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The objective of this study is to identify independent risks and protective factors and to construct a mortality prediction model for gastrectomy in the Chinese population. This is a population-based prospective cohort at an institutional level. Seventy-two participating hospitals reported their annual gastrectomy data between 2014 and 2016, while 44 variables covering the institution and surgical information were included in the analysis. We used R software to encode and complete data pre-processing. The first difference model was applied to build the risk model. Data from 2014 and 2015 were assigned to risk model development, while data from 2016 was used for validation. In the included centers with 94,277 gastric cancer cases, the in-hospital mortality rate was 0.32%. The regression model revealed that provinces with low-middle GDP, hospitals with annual gastrectomy volume between 100 and 500, greater volume of urgent surgeries performed, larger proportion of males, and a higher proportion of liver metastasis were independent risk factors for mortality following gastric surgeries, while higher laparoscopic resection volume, greater volume of distal gastrectomy with B2 reconstruction, and larger proportion of palliative surgery were independent protective factors ( < 0.05, respectively). In the prediction test, the mean square error of the training set was 0.948, while that of the test set was 0.728, demonstrating the effectiveness of this model. We constructed the first mortality risk prediction model for gastric cancer surgery in the Chinese population. The identified risk factors will help with the therapy selection, while further informing Chinese medical policy decision-makers.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779801 | PMC |
http://dx.doi.org/10.3389/fonc.2019.00846 | DOI Listing |
Drug Alcohol Rev
September 2025
The Prescription Drug Misuse Education and Research (PREMIER) Center, University of Houston, Houston, Texas, USA.
Introduction: Buprenorphine is effective for opioid use disorder (OUD), yet adherence remains suboptimal. This study aimed to identify adherence trajectories, explore their predictors, and assess their association with opioid overdose risk and healthcare costs.
Methods: A retrospective cohort study was conducted using the Merative MarketScan Commercial Database, which includes a nationally representative sample of individuals with private, employer-sponsored health insurance in the United States.
Hypertension
September 2025
Department of Hypertension, Center for Epidemiological Studies and Clinical Trials, the Shanghai Institute of Hypertension, Shanghai Key Laboratory of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, China (J.W.).
Background: The association between season of screening blood pressure (BP) measurement and adverse outcomes has not been examined among populations without prior physician-diagnosed hypertension. We aimed to investigate the association between the season of screening clinic BP measurement and the risk of all-cause mortality.
Methods: This was a prospective cohort study, and data were analyzed from an ongoing community hypertension screening program in Shanghai between 2018 and 2024.
Stroke
September 2025
Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York. (F.C.P., M.R., M.S., A.K., S.G., S.A., S.P., J.C., D.J.R.).
Background: Major ABO-incompatible platelet transfusions are associated with poor intracerebral hemorrhage (ICH) outcomes, yet drivers for this relationship remain unclear. Brain magnetic resonance imaging (MRI) ischemic lesions after ICH are neuroimaging biomarkers of secondary brain injury and are associated with poor outcomes. Given that ABO-incompatible platelet transfusions can induce immune complex formation, thrombo-inflammation, and endothelial barrier disruption, factors that could exacerbate cerebral ischemia, we explored whether major ABO-incompatible platelet transfusions are risk factors for ischemic lesions on brain MRI after ICH.
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September 2025
Division of Cardiology, Emory University School of Medicine, Atlanta, GA. (A.K.Y., A.C.R., L.S.S., A.A.Q., Y.V.S.).
Background: Cardio-kidney-metabolic (CKM) disease represents a significant public health challenge. While proteomics-based risk scores (ProtRS) enhance cardiovascular risk prediction, their utility in improving risk prediction for a composite CKM outcome beyond traditional risk factors remains unknown.
Methods: We analyzed 23 815 UK Biobank participants without baseline CKM disease, defined by -Tenth Revision codes as cardiovascular disease (coronary artery disease, heart failure, stroke, peripheral arterial disease, atrial fibrillation/flutter), kidney disease (chronic kidney disease or end-stage renal disease), or metabolic disease (type 2 diabetes or obesity).
Circ Genom Precis Med
September 2025
Clinical Pharmacology and Precision Medicine, William Harvey Research Institute, London, United Kingdom (W.J.Y., M.M.S., J.R., S.v.D., H.R.W., A.T., P.B.M.).
Background: There is a higher prevalence of heart rate corrected QT (QTc) prolongation in patients with diabetes and metabolic syndrome. QT interval genome-wide association studies have identified candidate genes for cardiac energy metabolism, and experimental studies suggest that polyunsaturated fatty acids have direct effects on ion channel function. Despite this, there has been limited study of metabolite concentration relationships with QT intervals.
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