Role of urinary biomarkers for diagnosis and prognosis of kidney stone disease

Critical assessment of the reported bidirectional associations between gallstone, non-alcoholic fatty liver, and kidney stone diseases

The recent article by Jiang et al published in World Journal of Gastroenterology reports substantial bidirectional associations between gallstone disease (GSD), non-alcoholic fatty liver disease (NAFLD), and kidney stone disease (KSD), based on multicenter cross-sectional studies and a systematic review with meta-analysis. While the findings have the potential to significantly impact clinical and preventive strategies, several methodological issues merit closer examination. This letter critiques key aspects of the study, including sample population heterogeneity, potential confounding variables, and the reliance on cross-sectional data that may limit causal inferences. We also discuss the generalizability of these results to broader populations given the study's focus on the Chinese demographic. By addressing these concerns, we suggest a more nuanced interpretation of the associations between GSD, NAFLD, and KSD, advocating for longitudinal studies to validate these findings and enhance their applicability in global health contexts.

Automatic kidney stone identification: an adaptive feature-weighted LSTM model based on urine and blood routine analysis

Kidney stones are the most common urinary system diseases, and early identification is of great significance. The purpose of this study was to use routine urine and blood detection indices to build a deep learning (DL) model to identify the presence of kidney stones in the early stage. A retrospective analysis was conducted on patients with kidney stones who were treated at West China Hospital of Sichuan University from January 2020 to June 2023. A total of 1130 individuals presenting with kidney stones and 1230 healthy subjects were enrolled. The first blood and urine laboratory data of participants at our hospital were collected, and the data were divided into a training dataset (80%) and a verification dataset (20%). Additionally, a long short-term memory (LSTM)-based adaptive feature weighting model was trained for the early identification of kidney stones, and the results were compared with those of other models. The performance of the model was evaluated by the area under the subject working characteristic curve (AUC). The important predictive factors are determined by ranking the characteristic importance of the predictive factors. A total of 17 variables were screened; among the top 4 characteristics according to the weight coefficient in this model, urine WBC, urine occult blood, qualitative urinary protein, and microcyte percentage had high predictive value for kidney stones in patients. The accuracy of the kidney stone (KS-LSTM) learning model was 89.5%, and the AUC was 0.95. Compared with other models, it has better performance. The results show that the KS-LSTM model based on routine urine and blood tests can accurately identify the presence of kidney stones. And provide valuable assistance for clinicians to identify kidney stones in the early stage.

The association between C-reactive protein levels and the risk of kidney stones: a population-based study

OBJECTIVES

The relationship between C-reactive protein (CRP) and the risk of developing kidney stones is unclear, and we aimed to assess the association between CRP and kidney stones in US adults.

METHODS

We used data from NHANES 2007-2010, and we excluded participants who were under 18 years of age and lacked data on CRP and kidney stones. Finally, we included a total of 11,033 participants and performed weighted multivariate regression analysis and subgroup analysis to assess the independent relationship between CRP and kidney stones.

RESULTS

The mean prevalence of kidney stones among the participants was 9.8%. Notably, as CRP levels increased, the prevalence of kidney stones exhibited a corresponding rise across quartiles (Kidney stones: Quartile 1: 7.59%; Quartile 2: 8.77%; Quartile 3: 9.64%; Quartile 4: 10.89%). CRP was positively associated with the risk of kidney stones (Model 1: OR = 1.09, 95% CI: 1.01-1.18, p = 0.03; Model 2: OR = 1.09, 95% CI: 1.00-1.18, p = 0.03, Model 3: OR = 1.14, 95%CI: 1.02-1.26, p = 0.04). Participants in the highest CRP quartile experienced a 69% increased risk of kidney stones compared to those in the lowest quartile (OR = 1.64, 95% CI: 1.04-2.59, p = 0.03). Notably, interaction tests revealed that gender, BMI, diabetes, hypertension, CKD and smoking or alcohol consumption status did not significantly influence the association between CRP and kidney stones.

CONCLUSIONS

Our findings reveal a significant association between higher CRP levels and an increased risk of kidney stones. In clinical practice, heightened awareness of CRP as a potential biomarker could aid in risk assessment and management strategies for kidney stone patients.

Urinary neutrophil gelatinase-associated lipocalin level as a biomarker of acute kidney injury following extracorporeal shock wave lithotripsy

Introduction

Although extracorporeal shock wave lithotripsy (ESWL) is minimally invasive and highly efficient for the management of kidney stones, adverse effects have been described. Available indicators of renal function exhibit insufficient sensitivity in acute renal injury (AKI). We aimed to evaluate the severity of the kidney tissue response to ESWL injury by measuring the urinary neutrophil gelatinase-associated lipocalin (uNGAL), which can indicate AKI in its early phase.

Material and methods

The prospective, controlled study included 62 patients with nephrolithiasis undergoing single ESWL treatment. uNGAL level was measured before the procedure, and 6 h and 12 h after.

Results

The median uNGAL level increased by 126.0%, 6 h after ESWL (p <0.001). The growth rate continued and 12 h after was higher by 583.7%, compared to the pre-treatment level (p <0.001). The median value of estimated glomerular filtration rate (eGFR) dropped by 15.3% 12 h after the treatment (p <0.001). It increased by 5.0% in the period 7 days to 3 months after (p <0.001) and after 3 months it was lower by 10.1% compared to pre-ESWL values (p <0.001). uNGAL level after 12 h was significantly negatively associated with eGFR, 12 h, 7 days and 3 months after the ESWL. The sensitivity of uNGAL 12 h after ESWL was 60.6%; its specificity was 75.0%, with a positive predictive value of 74.0% and negative predictive value of 61.7%.

Conclusions

uNGAL appears to be a useful biomarker for the assessment and prediction of AKI. It was noticed that uNGAL had the highest predictive value 12 h after the ESWL treatment.

Minimally Invasive Surgery for the Treatment of Ureteric Stones - State-of-the-Art Review

The landscape of managing ureteric stones has evolved over the last few decades and several treatment options exist depending on the stone size, location, and other patient and stone factors. While open surgery is now rarely performed, the use of medical expulsive therapy (MET) has been controversial and perhaps only recommended for large distal ureteric stones. The mainstay treatment balances between shockwave lithotripsy (SWL) and ureteroscopy (URS), with the latter usually recommended for larger stones. While the principles of ureteric stone management have remained largely unchanged, the modern era has generated new methods and means to deliver it. Advancements have occurred in all domains of endourology to try and refine treatment and balance it with cost, patient choice and quality of life. Dissemination of technologies and demonstration of their efficacy and safety will eventually result in new recommendations among international guidelines and evolution of new gold standards.