Comparison of prediction equations to estimate glomerular filtration rate in Chinese patients with chronic kidney disease

Noninvasive assessment of single kidney glomerular filtration rate using multiple diffusion weighted imaging models

PURPOSE

This study aimed to assess single kidney glomerular filtration rate (GFR) using various diffusion weighted imaging (DWI) models.

METHODS

We reviewed adult patients with kidney diseases who underwent magnetic resonance imaging (MRI) examination from February 2021 to December 2023. DWI with 13 b-values was performed using 3.0-T scanners. Diffusion parameters were calculated with multi-slice ROIs positioned in renal parenchyma using four DWI models, including monoexponential model (MEM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), and intravoxel incoherent motion (IVIM). The split GFRs were measured by 99mTc-DTPA scintigraphy using Gates' method. Four different regression algorithms including the linear regression, regression tree, Gaussian regression and support vector machine (SVM) regression were employed to predict the GFR value based on different diffusion parameters. The leave-one-out cross validation was used to evaluate prediction ability of different models, and the performance of each model was quantified using the root mean square error (RMSE) and correlation coefficient.

RESULTS

Fifteen (male/female, 10/5; age, 41.60±10.83 years) patients were included in this study. Among the four DWI models, the IVIM parameters with SVM regression model achieved the best performance with 0.184 RMSE and 0.789 correlation coefficient ( p < 0.001 ). The parameters combining the four DWI models with SVM regression algorithm achieved the best performance in this study, with 0.171 RMSE and 0.815 correlation coefficient ( p < 0.001 ).

CONCLUSION

The DWI characteristics are able to serve as imaging biomarkers for assessing the function of single kidney. The integration of DWI into clinical practice could contribute to the advancement of non-invasive diagnostic methodologies.

Applicability of 14 Formulas for Estimating Glomerular Filtration Rate in the Evaluation of Renal Function before and after Nephron-Sparing Surgery in Patients with Renal Tumors

To compare the applicability of 14 equations of estimating glomerular filtration rate (eGFR) before and after nephron-sparing surgery (NSS) for renal function assessment of patients with renal tumors. Preoperative and postoperative GFR is measured by emission computed tomography (ECT) with 99mTc-DTPA as an imaging agent as reference GFR (rGFR) to compare with all formulas. Spearman correlation analysis and Bland-Altman agreement analysis were used to evaluate the correlation between rGFR and eGFR1 to 14 before and after surgery. A total of 50 cases including 22 males and 28 females were included. The results of preoperative eGFR1-14 correlated with rGFR (P < 0.05). The calculation results of all estimation formulas have a significant correlation with preoperative GFR. Preoperative MDRD-I, CKD-EPI SCysC, and FAS Scr-SCysC have good consistency. The CG formula has the highest precision and FAS Scr-SCysC has the highest accuracy. A total of 30 patients followed up after surgery, and postoperative rGFR correlated with CG, CKD-EPI, FAS, and BIS formulas (P < 0.05). But postoperative rGFR has no significant correlation with MDRD and Schwartz (P > 0.05). Postoperative CKD-EPI Scr-SCysC has best consistency, and FAS Scr-SCysC has the highest accuracy and precision. Our data suggest that eGFR equations evaluated by both serum creatinine (Scr) and cystatin C (SCysC) is not necessarily better than those evaluated by one of them alone. Among all enrolled equations, FAS Scr-SCysC is the best one to evaluate postoperative GFR in patients with renal tumors.

The Pharmacokinetics of Levetiracetam in Critically Ill Adult Patients: An Intensive Care Unit Clinical Study

The aim of this study was to investigate levetiracetam pharmacokinetics in critically ill adult intensive care patients and to identify pathophysiological factors affecting its kinetics. Fourteen critically ill patients in an intensive care unit were enrolled in the study and received intravenous levetiracetam. Blood samples were collected at specific time points to determine the levetiracetam pharmacokinetics. Patient characteristics such as renal function, demographics, disease severity, organ dysfunction, and biochemical laboratory tests were evaluated for their influence on the kinetics of levetiracetam. Estimated glomerular filtration rate (eGFR) had a statistically significant (p = 0.001) effect on levetiracetam clearance. None of the other patient characteristics had a statistically significant effect on the pharmacokinetics. Simulations of dosing regimens revealed that even typically administered doses of levetiracetam may result in significantly increased concentrations and risk of drug toxicity in patients with impaired renal function. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score differed significantly among the three groups with different epileptic activity (p = 0.034). The same groups also differed in terms of renal function (p = 0.031). Renal dysfunction should be considered when designing levetiracetam dosage. Patients with a low APACHE II score had the lowest risk of experiencing epileptic seizures.

Artificial neural network for the prediction model of glomerular filtration rate to estimate the normal or abnormal stages of kidney using gamma camera

OBJECTIVE

Chronic kidney disease (CKD) is evaluated based on glomerular filtration rate (GFR) using a gamma camera in the nuclear medicine center or hospital in a routine procedure, but the gamma camera does not provide the accurate stages of the diseases. Therefore, this research aimed to find out the normal or abnormal stages of CKD based on the value of GFR using an artificial neural network (ANN).

METHODS

Two hundred fifty (Training 188, Testing 62) kidney patients who underwent the ultrasonography test to diagnose the renal test in our nuclear medical centre were scanned using gamma camera. The patients were injected with 99mTc-DTPA before the scanning procedure. After pushing the syringe into the patient's vein, the pre-syringe and post syringe radioactive counts were calculated using the gamma camera. The artificial neural network uses the softmax function with cross-entropy loss to diagnose CKD normal or abnormal labels depending on the value of GFR in the output layer.

RESULTS

The results showed that the accuracy of the proposed ANN model was 99.20% for K-fold cross-validation. The sensitivity and specificity were 99.10% and 99.20%, respectively. The Area under the curve (AUC) was 0.9994.

CONCLUSION

The proposed model using an artificial neural network can classify the normal or abnormal stages of CKD. After implementing the proposed model clinically, it may upgrade the gamma camera to diagnose the normal or abnormal stages of the CKD with an appropriate GFR value.

Estimated GFR: time for a critical appraisal

Since 1957, over 70 equations based on creatinine and/or cystatin C levels have been developed to estimate glomerular filtration rate (GFR). However, whether these equations accurately reflect renal function is debated. In this Perspectives article, we discuss >70 studies that compared estimated GFR (eGFR) with measured GFR (mGFR), involving ~40,000 renal transplant recipients and patients with chronic kidney disease (CKD), type 2 diabetes mellitus or polycystic kidney disease. Their results show that eGFR often differed from mGFR by ±30% or more, that eGFR values incorrectly staged CKD in 30-60% of patients, and that eGFR and mGFR gave different rates of GFR decline. Errors were unpredictable, and comparable for equations based on creatinine and/or cystatin C. We argue, therefore, that the persistence of these errors (despite intensive research) suggests that the problem lies with using creatinine and/or cystatin C as markers of renal function, rather than with the mathematical methods used for GFR estimation.

Simple equation for calculation of plasma clearance for evaluation of renal function without urine collection in rats

To develop an equation for the evaluation of renal function in rats using three dilutions of plasma samples and to validate this method by comparison with a reference method. The investigation was conducted in Sprague-Dawley (SD) rats after delivery of three doses of iohexol, with blood samples collected before and after dosage using a quantitative blood collection method. Plasma iohexol concentrations were detected by high performance liquid chromatography (HPLC). The extraction recovery of iohexol from plasma was >97.30% and the calibration curve was linear (r²  = 0.9997) over iohexol concentrations ranging from 10 to 1000 µg/mL. The method had an RE of <9.310 and intra- and inter-day RSD of <5.137% and <3.693%, respectively. The plasma clearance values obtained from the equation correlated closely (r = 0.763) with those obtained using the reference method. The relatively correlation in the results obtained using the method under investigation and the reference method indicate that this new equation can be used for preliminary assessment of renal function in rats.

Long-term effects intensive medical therapy on the development and progression of subclinical atherosclerosis and the metabolic syndrome in Chinese patients with type 2 diabetes mellitus

BACKGROUND

Few studies have investigated the progression of subclinical atherosclerosis and metabolic syndrome (MetS) in Chinese patients with type 2 diabetes mellitus (T2DM). This study was to compare the long-term effects of intensive medical therapy on the development and progression of subclinical atherosclerosis and MetS in Chinese T2DM patients with that of a conventional treatment regimen.

METHODS

A total of 316 T2DM patients were randomized to receive conventional pharmacological treatment or intensive medical therapy, consisting of diet and exercise counseling, from 2002 to 2014 at our hospital in Changsha, China. Clinical indicators of subclinical atherosclerosis and MetS were evaluated over the 12-year follow-up period. A χ analysis or t tests was used to compare the data between the 2 groups. Risk factors for subclinical atherosclerosis were identified using Cox proportional hazard models.

RESULTS

The incidence of subclinical atherosclerosis increased in both groups over time, and did not differ significantly between the 2 groups at the end of the study. However, after 6 years of treatment, the risk of subclinical atherosclerosis was significantly lower in the intensive medical therapy group, based on intima-media thickness (IMT) measurements, compared with that in the conventional treatment (44.2% vs. 69.7%; P < 0.01). Age, creatinine, and IMT of the common iliac artery were significantly associated with subclinical atherosclerosis. Although the indicators of MetS did not differ significantly at the end of study, the success rate for the management of MetS in the intensive medical therapy group was significantly higher than that in the conventional treatment group in 2006, 2008, 2010, and 2012.

CONCLUSIONS

The incidence of atherosclerosis in the intensive medical therapy group was significantly lower than that in the conventional treatment group from 2006 to 2010 (P < 0.05), and the incidence of MetS in the intensive medical therapy group was significantly higher than that in the conventional treatment group from 2006 to 2012. Kaplan-Meier estimations showed that the risk of subclinical atherosclerosis in the intensive medical therapy group was significantly lower than that in the conventional treatment group (P < 0.001), whereas the risk of MetS was not significantly different between the treatment groups (P > 0.05).

Modified glomerular filtration rate-estimating equations developed in asiatic population for chinese patients with type 2 diabetes

Objectives. To evaluate eight modified equations developed in Asiatic populations in type 2 diabetic patients in China. Methods. A total of 209 Chinese patients with type 2 diabetes were recruited. Using the technetium-99m diethylenetriaminepentaacetic acid-glomerular filtration rate (GFR) to act as the reference, comparisons of their efficiency to estimate GFR in the subjects were made between various equations. Results. Median of difference of the Chinese equation 1 was the lowest (median of difference, 0.51 mL/min/1.73 m(2)). Median percent of absolute difference of the Chinese equation 2 was less than those of the other equations (26.97 versus ranged from 32.54 to 37.61 mL/min/1.73 m(2), [P < 0.001 for all]). Precision of the simplified reexpressed MDRD equation was the best (92.9 mL/min/1.73 m(2)). Accuracies of the Chinese equation 2 were greater (P < 0.05 for all). There was also an improvement in chronic kidney disease (CKD) stage misclassification of the Chinese equation 2 (55.0 versus ranged from 61.2 to 64.6%, [P < 0.001 for all]). However, the 30% accuracies of all the equations were less than 70%. Conclusions. Our study highlighted a limitation in the use of the above equations in the majority of Chinese diabetic subjects. A better equation is needed in order to give an accurate estimation of GFR in type 2 diabetic patients in China.

A comparison of the performances of an artificial neural network and a regression model for GFR estimation

BACKGROUND

Accurate estimation of glomerular filtration rate (GFR) is important in clinical practice. Current models derived from regression are limited by the imprecision of GFR estimates. We hypothesized that an artificial neural network (ANN) might improve the precision of GFR estimates.

STUDY DESIGN

A study of diagnostic test accuracy.

SETTING & PARTICIPANTS

1,230 patients with chronic kidney disease were enrolled, including the development cohort (n=581), internal validation cohort (n=278), and external validation cohort (n=371).

INDEX TESTS

Estimated GFR (eGFR) using a new ANN model and a new regression model using age, sex, and standardized serum creatinine level derived in the development and internal validation cohort, and the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) 2009 creatinine equation.

REFERENCE TEST

Measured GFR (mGFR).

OTHER MEASUREMENTS

GFR was measured using a diethylenetriaminepentaacetic acid renal dynamic imaging method. Serum creatinine was measured with an enzymatic method traceable to isotope-dilution mass spectrometry.

RESULTS

In the external validation cohort, mean mGFR was 49±27 (SD) mL/min/1.73 m2 and biases (median difference between mGFR and eGFR) for the CKD-EPI, new regression, and new ANN models were 0.4, 1.5, and -0.5 mL/min/1.73 m2, respectively (P<0.001 and P=0.02 compared to CKD-EPI and P<0.001 comparing the new regression and ANN models). Precisions (IQRs for the difference) were 22.6, 14.9, and 15.6 mL/min/1.73 m2, respectively (P<0.001 for both compared to CKD-EPI and P<0.001 comparing the new ANN and new regression models). Accuracies (proportions of eGFRs not deviating >30% from mGFR) were 50.9%, 77.4%, and 78.7%, respectively (P<0.001 for both compared to CKD-EPI and P=0.5 comparing the new ANN and new regression models).

LIMITATIONS

Different methods for measuring GFR were a source of systematic bias in comparisons of new models to CKD-EPI, and both the derivation and validation cohorts consisted of a group of patients who were referred to the same institution.

CONCLUSIONS

An ANN model using 3 variables did not perform better than a new regression model. Whether ANN can improve GFR estimation using more variables requires further investigation.

Estimation of glomerular filtration rate by a radial basis function neural network in patients with type-2 diabetes mellitus

BACKGROUND

Accurate and precise estimates of glomerular filtration rate (GFR) are essential for clinical assessments, and many methods of estimation are available. We developed a radial basis function (RBF) network and assessed the performance of this method in the estimation of the GFRs of 207 patients with type-2 diabetes and CKD.

METHODS

Standard GFR (sGFR) was determined by (99m)Tc-DTPA renal dynamic imaging and GFR was also estimated by the 6-variable MDRD equation and the 4-variable MDRD equation.

RESULTS

Bland-Altman analysis indicated that estimates from the RBF network were more precise than those from the other two methods for some groups of patients. However, the median difference of RBF network estimates from sGFR was greater than those from the other two estimates, indicating greater bias. For patients with stage I/II CKD, the median absolute difference of the RBF network estimate from sGFR was significantly lower, and the P50 of the RBF network estimate (n = 56, 87.5%) was significantly higher than that of the MDRD-4 estimate (n = 49, 76.6%) (p < 0.0167), indicating that the RBF network estimate provided greater accuracy for these patients.

CONCLUSIONS

In patients with type-2 diabetes mellitus, estimation of GFR by our RBF network provided better precision and accuracy for some groups of patients than the estimation by the traditional MDRD equations. However, the RBF network estimates of GFR tended to have greater bias and higher than those indicated by sGFR determined by (99m)Tc-DTPA renal dynamic imaging.

Estimating glomerular filtration rates in elderly Chinese patients with chronic kidney disease: performance of six modified formulae developed in Asian populations

Objectives

The aim of the present study was to evaluate modified glomerular filtration rate (GFR) prediction formulae in an elderly Chinese population with chronic kidney disease (CKD).

Methods

A total of 378 elderly Chinese patients with CKD were enrolled. The GFR was estimated with six modified GFR prediction formulae. The performances of the estimated GFRs were compared with those of the standard GFRs measured by technetium-99m diethyl-enetraminepentaacetic acid.

Results

Biases were similar for Chinese formula 1, the Asian formula, and Chinese formula 2 (median difference, 2.22 mL/min/1.73 m² and 2.59 mL/min/1.73 m² for Chinese formula 1 and the Asian formula, respectively, versus (vs) 3.69 mL/min/1.73 m² for Chinese formula 2 [P = 0.298 and P = 0.913, respectively]). Precision was improved with the Japanese formula (interquartile range of the difference, 3.14 mL/min/1.73 m² of the Japanese formula versus 15.53–23.06 mL/min/1.73 m² of the other formulae). The accuracy of Chinese formula 2 was the highest (30% accuracy, 59.3% vs range 37.8–54.0% [P < 0.05 for all comparisons]). However, none of the modified formulae surpassed the acceptable tolerance (>70%), and the GFR category misclassification rates for all the formulae exceeded 50%.

Conclusion

Our findings suggest that all six modified formulae developed in Asian populations may show great bias in elderly Chinese patients with CKD. Also, our study suggests the need for uniform measures for the assessment of CKD in the elderly to guarantee better sensitivity and specificity.

Multicenter study of creatinine- and/or cystatin C-based equations for estimation of glomerular filtration rates in Chinese patients with chronic kidney disease

OBJECTIVE

To establish equations for the estimation of glomerular filtration rates (eGFRs) based on serum creatinine (SCr) and/or serum cystatin C (SCysC) in Chinese patients with chronic kidney disease (CKD), and to compare the new equations with both the reference GFR (rGFR) and the literature equations to evaluate their applicability.

METHODS

The 788 Chinese CKD patients were randomly divided into two groups, the training group and the testing group, to establish new eGFR-formulas based on serum CysC and to validate the established formulas, respectively. (99m)Tc-DTPA clearance (as the rGFR), serum Cr, and serum CysC were determined for all patients, and GFR was calculated using the Cockcroft-Gault equation (eGFR1), the MDRD formula (eGFR2), the CKD-EPI formulas (eGFR3, eGFR4), and the Chinese eGFR Investigation Collaboration formulas (eGFR5, eGFR6). The accuracy of each eGFR was compared with the rGFR.

RESULTS

The training and testing groups' mean GFRs were 50.84±31.36 mL/min/1.73 m(2) and 54.16±29.45 mL/min/1.73 m(2), respectively. The two newly developed eGFR formulas were fitted using iterative computation: [Formula: see text] and [Formula: see text]. Significant correlation was observed between each eGFR and the rGFR. However, proportional errors and constant errors were observed between rGFR and eGFR1, eGFR2, eGFR4, eGFR5 or eGFR6, and constant errors were observed between eGFR3 and rGFR, as revealed by the Passing & Bablok plot analysis. The Bland-Altman analysis illustrated that the 95% limits of agreement of all equations exceeded the previously accepted limits of <60 mL/min •1.73 m(2), except the equations of eGFR7 and eGFR8.

CONCLUSION

The newly developed formulas, eGFR7 and eGFR8, provide precise and accurate GFR estimation using serum CysC detection alone or in combination with serum Cr detection. Differences in detection methods should be carefully considered when choosing literature eGFR equations to avoid misdiagnosis and mistreatment.

Improved glomerular filtration rate estimation by an artificial neural network

Background

Accurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional surveys have not resolved questions about ANN performance.

Methods

A total of 1,180 patients that had chronic kidney disease (CKD) were enrolled in the development data set, the internal validation data set and the external validation data set. Additional 222 patients that were admitted to two independent institutions were externally validated. Several ANNs were constructed and finally a Back Propagation network optimized by a genetic algorithm (GABP network) was chosen as a superior model, which included six input variables; i.e., serum creatinine, serum urea nitrogen, age, height, weight and gender, and estimated GFR as the one output variable. Performance was then compared with the Cockcroft-Gault equation, the MDRD equations and the CKD-EPI equation.

Results

In the external validation data set, Bland-Altman analysis demonstrated that the precision of the six-variable GABP network was the highest among all of the estimation models; i.e., 46.7 ml/min/1.73 m² vs. a range from 71.3 to 101.7 ml/min/1.73 m², allowing improvement in accuracy (15% accuracy, 49.0%; 30% accuracy, 75.1%; 50% accuracy, 90.5% [P<0.001 for all]) and CKD stage classification (misclassification rate of CKD stage, 32.4% vs. a range from 47.3% to 53.3% [P<0.001 for all]). Furthermore, in the additional external validation data set, precision and accuracy were improved by the six-variable GABP network.

Conclusions

A new ANN model (the six-variable GABP network) for CKD patients was developed that could provide a simple, more accurate and reliable means for the estimation of GFR and stage of CKD than traditional equations. Further validations are needed to assess the ability of the ANN model in diverse populations.

Using mathematical algorithms to modify glomerular filtration rate estimation equations

BACKGROUND

The equations provide a rapid and low-cost method of evaluating glomerular filtration rate (GFR). Previous studies indicated that the Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease-Epidemiology (CKD-EPI) and MacIsaac equations need further modification for application in Chinese population. Thus, this study was designed to modify the three equations, and compare the diagnostic accuracy of the equations modified before and after.

METHODOLOGY

With the use of (99 m)Tc-DTPA renal dynamic imaging as the reference GFR (rGFR), the MDRD, CKD-EPI and MacIsaac equations were modified by two mathematical algorithms: the hill-climbing and the simulated-annealing algorithms.

RESULTS

A total of 703 Chinese subjects were recruited, with the average rGFR 77.14±25.93 ml/min. The entire modification process was based on a random sample of 80% of subjects in each GFR level as a training sample set, the rest of 20% of subjects as a validation sample set. After modification, the three equations performed significant improvement in slop, intercept, correlated coefficient, root mean square error (RMSE), total deviation index (TDI), and the proportion of estimated GFR (eGFR) within 10% and 30% deviation of rGFR (P10 and P30). Of the three modified equations, the modified CKD-EPI equation showed the best accuracy.

CONCLUSIONS

Mathematical algorithms could be a considerable tool to modify the GFR equations. Accuracy of all the three modified equations was significantly improved in which the modified CKD-EPI equation could be the optimal one.