Publications by authors named "U Berg"
The aim of the present study was to extend the creatinine-based Lund-Malmö GFR equation for use with rescaled cystatin C (r-LMR) and validate it against measured GFR (mGFR) in the EKFC cystatin C cohort of children ( = 2,293) and adults ( = 7,727). Rescaling was obtained by dividing each biomarker by a Q-value, representing the population-specific median biomarker level among healthy individuals. Validation included median bias/precision/accuracy (percent estimates within ±30% of mGFR, P).
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- The study evaluates the effectiveness of machine learning (ML) techniques in predicting glomerular filtration rate (GFR) compared to the traditional EKFC equation, which measures kidney function.
- Using data from 19,629 patients across 13 cohorts, the researchers tested various ML methods, particularly focusing on factors like age, sex, and serum creatinine levels.
- Results indicated that the random forest (RF) method performed similarly to EKFC, with slight advantages for RF in younger patients, suggesting ML could enhance future GFR prediction methods.
Background: Creatinine-based equations are the most used to estimate glomerular filtration rate (eGFR). The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), the re-expressed Lund-Malmö Revised (r-LMR) and the European Kidney Function Consortium (EKFC) equations are the most validated. The EKFC and r-LMR equations have been suggested to have better performances in young adults, but this is debated.
View Article and Find Full Text PDFBackground: Investing in midwives educated according to international standards is crucial for achieving Sustainable Development Goals in maternal and newborn health. Applying a person-centred care approach and using simulation-based learning to improve the learning experience for midwifery students may enhance the quality of childbirth care. This protocol describes a study evaluating the implementation of person-centred approach and simulation-based learning in childbirth as part of a midwifery education programme at the Evangelical University in Africa, DRC.
View Article and Find Full Text PDFObjective: Ensuring quality of maternal and newborn healthcare is challenging in the Democratic Republic of Congo (DRC) as the maternal and newborn mortality and morbidity rate is high. Essential for quality care is a person-centred approach. One model of person-centred care (PCC) has been developed at Gothenburg University.
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