Dataset Information

Rounding of low serum creatinine levels and consequent impact on accuracy of bedside estimates of renal function in cancer patients.

ABSTRACT: To compare glomerular filtration rate measured by technetium-99m ([Tc(99m)]) DTPA clearance with estimated creatinine clearance (CrCl) (Cockcroft and Gault (C&G) method) in patients with serum creatinine (Scr) levels <0.06 mmol l(-1), and determine the effect of rounding serum creatinine to 0.06 mmol l(-1). Patients with serum creatinine values <0.06 mmol l(-1) at the time of [Tc(99m)] clearance determination were identified. Creatinine clearance was calculated by the C&G method using both actual and rounded Scr values. A total of 419 adults had GFR measured by technetium-99m diethyl triamine penta-acetic acid ([Tc(99m)] DTPA) clearance. Out of this group, 26 patients had a serum creatinine value <0.06 mmol l(-1). The C&G estimates of renal function using actual serum creatinine resulted in an overall overestimation of 12.9% when compared to [Tc(99m)] DTPA clearance. When the value of serum creatinine was rounded to 0.06 mmol l(-1), the formula underestimated renal function by -7.0%. Analysis of estimated creatinine clearance for different levels of renal function showed significant differences to [Tc(99m)] DTPA clearance. Rounding up of serum creatinine to 0.06 mmol l(-1) improved the predictive ability of the C&G method for the patients with [Tc(99m)] DTPA clearance 100 ml min(-1). This work indicates that when bedside estimates of renal function are calculated using the C&G formula actual Scr should be used first to estimate CrCl. If the resultant CrCl is

SUBMITTER: Dooley MJ

PROVIDER: S-EPMC2409618 | biostudies-other | 2004 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Current practice in anticoagulation dosing relies on kidney function estimated by serum creatinine using the Cockcroft-Gault equation. However, creatinine can be unreliable in patients with low or high muscle mass. Cystatin C provides an alternative estimation of glomerular filtration rate (eGFR) that is independent of muscle. OBJECTIVE:We compared cystatin C-based eGFR (eGFRcys) with multiple creatinine-based estimates of kidney function in hospitalized patients receiving anticoagulants, to assess for discordant results that could impact medication dosing. DESIGN:Retrospective chart review of hospitalized patients over 1 year who received non-vitamin K antagonist anticoagulation, and who had same-day measurements of cystatin C and creatinine. PARTICIPANTS:Seventy-five inpatient veterans (median age 68) at the San Francisco VA Medical Center (SFVAMC). MAIN MEASURES:We compared the median difference between eGFR by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) study equation using cystatin C (eGFRcys) and eGFRs using three creatinine-based equations: CKD-EPI (eGFREPI), Modified Diet in Renal Disease (eGFRMDRD), and Cockcroft-Gault (eGFRCG). We categorized patients into standard KDIGO kidney stages and into drug-dosing categories based on each creatinine equation and calculated proportions of patients reclassified across these categories based on cystatin C. KEY RESULTS:Cystatin C predicted overall lower eGFR compared to creatinine-based equations, with a median difference of - 7.1 (IQR - 17.2, 2.6) mL/min/1.73 m2 versus eGFREPI, - 21.2 (IQR - 43.7, - 8.1) mL/min/1.73 m2 versus eGFRMDRD, and - 25.9 (IQR - 46.8, - 8.7) mL/min/1.73 m2 versus eGFRCG. Thirty-one to 52% of patients were reclassified into lower drug-dosing categories using cystatin C compared to creatinine-based estimates. CONCLUSIONS:We found substantial discordance in eGFR comparing cystatin C with creatinine in this group of anticoagulated inpatients. Our sample size was limited and included few women. Further investigation is needed to confirm these findings and evaluate implications for bleeding and other clinical outcomes. NIH TRIAL REGISTRY NUMBER:Not applicable.

Project description:BackgroundSeveral predictive factors for chronic kidney disease (CKD) following radical nephrectomy (RN) or partial nephrectomy (PN) have been identified. However, early postoperative laboratory values were infrequently considered as potential predictors. Therefore, this study aimed to develop predictive models for CKD 1 year after RN or PN using early postoperative laboratory values, including serum creatinine (SCr) levels, in addition to preoperative and intraoperative factors. Moreover, the optimal SCr sampling time point for the best prediction of CKD was determined.MethodsData were retrospectively collected from patients with renal cell cancer who underwent laparoscopic or robotic RN (n = 557) or PN (n = 999). Preoperative, intraoperative, and postoperative factors, including laboratory values, were incorporated during model development. We developed 8 final models using information collected at different time points (preoperative, postoperative day [POD] 0 to 5, and postoperative 1 month). Lastly, we combined all possible subsets of the developed models to generate 120 meta-models. Furthermore, we built a web application to facilitate the implementation of the model.ResultsThe magnitude of postoperative elevation of SCr and history of CKD were the most important predictors for CKD at 1 year, followed by RN (compared to PN) and older age. Among the final models, the model using features of POD 4 showed the best performance for correctly predicting the stages of CKD at 1 year compared to other models (accuracy: 79% of POD 4 model versus 75% of POD 0 model, 76% of POD 1 model, 77% of POD 2 model, 78% of POD 3 model, 76% of POD 5 model, and 73% in postoperative 1 month model). Therefore, POD 4 may be the optimal sampling time point for postoperative SCr. A web application is hosted at https://dongy.shinyapps.io/aki_ckd .ConclusionsOur predictive model, which incorporated postoperative laboratory values, especially SCr levels, in addition to preoperative and intraoperative factors, effectively predicted the occurrence of CKD 1 year after RN or PN and may be helpful for comprehensive management planning.

Dataset Information

Rounding of low serum creatinine levels and consequent impact on accuracy of bedside estimates of renal function in cancer patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets