Does severity of renal scarring on DMSA scan predict abnormalities in creatinine clearance?
ABSTRACT To examine the relationship between severity of renal scarring and creatinine clearance. Existing studies on renal scarring and functional outcomes have focused on the presence or absence of scarring.
Patients with a history of urinary tract infection leading to the diagnosis of vesicoureteral reflux were recruited. These subjects were admitted to a pediatric research center for an in-patient collection of 24-hour urine to be sent for creatinine and protein. DMSA scans performed at least 6 months after documented urinary tract infection were graded by 3 independent, blinded pediatric urologists for renal scarring according to the Randomized Intervention for Children with Vesicoureteral Reflux study criteria.
Twenty-nine subjects (14 girls, 15 boys) with a median age of 7 years were recruited. Scar grading was reliable between the observers with a Kappa score of 0.66-0.75. On DMSA scan, 10% were scar-free, 62% had unilateral scars, and 28% had bilateral scars. Mean creatinine clearance was 123 for those with unilateral disease and 100 for those with bilateral disease (P = .048). Median proteinuria (58 mg/dL) and serum creatinine (0.5 mg/dL) were similar between the 2 groups. Creatinine clearance did not differ according to average scar grade, taking both kidneys into account.
In children with vesicoureteral reflux, although those with bilateral scarring have a significantly lower creatinine clearance than those with unilateral scarring, the severity of scar grade alone does not predict overall creatinine clearance with short-term follow-up.
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ABSTRACT: Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer-generated random numbers, uniformly distributed on (0, 1), can be very different depending on the selection of pseudo-random number (PRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the resulting error variances can even be of different orders of magnitude. Furthermore, practical techniques for variance reduction such as importance sampling and stratified sampling can be applied in most Monte Carlo simulations and significantly improve the results. A comparative analysis of these strategies has been carried out for computational applications in planar and spatial contexts. Based on these experiments, and on some practical examples of geodetic direct and inverse problems, conclusions and recommendations concerning their performance and general applicability are included.Computers & Geosciences 01/2011; 37:928-934. · 1.83 Impact Factor