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Quantification of excretory renal function and urinary protein excretion by determination of body cell mass using bioimpedance analysis

Overview of attention for article published in BMC Nephrology, October 2015
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Quantification of excretory renal function and urinary protein excretion by determination of body cell mass using bioimpedance analysis
Published in
BMC Nephrology, October 2015
DOI 10.1186/s12882-015-0171-9
Pubmed ID

Stefan Flury, Johannes Trachsler, Albin Schwarz, Patrice M. Ambühl


Creatinine clearance (CrCl) based on 24 h urine collection is an established method to determine glomerular filtration rate (GFR). However, its measurement is cumbersome and the results are frequently inaccurate. The aim of this study was to develop an alternative method to predict CrCl and urinary protein excretion based on plasma creatinine and the quantification of muscle mass through bioimpedance analysis (BIA). In 91 individuals with normal and impaired renal function CrCl was measured from 24 h urine excretion and plasma creatinine concentration. A model to predict 24 h-creatininuria was developed from various measurements assessing muscle mass such as body cell mass (BCM) and fat free mass (FFM) obtained by BIA, skinfold caliper and other techniques (training group, N = 60). Multivariate regression analysis was performed to predict 24 h-creatininuria and to calculate CrCl. A validation group (N = 31) served to compare predicted and measured CrCl. Overall (accuracy, bias, precision, correlation) the new BIA based prediction model performed substantially better compared with measured CrCl (P15 = 87 %, bias = 0, IQR of differences = 7.9 mL/min/1.73 m(2), R = 0.972) versus established estimation formulas such as the 4vMDRD (P15 = 26 %, bias = -8.3 mL/min/1.73 m(2), IQR = 13.7 mL/min/1.73 m(2), R = 0.935), CKD-EPI (P15 = 29 %, bias = -7.0 mL/min/1.73 m(2), IQR = 12.1 mL/min/1.73 m(2), R = 0.932, Cockcroft-Gault equations (P15 = 55 %, bias = -4.4 mL/min/1.73 m(2), IQR = 9.0 mL/min/1.73 m(2), R = 0.920). The superiority of the new method over established prediction formulas was most obvious in a subgroup of individuals with BMI > 30 kg/m(2) and in a subgroup with CrCl > 60 mL/min/1.73 m(2). Moreover, 24 h urinary protein excretion could be estimated accurately by normalization with 24 h-creatininuria derived from BIA based BCM. Prediction of CrCl based on estimated urinary creatinine excretion determined from measurement of BCM by BIA technique is both accurate and convenient to quantify renal function in normal and diseased states. This new method may become particularly helpful for the evaluation of patients with borderline renal insufficiency and/or with abnormal body composition.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 17%
Other 3 13%
Student > Doctoral Student 3 13%
Student > Postgraduate 3 13%
Student > Bachelor 3 13%
Other 4 17%
Unknown 3 13%
Readers by discipline Count As %
Medicine and Dentistry 12 52%
Agricultural and Biological Sciences 2 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 9%
Psychology 1 4%
Sports and Recreations 1 4%
Other 1 4%
Unknown 4 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 September 2016.
All research outputs
of 9,365,896 outputs
Outputs from BMC Nephrology
of 1,071 outputs
Outputs of similar age
of 98,845 outputs
Outputs of similar age from BMC Nephrology
of 6 outputs
Altmetric has tracked 9,365,896 research outputs across all sources so far. This one has received more attention than most of these and is in the 59th percentile.
So far Altmetric has tracked 1,071 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 98,845 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them