depression scores; patients’ illness perception positively predicted their anxiety scores, and only living with children, patients’ mindfulness and self-compassion levels were negatively predicted their anxiety scores. …”
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Concentration and the value of D-dimer in the diagnosis of deep vein thrombosis by Van Nguyen-Thanh Phan, De Nhi Nguyen, Tri Dang-Minh Bui, Minh Duc Tong, Trung Hoang Nguyen, Dung Thi-Ngoc Nguyen

“…Conclusion: With a threshold of D-dimer concentration of 500 ng/mL to determine deep venous thrombosis, the specificity and positive predictive value of the method are low, but the sensitivity and negative predictive value are high. …”
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Plasma fibronectin is a prognostic biomarker of disability in Parkinson’s disease: a prospective, multicenter cohort study by Shuzhen Zhu, Hualin Li, Zifeng Huang, Yiheng Zeng, Jianmin Huang, Guixia Li, Shujuan Yang, Hang Zhou, Zihan Chang, Zhenchao Xie, Rongfang Que, Xiaobo Wei, Minzi Li, Yanran Liang, Wenbiao Xian, Mengyan Li, Ying Pan, Fanheng Huang, Lin Shi, Chengwu Yang, Chao Deng, Lucia Batzu, Karolina Poplawska-Domaszewicz, Shuhan Chen, Ling-Ling Chan, K Ray Chaudhuri, Eng-King Tan, Qing Wang

“…Abstract In a prospective longitudinal study with 218 Parkinson’s disease (PD) patients in the discovery cohort and 84 in the validation cohort, we aimed to identify novel blood biomarkers predicting disability milestones in PD. Through Least Absolute Shrinkage and Selection Operator-Cox (Lasso-Cox) regression, developed nomogram predictive model and Linear mixed-effects models, we identified low level of plasma fibronectin (pFN) as one of the best-performing risk markers in predicting disability milestones. …”
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Immunocytochemistry and DNA-image Cytometry in Diagnostic Effusion Cytology. II. Diagnostic Accuracy in Equivocal Smears by Helma Motherby, Nicolaus Friedrichs, Mary Kube, Bahram Nadjari, Kristiane Knops, Andreas Donner, Betty Baschiera, Peter Dalquen, Alfred Böcking

“…Positive predictive value was 97.7%, the negative one 79.2%.…”
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Strength Theory Model of Unsaturated Soils with Suction Stress Concept by Pan Chen, Changfu Wei, Jie Liu, Tiantian Ma

“…The model is able to predict conveniently the strength changes of unsaturated soils undergoing repeated changes of water content. …”
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Does bladder outflow obstruction obfuscate the traditional clinical factors that are used to assess the risk of prostate cancer at rapid‐access diagnostic clinics? by Thomas Philip Cahill, Samuel Joseph Withey, Steve Hazell, Declan Cahill, Netty Kinsella

“…Abstract Objectives To understand whether bladder outflow obstruction influences the association between traditional clinical predictive factors, particularly prostate‐specific antigen (PSA) density and clinically significant prostate cancer (csPCa). …”
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Association of estimated glucose disposal rate with metabolic syndrome prevalence and mortality risks: a population-based study by Xiaoli Chen, Aihua Li, Qilin Ma

“…Conclusion eGDR is strongly associated with MetS and predicts all-cause and CVD mortality in individuals with MetS. …”
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Early Radiologic Diagnosis of Pulmonary Infection in Febrile Neutropenic Patients: A Comparison of Serial Chest Radiography and Single CT Chest by Wanaporn Burivong, Thanatorn Sricharoen, Apichart Thachang, Sunsiree Soodchuen, Panitpong Maroongroge, Vichit Leelasithorn

“…Sensitivity, specificity, positive predictive value, and negative predictive value of serial chest film in the early radiologic diagnosis of pulmonary infection are 50%, 74%, 61%, and 64%, respectively. …”
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Postanesthetic Cold Sensibility Test as an Indicator for the Efficacy of Inferior Alveolar Nerve Block in Patients with Symptomatic Irreversible Pulpitis of Mandibular Molars by Mohamed El Sayed, Kamis Gaballah

“…The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and Youden index for the cold test were 0.87, 0.91, 0.93, 0.84, 0.89, and 0.78, respectively. …”
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Statistical trend analysis and forecast modeling of air pollutants by A. Jaiswal, C. Samuel, V.M. Kadabgaon

“…Autoregressive integrated moving average model (1,1,1) is also used on the annual concentration levels to predict forthcoming year's annual pollutants value. …”
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Comparison of serum ischemia modified albumin levels between preeclamptic and healthy pregnant women by Dinç Zuhal, Çakar Erbil, Kumru Pınar, Erel Özcan, Neşelioğlu Salim, Cimsit Nilüfer, Boz Gizem

“…When IMA threshold value of >0.98 was taken to predict preeclampsia; the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated as 65.15%, 64.71%, 64.18%, and 65.67%, respectively. …”
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Assessment of Racial Bias within the Risk Analysis Index of Frailty by Michael A. Jacobs, MS, Leslie R. M. Hausmann, PhD, Robert M. Handzel, MD, MS, Susanne Schmidt, PhD, Carly A. Jacobs, MPH, Daniel E. Hall, MD, MDiv, MHSc

“…Conclusions:. The RAI tends to predict mortality among Black patients better than it predicts mortality among White patients. …”
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Changes in the Parietal Lobe Subregion Volume at Various Stages of Alzheimer’s Disease and the Role in Cognitively Normal and Mild Cognitive Impairment Conversion by Fang Lu, Qing Ma, Cailing Shi, Wenjun Yue

“…The model consisting of the left IPL_6_4 (caudal area 40) and bilateral IPL_6_5 showed the best combination for predicting the CN progression to MCI. The left IPL_6_1 (caudal area 39) showed the best predictive power in predicting the progression of MCI to AD. …”
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Eosinophilic Asthma Secondary to Adjuvant Anti-PD-1 Immune Checkpoint Inhibitor Treatment in a Melanoma Patient by P. Kissoonsingh, B. Sutton, Syed U. Iqbal, Lalit Pallan, Neil Steven, L. Khoja

“…Peak expiratory flow rate was 94% predicted, and corrected gas transfer was 6.29 (78% predicted) with KCO 1.18 (93% predicted). …”
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Design Tools for Bolted End-Plate Beam-to-Column Joints by Giusy Terracciano, Gaetano Della Corte, Gianmaria Di Lorenzo, Raffaele Landolfo

“…Predicting the response of beam-to-column joints is essential to evaluate the response of moment frames. …”
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Relationships between Academic Achievement, Awareness about the Postgraduate Study and Postgraduate Study Intentions by İlhan İlter

“…The results of the analysis showed that academic achievement directly predicted the awareness about PG study and the PG study intention. …”
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Experimental Study on RC Deep Beams with Non-Prestressed Tendons as Main Reinforcement by Seyed Mohammad Reza Mortazavi, Milad Shakiba

“…In addition, test results were compared with the predicted theoretical values. The theoretical model was able to predict the experimental load-deflection curves almost accurately. …”
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The Role of Spiritual Intelligence and Emotion Regulation in Students Resiliency by Fareba Karemi, Zahra Nikmanesh

“…The stepwise regression analysis showed that in the first step spiritual intelligence, alone, predicts.11 of resilience (P<.001) and in the second step of spiritual intelligence and emotion regulation together predicts.14 of resilience (P<.001). …”
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Language-specific neural dynamics extend syntax into the time domain. by Cas W Coopmans, Helen de Hoop, Filiz Tezcan, Peter Hagoort, Andrea E Martin

“…Here, we test 3 different models of the temporal spell-out of syntactic structure against brain activity of people listening to Dutch stories: an integratory bottom-up parser, a predictive top-down parser, and a mildly predictive left-corner parser. …”
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