Creatinine clearance, different methods of determination.

Thomis, J.; Soep, H.; Hallynck, Th.; Boelaert, Johan R.; Daneels, R; Dettli, L

doi:10.1111/j.1365-2125.1982.tb01378.x

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…The numbers of abnormality in biomarkers could be derived after data labeling. Certain secondary biomarkers, such as the estimated creatinine clearance that is used to evaluate kidney health[ 39 , 40 ], could also be derived after data cleaning.…”

Section: Methodsmentioning

confidence: 99%

Trend analysis for national surveys: Application to all variables from the Canadian Health Measures Survey cycle 1 to 4

Chao

et al. 2018

PLoS ONE

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BackgroundTrend analysis summarizes patterns over time in the data to show the direction of change and can be used to investigate uncertainties in different time points and associations with other factors. However, this approach is not widely applied to national surveys and only selected outcomes are investigated. This study demonstrates a research framework to conduct trend analysis for all variables in a national survey, the Canadian Health Measures Survey (CHMS).Data and methodsThe CHMS cycle 1 to 4 was implemented between 2007 and 2015. The characteristics of all variables were screened and associated to the weight variables. Missing values were identified and cleaned according to the User Guide. The characteristics of all variables were extracted and used to guide data cleaning. Trend analysis examined the statistical significance of candidate predictors: the cycles, age, sex, education, household income and body mass index (BMI). R (v3.2) and RStudio (v0.98.113) were used to develop the framework.ResultsThere were 26557 variables in 79 data files from four cycles. There were 1055 variables significantly associated with the CHMS cycles and 2154 associated with the BMI after controlling for other predictors. The trend of blood pressure was similar to those published.ConclusionTrend analysis for all variables in the CHMS is feasible and is a systematic approach to understand the data. Because of trend analysis, we have detected data errors and identified several environmental biomarkers with extreme rates of change across cycles. The impact of these biomarkers has not been well studied by Statistics Canada or others. This framework can be extended to other surveys, especially the Canadian Community Health Survey.

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Section: Methodsmentioning

confidence: 99%

Trend analysis for national surveys: Application to all variables from the Canadian Health Measures Survey cycle 1 to 4

Chao

et al. 2018

PLoS ONE

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“…16 It closely correlates to the total body water that is measured by DEXA. 10 The 50-kg LBM is the mean LBM of a 25-year-old man 15 and is used in the GFR normalization, 15,17 the Cockcroft-Gault formula adjusted for LBM, 18 and others. 17 After correcting creatinine clearance rate with LBM, the chemotherapy regimen was better calculated.…”

mentioning

confidence: 99%

“…10 The 50-kg LBM is the mean LBM of a 25-year-old man 15 and is used in the GFR normalization, 15,17 the Cockcroft-Gault formula adjusted for LBM, 18 and others. 17 After correcting creatinine clearance rate with LBM, the chemotherapy regimen was better calculated. 19 On the basis of the data from 95 healthy adults and 56 children, Peters et al 9 supposed that LBM was preferable to BSA and extracellular fluid volume in correcting GFR.…”

mentioning

confidence: 99%