Updating AFP Level in Chronic Hepatitis B to Evaluate the Risk of Hepatocellular Carcinoma Occurrence by Juferdy Kurniawan, Jane Andrea Christiano Djianzonie, Edi Mulyana, Dicky Levenus Tahapary, Andri Sanityoso Sulaiman, Ika Prasetya Wijaya, Sally Aman Nasution, Siti Setiati

“…Results: For HCC surveillance caused by hepatitis B virus, ROC curve analysis resulted in an area under the curve (AUC) of 0.792 (95% CI, 0.719-0.866), and the cut-off value with the highest Youden index was 8.7 ng/ml, with 58% sensitivity, 94% specificity, positive predictive value (PPV)  56.14%, negative predictive value (NPV) 94.43%, positive likelihood ratio (LR+) 10.08, and negative likelihood ratio (LR-) 0.46. …”
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Using a transformer language model to curate a pulmonary embolism dataset from the Medical Information Mart for Intensive Care IV: MIMIC-IV-Ext-PE by Barbara D. Lam, Shengling Ma, Iuliia Kovalenko, Peiqi Wang, Omid Jafari, Ang Li, Steven Horng

“…Diagnosis codes had a sensitivity of 95.4% and a positive predictive value of 83.8% in the subset of 11,990 reports with an associated discharge diagnosis code. …”
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Alterations in nailfold videocapillaroscopy among patients with connective tissue diseases combined with pulmonary arterial hypertension: A cross-sectional study by Zhicheng Tang, Fan Yang, Haolin Wu, Ying Zhao, Jingyi Shen, Huiming Hong, Fanzhang Yin, Xiaolei Ma, Linyu Geng, Xue Xu, Yu Wei, Huayong Zhang

“…This method demonstrates potential diagnostic and predictive value for detecting microcirculation alterations in these patients.…”
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An alternative colorimetric RT-LAMP assay for the rapid detection of SARS-CoV-2: development and validation in Thailand by Wiphat Klayut, Thanee Wongchai, Nattagarn Chuenchom, Payu Bhakdeenuan, Supranee Bunchoo, Sopa Srisungngam, Sirilada Suphankong, Benjawan Phetsuksiri, Ballang Uppapong, Janisara Rudeeaneksin

“…The assay demonstrated diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 90.48% (95% CI: 86.36–93.68%), 87.00% (95% CI: 81.53–91.33%), 100% (95% CI: 95.07–100%), 100% (95% CI: not available), and 73.74% (95% CI: 66.22–80.07%), respectively, compared to the rtRT-PCR. …”
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Evaluation of ChatGPT-4 for the detection of surgical site infections from electronic health records after colorectal surgery: A pilot diagnostic accuracy study by Josep M. Badia, Daniel Casanova-Portoles, Estela Membrilla, Carles Rubiés, Miquel Pujol, Joan Sancho

“…Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. …”
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Lung cancer screening in Finland: a prospective randomized trial by Viktor Wichmann, Sanna Iivanainen, Lauri Mattila, Veli-Pekka Kokkonen, Airi Jartti, Antti Kurtti, Riitta Kaarteenaho, Heidi Andersen, Antti Jekunen, Tuula Vasankari, Jussi Koivunen

“…The screening examination uptake was high with both screening rounds, while the positive predictive value for lung cancer detection remained at good level. …”
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Association of lung ultrasound score with 72-hour intubation needs in pneumonia patients presenting to the emergency department by Tanyaporn Nakornchai, Apichaya Monsomboon, Panrada Pathomkajonkul, Ronnapop Jaluspikultip, Rathachai Kaewlai, Nattakarn Praphruetkit, Tipa Chakorn, Sattha Riyapan, Usapan Surabenjawong, Wansiri Chaisirin, Netiporn Thirawattanasoot

“…The optimal cutoff value of 16 yielded a sensitivity of 88.9%, specificity of 69.4%, positive predictive value of 42.1%, and negative predictive value of 96.2%. …”
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Identifying malignant pleural effusion from tubercular pleural effusion by study of cancer ratio and cancer ratio plus by Subhankar Saren, Animesh Mandal, Amit Kumar Das, Ranjit Kumar Haldar, Sudipta Pandit

“…Both CR and CR plus had sensitivity of 95.12% (95% CI 80.03–98.64), specificity of 80% (95% CI 60.80–91.16), positive predictive value of 90.69, and negative predictive value of 88.88 in diagnosing MPE. …”
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Updating AFP Level in Chronic Hepatitis B to Evaluate the Risk of Hepatocellular Carcinoma Occurrence by Juferdy Kurniawan, Jane Andrea Christiano Djianzonie, Edi Mulyana, Dicky Levenus Tahapary, Andri Sanityoso Sulaiman, Ika Prasetya Wijaya, Sally Aman Nasution, Siti Setiati

“…Results: For HCC surveillance caused by hepatitis B virus, ROC curve analysis resulted in an area under the curve (AUC) of 0.792 (95% CI, 0.719-0.866), and the cut-off value with the highest Youden index was 8.7 ng/ml, with 58% sensitivity, 94% specificity, positive predictive value (PPV)  56.14%, negative predictive value (NPV) 94.43%, positive likelihood ratio (LR+) 10.08, and negative likelihood ratio (LR-) 0.46. …”
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Diagnostic Accuracy of Contrast-Enhanced Ultrasonography for the Assessment of Small Renal Mass: A Prospective Study by Jae-Wook Chung, Seo Young Park, Seunghee Woo, Yun Ah Kim, Jun-Koo Kang, Yun-Sok Ha, Jun Nyung Lee, Bum Soo Kim, Tae-Hwan Kim, Ghil Suk Yoon, Tae Gyun Kwon, See Hyung Kim

“…The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of KDCT were 89.3%, 10.0%, 73.5%, and 25.0%, respectively. …”
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Evaluation of CE-MATRIX-Enhanced FLAIR imaging in the detection of leptomeningeal metastasis by Junhui Yuan, Shaobo Fang, Fan Meng, Yue Wu, Dongqiu Shan, Chunmiao Xu, Renzhi Zhang, Xuejun Chen

“…Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) values were calculated and compared using Z-tests. …”
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The Prognostic Role of Serum Procalcitonin for Adult Patients with Acute Diarrhea in the Emergency Department by Antonella Gallo, Marcello Covino, Eleonora Ianua’, Andrea Piccioni, Davide Della Polla, Benedetta Simeoni, Francesco Franceschi, Francesco Landi, Massimo Montalto

“…</b> Of a total of 1910 patients, early PCT values (cut-off of 0.5 ng/mL) did not show a significant predictive value for infective diarrhea (OR 0.554 [0.395–0.778]), nor for bacterial diarrhea (OR 0.596 [0.405–0.875]). …”
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Impact of Rosacea on Keratinocyte Skin Cancers: A Prospective Case-Control Study of Basal and Squamous Cell Carcinoma Risk by Asli Aksu, Aysenur Demir, Hatice Gunay, Pinar Ozdemir Cetinkaya, Birgul Ozkesici Kurt, Hazel Ezgi Kaya, Ilknur Altunay, Deniz Altınel

“…The sensitivity, specificity, negative predictive value and positive predictive value for rosacea were 45.5%, 86%, 61.2% and 76.5%, respectively (AUC 0.658, 95% CI 0.604-0.711, P=0.000), while for ETR it was 44%, 86.5%, 60.7% and 76.5%, respectively (AUC 0.653, 95% CI 0.599-0.706, P=0.000). …”
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Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma by Yu Mori, Hainan Ren, Naoko Mori, Munenori Watanuki, Shin Hitachi, Mika Watanabe, Shunji Mugikura, Kei Takase

“…The model from intraosseous lesions on the T1-weighted images showed the highest diagnostic performance in discriminating 3-year non-survivors from survivors (AUCs of 0.99 and 0.88 in the training and validation sets) with a sensitivity, specificity, positive predictive value, and negative predictive value of 85.7%, 92.6%, 75.0%, and 96.2%, respectively. …”
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Synoptic reporting accuracy for computed tomography pulmonary arteriography among patients suspected of pulmonary embolism by Isabela A. Woller, Scott C. Woller, Scott M. Stevens, James F. Lloyd, Karen E. Conner, Benjamin H. Gordon, Greg L. Snow, Peter Jones, Joseph R. Bledsoe

“…Results Synoptic reporting and manual review agreed in 99.2% of patients undergoing CTPA for suspected PE, agreed on the presence of PE in 196 of 199 (98.5%) cases, the absence of PE in 200 of 200 (100%) cases with a sensitivity of 87.6% (76.1–96.1) a specificity of 99.9% (99.7%–100%), a positive predictive value of 99.5% (98.1–100), and a negative predictive value of 98% (95.7%–99.5%). …”
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Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning [version 1; peer review: awaiting peer review] by David Garrett Brown, Darwin J. Operario, Lan Wang, Shanrui Wu, Daniel T. Leung, Eric R. Houpt, James A. Platts-Mills, Jie Liu, Ben J. Brintz

“…We used 5-fold cross-validation to tune the models and assessed performance using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and mean absolute error (MAE). …”
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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases by Huai-wen Zhang, Yi-ren Wang, Bo Hu, Bo Song, Zhong-jian Wen, Lei Su, Xiao-man Chen, Xi Wang, Ping Zhou, Xiao-ming Zhong, Hao-wen Pang, You-hua Wang

“…Multiple evaluation metrics, including the specificity, sensitivity, negative predictive value, positive predictive value, accuracy, Matthews correlation coefficient, and the Youden index, were used to assess the model’s performance. …”
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Hereditary angioedema diagnosis evaluation score (HADES): A new clinical scoring system for predicting hereditary angioedema with C1 inhibitor deficiency by Ricardo Zwiener, MD, Rafael Zamora, MD, Carlos María Galmarini, MD, PhD, Laura Brion, PhD, Laura Arias, MD, Andrea Pino, MD, Paula Rozenfeld, PhD

“…The predictive score demonstrated favorable performance in identifying HAE cases within the index population (range, 0-18.5), with low scores (1.5-6.5) associated with high sensitivity (100%) and negative predictive value (100%), and high scores (≥15) associated with high specificity (99.4%) and positive predictive value (75.0%). …”
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Using machine learning models to predict post-revascularization thrombosis in PAD by Samir Ghandour, Adriana A. Rodriguez Alvarez, Isabella F. Cieri, Shiv Patel, Mounika Boya, Rahul Chaudhary, Rahul Chaudhary, Rahul Chaudhary, Anna Poucey, Anahita Dua

“…Model performance was assessed by area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value.ResultsOf the 308 patients analyzed, 66% were male, 84% were White, and 18.3% experienced an ATE during the one-year post-revascularization follow-up period. …”
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Diagnostic value of serum origin recognition complex protein 1 in the progression of HBVrelated liver fibrosis by LIANG Hongqian, HUANG Long, REN Aoli, SU Minghua, HU Bobin, LI Qingmei, SU Tumei, YIN Qianbing, LI Aining, JIANG Jianning

“…The area under the ROC curve of serum ORC1 in the diagnosis of liver cirrhosis was 0.644 (P < 0.05), the cutoff value was 1, 000.46 ng/L and the sensitivity, specificity, positive predictive value, negative predictive value, and consistency rate were 56.0%, 76.3%, 35.0%, 88.4%, and 72.5%, respectively. …”
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