Search

IntroductionTo use Google Insights search volume and publicly available economic indicators to test the hypothesis that sperm, egg, and blood donations increase during economic downturns and to demonstrate the feasibility of using Google search volume data to predict national trends in actual sperm, egg, and blood donations rates.Materials and methodsCross-correlation statistical analysis comparing Google search data for terms relating to blood, egg, and sperm donations with various economic indicators including the S&P 500 closing values, gross domestic product (GDP), the U.S. Index of Leading Indicators (U.S. Leading Index), gross savings rate, mortgage interest rates, unemployment rate, and consumer price index (CPI) from 2004-2011. A secondary analysis determined the Pearson correlation coefficient between Google search data with actual sperm, egg, and blood donation volume in the U.S. as measured by California Cryobank, the National Assisted Reproductive Technology Surveillance System, and the National Blood Collection and Utilization Survey, respectively. Significance of cross-correlation and Pearson correlation analysis as indicated by p value.ResultsThere were several highly significant cross-correlation relationships between search volume and various economic indicators. Correlation between Google search volume for the term 'sperm donation,' 'egg donation,' and 'blood donation' with actual number of sperm, egg and blood donations in the United States demonstrated Pearson correlation coefficients of 0.2 (p > 0.10), -0.1 (p > 0.10), and 0.07 (p > 0.10), respectively. Temporal analysis showed an improved correlation coefficient of 0.9 (p < 0.05) for blood donation when shifted 12 months later relative to Google search volume.ConclusionGoogle search volume data for search terms relating to sperm, egg, and blood donation increase during economic downturns. This finding suggests gamete and bodily fluid donations are influenced by market forces like other commodities. Google search may be useful for predicting blood donation trends but is more limited in predicting actual semen and oocyte donation patterns.

Introduction: To identify factors associated with the development of chronic kidney disease (CKD) after nephrectomy and to create a clinical model to predict CKD after nephrectomy for kidney cancer for clinical use., Materials and Methods: We identified 144 patients who had normal renal function (eGFR > 60) prior to undergoing nephrectomy for kidney cancer. Selected cases occurred between 2007 and 2010 and had at least 30 days follow up. Sixty-six percent (n = 95) underwent radical nephrectomy and 62.5% (n = 90) developed CKD (stage 3 or higher) postoperatively. We used univariable analysis to screen for predictors of CKD and multivariable logistic regression to identify independent predictors of CKD and their corresponding odds ratios. Interaction terms were introduced to test for effect modification. To protect against over-fitting, we used 10-fold cross-validation technique to evaluate model performance in multiple training and testing datasets. Validation against an independent external cohort was also performed., Results: Of the variables associated with CKD in univariable analysis, the only independent predictors in multivariable logistic regression were patient age (OR = 1.27 per 5 years, 95% CI: 1.07-1.51), preoperative glomerular filtration rate (GFR), (OR = 0.70 per 10 mL/min, 95% CI: 0.56-0.89), and receipt of radical nephrectomy (OR = 4.78, 95% CI: 2.08-10.99). There were no significant interaction terms. The resulting model had an area under the curve (AUC) of 0.798. A 10-fold cross-validation slightly attenuated the AUC to 0.774 and external validation yielded an AUC of 0.930, confirming excellent model discrimination., Conclusions: Patient age, preoperative GFR, and receipt of a radical nephrectomy independently predicted the development of CKD in patients undergoing nephrectomy for kidney cancer in a validated predictive model.

Although Wilms tumor is the most common primary renal malignancy in children, it is exceedingly rare in adults and has an estimated incidence of less than 0.2 cases per million. Little is known about the biology of this tumor in adults and clinicians have had to rely on pediatric treatment protocols. Overall, prognosis is worse in adults, though like in children, unfavorable histology and higher stage at presentation confer a worse prognosis.

The prevalence of urolithiasis has been increasing for the past few decades in industrialized nations. Uric acid calculi account for a significant percentage of urinary stones. Certain risk factors may be involved in the pathogenesis of uric acid nephrolithiasis, including hyperuricosuria, low urinary volume, and persistently low urinary pH. Patients with medical conditions that promote profound hyperuricosuria are at high risk of developing uric acid calculi. These conditions include chronic diarrheal states; myeloproliferative disorders; insulin resistance, including diabetes mellitus; and monogenic metabolic disorders, such as Lesch-Nyhan syndrome. Computed tomography can provide a definitive diagnosis. Except in cases in which there is severe obstruction, progressive azotemia, serious infection, or unremitting pain, the initial treatment of patients with uric acid nephrolithiasis should be medical dissolution therapy because this approach is successful in the majority of cases. A thorough review of the epidemiology and pathophysiology of uric acid nephrolithiasis is crucial for the diagnosis, treatment, and prevention of stones in patients with this condition.