Results 241 to 250 of about 343,907 (366)

Beyond Traditional Screening: The Future of Heart Failure Detection With Biomarkers and AI

iNew Medicine, EarlyView.
Advancing HF Screening: Integrating Technology and Risk Factors Across Eras. This diagram provides a comprehensive review of the historical developments and projected trends of heart failure (HF) screening methodologies, with the prevalent risk factors for HF depicted at the base.
Xiaofeng Fang, Yinbo Xu, Yiting Zhao, Liuyi Li, Zhengyi Cheng, Zhongqi Zhang, Yuhang Luo, Qiaoling Liu, Chen Gong, Shichun Shen   +9 more
wiley   +1 more source

Innovative Insights into Interleukin-Mediated Macrophage Polarization: Metabolic Reprogramming and Inflammatory Pathway Crosstalk in Chronic Kidney Disease and Therapeutic Implications-A Narrative Review. [PDF]

Int J Gen Med
Jiang Z, Zhang X, Jin L, Han M, Zhang Y, Jiang Y, Zhang J, Jin L.   +7 more
europepmc   +1 more source

Response to the Nephrological perspectives on the underutilization of SGLT2i in heart failure and chronic kidney disease

ESC Heart Failure, Volume 12, Issue 2, Page 1492-1493, April 2025.
Umut Kocabas
wiley   +1 more source

Glycemic Regulation and Renal Function by Heavy Metal Exposure: A Cross‐Sectional Analysis on Cement Plant Workers

Journal of Applied Toxicology, EarlyView.
ABSTRACT Heavy metal exposure is known to have various effects on renal function and blood glucose regulation. The main objective of this study was to evaluate the effects of cement dust and some metal (cadmium, manganese, nickel, and zinc) exposure on blood glucose and renal function parameters in male cement plant workers.
Duygu Seyhan Erdoğan, Fatma Bozdag, Fatıma Betül Topcu, Osman Burak Demirbas, Sultan Pinar Cetintepe, Mustafa Necmi Ilhan   +5 more
wiley   +1 more source

The impact of multiple long-term conditions on mortality, progression to kidney failure and health-related quality of life among people with chronic kidney disease: a multicentre cohort study (NURTuRE-CKD). [PDF]

Ann Med
Boateng I, Phillips T, Harris S, Aiyegbusi OL, Cockwell P, Kalra PA, McDonnell T, Lucas B, Roderick PJ, Wheeler DC, Taal MW, Fraser SDS.   +11 more
europepmc   +1 more source

Nephrological perspectives on the underutilization of SGLT2is in heart failure and chronic kidney disease

ESC Heart Failure, Volume 12, Issue 2, Page 1490-1491, April 2025.
Özant Helvacı, Ömer Faruk Akçay, Emre Yaşar, Ülver Derici, Galip Güz   +4 more
wiley   +1 more source

Prediction of Chronic Kidney Disease Based on Simulated Serum Analysis by Vibrational Spectroscopy. [PDF]

Biosensors (Basel)
Serrano D, Zoio P, Fonseca LP, Calado CRC.   +3 more
europepmc   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Survival of Hematologic Malignancy In Patients With Early-Stage Chronic Kidney Disease (SHIP-CKD). [PDF]

Cancer Med
Tungjitviboonkun S, Schulte B, Shi K, Gardev E, Bracci PM.   +4 more
europepmc   +1 more source

Pre‐Imaging Clinical Factors Associated With Cardiac MR Image Quality Using Large Language Model‐Enabled Data Extraction

Journal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Background Poor cardiac MR image quality can prompt repeat examinations and hinder clinical decision‐making. Purpose To evaluate whether pre‐imaging clinical information, extracted using a large language model (LLM), is independently associated with cardiac MR image quality. Study Type Retrospective.
Hong Yu, Masha Bondarenko, Ali Nowroozi, Yoo Jin Lee, Adrian Serapio, Punita Kaveti, Jae Ho Sohn   +6 more
wiley   +1 more source