Objective: To compare existing glomerular filtration rate (GFR) prediction equations with the gold standard, inulin clearance, in pregnancy.
Methods: Five equations were assessed for precision, bias, and accuracy in prediction of true GFR, measured by inulin clearance in 12 healthy, pregnant women during the second (T2) and third (T3) trimesters and in postpartum (PP).
Results: Precision was greatest with 24-hour creatinine clearance estimation of GFR (R(2) = 13% (T2), R(2) = 26% (T3)). Other than 100/SCr, all equations underestimated true GFR. 30% accuracy was greatest in 100/SCr (83% (T2), 92% (T3)).
Conclusions: Current GFR prediction formulae do not appear to be sufficient for estimating GFR in the gravid state.
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http://dx.doi.org/10.1080/10641950801986720 | DOI Listing |
Soc Sci Med
December 2024
Department of Kinesiology and Health Education, University of Texas at Austin, United States.
Climate-related disasters pose significant risks to mental health and well-being globally. Individuals from disaster-prone regions, such as Puerto Rico, are at even greater risk. The devastating effects of recurrent hurricanes, compounded with pre-existing structural disparities (e.
View Article and Find Full Text PDFChronic kidney disease (CKD) is a common clinical condition with significant health risks for patients and is widely recognised as a major public health concern. Laboratory medicine plays a crucial role in both diagnosing and managing CKD, as diagnosis and staging rely on estimated glomerular filtration rate (GFR) and evaluating albuminuria (or proteinuria). It was evident that the laboratory assessment of CKD in Malaysia is not standardised.
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December 2024
Faculty of Humanities, North-West University Mafikeng, Mafikeng, South Africa.
Bullying among South African adolescents is a critical public health issue. This study explores the relationship between childhood adversity, peer influence, and personality traits in predicting bullying perpetration. Data from 769 high school learners were analysed using Structural Equation Modelling.
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December 2024
School of Civil Engineering, Liaoning Technical University, Fuxin, 123000, China.
Blasting excavation is widely used in mining, tunneling and construction industries, but it leads to produce ground vibration which can seriously damage the urban communities. The peak particle velocity (PPV) is one of main indicators for determining the extent of ground vibration. Owing to the complexity of blasting process, there is controversy over which parameters will be considered as the inputs for empirical equations and machine learning (ML) algorithms.
View Article and Find Full Text PDFThe study explore machine learning (ML) techniques to predict temperature-dependent photoluminescence (PL) spectra in colloidal CdSe nanoplatelets (NPLs), leveraging polynomial regression models trained on experimental data from 85 to 270 K spanning temperatures to forecast PL spectra backward to 0 K and forward to 300 K. 6th-degree polynomial models with Tweedie regression were optimal for band energy ([Formula: see text]) predictions up to 300 K, while 9th-degree models with LassoLars and Linear Regression regressors were suitable for backward predictions to 0 K. For exciton energy ([Formula: see text]), the Lasso model of degree 5 and the Ridge model of degree 4 performed well up to 300 K, while the Tweedie model of degree 2 and Theil-Sen model of degree 2 showed promise for predictions to 0 K.
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