Mediators of the Effects of Gender on Uric Acid Nephrolithiasis: A Novel Application of Structural Equation Modeling

Machine learning models for screening clinically significant nephrolithiasis in overweight and obese populations

PURPOSES

Our aim is to build and evaluate models to screen for clinically significant nephrolithiasis in overweight and obesity populations using machine learning (ML) methodologies and simple health checkup clinical and urine parameters easily obtained in clinics.

METHODS

We developed ML models to screen for clinically significant nephrolithiasis (kidney stone > 2 mm) in overweight and obese populations (body mass index, BMI ≥ 25 kg/m2) using gender, age, BMI, gout, diabetes mellitus, estimated glomerular filtration rate, bacteriuria, urine pH, urine red blood cell counts, and urine specific gravity. The data were collected from hospitals in Kaohsiung, Taiwan between 2012 and 2021.

RESULTS

Of the 2928 subjects we enrolled, 1148 (39.21%) had clinically significant nephrolithiasis and 1780 (60.79%) did not. The testing dataset consisted of data collected from 574 subjects, 235 (40.94%) with clinically significant nephrolithiasis and 339 (59.06%) without. One model had a testing area under curve of 0.965 (95% CI, 0.9506-0.9794), a sensitivity of 0.860 (95% CI, 0.8152-0.9040), a specificity of 0.947 (95% CI, 0.9230-0.9708), a positive predictive value of 0.918 (95% CI, 0.8820-0.9544), and negative predictive value of 0.907 (95% CI, 0.8756-0.9371).

CONCLUSION

This ML-based model was found able to effectively distinguish the overweight and obese subjects with clinically significant nephrolithiasis from those without. We believe that such a model can serve as an easily accessible and reliable screening tool for nephrolithiasis in overweight and obesity populations and make possible early intervention such as lifestyle modifications and medication for prevention stone complications.

Urinary Risk Profile, Impact of Diet, and Risk of Calcium Oxalate Urolithiasis in Idiopathic Uric Acid Stone Disease

The role of diet in the pathogenesis of uric acid (UA) nephrolithiasis is incompletely understood. This study investigated the effect of dietary intervention on the risk of UA stone formation under standardized conditions. Twenty patients with idiopathic UA stone disease were included in the study. Dietary intake and 24 h urinary parameters were collected on the usual diet of the patients and a standardized balanced mixed diet. Although urinary UA excretion did not change, the relative supersaturation of UA decreased significantly by 47% under the balanced diet primarily due to the significant increase in urine volume and pH. Urinary pH was below 5.8 in 85% of patients under the usual diet, and in 60% of patients under the balanced diet. The supersaturation of calcium oxalate declined significantly under the balanced diet due to the significant decrease in urinary calcium and oxalate excretion and the increase in urine volume. Dietary intervention is a key component in the management of UA nephrolithiasis. Urinary calcium and oxalate excretion should also be monitored in patients with pure UA calculi to reduce the risk of mixed stone formation with calcium oxalate. Lower urinary pH in UA stone patients can only be partially explained by diet.

Structural modeling for Oxford histological classifications of immunoglobulin A nephropathy

In immunoglobulin A nephropathy (IgAN), Cox regression analysis can select independent prognostic variables for renal functional decline (RFD). However, the correlation of the selected histological variables with clinical and/or treatment variables is unknown, thereby making histology-based treatment decisions unreliable. We prospectively followed 946 Japanese patients with IgAN for a median of 66 mo. and applied structural equation modeling (SEM) to identify direct and indirect effects of histological variables on RFD as a regression line of estimated glomerular filtration rate (eGFR) via clinical variables including amount of proteinuria, eGFR, mean arterial pressure (MAP) at biopsy, and treatment variables such as steroid therapy with/without tonsillectomy (ST) and renin–angiotensin system blocker (RASB). Multi-layered correlations between the variables and RFD were identified by multivariate linear regression analysis and the model’s goodness of fit was confirmed. Only tubular atrophy/interstitial fibrosis (T) had an accelerative direct effect on RFD, while endocapillary hypercellularity and active crescent (C) had an attenuating indirect effect via ST. Segmental sclerosis (S) had an attenuating indirect effect via eGFR and mesangial hypercellularity (M) had accelerative indirect effect for RFD via proteinuria. Moreover, M and C had accelerative indirect effect via proteinuria, which can be controlled by ST. However, both T and S had additional indirect accelerative effects via eGFR or MAP at biopsy, which cannot be controlled by ST. SEM identified a systemic path links between histological variables and RFD via dependent clinical and/or treatment variables. These findings lead to clinically applicable novel methodologies that can contribute to predict treatment outcomes using the Oxford classifications.

Prediction of the Uric Acid Component in Nephrolithiasis Using Simple Clinical Information about Metabolic Disorder and Obesity: A Machine Learning-Based Model

There is a great need for a diagnostic tool using simple clinical information collected from patients to diagnose uric acid (UA) stones in nephrolithiasis. We built a predictive model making use of machine learning (ML) methodologies entering simple parameters easily obtained at the initial clinical visit. Socio-demographic, health, and clinical data from two cohorts (A and B), both diagnosed with nephrolithiasis, one between 2012 and 2016 and the other between June and December 2020, were collected before nephrolithiasis treatment. A ML-based model for predicting UA stones in nephrolithiasis was developed using eight simple parameters-sex, age, gout, diabetes mellitus, body mass index, estimated glomerular filtration rate, bacteriuria, and urine pH. Data from Cohort A were used for model training and validation (ratio 3:2), while data from Cohort B were used only for validation. One hundred and forty-six (13.3%) out of 1098 patients in Cohort A and 3 (4.23%) out of 71 patients in Cohort B had pure UA stones. For Cohort A, our model achieved a validation AUC (area under ROC curve) of 0.842, with 0.8475 sensitivity and 0.748 specificity. For Cohort B, our model achieved 0.936 AUC, with 1.0 sensitivity, and 0.912 specificity. This ML-based model provides a convenient and reliable method for diagnosing urolithiasis. Using only eight readily available clinical parameters, including information about metabolic disorder and obesity, it distinguished pure uric acid stones from other stones before treatment.

Sex Differences in Renal Function: Participation of Gonadal Hormones and Prolactin

Kidney pathophysiology is influenced by gender. Evidence suggests that kidney damage is more severe in males than in females and that sexual hormones contribute to this. Elevated prolactin concentration is common in renal impairment patients and is associated with an unfavorable prognosis. However, PRL is involved in the osmoregulatory process and promotes endothelial proliferation, dilatation, and permeability in blood vessels. Several proteinases cleavage its structure, forming vasoinhibins. These fragments have antagonistic PRL effects on endothelium and might be associated with renal endothelial dysfunction, but its role in the kidneys has not been enough investigated. Therefore, the purpose of this review is to describe the influence of sexual dimorphism and gonadal hormones on kidney damage, emphasizing the role of the hormone prolactin and its cleavage products, the vasoinhibins.

Large database study of urinary stone composition in South Korea: Korean Society of Endourology and Robotics (KSER) research series

Purpose

To evaluate the characteristics of urinary stone composition in a Korean population using a large database of stone composition.

Materials and Methods

From January 1, 2014, to June 30, 2019, a total of 33,078 urinary stone composition data were analyzed. Stone composition was classified into four main groups: calcium oxalate (CaOx), struvite, uric acid (UA), and calcium phosphate (CaP). We examined the relationship between stone composition and sex, age, geographic region, calendar month, and season.

Results

The CaOx group (46.41%) was the largest, followed by the struvite group (29.66%), UA group (19.61%), and CaP group (4.32%). The CaOx group tended to decrease with age, but the UA group increased with age. Also, the CaOx group had the highest percentage in summer and the lowest in spring (p<0.001). The struvite and CaP groups had higher percentages of females than males (struvite: 36.6% vs. 25.7%, p<0.001; CaP: 6.2% vs. 3.3%, p<0.001). Conversely, the UA stones were more common in males than in females (24.5% vs. 11.0%, p<0.001). The UA group had the lowest percentage in the capital region (p<0.001). The total male-to-female ratio decreased over time from 1.95:1 in 2014 to 1.67:1 in 2018 (p<0.001).

Conclusions

There were differences for each stone composition in the percentages according to sex, age, geographic region, month, and season. Identifying these differences based on the stone composition is vital for the treatment and prevention of urinary stones.

Gender and side distribution of urinary calculi using ultrasound imaging

Introduction:

Urinary calculi constitute a significant medical problem worldwide. Due to lack of previous studies on gender and side distribution of urinary calculi, the current study was conducted.

Patients and Methods:

This retrospective study involved 590 urinary calculi from the electronic reports of 266 patients. Gender and side distribution were compared using Chi-square test. Relationship between gender and side of urinary calculi was analyzed using cross tabulation test.

Results:

This study involved 590 urinary calculi reported in 266 patients. Among 590 calculi; 565 (95.8%) were in adults, and 25 (4.2%) were in children. Urinary calculi were in male in 397 (67.3%) and in female in 193 (32.7%). Calculi were 304 (51.5%) in right side, and 286 (48.5%) in left side. Exactly 507 (85.9%) of calculi were in the kidneys, and 83 (14.1%) in the ureters. No significant relationship between gender and side of the calculi (P = 0.238), (Odds ratio 0.869, 95% Confidence interval 0.615-1.226).

Conclusion:

Urinary calculi affect male more than female and adults more than children. No significant relationship between calculi and right or left side of the body.

Uric acid stone disease: lessons from recent human physiologic studies

PURPOSE OF REVIEW

An overly acidic urine resulting in supersaturation of urine with respect to uric acid is the major mechanism responsible for uric acid nephrolithiasis. The present review summarizes findings from recent human physiologic studies examining the pathophysiology and reversibility of low urine pH in uric acid stone formers.

RECENT FINDINGS

Epidemiologic and metabolic studies have confirmed an increase in the prevalence of uric acid nephrolithiasis and reported its association with several features of the metabolic syndrome including dyslipidemia, hyperglycemia, hepatic steatosis, and greater visceral adiposity. Physiologic studies in uric acid stone formers have identified diet-independent excessive net acid excretion and concomitant reduction in urinary buffering from impaired renal ammoniagenesis as the two causes underlying the greater aciduria. Administration of the insulin sensitizer pioglitazone to uric acid stone formers reduced the acid load presented to the kidney and enhanced ammoniagenesis and ammonium excretion, resulting in significantly higher urine pH.

SUMMARY

Recent human physiologic studies have identified greater acid excretion and reduced urinary buffering by ammonia as two culprits of aciduria in uric acid nephrolithiasis that can be reversed by pioglitazone, raising new questions regarding the origin of the aciduria and opening the door to pathophysiology-based treatment of uric acid stones.

Pink Urine Syndrome: A Combination of Insulin Resistance and Propofol

Pink urine syndrome is mostly seen in patients treated with propofol anesthesia. The pink color is attributed to the presence of large concentrations of uric acid (and pigment), which is excreted in large amounts when propofol is given. We describe a case of propofol-induced pink urine syndrome and perform a comprehensive, evidence-based review. We discuss prior case studies already published in the literature as we speculate on the pathophysiology and how it translates to a clinically relevant entity.