Predictive value of sub classification of focal segmental glomerular sclerosis in Oxford classification of IgA nephropathy by Fang Yu, Xuejing Zhu, Shuguang Yuan, Xiaojun Chen, Zheng Li, Zhong Qu, Hong Liu, Lin Sun, Fuyou Liu

“…Background The Oxford classification of IgA nephropathy (IgAN) was revised in 2016 which lacked sufficient evidence for prognostic value of subclassification of focal segmental glomerular sclerosis (S lesion), and the proper proportion of S lesion for subclassification remains undetermined.Aim This study aimed to explore the predictive value of the new subclassification of S score on renal outcomes of IgAN patients.Methods 348 patients with IgAN-associated S lesion were enrolled. …”
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Predictive Value of IL-6 and PDGF-AA for 28-Day Mortality Risk in Critical Ill Patients by Wu L, Zhang Y, Gu L, Wang J, Wei B, Liu Y

“…The purpose of this study was to evaluate the prognostic value of interleukin-6 (IL-6) and platelet-derived growth factor AA(PDGF-AA) in predicting 28-day mortality in critically ill patients.Methods: 199 critically ill patients were recruited from the emergency department of the Beijing Chaoyang Hospital, Capital Medical University, between October 2020 and April 2021. …”
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Prognostic and predictive value of tumor infiltration proportion within lymph nodes in N1 colorectal cancer by Rujie Chen, Jun Zhu, Jun Zhu, Dong Xu, Xiaoyan Fan, Yihuan Qiao, Xunliang Jiang, Jun Hao, Yongtao Du, Xihao Chen, Guo Yuan, Jipeng Li, Jipeng Li

“…IntroductionLymph node metastasis is a crucial determinant of prognosis in colorectal cancer (CRC), significantly impacting survival outcomes and treatment decision-making. This study aims to evaluate the prognostic value of tumor infiltration proportion within lymph nodes (TIPLN) in N1 CRC patients and to develop a TIPLN-based nomogram to predict prognosis.MethodsA total of 416 N1 CRC patients who underwent radical resection were enrolled and divided into training and validation cohorts. …”
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Toll-like Receptor Gene Polymorphisms as Predictive Biomarkers for Response to Infliximab in Japanese Patients with Crohn’s Disease by Jingjing Wei, Hiroki Kurumi, Hajime Isomoto, Ryohei Ogihara, Kayoko Matsushima, Haruhisa Machida, Tetsuya Ishida, Tatsuro Hirayama, Naoyuki Yamaguchi, Yukina Yoshida, Kazuhiro Tsukamoto

“…The therapeutic responses were evaluated at 10 weeks, 1 year, and 2 years using three different inheritance models. …”
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Predictive effects of advanced lung cancer inflammation index and serum vitamin D on mortality in patients with asthma by Ting Li, Qi Wang, Yuhan Li, Wenyong Zhang, Manyu Chen, Bihua Deng, Lin Liang, Weixian Lin, Yuying Lin, Ying Meng

“…This study aimed to evaluate their independent and combined predictive value of mortality in asthma patients. …”
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Predictive potential of cardiovascular risk factors and their associations with arterial stiffness in people of European and Korean ethnic groups by T. A. Brodskaya, V. A. Nevzorova, K. I. Shakhgeldyan, B. I. Geltser, D. A. Vrazhnov, Yu. V. Kistenev

“…To compare the effect of cardiovascular risk factors on aortic stiffness in people of European and East Asian ethnic groups.Material and methods. A total of 266 patients aged 18-60 years of European (n=133) and Korean (n=133) ethnic groups were examined. …”
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Assessing cross-national inequalities and predictive trends in gout burden: a global perspective (1990–2021) by Mingyang Li, Qilong Nie, Qilin Xia, Zeping Jiang, Zeping Jiang

“…Decomposition analysis quantified the impact of demographic factors, while advanced analysis assessed the relationship between gout burden and socioeconomic development. Prediction models forecasted future trends, and cross-national inequalities were evaluated to highlight disparities across regions with different development levels.ResultsBetween 1990 and 2021, the global prevalence of gout increased from 22,264,515 (95% UI: 17,793,190–27,965,605) to 56,474,572 (95% UI: 45,161,987–70,288,316), with the age-standardized prevalence rate (ASPR) rising from 536.54 to 653.82 per 100,000 population [(Estimated annual percentage changes) EAPC: 0.87%, 95% CI: 0.80–0.95]. …”
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Predictive Value of TRUS and CEUS Parameters for Lymph Node Metastasis in Rectal Cancer: A Retrospective Study by Su S, Huang X, Li X, Meng J, Huang J

“…Shitao Su,* Xuanzhang Huang,* Xigui Li, Jun Meng, Jianyuan Huang Department of Medical Ultrasound, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jianyuan Huang, Department of Medical Ultrasound, the First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530001, People’s Republic of China, Tel +86 771 5356899, Email huangjianyuan@sr.gxmu.edu.cnPurpose: To assess the predictive value of transrectal ultrasound (TRUS) combined with qualitative and quantitative parameters of contrast-enhanced ultrasound (CEUS) for lymph node metastasis (LNM) in rectal cancer (RC).Patients and Methods: This retrospective study analyzed preoperative clinical data, qualitative and quantitative TRUS and CEUS parameters, and postoperative pathological data from 535 patients with RC confirmed by surgical pathology. …”
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Risk Factors of Positive Endocervical Curettage and Predictive Model Construction Based on Primary Human Papillomavirus Screening by Hangjing Gao MS, Guanxiang Huang MS, Binhua Dong MS, Ye Li MS, Hongning Cai MD, Xianqian Chen MS, Tingting Jiang MS, Kelvin Stefan Osafo MS, Dabin Liu MS, Jiancui Chen MS, Huihua Ge MS, Diling Pan MS, Huifeng Xue MS, Pengming Sun PhD, MD

“…Logistic regression was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs). The prediction model was presented as a nomogram and evaluated for discrimination and calibration. …”
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Predictive model based on blood cell analysis and coagulation function indicators for neuroblastic tumors staging diagnosis by Yanzi Zhang, Yanzi Zhang, Lihong Zhang, Lihong Zhang, Mengmeng Chen, Mengmeng Chen, Qin Dong, Qin Dong, Chong Hu, Chong Hu, Juan Wang, Juan Wang, Jiao Meng, Jiao Meng, Xin Lv, Xin Lv

“…Furthermore, a probability prediction model developed using age, TT, Mon#, and Hb successfully differentiated advanced neuroblastic tumors from ganglioneuroma. …”
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Machine learning-based predictive model for acute pancreatitis-associated lung injury: a retrospective analysis by Zhaohui Du, Qiaoling Ying, Yisen Yang, Huicong Ma, Hongchang Zhao, Jie Yang, Zhenjie Wang, Chuanming Zheng, Shurui Wang, Qiang Tang

“…This study aims to develop a prediction model for the diagnosis of APALI based on machine learning algorithms.MethodsThis study included data from the First Affiliated Hospital of Bengbu Medical College (July 2012 to June 2022), which were randomly categorized into the training and testing set. …”
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Predictive machine-learning model for screening iron deficiency without anaemia: a retrospective cohort study by Girish N Nadkarni, Orly Efros, Eyal Klang, Shelly Soffer, Gili Kenet, Aya Mudrik, Renana Robinson

“…The primary hypothesis was that an ML model could achieve better accuracy in identifying low ferritin levels (<30 ng/mL) in non-anaemic patients compared with traditional methods.Design A retrospective cohort study.Setting Data were derived from secondary and tertiary care facilities within the eight-hospital Mount Sinai Health System, an urban academic health system.Participants The study included 211 486 adult patients (aged ≥18 years) with normal haemoglobin levels (≥130 g/L for men and ≥120 g/L for women) and recorded ferritin measurements.Primary and secondary outcome measures The primary outcome was the prediction of low ferritin levels (<30 ng/mL) using extreme gradient-boosted decision trees, an ML algorithm suited for structured clinical data. …”
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Predictive Value of Plasma D-Dimer for Cerebral Herniation Post-Thrombectomy in Acute Ischemic Stroke Patients by Zhang W, Xing W, Feng J, Wen Y, Zhong X, Ling L, He J

“…Receiver operating characteristic curve (ROC) was used to evaluate the predictive value of D-dimer level for cerebral herniation.Results: Among 278 enrolled patients, 20 cases (7.19%) experienced cerebral herniation. …”
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Nomogram Predictive Model for Vaginal Birth after One Prior Cesarean Section: A Retrospective Study by Fangyuan Zheng, Yangfang Sun, Xuening Liang, Jinying Zhou, Yun Chen

“…Three different VBAC prediction models were evaluated by plotting receiver operating characteristic (ROC) curves, calibration curves, and decision curves. …”
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Enhancing the Prediction of Dam Deformations: A Novel Data-Driven Approach by Jonas Ziemer, Gideon Stein, Carolin Wicker, Jannik Jänichen, Daniel Klöpper, Katja Last, Joachim Denzler, Christiane Schmullius, Maha Shadaydeh, Clémence Dubois

“…Through a comprehensive evaluation of advanced data-driven approaches, we demonstrated considerable improvements in predicting dam deformations and evaluating their drivers. …”
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AI models for the identification of prognostic and predictive biomarkers in lung cancer: a systematic review and meta-analysis by Hind M. AlOsaimi, Aseel M. Alshilash, Layan K. Al-Saif, Jannat M. Bosbait, Roaa S. Albeladi, Dalal R. Almutairi, Alwaleed A. Alhazzaa, Tariq A. Alluqmani, Saud M. Al Qahtani, Sara A. Almohammadi, Razan A. Alamri, Abdullah A. Alkurdi, Waleed K. Aljohani, Raghad H. Alraddadi, Mohammed K. Alshammari

“…IntroductionThis systematic review and meta-analysis aim to evaluate the efficacy of artificial intelligence (AI) models in identifying prognostic and predictive biomarkers in lung cancer. …”
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Prediction Model of Late Fetal Growth Restriction with Machine Learning Algorithms by Seon Ui Lee, Sae Kyung Choi, Yun Sung Jo, Jeong Ha Wie, Jae Eun Shin, Yeon Hee Kim, Kicheol Kil, Hyun Sun Ko

“…Conclusions: A simplified machine learning model for predicting late FGR may be useful for evaluating individual risks in the early third trimester.…”
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Predictive value of the stone-free rate after percutaneous nephrolithotomy based on multiple machine learning models by Zhao Rong Liu, Zhao Rong Liu, Zhan Jiang Yu, Jie Zhou, Jian Biao Huang

“…For the top-performing prediction model, the study further employed the SHapley Additive exPlanations (SHAP) method to enhance model interpretability by elucidating the contribution of individual features to the prediction outcomes and ranking the relative importance of the predictive data. …”
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Predictive value and optimal cut-off level of high-sensitivity troponin T in patients with acute pulmonary embolism by Moojun Kim, Chang-Ok Seo, Yong-Lee Kim, Hangyul Kim, Hye Ree Kim, Yun Ho Cho, Jeong Yoon Jang, Jong-Hwa Ahn, Min Gyu Kang, Kyehwan Kim, Jin-Sin Koh, Seok-Jae Hwang, Jin Yong Hwang, Jeong Rang Park

“…Background/Aims Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). …”
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Symptomatic posttreatment edema after stereotactic radiotherapy (SRS/FSRS) for intracranial meningiomas: patterns and predictive factors by Dorra Aissaoui, Naoual Oulmoudne, Houda Bahig, Giuseppina Laura Masucci, Robert Moumdjian, David Roberge, Cynthia Menard, Laurent Létourneau-Guillon, Carole Lambert, Jean-Paul Bahary

“…Our study aims at reviewing rates of SPTE in a large cohort of a single institution and identifying possible predictive factors. Methods: We retrospectively analyzed data of 293 patients with 304 intracranial meningiomas irradiated at our institution between 2005 and 2018. …”
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