Interleukin-34 as a Robust Predictor of No-Reflow Phenomenon in ST-Elevation Myocardial Infarction: Insights into Inflammatory Mechanisms and Clinical Implications by Mehdi Karasu, Hasan Ata Bolayır, İbrahim Aktaş

“…ROC analysis showed IL-34’s significant predictive value (area under the curve: 0.972, p<0.001). …”
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Radio Pathological Correlation of Thyroid Nodules Using Tirads Based Ultrasound Classification and Bethesda Classification for FNAC: a Prospective Study by Richa TIWARI, Ruchi GUPTA, Amit Kumar VERMA, Sanjeev KUMAR, Yogita KATIYAR

“…Findings were compared to assess the sensitivity, specificity, PPV (positive predictive value) and NPV (negative predictive value) of ultrasound in differentiating benign from malignant nodules. …”
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Combination of oximetry and sleep questionnaires as screening tools for CPAP initiation in patients with obstructive sleep apnea by A. Pataka, G. Kalamaras, E. Vlachogianni, P. Argyropoulou

“…Questionnaires alone had limited value as screening tools for CPAP initiation; the combination of oximetry with questionnaires did not improve their predictive value.…”
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Relationship of serum phosphorus level with acute cerebrovascular disease by Sami Ataman, Abdullah Sadık Girişgin, Mustafa Kürşat Ayranci, Kadir Küçükceran

“…The optimum cut-off value for phosphorus was calculated as 3.47 (mg/dl) and the sensitivity of this cut-off value was found to be 89%, specifically 86.9%, positive predictive value (ppv) as 77.4% and negative predictive value (npv) as 94%. …”
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Risk-factor Model Derivation and Validation for the Detection of Oral Potentially Malignant Disorders among General Population of Towns in Pune District, Maharashtra, India by Khushboo Thakkar, Sahana Hegde Shetiya, Dipti Agarwal, Sudhir L. Jadhav

“…On validation of the risk factor model, the sensitivity, specificity, and the negative predictive value of the model for the detection of OPMD was found to be good. …”
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Comparative evaluation of spatiotemporal methods for effective dengue cluster detection with a case study of national surveillance data in Thailand by Chawarat Rotejanaprasert, Kawin Chinpong, Andrew B. Lawson, Richard J. Maude

“…Evaluation metrics included accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Bayesian models and FlexScan emerged as top performers, demonstrating superior accuracy and sensitivity. …”
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Prognostic potential of inflammatory markers in chronic kidney disease patients combined with acute myocardial infarction by Peizhu Dang, Bohan Li, Yongxin Li

“…NLR may provide superior predictive value compared to other markers.…”
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Mean Platelet Volume-to-Albumin Ratio as a Predictor of Mortality in Patients with Febrile Neutropenia: An Observational Study by Jelena Dimitrijević, Marina Čalamać, Ognjen Đurmez, Marko Stojanović

“…The MPV/ALB ratio was calculated at admission, and its predictive value for mortality was assessed using receiver operating characteristic (ROC) curve analysis. …”
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An Online Tool for Correcting Performance Measures of Electronic Phenotyping Algorithms for Verification Bias by Ajay Bhasin, Sue Bielinski, Abel N. Kho, Nicholas Larson, Laura J. Rasmussen-Torvik

“…., sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) are often employed. …”
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Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer by Adrian Wai Chan, Lakshmanan Sannachi, Daniel Moore-Palhares, Archya Dasgupta, Sonal Gandhi, Rossanna Pezo, Andrea Eisen, Ellen Warner, Frances C. Wright, Nicole Look Hong, Ali Sadeghi-Naini, Mia Skarpathiotakis, Belinda Curpen, Carrie Betel, Michael C. Kolios, Maureen Trudeau, Gregory J. Czarnota

“…The sensitivity, specificity, positive predictive value, negative predictive value, and F1 score for determining chemotherapy response of all patients in the validation cohort were 94%, 67%, 96%, 57%, and 95%, respectively. …”
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Coronary Computed Tomography Angiogram in Patients with Stable Chest Pain by Zhivka Stoykova

“…The sensitivity of the methodology was 93% (CI 89% - 98%), the specificity 57% (CI 89% - 98%), the positive predictive value was 88%, and the negative predictive value was 73%. …”
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Advancing Breast Cancer Diagnosis: A Comprehensive Machine Learning Approach for Predicting Malignant and Benign Cases with Precision and Insight in a Neutrosophic Environment usin... by Nihar Ranjan Panda, R. Rajalakshmi, Surapati Pramanik, Mana Donganont, Prasanta Kumar Raut

“…Four top machine learning algorithms are trained and evaluated with a series of performance measures such as accuracy, positive predictive value (PPV), negative predictive value (NPV), F1-score, etc. …”
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Ferroptosis-related genes as prognostic markers for survival and immunotherapy in triple-negative breast cancer: analysis of public databases and a single institution by Yizhao Xie, Zhonghua Tao, Biyun Wang, Yannan Zhao, Xinyu Chen, Bin Li, Jinyan Wang, Guangliang Chen, Xichun Hu

“…Conclusion: Ferroptosis-related genes had potential prognostic value and predictive value for breast cancer immunotherapy.…”
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Diagnostic value of serum markers and C-reactive protein of joint fluid in purulent arthritis by Chaoyan Xu, Changyi Lin, Damei Ye, Peicheng Wu, Minghui Song, Youtian Liu, Qiong Deng, Xueyan Huang, Zhongxiao Fan, Xuelan You

“…Notably, joint fluid CRP demonstrated the highest predictive value among the indicators. …”
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Improving OSA screening efficiency with subjective questionnaires: integrating STOP-Bang, ESS, and Berlin by Riken Chen, Yuan Zhang, Weilong Ye, Zhaojun Chen, Weifeng Liao, Huizhao Liao, Tingting Sun, Huan Li, Junfen Cheng, Wang Liu, Weimin Yao, Yitian Yang

“…The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic (ROC) curves were calculated for each questionnaire, and the accuracy and predictive value of combining the STOP-Bang, ESS, and Berlin questionnaires for OSA screening were analyzed.ResultsAmong the individual scales, the Berlin questionnaire had the highest area under the curve (AUC), demonstrating the best diagnostic performance and the highest PPV. …”
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Validation of automated paper screening for esophagectomy systematic review using large language models by Rashi Ramchandani, Eddie Guo, Esra Rakab, Jharna Rathod, Jamie Strain, William Klement, Risa Shorr, Erin Williams, Daniel Jones, Sebastien Gilbert

“…For preoperative risk factors, the model showed a recall of 67% for included studies, a positive predictive value of 65%, and a negative predictive value of 85%, with a false positive rate of 15% and a macro-F1 score of 0.66. …”
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Application value of transrectal contrast-enhanced ultrasound combined with magnetic resonance imaging in T staging and treatment decision-making for middle and low rectal cancer by ZHAO Ran, ZHAN Weiwei, LI Cheng, TANG Hailang, BO Yulian, LIU Kun

“…Result The combined examination for T1 rectal cancer showed a sensitivity of 87.5%, specificity of 99%, positive predictive value of 99.9%, and negative predictive value of 96.7%. …”
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Neutrophil extracellular traps as a promising marker of poor prognosis in operated patients with infective endocarditisarditis. by E. O. Kotova, A. Yu. Moiseeva, Zh. D. Kobalava, A. S. Pisyaryuk, D. V. Kassina, A. S. Gur’ev, T. A. Gusarova

“…The threshold value of dynamic NET ≥11,2% predicted in-hospital death with high accuracy (sensitivity 80,0%, specificity 90,0%, positive predictive value 66,7%, negative predictive value 100,0%, area under the curve 0,915, p=0,003) and the development of postoperative sepsis (sensitivity 75,0%, specificity 88,0%, positive predictive value 60,0%, negative predictive value 100,0%, area under the curve 0,884, p=0,01). …”
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Usefulness of the BIG Score in Predicting Massive Transfusion and In-Hospital Death in Adult Trauma Patients by Sejun Park, Il Jae Wang, Seok-Ran Yeom, Sung-Wook Park, Suck Ju Cho, Wook Tae Yang, Wonwoong Tae, Up Huh, Chanhee Song, Yeaeun Kim, Jong-Hwan Park, Youngmo Cho

“…This study aimed to evaluate the predictive value of BIG score for mortality and the need for MT in adult trauma patients. …”
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Impact of narrow band imaging in prediction of histology of advanced colorectal neoplasia by Tomas Grega, Klara Kmochova, Katerina Hejcmanova, Ondrej Ngo, Nadija Brodyuk, Ondrej Majek, Jan Bures, Petr Urbanek, Miroslav Zavoral, Stepan Suchanek

“…Additionally, we evaluated the sensitivity and positive predictive value (PPV) of the JNET and NICE classifications individually for high-grade lesions (including HGD adenomas, intramucosal carcinomas, and T1 carcinomas). …”
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