Modification Of Diet In Renal Disease Equation Research Articles

The prevalence of acute kidney injury in patients with community-acquired pneumonia who required mechanical ventilation.

Community-acquired pneumonia (CAP) is a common reason for intensive care unit (ICU) admission and sepsis. Acute kidney injury (AKI) is a frequent complication of community-acquired pneumonia and is associated with increased short- and long-term morbidity and mortality and healthcare costs. Describe the prevalence of AKI in patients with CAP requiring mechanical ventilation and evaluate its association with inhospital mortality. Retrospective cohort. Intensive care unit. We included patients with CAP on mechanical ventilation. Patients were categorized according to the development of AKI in the first 24 hours of ICU admission using the Kidney Disease Improving Global Outcomes (KDIGO) classification from no AKI, stage 1 AKI, stage 2 AKI, and stage 3 AKI. The primary outcome was hospital mortality. Secondary outcomes were ICU mortality, hospital and ICU length of stay, ventilation duration, tracheostomy, and renal replacement therapy requirement. Of 1536 patients included in the study, 829 patients (54%) had no AKI while 707 (46%) developed AKI. In-hospital mortality was 288/829 (34.8%) for patients with no AKI, 43/111 (38.7%) for stage 1 AKI, 86/216 (40%) for stage 2 AKI, and 196/380 (51.7%) for stage 3 AKI (P<.0001). Multivariate analysis revealed that stages 1, 2, or 3 AKI compared to no AKI were not independently associated with in-hospital mortality. Older age, vasopressor use; decreased Glasgow coma scale, PaO2/Fio2 ratio and platelet count, increased bilirubin, lactic acid and INR were associated with increased mortality while female sex was associated with reduced mortality. Among mechanically ventilated patients with CAP, AKI was common and was associated with higher crude mortality. The higher mortality could not be attributed alone to AKI, but rather appeared to be related to multi-organ dysfunction. Single-center retrospective study with no data on baseline serum creatinine and the use of estimated baseline creatinine distributions based on the MDRD (Modification of Diet in Renal Disease)equation which may lead to an overestimation of AKI. Second, we did not have data on the microbiology of pneumonia, appropriateness of antibiotic therapy or the administration of other medications that have been demonstrated to be associated with AKI.

Biological variation in the estimated glomerular filtration rate of healthy individuals within 24h calculated using 2021CKD-EPI equations.

Use the MDRD (Modification of Diet in Renal Disease) and 2021 CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation void of race coefficients (CKD-EPICrea, CKD-EPICys-C, and CKD-EPICrea+Cys-C) to estimate the BV (Biological variation) of eGFR (estimated glomerular filtration rate) within 24h in a healthy population to help explain future studies using eGFR in the context of a known BV. Blood samples were collected from 30 healthy subjects at six time points within 24h. Serum creatinine (S-Crea) and serum cystatin C (S-Cys-C) were measured, and the BV of eGFR was calculated. Outlier and variance homogeneity analyses were performed, followed by CV-ANOVA on trend-corrected data. The eGFR CVI for the four equations (MDRD, CKD-EPICrea, CKD-EPICys-C, and CKD-EPICrea+Cys-C) were 8.39% (7.50-9.51%), 3.90% (3.49-4.42%), 6.58% (5.88-7.46%), and 5.03% (4.50-5.71%), respectively. The corresponding II and RCVpos/neg values were 0.69, 0.48, 0.51, and 0.31, and (29.30%, - 22.66%), (12.69%, - 11.2 6%), (20.97%, - 17.33%), and (15.88%, - 13.70%), respectively; RCVpos /neg of eGFR was highest in the MDRD equation and lowest in the CKD-EPI Crea equation. Additionally, the RCVpos/neg values of the individual was highest in the MDRD equation and lowest in the CKD-EPICrea+Cys-C equation; they are (56.51%, - 36.11%) and (5.01%, - 4.77%), respectively. We present data on the 24h BV eGFR of the 2021 CKD-EPI equations. The presence of BV has impact on the interpretation of GFR results, affecting CKD disease grading. The RCVpos/neg differences were large among the individuals. When using eGFRs based on the MDRD and CKD-EPI equations, it is necessary to combine RCVpos/neg values before interpreting the results.

Impaired kidney function and the risk of all-cause mortality and cardiovascular disease among Chinese hypertensive adults: Using three different equations to estimate the glomerular filtration rate

ObjectivesWe aimed to seek accurate assessments of the glomerular filtration rate (GFR) in a Chinese hypertensive population to identify individuals at high risk for chronic kidney disease (CKD) progression. Then, the risk of cardiovascular disease (CVD) and all-cause death due to kidney injury were further investigated under appropriate GFR-estimation equations. MethodsIn this prospective follow-up cohort study of 10,171 hypertensive patients, we compared the discrimination power of a trio of GFR-estimation equations using Harrell's C-index, measuring the model fit by calculating the Akaike information criterion. Univariate and multivariable logistic regression analyses were respectively used to calculate the hazard ratio (HR) and 95% confidence interval [CI] values for CKD progression. In addition, we also assessed the risk of CVD and all-cause death with impaired renal function using multivariable-adjusted Cox regression models. ResultsThe Modification of Diet in Renal Disease (MDRD) equation showed the highest C-index range for the predicted probability of CKD progression in the fully adjusted model. During MDRD analysis, a low eGFR (60–89 mL/min/1.73m2 or < 60 mL/min/1.73m2) was an independent risk factor for CVD, especially stroke (1.28 [95% CI, 1.05–1.55] and 1.89 [95% CI, 1.08–3.31]), as well as all-cause mortality (1.28 [95% CI, 1.09–1.50] and 1.68 [95% CI, 1.01–2.78]). ConclusionsThe MDRD equation seems to be more suitable for screening CKD progression in Chinese hypertensive populations, targeting potential risk factors for effective prevention to reduce renal impairment so as to further limit CVD morbidity and mortality.

Exploring an Unknown Corner of a Well-Known Topic: HIIE Influence on Renal Health and Filtration in Healthy Individuals Free of Cardiometabolic Diseases.

Aerobic exercise, specifically high-intensity interval exercise (HIIE), and its effects on renal health and filtration (RHF) are not well understood. Several studies support incorporating contemporary biomarkers serum cystatin C (CyC) and urine epidermal growth factor (uEGF) to combat the volatility of serum creatinine (sCr). Using these biomarkers, we examined the acute influences HIIE has on RHF to determine if there is a ceiling effect in healthy populations. The purpose was to determine the influence of an acute bout of HIIE on RHF. Thirty-six participants (n = 22 males; n = 14 females; age 37.6 ± 12.4 years.; BF% 19.2 ± 7.1%; VO2max 41.8 + 7.4 mL/kg/min) completed 30 min of HIIE on a treadmill (80% and 40% of VO2reserve in 3:2 min ratio). Blood and urine samples were obtained under standardized conditions before, 1 h, and 24 h post-exercise. CyC, sCR, uEGF, urine creatinine (uCr), uCr/uEGF ratio, and multiple estimates of glomerular filtration rate (eGFR) Modification of Diet in Renal Disease (MDRD) and CKD-EPI equations were used. The analysis employed paired sample t-tests and repeated measures ANOVAs. CyC, uEGF, uCr, and uCr/uEGF ratio concentrations were not altered between timepoints. sCr increased 1 h post-exercise (p > 0.002) but not at 24 h post-exercise. eGFR decreased in the MDRD and CKD-EPI equations at 1 h (p > 0.012) with no changes at 24 h post-exercise. CyC and sCr/CyC demonstrated no significant changes. CyC and uEGF are not altered by acute HIIE. The results demonstrate a potential ceiling effect in contemporary and traditional biomarkers of RHF, indicating improvements in RHF may be isolated to populations with reduced kidney function.

Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy

BackgroundThere are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of inconsistent methods of estimating baseline serum creatinine (sCr) may result in a poor understanding of these models’ effectiveness in clinical practice. Until now, the performance of such models with different baselines has not been compared on a single dataset. Additionally, AKI prediction models are known to have a high rate of false positive (FP) events regardless of baseline methods. This warrants further exploration of FP events to provide insight into potential underlying reasons.ObjectiveThe first aim of this study was to assess the variance in performance of ML models using three methods of baseline sCr on a retrospective dataset. The second aim was to conduct an error analysis to gain insight into the underlying factors contributing to FP events.Materials and methodsThe Intensive Care Unit (ICU) patients of the Medical Information Mart for Intensive Care (MIMIC)-IV dataset was used with the KDIGO (Kidney Disease Improving Global Outcome) definition to identify AKI episodes. Three different methods of estimating baseline sCr were defined as (1) the minimum sCr, (2) the Modification of Diet in Renal Disease (MDRD) equation and the minimum sCr and (3) the MDRD equation and the mean of preadmission sCr. For the first aim of this study, a suite of ML models was developed for each baseline and the performance of the models was assessed. An analysis of variance was performed to assess the significant difference between eXtreme Gradient Boosting (XGB) models across all baselines. To address the second aim, Explainable AI (XAI) methods were used to analyse the XGB errors with Baseline 3.ResultsRegarding the first aim, we observed variances in discriminative metrics and calibration errors of ML models when different baseline methods were adopted. Using Baseline 1 resulted in a 14% reduction in the f1 score for both Baseline 2 and Baseline 3. There was no significant difference observed in the results between Baseline 2 and Baseline 3. For the second aim, the FP cohort was analysed using the XAI methods which led to relabelling data with the mean of sCr in 180 to 0 days pre-ICU as the preferred sCr baseline method. The XGB model using this relabelled data achieved an AUC of 0.85, recall of 0.63, precision of 0.54 and f1 score of 0.58. The cohort size was 31,586 admissions, of which 5,473 (17.32%) had AKI.ConclusionIn the absence of a widely accepted method of baseline sCr, AKI prediction studies need to consider the impact of different baseline methods on the effectiveness of ML models and their potential implications in real-world implementations. The utilisation of XAI methods can be effective in providing insight into the occurrence of prediction errors. This can potentially augment the success rate of ML implementation in routine care.

Correlation of eGFR values estimated by different equations based on creatinine and cystatin-C in patients on hemodialysis treatment at Teaching Hospital Karapitiya, Galle, Sri Lanka

The present study was to compare eGFR values estimated from different equations based on creatinine and cystatin-C in patients on hemodialysis treatment. eGFR values were calculated using Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology equations based on Creatinine (CKD-EPICr) and cystatin-C values alone (CKDEPI Cys C) and by their combination (CKD-EPICr-Cys C), using 40 pre-dialysis samples. No significant differences in renal function parameters and eGFR were observed, either between male (55%) and female (45%) patients or within different age groups (p&gt;0.05). Certain levels of agreement (p&gt;0.05) were observed between the equations, except for the values derived from CKD-EPICys C and CKD-EPICr-Cys C (p = 0.022). Significant positive correlations were observed between all selected equations. The highest correlation was observed between CKD-EPICr and MDRD (r = 0.998, p = 0.000), whereas the lowest correlation was found between MDRD and CKD-EPICys C (r = 0.552, p = 0.000). The present findings revealed that MDRD and CKD-EPICr equations are suitable for the calculation of eGFR in routine local clinical settings for the assessment of progression of kidney impairment in patients with CKD on hemodialysis treatment. However, the use of CKD-EPICr-Cys C rather than the CKD-EPICys C is recommended as a confirmatory tool where necessary.

Abstract P374: Greater Burden Of Chronic Kidney Disease Is Associated With Hypertension Prevalence And Management In South Africa

Introduction: Complications e.g., chronic kidney disease (CKD) are frequent with longstanding hypertension, particularly if poorly managed. Hypothesis: We assessed the hypothesis that prevalence and associations of CKD differed by hypertension prevalence, awareness, treatment and control in South Africa using five CKD estimates. Methods: In this randomly selected cross-sectional study, glomerular filtration rate (GFR) was estimated by CKD Epidemiology Collaboration (CKD-EPI) equations [CKD-EPI creatinine (CKD-EPIcr), CKD-EPI cystatin C, CKD-EPI creatinine-cystatin C], Modification of Diet in Renal Disease (MDRD) and Cockcroft-Gault formula (CGF). Blood pressures were measured, and history of hypertension management collected. Results: Among 1092 participants, mean age 43.5 years, 64% women, the prevalence of hypertension was 42% with similar rates in men (41%) and women (43%). In participants with hypertension (n=460), awareness, treatment and control were 61.5% (283/460), 47.2% (217/460) and 27.0% (124/460), with better rates in women compared with men (p&lt;0.001). CKD prevalence (GFR&lt;60 mL/min/1.73m 2 ) was 2.0-5.9% overall using 5 formulae, and significantly higher in participants with (3.9-10.2%) compared to without hypertension (0.6-2.7%) (p&lt;0.001). In participants with hypertension, CKD was higher in those aware (5.7-13.8%) vs unaware (1.1-4.5%) of their diagnosis (p≤0.015), on treatment (6.9-14.3%) vs none (1.2-6.6%) (p≤0.016), and those with controlled (BP&lt;140/90 mmHg) vs uncontrolled hypertension (6.5-15.1% vs. 3-8%, p≤0.096). In models adjusted for age, sex and obesity, higher hypertension prevalence and awareness were significantly (p&lt;0.05) associated with CKD by CKD-EPIcr and MDRD equations; hypertension treatment was significantly associated with CKD by CKD-EPIcr, MDRD and CGF formulae, while hypertension control was not associated with CKD. Conclusions: This study highlights the higher prevalence and greater likelihood of CKD in participants with hypertension and those who were diagnosed and receiving treatment, likely due to the longer duration of their hypertension compared with their counterparts. Higher CKD in the diagnosed and treated reinforces the need for optimal control, which was low in this cohort.

Comparison of CKD-EPI, C-G and MDRD equations for estimating glomerular filtration rate in chronic kidney disease population in South-Western Nigeria

Background: Ethnic variabilities make reliability of formula equations for assessing glomerular filtration rate (GFR) doubtful in many  populations. We compared Cockroft-Gault (CG), modification of diet in renal disease (MDRD), and chronic kidney diseases epidemiology  collaboration (CKD-EPI) equations in adult Nigerian CKD subjects.&#x0D; Methodology: We measured 24-hour-urinary creatinine clearance of 311 adult CKD patients and compared with the three estimated  equations. Bland-Altman plots were used to assess agreement between estimated equations and measured creatinine clearance (mGFR).  Receiver-operating curve (ROC) analysis was used to assess the diagnostic power of the equations. Equation with accuracy within 30% of mGFR of ≥90% was considered acceptable for use.&#x0D; Results: Mean age was 41.9±12.7 years with 182(58.5%) females. The mean GFR using  CKD-EPI, 2 MDRD and CG equations were 69.5±33.9, 65.9±33.0 and 66.2±30.9 mls/min/1.73m respectively 2 (mGFR 68.3±31.1mls/min /1.73m ). The 3 equations showed positive correlation to mGFR (r=0.95) but CKD-EPI had the least bias.&#x0D; Conclusion: All three equations  can be used but CKD-EPI equation is preferable in Nigerian CKD patients, especially with GFR&gt; 60mls/min.  

Diagnostic value of neutrophil gelatinase-associated lipocalin (NGAL) as an early biomarker for detection of renal failure in hypertensives: a case–control study in a regional hospital in Ghana

BackgroundRenal failure is one of the most serious vascular effects of hypertension. For better therapy and prevention of complications, early kidney disease identification in these patients is absolutely essential. However, current studies have proposed plasma Neutrophil Gelatinase Associated Lipocalin (pNGAL) to be a better biomarker comparative to serum creatinine (SCr). This study assessed the diagnostic utility of plasma neutrophil gelatinase-associated lipocalin (pNGAL) as a biomarker for early nephropathy diagnosis in hypertensive individuals.MethodsThis hospital-based case–control study comprised 140 hypertensives and 70 healthy participants. A well-structured questionnaire and patient case notes were used to document relevant demographic and clinical information. 5 ml of venous blood sample was taken to measure fasting blood sugar levels, creatinine, and plasma NGAL levels. All data were analyzed using the Statistical Package for Social Sciences (SPSS release 20.0, copyrite©SPSS Inc.) and a p-value < 0.05 was considered statistically significant.ResultsIn this study the plasma neutrophil gelatinase-associated lipocalin (NGAL) levels were significantly higher in cases compared to controls. Hypertensive cases also had significantly higher waist-circumference compared to the control group. The median fasting blood sugar level was significantly higher in cases compared to controls. This study established the use of Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), and Cockcroft and Gault formula (CG) as the most accurate predictive equations for assessing renal dysfunction. The threshold for NGAL above which renal impairment can be assessed was found to be 109.4 ng/ml (sen-91%, spec. – 68%), 120 ng/ml (sen- 100%, spec- 72%) and 118.6 ng/ml (sen- 83%, spec- 72%) for MDRD, CKD-EPI and CG equations respectively. The prevalence of CKD was 16.4%, 13.6% and 20.7% respectively using the MDRD, CKD-EPI and CG.ConclusionFrom this study, pNGAL is a better indicator of kidney impairment in the early stages of CKD as compared with sCr in general hypertensive population.

MP12-08 EVALUATING THE IMPACT OF EXCLUDING THE RACE FACTOR FROM THE eGFR EQUATION ON BLADDER CANCER TREATMENT OPTIONS

You have accessJournal of UrologyCME1 Apr 2023MP12-08 EVALUATING THE IMPACT OF EXCLUDING THE RACE FACTOR FROM THE eGFR EQUATION ON BLADDER CANCER TREATMENT OPTIONS Amir Khan, Shu Wang, Rehan Choudhary, Michael Phelan, Eberechukwu Onukwugha, and M. Minhaj Siddiqui Amir KhanAmir Khan More articles by this author , Shu WangShu Wang More articles by this author , Rehan ChoudharyRehan Choudhary More articles by this author , Michael PhelanMichael Phelan More articles by this author , Eberechukwu OnukwughaEberechukwu Onukwugha More articles by this author , and M. Minhaj SiddiquiM. Minhaj Siddiqui More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003227.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The estimated glomerular filtration rate (eGFR) equation is based on several factors among which the race factor has been broadly criticized. In September 2021, the National Kidney Foundation and American Society of Nephrology Task Force announced a new race-free calculation for eGFR. Aspects of treatment decisions for muscle-invasive bladder cancer (MIBC) are dependent on eGFR, specifically neoadjuvant cisplatin eligibility and choice of diversion with cystectomy. Herein, we evaluate the impact of removal of race-based eGFR calculation on the management of patients with MIBC. METHODS: Using the National Surgical Quality Improvement Program database, adult patients diagnosed with MIBC and who received radical cystectomy from 2015 to 2020 were included in this study. eGFR was calculated using the Modification of Diet in Renal Disease (MDRD) equation. We calculated the proportion of African American patients who were candidates for neobladder urinary diversions and cisplatin-based chemotherapy using >30 and >60 ml/min/1.73m2 as the cutoff for eGFR, respectively, as calculated with and without the race factor. RESULTS: African Americans constituted 4.5% (579) of the total sample population (12,192) among which 39.7% (230) were female and 60.3% (349) were male. There was no association of eGFR with gender. Using the MDRD equation, the mean eGFR decreased from 70.0 to 57.8 ml/min/1.73m2 after removing the race factor. With the adjusted eGFR without race, 4.1% fewer patients (94.6% vs 90.5%) were eligible for neobladder urinary diversion with a >30 ml/min/1.73m2 eGFR cutoff. Furthermore, among patients who were previously eligible to receive cisplatin chemotherapy, 18.0% fewer patients (63.0% vs 45.0%) would remain eligible with a >60 ml/min/1.73m2 eGFR. (Figure 1) CONCLUSIONS: Excluding race from the eGFR equation will preclude some previously eligible African American patients for certain treatment in bladder cancer management. Further studies are needed to understand the relative risks and benefits of decisions that are based on the adjusted eGFR. Source of Funding: No source of funding © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e136 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Amir Khan More articles by this author Shu Wang More articles by this author Rehan Choudhary More articles by this author Michael Phelan More articles by this author Eberechukwu Onukwugha More articles by this author M. Minhaj Siddiqui More articles by this author Expand All Advertisement PDF downloadLoading ...

Glomerular Filtration Rate: Comparison of Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Equations with the Effect of Age in a Tertiary Hospital in Terengganu, Malaysia

Objective: The Malaysian Ministry of Health Clinical Practice Guideline 2018 recommends the clinical use of the CKD-EPI equation instead of the MDRD equations. This study aims to examine mean eGFR and prevalence of chronic kidney disease (CKD) using both equations based on different age groups and to ascertain inter-rater agreement between both equations, particularly in the elderly in a tertiary hospital in Terengganu, Malaysia. Method: Serum creatinine results were extracted from the lab information system (LIS) for a 1-year duration in a patient more than and equal to 18 years old (≥18 years old). The first creatinine results from 69,329 people were used to estimate GFR using both equations. The mean eGFR, prevalence of the CKD and agreement between those two equations were compared. Result: In comparison with the MDRD equation, CKD-EPI revealed lower mean eGFR (82.63 vs 85.42 mL/min/1.73m², p&lt;0.001) and reduce in the prevalence of the chronic kidney disease (CKD) (25.7% vs 28.4%). When subdivided by age, the prevalence of CKD reduced in the age group 18-79 years but increased in the elderly age &gt;80 years. The numerical agreement of eGFR was excellent (ICC = 0.883), and the categorical agreement of CKD was almost perfect in all age groups. (ƙ= 0.932). Conclusion: CKD-EPI equation reduces the prevalence of CKD in young people and increases prevalence in the elderly (&gt;80 years old). However, the CKD-EPI equation is an appropriate alternative to the MDRD equation for all age groups, including the elderly. Further validation studies involving a large multiethnic and adequate elderly population in Malaysia are much needed.

Association between Decreased Estimated Glomerular Filtration Rates and Long-term Mortality in Korean Patients with Acute Myocardial Infarction.

A reduced estimated glomerular filtration rate (eGFR) is a predictor for mortality in patients with acute myocardial infarction (AMI). This study aimed to compare mortality according to the GFR and eGFR calculation methods during long-term clinical follow-ups. Using the Korean Acute Myocardial Infarction Registry-National Institutes of Health Data, 13,021 patients with AMI were included in this study. Patients were divided into the surviving (n=11,503, 88.3%) and deceased (n=1,518, 11.7%) groups. Clinical characteristics, cardiovascular risk factors, and 3-year mortality-related factors were analyzed. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations. The surviving group was younger than the deceased group (62.6±12.4 vs. 73.6±10.5 years, p<0.001), whereas the deceased group had higher hypertension and diabetes prevalences than the surviving group. A high Killip class was more frequently observed in the deceased group. eGFR was significantly lower in the deceased group (82.2±24.1 vs. 55.2±28.6 ml/min/1.73 m2, p<0.001). Multivariate analysis revealed that low eGFR was an independent risk factor for mortality during the 3-year follow-up. The CKD-EPI equation was more useful for predicting mortality than the MDRD equation (0.766; 95% confidence interval [CI], 0.753-0.779 vs. 0.738; 95% CI, 0.724-0.753; p=0.001). Decreased renal function was a significant predictor of mortality after 3 years in patients with AMI. The CKD-EPI equation was more useful for predicting mortality than the MDRD equation.

A Deep Learning Approach for the Estimation of Glomerular Filtration Rate.

An accurate estimation of glomerular filtration rate (GFR) is clinically crucial for kidney disease diagnosis and predicting the prognosis of chronic kidney disease (CKD). Machine learning methodologies such as deep neural networks provide a potential avenue for increasing accuracy in GFR estimation. We developed a novel deep learning architecture, a deep and shallow neural network, to estimate GFR (dlGFR for short) and examined its comparative performance with estimated GFR from Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. The dlGFR model jointly trains a shallow learning model and a deep neural network to enable both linear transformation from input features to a log GFR target, and non-linear feature embedding for stage of kidney function classification. We validate the proposed methods on the data from multiple studies obtained from the NIDDK Central Database Repository. The deep learning model predicted values of GFR within 30% of measured GFR with 88.3% accuracy, compared to the 87.1% and 84.7% of the accuracy achieved by CKD-EPI and MDRD equations (p = 0.051 and p &lt; 0.001, respectively). Our results suggest that deep learning methods are superior to equations resulting from traditional statistical methods in estimating glomerular filtration rate. Based on these results, an end-to-end predication system has been deployed to facilitate use of the proposed dlGFR algorithm.

How Websites and Mobile Applications Wrongly Calculate eGFR by MDRD Equation

Equations to estimate glomerular filtration rate (GFR) are routinely used for the diagnosis and classification of chronic kidney diseases (CKDs). Modification of Diet in Renal Disease (MDRD) equation is an old one and has been replaced in many countries by CKD Epidemiology Collaboration (CKD-EPI) equation, but MDRD is still available in routine practice worldwide, especially in developing countries. Many users of MDRD, don’t know that it has two different versions (equations). This idea makes confusion in practice and affected the developers of this equation in internet websites and mobile applications. In this review, we will focus on this dilemma and try to solve it by explaining the basics of these two versions, and when I can choose each version, then the reflection of this issue on about 105 websites/Applications from different countries around the world. After that, we will give recommendations for both developers and seekers of this equation about overcoming this debate.

Effect of Glomerular Filtration Rate by Different Equations on Prediction Models for End-Stage Renal Disease in Diabetes.

Background and ObjectivesThe study aimed to evaluate the performance of a predictive model using the kidney failure risk equation (KFRE) for end-stage renal disease (ESRD) in diabetes and to investigate the impact of glomerular filtration rate (GFR) as estimated by different equations on the performance of the KFRE model in diabetes.Design, Setting, Participants, and MeasurementsA total of 18,928 individuals with diabetes without ESRD history from the UK Biobank, a prospective cohort study initiated in 2006–2010, were included in this study. Modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI) or revised Lund–Malmö (r-LM) were used to estimate GFR in the KFRE model. Cox proportional risk regression was used to determine the correlation coefficients between each variable and ESRD risk in each model. Harrell’s C-index and net reclassification improvement (NRI) index were used to evaluate the differentiation of the models. Analysis was repeated in subgroups based on albuminuria and hemoglobin A1C (HbA1c) levels.ResultsOverall, 132 of the 18,928 patients developed ESRD after a median follow-up of 12 years. The Harrell’s C-index based on GFR estimated by CKD-EPI, MDRD, and r-LM was 0.914 (95% CI = 0.8812–0.9459), 0.908 (95% CI = 0.8727–0.9423), and 0.917 (95% CI = 0.8837–0.9496), respectively. Subgroup analysis revealed that in diabetic patients with macroalbuminuria, the KFRE model based on GFR estimated by r-LM (KFRE-eGFRr-LM) had better differentiation compared to the KFRE model based on GFR estimated by CKD-EPI (KFRE-eGFRCKD-EPI) with a KFRE-eGFRr-LM C-index of 0.846 (95% CI = 0.797–0.894, p = 0.025), while the KFRE model based on GFR estimated by MDRD (KFRE-eGFRMDRD) showed no significant difference compared to the KFRE-eGFRCKD-EPI (KFRE-eGFRMDRD C-index of 0.837, 95% CI = 0.785–0.889, p = 0.765). Subgroup analysis of poor glycemic control (HbA1c >8.5%) demonstrated the same trend. Compared to KFRE-eGFRCKD-EPI (C-index = 0.925, 95% CI = 0.874–0.976), KFRE-eGFRr-LM had a C-index of 0.935 (95% CI = 0.888–0.982, p = 0.071), and KFRE-eGFRMDRD had a C-index of 0.925 (95% CI = 0.874–0.976, p = 0.498).ConclusionsIn adults with diabetes, the r-LM equation performs better than the CKD-EPI and MDRD equations in the KFRE model for predicting ESRD, especially for those with macroalbuminuria and poor glycemic control (HbA1c >8.5%).

Relationship between Arterial Stiffness and Renal Function Determined by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Equations in a Chinese Cohort Undergoing Health Examination.

Background The association between arterial stiffness and cardiovascular risk in CKD and ESRD patients is well established. However, the relationship between renal function estimation and properties of large arteries is unclear due to the four different methods used to quantify glomerular filtration. This study investigated the relationship between carotid-femoral pulse wave velocity (c-fPWV), as a measure of arterial stiffness, and accepted metrics of renal function. Methods This cross-sectional study was conducted in 431 health examination individuals in China, enrolled from January 2017 to June 2019. c-fPWV and blood pressure were measured, and blood samples were obtained for all participants. Four different methods were used to determine the estimated glomerular filtration rate (eGFR) as described by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations: (i) CKD-EPISCr formula based on SCr, (ii) CKD-EPICysC formula based on CysC, (iii) CKD-EPISCr/CysC formula based on Cr and CysC, and (iv) MDRD. Results Of all of the study participants (average age 53.1 ± 13.0 years, 68.1% male), 23.7% had diabetes mellitus and 66.6% had hypertension. The average eGFR values determined by the CKD-EPISCr, CKD-EPICysC, CKD-EPISCr/CysC, and MDRD equations were 91.9 ± 15.6, 86.8 ± 21.4, 89.6 ± 18.3, and 90.7 ± 16.6 ml/min/1.73m2, respectively. c-fPWV was significantly and negatively correlated with eGFR determined by CKD-EPISCr (r = −0.336, P < 0.001), CKD-EPICysC (r = −0.385, P < 0.001), CKD-EPISCr/CysC (r = −0.378, P < 0.001), and MDRD (r = −0.219, P < .001) equations. After adjusting for confounding factors, c-fPWV remained significantly and negatively correlated with eGFR determined by the CKD-EPICysC equation (β = −0.105, P = 0.042) and significantly and positively correlated with age (β = 0.349, P ≤ 0.01), systolic pressure (β = 0.276, P ≤ 0.01), and hypoglycemic drugs (β = 0.101, P = 0.019). Conclusion In a health examination population in China, c-fPWV is negatively correlated with eGFR determined by four different equations; however, only the metric of eGFR determined by the equation for CKD-EPICysC showed an independent relation with c-fPWV.

Comparison of CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) formula based eGFR (estimated glomerular filtration rate) with C-G (Cockcroft-Gaul) and MDRD (Modification of Diet in Renal Disease) formula based eGFR in adult Bangladeshi population

Glomerular filtration rate (GFR) is the most important and accurate measure of overall kidney functions both in good health and disease because it is the sum of the filtration rates in each of the functioning nephrons .Different GFR measuring methods have some limitations.The objective of this study was to compare the CKD-EPI formula based eGFR with that of Cock- croft- Gault formula &amp; 4 variable MDRD formula based eGFR.This Cross-sectional analytical study was done in the Department of Biochemistry &amp; Molecular biology, BSMMU September during the period of July 2017 to August 2018. Serum creatinine was measured and eGFR by MDRD, CKD-EPI and Cockcroft-Gault formula was calculated using the respective equations on online calculator. Comparison of eGFR values between CKD-EPI &amp; MDRD formula and between CKD-EPI &amp; Cockcroft-Gault formula were done among different groups. Compari- son was done by Bland Altman agreement test to see the agreement on the measurement of GFR between three equation based eGFR method. Pearson‘s correlation test revealed a positive correlation between C-G and CKD-EPI (r = 0.779), but a stronger correlation between MDRD and CKD-EPI (r = 0.934). Bland-Altman plot showed strong agreement between CKD-EPI &amp; 4–variable MDRD than between CKD-EPI &amp; C-G formula. From this study we may conclude CKD-EPI and MDRD formula showed better agreement than between CKD-EPI and Cockcroft-Gault formula. So, this study suggests that CKD-EPI and MDRD equations can be used to estimate GFR more effectively than Cockcroft-Gault equation in Bangladeshi population. BSMMU J 2021; 14(4): 152-156

Paradoxical mortality of high estimated glomerular filtration rate reversed by 24-h urine creatinine excretion rate adjustment: sarcopenia matters.

BackgroundMuscle wasting may explain the paradoxical mortality of patients with high estimated glomerular filtration rates (eGFRs) derived from equation methods. However, empirical evidence and solutions remain insufficient.MethodsIn this retrospective cohort study, we compared the performance of equation methods for predicting all‐cause mortality; we used 24‐h creatinine clearance (24‐h CrCl), equation‐based eGFRs, and a new eGFR estimating equation weighting for population 24‐h urine creatinine excretion rate (U‐CER). From 2003 to 2018, we identified 4986 patients whose data constituted the first 24‐h CrCl measurement data in the Clinical Research Data Repository of China Medical University Hospital and were followed up for at least 5 years after careful exclusion. Three GFR estimation equations [the Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI), Modification of Diet in Renal Disease (MDRD) Study, and Taiwanese MDRD], 24‐h CrCl, and 24‐h U‐CER–adjusted eGFR were used.ResultsA high correlation was observed among the eGFR levels derived from the equation methods (0.995–1.000); however, the correlation decreased to 0.895–0.914 when equation methods were compared with the 24‐h CrCl or 24‐h U‐CER–adjusted equation‐based eGFR. In the Bland–Altman plots, the average discrepancy between the equation methods and the 24‐h CrCl method was close to zero (maximal bias range: 5.12 for the Taiwanese MDRD equation vs. 24‐h CrCl), but the range in limit of agreement was wide, from ±43.7 mL/min/1.73 m2 for the CKD‐EPI equation to ±54.3 mL/min/1.73 m2 for the Taiwanese MDRD equation. A J‐shaped dose–response relationship was observed between all equation‐based eGFRs and all‐cause mortality. Only 24‐h CrCl exhibited a non‐linear negative dose–response relationship with all‐cause mortality. After adjustment for 24‐h U‐CER in the statistical model, the paradoxical increase in mortality risk for an eGFR of >90 mL/min/1.73 m2 returned to null. When 24‐h U‐CER was used directly to correct eGFR, the monotonic non‐linear negative relationship with all‐cause mortality was almost identical to that of 24‐h CrCl.ConclusionsThe 24‐h U‐CER–adjusted eGFR and 24‐h CrCl are viable options for informing mortality risk. The 24‐h U‐CER adjustment method can be practically implemented to eGFR‐based care and effectively mitigate the inherent confounding biases from individual's muscle mass amount due to both sex and racial differences.

Utilizing Longitudinal Within-Individual Changes of Serum Creatinine, Cystatin C, and/or eGFR to Optimize Clinical Sensitivity and Eliminate Race and Gender Corrections.

The recent recommendation by the American Society of Nephrology/National Kidney Foundation task force to immediately eliminate the “race” factor in the estimated glomerular filtration rate (eGFR) equation (1) is a much-needed and long-overdue correction of the original Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFR equations. While the primary and continual goal of the MDRD, CKD-EPI, and other eGFR equations has been to agree with measured GFR (mGFR), we believe this was misguided as shown by the necessity of updating to the CKD-EPI (2021) equation to improve its clinical ability to detect and monitor changes in kidney function for all persons. This new emphasis will enhance the role of the eGFR as a clinical guide for determining chronic kidney disease (CKD) stage and possible referral to nephrology. Because eGFR is calculated from serum creatinine (sCr) and/or cystatin C (sCysC), which are reliable measurements, we propose that these measurements and eGFRs calculated from them are actually more clinically useful, more reliable, and far more used than mGFRs, which have much greater analytical and physiological variation (2–5). Indeed, it was the variability of the mGFR, not the more reliable sCr, that required both the MDRD and CKD-EPI equations to accept wide error tolerances of ±30%, with 81% of the MDRD eGFRs and 84% of CKD-EPI eGFRs within the 30% error tolerance.

Kidney Function According to Different Equations in Patients Admitted to a Cardiology Unit and Impact on Outcome.

Background: This paper aims to evaluate the concordance between the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula and alternative equations and to assess their predictive power for all-cause mortality in unselected patients discharged alive from a cardiology ward. Methods: We retrospectively included patients admitted to our Cardiology Division independently of their diagnosis. The total population was classified according to Kidney Disease: Improving Global Outcomes (KDIGO) categories, as follows: G1 (estimated glomerular filtration rate (eGFR) ≥90 mL/min/1.73 m2); G2 (eGFR 89–60 mL/min/1.73 m2); G3a (eGFR 59–45 mL/min/1.73 m2); G3b (eGFR 44–30 mL/min/1.73 m2); G4 (eGFR 29–15 mL/min/1.73 m2); G5 (eGFR <15 mL/min/1.73 m2). Cockcroft-Gault (CG), CG adjusted for body surface area (CG-BSA), Modification of Diet in Renal Disease (MDRD), Berlin Initiative Study (BIS-1), and Full Age Spectrum (FAS) equations were also assessed. Results: A total of 806 patients were included. Good agreement was found between the CKD-EPI formula and CG-BSA, MDRD, BIS-1, and FAS equations. In subjects younger than 65 years or aged ≥85 years, CKD-EPI and MDRD showed the highest agreement (Cohen’s kappa (K) 0.881 and 0.588, respectively) while CG showed the lowest. After a median follow-up of 407 days, overall mortality was 8.2%. The risk of death was higher in lower eGFR classes (G3b HR4.35; 95%CI 1.05–17.80; G4 HR7.13; 95%CI 1.63–31.23; G5 HR25.91; 95%CI 6.63–101.21). The discriminant capability of death prediction tested with ROC curves showed the best results for BIS-1 and FAS equations. Conclusion: In our cohort, the concordance between CKD-EPI and other equations decreased with age, with the MDRD formula showing the best agreement in both younger and older patients. Overall, mortality rates increased with the renal function decreasing. In patients aged ≥75 years, the best discriminant capability for death prediction was found for BIS-1 and FAS equations.