Aims: China has the largest number of adults with diabetes. Although multiple metabolic risk factors (MRFs) are implicated in the development of diabetes, it remains unclear how they progress during the development of diabetes among Chinese. We examined trajectories of multiple MRFs among Chinese and identified the critical period when drastic changes occurred during the development of diabetes.
Methods: This prospective cohort study included participants since 2006-2007 in the Kailuan study. People attended biennial examinations until 2017 with additions of new participants at each examination cycle. The time when a participant first completed the examination was served as the baseline. A total of 122,659 participants without prevalent diabetes at baseline and with complete follow-up data were included. MRFs were collected via biennial physical examinations and laboratory measures. Incident diabetes cases were identified via biennial fasting glucose tests and self-reported physician-diagnosis.
Results: During up to 12 years of follow-up, 14,922 incident diabetes cases were identified. Compared with participants who did not develop diabetes, those who developed diabetes had more adverse levels of most MRFs at baseline and during follow-up. Abrupt increases in multiple MRFs (including fasting glucose, surrogate insulin resistance indicators, lipids, systolic blood pressure, pulse pressure, heart rate, alanine aminotransferase, and C-reactive protein) were observed 3 years before the diagnosis of diabetes.
Conclusions: We identified 3 years before diabetes diagnosis as a critical period when multiple MRFs experienced drastic changes. This would have implications for early monitoring and timely prevention for individuals who experience sudden adverse progression of multiple MRFs.
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http://dx.doi.org/10.1016/j.diabet.2022.101348 | DOI Listing |
Hepatobiliary Pancreat Dis Int
November 2024
Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. Electronic address:
J Hepatocell Carcinoma
June 2024
Interventional Therapy Center for Oncology, Beijing You'an Hospital, Capital Medical University, Beijing, 100069, People's Republic of China.
Purpose: We explored the role of tumor size and number in the prognosis of HCC patients who underwent ablation and created a nomogram based on machine learning to predict the recurrence.
Patients And Methods: A total of 990 HCC patients who underwent transcatheter arterial chemoembolization (TACE) combined ablation at Beijing Youan Hospital from January 2014 to December 2021 were prospectively enrolled, including 478 patients with single small HCC (S-S), 209 patients with single large (≥30mm) HCC (S-L), 182 patients with multiple small HCC (M-S), and 121 patients with multiple large HCC (M-L). S-S patients were randomized in a 7:3 ratio into the training cohort (N=334) and the validation cohort (N=144).
J Imaging
March 2024
Group of Quality Assurance and Industrial Image Processing, Faculty of Mechanical Engineering, Technische Universität Ilmenau, 98693 Ilmenau, Germany.
Since 3D sensors became popular, imaged depth data are easier to obtain in the consumer sector. In applications such as defect localization on industrial objects or mass/volume estimation, precise depth data is important and, thus, benefits from the usage of multiple information sources. However, a combination of RGB images and depth images can not only improve our understanding of objects, capacitating one to gain more information about objects but also enhance data quality.
View Article and Find Full Text PDFMed Image Anal
May 2024
School of Automation, Northwestern Polytechnical University, Xi'an 710072, China. Electronic address:
Leukemia
February 2024
Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Medizinische Fakultät, Ludwig-Maximilians-Universität, Munich, Germany.
Membrane transporters are important determinants of drug bioavailability. Their expression and activity affect the intracellular drug concentration in leukemic cells impacting response to therapy. Pharmacogenomics represents genetic markers that reflect allele arrangement of genes encoding drug transporters associated with treatment response.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!