Objective: A worldwide increased incidence of urolithiasis has been observed over the past few decades. Insight into the composition of these stones can lead to enhanced medical treatment and outcomes. The objective of this study was to examine the distribution and chemical composition of urinary calculi in Southern Thailand over the past decade. Materials and Methods: An analysis was conducted on 2611 urinary calculi submitted to the Stone Analysis Laboratory, Songklanagarind Hospital, a single stone analysis laboratory in Southern Thailand. The analysis was performed from 2007 to 2020 using Fourier-transform infrared spectroscopy. The demographic results were described using descriptive statistical analyses, and the Chi-square test for trends was performed to identify changes in urinary calculi composition. Results: The patients’ demographic data revealed a male-to-female ratio of 2.2:1; the most common age group of affected men was 50–69 years, whereas the most common age group of affected women was 40–59 years. The most common components found in the calculi were uric acid (30.6%), mixed calcium oxalate with calcium phosphate (29.2%), and calcium oxalate (26.7%). We noted a trend of increasing uric acid calculi for 14 years (P = 0.00493), whereas the trend for the other major components was decreasing. Conclusion: The most common component of urinary calculi analyzed in Southern Thailand was uric acid, with a significant rising trend in proportion in the past decade; the trend of other major components, such as mixed calcium oxalate-calcium phosphate and calcium oxalate, decreased.
ObjectivesThe aims of the study are to analyze the potential risk factors associated with systemic inflammatory response syndrome after percutaneous nephrolithotomy for renal stones and to establish a predictive model to prevent postoperative early urosepsis postoperative with percutaneous nephrolithotomy and develop a novel nomogram.MethodsPatients who had undergone percutaneous nephrolithotomy between June 2012 and December 2019 were enrolled and classified into two groups according to their systemic inflammatory response status. Univariable and multivariable logistic regression analyses were performed to identify the predictive factors associated with systemic inflammatory response syndrome after percutaneous nephrolithotomy. The nomograms were developed by using the significant factors, and the discriminative ability was assessed using receiver operating characteristic curve analyses.ResultsTwo hundred sixty two patients with renal stones treated with percutaneous nephrolithotomy were enrolled, and systemic inflammatory response syndrome occurred in 117 patients (44%) after percutaneous nephrolithotomy. Multivariable logistic regression analysis revealed that the three factors independently related to systemic inflammatory response syndrome: renal stone size ≥3 cm, positive preoperative urine white blood cells, and positive preoperative urine culture. According to the results, the logistic regression analyses of significant factors were used to develop the nomogram. Developed nomogram prediction model displayed favorable fitting in the Hosmer-Lemeshow test (P = 0.938). Internal validation of the nomogram showed that the area under the receiver operating characteristic curve was 0.702.ConclusionsPositive preoperative urine white blood cells, positive urine culture, and renal stone size ≥3 cm are the most significant predictors. The novel nomogram helps identify high-risk individuals and facilitates the early detection of systemic inflammatory response syndrome after percutaneous nephrolithotomy.
Objective: To investigate the factors associated with systemic inflammatory response syndrome (SIRS) after percutaneous nephrolithotomy (PCNL) for upper urinary tract stones and establish a predictive model to prevent postoperative SIRS that correlates with PCNL. Methods: Patients who had undergone PCNL between June 2012 and December 2019 were retrospectively enrolled and categorized into groups according to their urosepsis status. Univariable and multivariate logistic regression analyses were performed to determine the predictive factors associated with SIRS after PCNL. Nomograms were generated using the predictors, and the discriminative ability was assessed using receiver operating characteristic (ROC) curve analyses. Results: A total of 262 PCNL patients were enrolled in this study, and SIRS occurred in 117 (44%) patients after PCNL. Multivariable logistic regression analysis suggested that there were three factors related to postoperative SIRS, namely stone size ≥ 3 cm (odds ratio [OR], 3.61; 95% confidence interval [CI], 2.08–6.26; p = 0.001), positive preoperative urine white blood cells (WBC) (OR, 3.1; 95% CI, 1.65–5.81; p = 0.028), and positive urine culture (OR, 2.89, 95% CI, 1.63–5.13; p = 0.017). According to the results of the logistic regression analysis, stone size ≥ 3 cm, positive preoperative urine WBC, and positive urine culture were used to develop the nomogram. A nomogram prediction model was established to calculate the cumulative probability of urosepsis after PCNL and displayed favorable fitting in the Hosmer–Lemeshow test (p=0.938). Internal validation of the nomogram showed that the area under the ROC curve was 0.702. Conclusion: Positive preoperative urine WBC, positive urine culture, and stone size ≥ 3 cm are the most significant predictors of SIRS after PCNL. The nomogram, which is based on independent risk factors, helps identify high-risk individuals and facilitates the early detection of SIRS after PCNL.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.