Comparison of iohexol plasma clearance formulas vs. inulin urinary clearance for measuring glomerular filtration rate

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Laurence Dubourg ◽  
Sandrine Lemoine ◽  
Brune Joannard ◽  
Laurence Chardon ◽  
Vandréa de Souza ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Root Mean Square Error ◽  
Glomerular Filtration ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Filtration Rate ◽  
Plasma Clearance ◽  
Mean Square ◽  
Concordance Correlation ◽  
Iohexol Plasma Clearance

AbstractObjectivesThe one-compartment iohexol plasma clearance has been proposed as a reliable alternative to renal inulin clearance. However, this method’s performance depends on the formula used to calculate glomerular filtration rate (GFR). This study reports on performance comparisons between various mathematical formulas proposed for iohexol plasma clearance vs. inulin urinary clearance.MethodsGFR was simultaneously determined by inulin and iohexol clearance in 144 participants (age: 10–84 years; glomerular filtration rate: 15–169 mL/min/1.73 m2). A retrospective cross-sectional study evaluated the performance of four formulas proposed to calculate plasma iohexol clearance (Brøchner–Mortensen, Fleming et al., Jødal–Brøchner–Mortensen, and Ng–Schwartz–Munoz). The performance of each formula was assessed using bias, precision (standard deviation of the bias), accuracy (percentage iohexol within 5, 10, and 15%), root mean square error, and concordance correlation coefficient vs. renal inulin clearance as reference.ResultsRegarding accuracy, there was no difference in root mean square error (RMSE), P5, P10, or P15 between the four formulas. The four concordance correlation coefficients (CCC) between the value from each formula and in-GFR were high and not significantly different. At in-GFR ≥90 mL/min/1.73 m2, Ng–Schwartz–Munoz formula performed slightly better than other formulas regarding median bias (−0.5; 95% CI [−3.0 to 2.0] and accuracy P15 (95.0; 95% CI [88.0–100.0]).ConclusionsThe studied formulas were found equivalent in terms of precision and accuracy, but the Ng–Schwartz–Munoz formula improved the accuracy at higher levels of in-GFR.

Simplified Method to Measure Glomerular Filtration Rate by Iohexol Plasma Clearance in Conscious Rats

Nephron ◽  
2016 ◽  
Vol 133 (1) ◽  
pp. 62-70 ◽  
Author(s):  
Fabiola Carrara ◽  
Nadia Azzollini ◽  
Giovanni Nattino ◽  
Daniela Corna ◽  
Sebastian Villa ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Glomerular Filtration ◽  
Filtration Rate ◽  
Plasma Clearance ◽  
Conscious Rats ◽  
Simplified Method ◽  
Iohexol Plasma Clearance

scholarly journals Population Pharmacokinetic Model of Iohexol in Dogs to Estimate Glomerular Filtration Rate and Optimize Sampling Time

2021 ◽  
Vol 12 ◽  
Author(s):  
Sarah Baklouti ◽  
Didier Concordet ◽  
Vitaliano Borromeo ◽  
Paola Pocar ◽  
Paola Scarpa ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Kidney Disease ◽  
Glomerular Filtration ◽  
Filtration Rate ◽  
Plasma Clearance ◽  
Sampling Time ◽  
Population Pharmacokinetic ◽  
Clinical Conditions ◽  
Sampling Times ◽  
Iohexol Plasma Clearance

Monitoring iohexol plasma clearance is considered a useful, reliable, and sensitive tool to establish glomerular filtration rate (GFR) and early stages of kidney disease in both humans and veterinary medicine. The assessment of GFR based on iohexol plasma clearance needs repeated blood sampling over hours, which is not easily attainable in a clinical setting. The study aimed to build a population pharmacokinetic (Pop PK) model to estimate iohexol plasma clearance in a population of dogs and based on this model, to indicate the best sampling times that enable a precise clearance estimation using a low number of samples. A Pop PK model was developed based on 5 iohexol plasma samples taken from 5 to 180 minutes (min) after an intravenous iohexol nominal dose of 64.7 mg/kg from 49 client-owned dogs of different breeds, sexes, ages, body weights, and clinical conditions (healthy or presenting chronic kidney disease CKD). The design of the best sampling times could contain either 1 or 2 or 3 sampling times. These were discretized with a step of 30 min between 30 and 180 min. A two-compartment Pop PK model best fitted the data; creatinine and kidney status were the covariates included in the model to explain a part of clearance variability. When 1 sample was available, 90 or 120 min were the best sampling times to assess clearance for healthy dogs with a low creatinine value. Whereas for dogs with CKD and medium creatinine value, the best sampling time was 150 or 180 min, for CKD dogs with a high creatinine value, it was 180 min. If 2 or 3 samples were available, several sampling times were possible. The method to define the best sampling times could be used with other Pop PK models as long as it is representative of the patient population and once the model is built, the use of individualized sampling times for each patient allows to precisely estimate the GFR.

Iohexol Plasma Clearance in Determining Glomerular Filtration Rate in Diabetic Patients

Renal Failure ◽  
1998 ◽  
Vol 20 (2) ◽  
pp. 277-284 ◽  
Author(s):  
Laura Pucci ◽  
Simona Bandinelli ◽  
Giuseppe Penno ◽  
Monica Nannipieri ◽  
Loredana Rizzo ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Glomerular Filtration ◽  
Filtration Rate ◽  
Plasma Clearance ◽  
Diabetic Patients ◽  
Iohexol Plasma Clearance

Measurement of glomerular filtration rate: Internal and external validations of the iohexol plasma clearance technique by HPLC

2014 ◽  
Vol 430 ◽  
pp. 84-85 ◽  
Author(s):  
Sergio Luis-Lima ◽  
Flavio Gaspari ◽  
Esteban Porrini ◽  
Martín García-González ◽  
Norberto Batista ◽  
...  
Keyword(s):  
Glomerular Filtration Rate ◽  
Glomerular Filtration ◽  
Filtration Rate ◽  
Plasma Clearance ◽  
Iohexol Plasma Clearance ◽  
Clearance Technique

scholarly journals Estimation of Apple Flowering Frost Loss for Fruit Yield Based on Gridded Meteorological and Remote Sensing Data in Luochuan, Shaanxi Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 1630
Author(s):  
Yaohui Zhu ◽  
Guijun Yang ◽  
Hao Yang ◽  
Fa Zhao ◽  
Shaoyu Han ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Minimum Temperature ◽  
Price Regulation ◽  
Flowering Period ◽  
Mean Square ◽  
Prevention Measures ◽  
Agricultural Insurance

With the increase in the frequency of extreme weather events in recent years, apple growing areas in the Loess Plateau frequently encounter frost during flowering. Accurately assessing the frost loss in orchards during the flowering period is of great significance for optimizing disaster prevention measures, market apple price regulation, agricultural insurance, and government subsidy programs. The previous research on orchard frost disasters is mainly focused on early risk warning. Therefore, to effectively quantify orchard frost loss, this paper proposes a frost loss assessment model constructed using meteorological and remote sensing information and applies this model to the regional-scale assessment of orchard fruit loss after frost. As an example, this article examines a frost event that occurred during the apple flowering period in Luochuan County, Northwestern China, on 17 April 2020. A multivariable linear regression (MLR) model was constructed based on the orchard planting years, the number of flowering days, and the chill accumulation before frost, as well as the minimum temperature and daily temperature difference on the day of frost. Then, the model simulation accuracy was verified using the leave-one-out cross-validation (LOOCV) method, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized root mean square error (NRMSE) were 0.69, 18.76%, and 18.76%, respectively. Additionally, the extended Fourier amplitude sensitivity test (EFAST) method was used for the sensitivity analysis of the model parameters. The results show that the simulated apple orchard fruit number reduction ratio is highly sensitive to the minimum temperature on the day of frost, and the chill accumulation and planting years before the frost, with sensitivity values of ≥0.74, ≥0.25, and ≥0.15, respectively. This research can not only assist governments in optimizing traditional orchard frost prevention measures and market price regulation but can also provide a reference for agricultural insurance companies to formulate plans for compensation after frost.

scholarly journals Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1020
Author(s):  
Yanqi Dong ◽  
Guangpeng Fan ◽  
Zhiwu Zhou ◽  
Jincheng Liu ◽  
Yongguo Wang ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Low Cost ◽  
Reference Value ◽  
Tree Height ◽  
Point Clouds ◽  
Tree Structure ◽  
Mean Square ◽  
Tree Model

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R2) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m3, rBias was 18.73%, RMSE was 0.12369 m3, rRMSE was 32.78%. To better evaluate the accuracy of QSM’s reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m3, and the rBias was −13.44%, RMSE was 0.13267 m3, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds.

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