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We conducted a retrospective study of 1055 patients with urinary stones who attended our single center from September 2017 to June 2024. Clinical data and laboratory indicators of patients were evaluated and compared with stone components. The most common type in our study was calcium oxalate (CaOx) stones (76.6%), followed by infection stones (13.2%) and uric acid (UA) stones (7.8%). Among the 1055 specimens, 899 (85.2%) cases were mixed component stones, of which calcium oxalate monohydrate (COM) and calcium oxalate dihydrate (COD) mixture were the most frequent (34.8%). There were only 156 cases (14.8%) of pure-component stones, of which anhydrous UA was the most frequent (7.0%). There were 738 males and 317 females, with a male-to-female ratio of 2.33:1. Male dominance was evident in CaOx stones (79.0 vs. 71.0%, P = 0.005). Female dominance was noted in infection stones (21.1 vs. 9.8%, P < 0.001). The multivariate analysis showed that higher serum albumin level was a risk factor for CaOx stone formation (OR = 2.959; 95% CI 1.470–5.953, P = 0.002). Women were more likely to develop infection stones than men (OR = 1.796; 95% CI 1.150–2.803, P = 0.010). As the urine pH increased, the risk of infection stones formation increased (OR = 2.521; 95% CI 1.809–3.513, P < 0.001). Moreover, a history of hypertension (OR = 2.339; 95% CI 1.409–3.881, P = 0.001), low urine pH (OR = 0.242; 95% CI 0.147–0.399, P < 0.001), and low serum albumin level (OR = 0.351; 95% CI 0.125–0.988, P = 0.047) were risk factors for the formation of UA stones. [ABSTRACT FROM AUTHOR]

Kidney stones and urolithiasis are kidney diseases that have a significant impact on health and well-being, and their incidence is increasing annually owing to factors such as age, sex, ethnicity, and geographical location. Accurate identification and volume measurement of kidney stones are critical for determining the appropriate surgical approach, as timely and precise treatment is essential to prevent complications and ensure successful outcomes. Larger stones often require more invasive procedures, and precise volume measurements are essential for effective surgical planning and patient outcomes. This study aimed to compare the ability of artificial intelligence (AI) to detect and measure kidney stone volume via CT-KUB images. CT KUB imaging data were analyzed to determine the effectiveness of AI in identifying the volume of kidney stones. The results were compared with measurements taken by radiologists. Compared with radiologists, the AI had greater accuracy, efficiency, and consistency in measuring kidney stone volume. The AI calculates the volume of kidney stones with an average difference of 80% compared with the volumes calculated by radiologists, highlighting a significant discrepancy that is critical for accurate surgical planning. The results suggest that artificial intelligence (AI) outperforms radiologists' manual calculations in measuring kidney stone volume. By integrating AI with kidney stone detection and treatment, there is potential for greater diagnostic precision and treatment effectiveness, which could ultimately improve patient outcomes. [ABSTRACT FROM AUTHOR]

Purpose: Advancements in medical treatments and increased access to healthcare have significantly extended the life expectancy of children with neurological disorders. However, this has also led to a higher incidence of secondary health issues, such as nephrolithiasis. This review aims to analyze the risk factors, management, and treatment outcomes for stone disease in children with neurological disorders and focus on specific risk factors such as immobilization, urinary tract infections, and metabolic abnormalities to identify key points in the occurrence of nephrolithiasis. Methods: A comprehensive literature search was conducted across two primary databases, PubMed and Ovid Medline, to identify studies on urolithiasis in children with neurological disorders. A total of 771 articles were initially identified. After removing four duplicate articles, 729 were excluded following title and abstract screening due to irrelevance. Thirty-eight articles were selected for full-text review, and after further exclusions, 11 articles were included in this review. Results: The studies mainly consisted of small-scale, single-center investigations. Nephrolithiasis were reported in 5–54% of patients across the studies. The most commonly identified risk factors were immobilization, urinary tract infections (UTIs), and hypercalciuria. Treatment options for urinary stones included medical expulsive therapy (MET), extracorporeal shock wave lithotripsy (ESWL), endoscopic surgery (RIRS), and percutaneous nephrolithotomy (PCNL). Conclusion: Key steps in managing these patients include monitoring bone mineral density, conducting a 24-h urine analysis to assess metabolic components (despite challenges in obtaining this), and encouraging physical activity as much as the patient's condition permits. [ABSTRACT FROM AUTHOR]

Background: Urolithiasis is a prevalent urological ailment characterized by increasing prevalence and recurrence rates, resulting in substantial social and economic burden. While men exhibit an incidence rate nearly twice that of women, this gender disparity is gradually diminishing. Nevertheless, the mechanisms underlying this condition remain incompletely elucidated. The identification of the urinary microbiome (urobiome) has provided a fresh perspective on urolithiasis. This study aimed to analyze the urobiome of unilateral stone formers in the renal pelvis and evaluate the variations in microbial diversity and community composition between males and females. Methods: Renal pelvis urine samples were obtained from a cohort of 21 male and 9 female patients and subsequently subjected to taxonomic and functional analysis using 2bRAD sequencing for Microbiome (2bRAD-M). The collected samples were categorized into four distinct groups, namely the stone side of males (SM), stone side of females (SF), non-stone side of males (NSM), and non-stone side of females (NSF). Results: Through the application of beta diversity analysis, dissimilarity was observed between NSM and NSF. Additionally, NSF exhibited a higher abundance of microbial populations, and a total of 29 distinct species were identified as differentially present between NSM and NSF using LEfSe. Lactobacillus iners, Atopobium deltae, Lawsonella clevelandensis, and Meyerozyma guilliermondii exhibited enrichment in the SF group compared to the SM group. Furthermore, we identified distinct species that differed between the SM and NSM groups, as well as the SF and NSF groups. Besides, we conducted COG annotation and KEGG pathway predictions, revealing significant differences in urobiome function across the different groups. Conclusion: Variations in microbial community composition and predicted functions were observed among the various groups. Future research could potentially leverage the urobiome to personalize urolithiasis treatment based on individual microbial characteristics, taking into account gender-specific differences. [ABSTRACT FROM AUTHOR]