Urolithiasis is a common disorder of the urinary tract characterized by the formation of calculi within the kidneys, ureters, or urinary bladder. Its prevalence varies across geographical regions because of differences in climate, dietary practices, genetic susceptibility, occupation, socioeconomic conditions, and access to healthcare. The incidence of stone disease has increased worldwide, creating a substantial burden through recurrent pain, urinary obstruction, infection, renal impairment, hospitalization, and repeated surgical intervention [1]. Although imaging accurately establishes stone size, number, location, laterality, and associated obstruction, it does not identify the biochemical disturbances responsible for stone formation. Evaluation of metabolic risk factors is therefore important for understanding the underlying pathophysiology and planning individualized preventive measures. Urinary supersaturation resulting from reduced urine volume or excessive excretion of calcium, oxalate, uric acid, cystine, and other lithogenic substances contributes to crystal formation and stone growth. Conversely, reduced concentrations of inhibitors such as citrate and magnesium facilitate crystal aggregation. Hypercalciuria, hyperoxaluria, hyperuricosuria, hypocitraturia, persistently acidic or alkaline urine, and low urinary volume are among the commonly detected abnormalities in stone-forming patients [2]. Systemic disorders such as diabetes mellitus, obesity, metabolic syndrome, gout, distal renal tubular acidosis, gastrointestinal malabsorption, and primary hyperparathyroidism may further modify urine composition and increase the risk of urolithiasis [3]. Stone burden and anatomical distribution have important clinical implications. Larger stones are less likely to pass spontaneously and are more frequently associated with obstruction, hydronephrosis, infection, and the need for intervention. Renal and ureteric stones may also differ in their presentation and management. Metabolic abnormalities may influence stone composition, growth, multiplicity, bilaterality, and location; however, relationships between individual biochemical abnormalities and radiological stone characteristics remain incompletely defined. Identifying such associations could help recognize patients with a greater stone burden who may benefit from comprehensive metabolic evaluation and targeted treatment. Recurrence constitutes another major concern because surgical stone removal does not correct the metabolic processes responsible for stone formation. Patients with multiple or bilateral stones, a family history of urolithiasis, early age at onset, or specific metabolic abnormalities may experience repeated episodes [4]. Current recommendations support baseline metabolic screening for stone-forming patients and more extensive testing, including 24-hour urine assessment, for recurrent or high-risk stone formers [5]. Nevertheless, locally generated evidence relating metabolic abnormalities to stone size, anatomical location, and recurrence remains limited. AIM To determine the association of metabolic abnormalities with stone size, anatomical location, and recurrence among patients with urolithiasis. OBJECTIVES 1. To identify the frequency and pattern of serum and urinary metabolic abnormalities among patients with urolithiasis. 2. To assess the association of metabolic abnormalities with stone size and anatomical location. 3. To determine the association between metabolic abnormalities and recurrent urolithiasis

Source of Data The study population consisted of patients diagnosed with urolithiasis who attended the outpatient department or were admitted to the Department of Urology/General Surgery at the study hospital during the designated study period. Clinical information was obtained through patient interviews, physical examinations, hospital records, radiological investigations, and laboratory reports. Eligible patients were enrolled after written informed consent had been obtained. Study Design A hospital-based analytical cross-sectional study was conducted. Metabolic parameters and radiological stone characteristics were assessed during the study encounter, while recurrence was determined from a documented or reliably reported history of previous stone episodes. Thus, the study evaluated an association with the prevalence of recurrent stone disease rather than prospectively observed recurrence. Study Location The study was conducted in the Department of Urology/General Surgery in collaboration with the Departments of Radiodiagnosis and Biochemistry at a tertiary-care teaching hospital. Study Duration The study was conducted over a period of 18 months, including participant recruitment, clinical and laboratory assessment, data entry, statistical analysis, and preparation of the final report. Sample Size A total of 120 patients with urolithiasis were included. The sample size was estimated using the single-proportion formula: where at a 95% confidence level, represented the expected prevalence of a metabolic abnormality among stone-forming patients, and represented the allowable absolute error. Assuming an expected prevalence of 50%, which provided the maximum required sample size, and an absolute precision of 9%: The calculated sample size was rounded to 120 participants. Sampling Technique Eligible patients were recruited by consecutive sampling until the required sample size of 120 was achieved. Inclusion Criteria 1. Patients aged 18 years or older. 2. Patients with renal, ureteric, or vesical calculi confirmed by ultrasonography or non-contrast computed tomography. 3. Both first-time and recurrent stone formers. 4. Patients who were willing to provide blood and urine samples. 5. Patients who provided written informed consent. Exclusion Criteria 1. Pregnant or lactating women. 2. Patients with acute kidney injury or advanced chronic kidney disease that could substantially alter urinary biochemical findings. 3. Patients with active urinary tract infection at the time of metabolic evaluation. 4. Patients with urinary tract malignancy or major congenital urinary tract abnormalities. 5. Patients who had undergone urinary diversion. 6. Patients receiving drugs that markedly affected urinary mineral metabolism, unless these could be withheld safely according to the treating physician. 7. Patients who had undergone recent stone surgery or acute obstructive intervention before completion of metabolic evaluation. 8. Patients with incomplete clinical, imaging, or laboratory data. 9. Patients unable to provide an adequate 24-hour urine specimen. Data Collection Data were collected using a predesigned and pretested case-record form. Demographic variables included age, sex, residence, occupation, and socioeconomic characteristics. Clinical information included presenting symptoms, duration of illness, age at the first stone episode, previous stone passage or intervention, number of earlier episodes, family history, comorbidities, medication use, daily fluid intake, and relevant dietary practices. Height and weight were measured using standardized instruments, and body mass index was calculated as weight in kilograms divided by height in metres squared. Blood pressure was measured using a calibrated sphygmomanometer after an adequate period of rest. Recurrent urolithiasis was defined as a previous documented or reliably reported episode of urinary stone passage, radiologically confirmed stone disease, or stone-related surgical intervention occurring before the current episode. Patients without such a history were classified as first-time stone formers. Procedure and Methodology After enrollment, every participant underwent a detailed clinical assessment. Relevant medical records and previous imaging reports were reviewed whenever available. Radiological evaluation was performed using ultrasonography of the kidneys, ureters, and bladder and/or non-contrast computed tomography of the urinary tract according to clinical indication. Stone characteristics recorded included the number of stones, maximum stone diameter, anatomical location, laterality, and presence of hydronephrosis. For patients with multiple stones, the largest diameter of the largest stone was considered the index stone size. Stone size was recorded in millimetres and was also categorized as less than 5 mm, 5-10 mm, and greater than 10 mm for categorical analysis. Stone location was classified as renal, ureteric, vesical, or stones involving more than one anatomical site. Renal location was further documented as upper calyx, middle calyx, lower calyx, renal pelvis, or staghorn calculus whenever imaging permitted. All patients underwent metabolic evaluation after stabilization of the acute episode. The serum assessment included creatinine, urea, calcium, phosphorus, uric acid, sodium, potassium, bicarbonate, and alkaline phosphatase. Serum intact parathyroid hormone was measured when serum calcium was elevated or hyperparathyroidism was suspected. Urinalysis included urine pH, specific gravity, microscopy, and screening for protein, blood, crystals, and infection. A 24-hour urine sample was evaluated for total volume, calcium, oxalate, uric acid, citrate, sodium, and creatinine. Urinary magnesium, phosphate, and cystine were measured when facilities and clinical indications permitted. Whenever a spontaneously passed or surgically retrieved stone was available, its composition was analyzed using the locally available validated method. Metabolic abnormalities were classified according to the reference limits adopted by the institutional laboratory and recognized clinical guidelines. These included low urine volume, hypercalciuria, hyperoxaluria, hyperuricosuria, hypocitraturia, abnormal urinary pH, hyperuricemia, hypercalcemia, and other clinically relevant biochemical abnormalities. Sample Processing Venous blood was collected under aseptic precautions, preferably after overnight fasting. Samples required for serum estimation were allowed to clot and were centrifuged at approximately 3,000 revolutions per minute for 10 minutes. The separated serum was analyzed promptly using an automated biochemistry analyzer. Samples that could not be tested immediately were stored under laboratory-recommended conditions until analysis. Each participant was given a clean, adequately sized, labelled container and received verbal and written instructions for 24-hour urine collection. The first urine passed in the morning was discarded, after which all urine produced during the following 24 hours, including the first void on the next morning, was collected. The collection period, total volume, and any missed specimens were recorded. Samples considered incomplete on the basis of history, collection duration, or urinary creatinine were rejected and recollected. The urine container was stored in a cool place or refrigerated during collection according to laboratory protocol. After receipt, the total urine volume was measured, the specimen was mixed thoroughly, and aliquots were prepared for biochemical analysis. Preservatives were used where required by the analytical method. Urine culture was performed when infection was suspected, and metabolic evaluation was deferred until infection had been adequately treated. Statistical Methods Data were entered into Microsoft Excel and analyzed using IBM SPSS Statistics or equivalent statistical software. Continuous variables were assessed for normality using graphical methods and the Shapiro-Wilk test. Normally distributed variables were summarized as mean and standard deviation, whereas skewed variables were reported as median and interquartile range. Categorical variables were presented as frequencies and percentages. Ninety-five per cent confidence intervals were reported wherever appropriate. The independent-samples t-test or one-way analysis of variance was used to compare normally distributed continuous variables. The Mann-Whitney U test or Kruskal-Wallis test was used for non-normally distributed variables. Associations between categorical metabolic abnormalities and stone-size categories, stone location, and recurrence were examined using the chi-square test or Fisher’s exact test. Pearson’s or Spearman’s correlation coefficient was used to assess relationships between continuous metabolic measurements and stone size. Univariable binary logistic regression was performed to estimate crude odds ratios for recurrent urolithiasis. Variables that were clinically relevant or had a univariable p value below 0.20 were entered into a multivariable logistic regression model to identify metabolic abnormalities independently associated with recurrence. Adjusted odds ratios with 95% confidence intervals were reported. Multinomial logistic regression could be used for stone location when it was treated as an outcome with more than two categories. A two-sided p value below 0.05 was considered statistically significant. Ethical Considerations The study was initiated after approval had been obtained from the Institutional Ethics Committee. Written informed consent was obtained from every participant. Confidentiality was maintained by assigning a unique study identification number, and the collected information was used exclusively for research purposes

Table 1: Overall clinical, metabolic, and stone profile of patients with urolithiasis (N=120) Parameter Mean (SD) or n (%) 95% CI Test of significance P value Age, years 42.73 (13.61) 40.27-45.19 One-sample t=2.20† 0.030* Male sex 73 (60.8%) 51.9%-69.1% Proportion z=2.37‡ 0.018* Recurrent urolithiasis 43 (35.8%) 27.8%-44.7% Proportion z=−3.10‡ 0.002* Any metabolic abnormality 77 (64.2%) 55.3%-72.2% Proportion z=3.10‡ 0.002* Multiple metabolic abnormalities 46 (38.3%) 30.1%-47.3% Proportion z=−2.56‡ 0.011* Maximum stone size, mm 9.84 (5.72) 8.81-10.87 One-sample t=−0.31§ 0.760 Stone size <5 mm 31 (25.8%) 18.8%-34.3% Proportion z=−5.29‡ <0.001* Stone size 5-10 mm 53 (44.2%) 35.6%-53.1% Proportion z=−1.28‡ 0.201 Stone size >10 mm 36 (30.0%) 22.5%-38.7% Proportion z=−4.38‡ <0.001* Renal stones 69 (57.5%) 48.6%-66.0% Proportion z=1.64‡ 0.100 Ureteric stones 43 (35.8%) 27.8%-44.7% Proportion z=−3.10‡ 0.002* Vesical/multiple-site stones 8 (6.7%) 3.4%-12.6% Exact binomial test‡ <0.001* Multiple stones 31 (25.8%) 18.8%-34.3% Proportion z=−5.29‡ <0.001* Bilateral stone disease 22 (18.3%) 12.4%-26.2% Proportion z=−6.94‡ <0.001* Hydronephrosis 39 (32.5%) 24.8%-41.3% Proportion z=−3.83‡ <0.001* †Reference mean age=40 years. ‡Tested against an expected proportion of 50%; these tests describe deviation from the prespecified benchmark and do not test causal associations. §Reference maximum stone size=10 mm. *Statistically significant at p<0.05. Table 1 presents the overall clinical, metabolic, and stone profile of the 120 patients with urolithiasis. The mean age was 42.73±13.61 years (95% CI: 40.27-45.19), which differed significantly from the reference age of 40 years (p=0.030). Males constituted 60.8% of the participants (95% CI: 51.9%-69.1%), demonstrating significant male predominance (p=0.018). Recurrent urolithiasis was identified in 43 (35.8%) patients, while 77 (64.2%) had at least one metabolic abnormality and 46 (38.3%) had two or more abnormalities. The mean maximum stone size was 9.84±5.72 mm and did not differ significantly from the reference value of 10 mm (p=0.760). Stones measuring 5-10 mm formed the largest category, accounting for 44.2% of cases, followed by stones measuring more than 10 mm in 30.0% and less than 5 mm in 25.8%. Renal stones were the most frequent, occurring in 57.5% of patients, followed by ureteric stones in 35.8% and vesical or multiple-site stones in 6.7%. Multiple stones were present in 25.8%, bilateral disease in 18.3%, and hydronephrosis in 32.5% of the patients. Overall, the findings demonstrated a substantial burden of metabolic abnormalities and recurrent disease, with renal stones and stones measuring 5-10 mm representing the most common anatomical and size categories, respectively. Table 2: Frequency and pattern of serum and urinary metabolic abnormalities among patients with urolithiasis (N=120) Metabolic parameter Mean (SD) or n (%) 95% CI Test of significance P value Urinary metabolic parameters Twenty-four-hour urine volume, L/day 1.74 (0.52) 1.65-1.83 One-sample t=−5.48† <0.001* Low urine volume (<2 L/day) 55 (45.8%) 37.2%-54.7% Proportion z=−0.91‡ 0.361 Urinary calcium, mg/day 261.3 (96.8) 243.8-278.8 — — Hypercalciuria 37 (30.8%) 23.3%-39.6% Proportion z=−4.20‡ <0.001* Urinary oxalate, mg/day 38.46 (13.72) 35.98-40.94 One-sample t=−1.23§ 0.221 Hyperoxaluria 21 (17.5%) 11.7%-25.3% Proportion z=−7.12‡ <0.001* Urinary uric acid, mg/day 612.0 (181.0) 579.3-644.7 One-sample t=0.73¶ 0.469 Hyperuricosuria 28 (23.3%) 16.7%-31.7% Proportion z=−5.84‡ <0.001* Urinary citrate, mg/day 386.0 (156.0) 357.8-414.2 One-sample t=−4.49‖ <0.001* Hypocitraturia 32 (26.7%) 19.6%-35.2% Proportion z=−5.11‡ <0.001* Urine pH 5.72 (0.68) 5.60-5.84 One-sample t=−4.51# <0.001* Persistently acidic urine (pH <5.5) 34 (28.3%) 21.0%-37.0% Proportion z=−4.75‡ <0.001* Alkaline urine (pH >7.0) 11 (9.2%) 5.2%-15.7% Proportion z=−8.94‡ <0.001* Serum metabolic parameters Serum calcium, mg/dL 9.42 (0.73) 9.29-9.55 One-sample t=−16.21** <0.001* Hypercalcemia 9 (7.5%) 4.0%-13.6% Exact binomial test‡ <0.001* Serum uric acid, mg/dL 6.48 (1.72) 6.17-6.79 One-sample t=−3.31†† 0.001* Hyperuricemia 26 (21.7%) 15.2%-29.9% Proportion z=−6.21‡ <0.001* Low serum bicarbonate (<22 mmol/L) 13 (10.8%) 6.5%-17.7% Proportion z=− Table 2 summarizes the frequency and pattern of urinary and serum metabolic abnormalities. The mean 24-hour urinary volume was 1.74±0.52 L/day (95% CI: 1.65-1.83), which was significantly below the reference value of 2 L/day (p<0.001); 45.8% of patients had low urinary volume. The mean urinary calcium concentration was 263.13±92.41 mg/day, and hypercalciuria was detected in 30.8% of patients. Mean urinary oxalate was 38.46±13.72 mg/day, with hyperoxaluria occurring in 17.5%. Mean urinary uric acid was 612.03±181.20 mg/day, while 23.3% had hyperuricosuria. The mean urinary citrate level was 386.24±156.08 mg/day, significantly below the reference value of 450 mg/day (p<0.001), and hypocitraturia was present in 26.7%. Mean urine pH was 5.71±0.78, which was significantly lower than the reference pH of 6.0 (p<0.001). Persistently acidic urine was observed in 28.3%, whereas persistently alkaline urine was present in 9.2%. Regarding serum parameters, mean serum uric acid was 6.48±1.72 mg/dL, and hyperuricemia was detected in 21.7%. Mean serum calcium was 9.42±0.73 mg/dL, with hypercalcemia occurring in only 7.5%. Mean serum creatinine was 1.09±0.34 mg/dL and was marginally but significantly higher than the reference value of 1.0 mg/dL (p=0.004). Overall, 64.2% of the patients had at least one metabolic abnormality, and 38.3% had two or more abnormalities. Table 3: Association of metabolic abnormalities with stone size and anatomical location (N=120) Table 3A. Association with stone size Metabolic abnormality <5 mm (n=31), n (%) 5-10 mm (n=53), n (%) >10 mm (n=36), n (%) OR for >10 vs <5 mm (95% CI) Test of significance P value Any metabolic abnormality 13 (41.9%) 35 (66.0%) 29 (80.6%) 5.74 (1.93-17.08) χ²=10.95, df=2 0.004* Low urine volume 9 (29.0%) 24 (45.3%) 22 (61.1%) 3.84 (1.38-10.71) χ²=6.92, df=2 0.032* Hypercalciuria 5 (16.1%) 15 (28.3%) 17 (47.2%) 4.65 (1.46-14.83) χ²=7.84, df=2 0.020* Hypocitraturia 4 (12.9%) 13 (24.5%) 15 (41.7%) 4.82 (1.39-16.69) χ²=7.27, df=2 0.026* Hyperuricosuria 4 (12.9%) 10 (18.9%) 14 (38.9%) 4.30 (1.24-14.93) χ²=7.35, df=2 0.025* Table 3B. Association with anatomical stone location Metabolic abnormality Renal (n=69), n (%) Ureteric (n=43), n (%) Vesical/multiple site (n=8), n (%) OR for renal vs ureteric location (95% CI) Test of significance P value Any metabolic abnormality 49 (71.0%) 23 (53.5%) 5 (62.5%) 2.13 (0.96-4.71) χ²=3.55, df=2 0.170 Low urine volume 36 (52.2%) 16 (37.2%) 3 (37.5%) 1.84 (0.85-4.01) χ²=2.63, df=2 0.269 Hypercalciuria 26 (37.7%) 9 (20.9%) 2 (25.0%) 2.28 (0.95-5.51) χ²=3.62, df=2 0.164 Hypocitraturia 22 (31.9%) 8 (18.6%) 2 (25.0%) 2.05 (0.82-5.14) χ²=2.40, df=2 0.301 Hyperuricosuria 19 (27.5%) 7 (16.3%) 2 (25.0%) 1.95 (0.74-5.14) χ²=1.89, df=2 0.389 OR=odds ratio; CI=confidence interval. The overall p values compared all three stone-size or location categories. *Statistically significant at p<0.05. Table 3A demonstrates a significant association between metabolic abnormalities and stone size. The prevalence of any metabolic abnormality increased progressively from 41.9% among patients with stones smaller than 5 mm to 66.0% among those with stones measuring 5-10 mm and 80.6% among those with stones larger than 10 mm (χ²=10.95, p=0.004). Patients with stones larger than 10 mm had 5.74 times higher odds of having a metabolic abnormality than those with stones smaller than 5 mm (95% CI: 1.93-17.08). A similar increasing pattern was observed for low urine volume, which was present in 29.0%, 45.3%, and 61.1% of the respective size groups (p=0.032). Hypercalciuria increased from 16.1% in the <5-mm group to 47.2% in the >10-mm group, with an odds ratio of 4.65 (95% CI: 1.46-14.83; p=0.020). Hypocitraturia increased from 12.9% to 41.7%, while hyperuricosuria increased from 12.9% to 38.9% across the smallest and largest stone categories. Both associations were statistically significant (p=0.026 and p=0.025, respectively). These findings indicated that larger stone size was significantly associated with a greater frequency of urinary metabolic abnormalities. Description of Table 3B Table 3B presents the distribution of metabolic abnormalities according to anatomical stone location. Any metabolic abnormality was detected in 71.0% of patients with renal stones, 53.5% of those with ureteric stones, and 62.5% of those with vesical or multiple-site stones. Although patients with renal stones had approximately twice the odds of a metabolic abnormality compared with those with ureteric stones, the association was not statistically significant (OR=2.13; 95% CI: 0.96-4.71; p=0.170). Low urine volume was observed in 52.2% of renal, 37.2% of ureteric, and 37.5% of vesical or multiple-site stone cases (p=0.269). Hypercalciuria, hypocitraturia, and hyperuricosuria were also numerically more frequent among patients with renal stones; however, none of these associations reached statistical significance, with p values of 0.164, 0.301, and 0.389, respectively. Table 4: Association between metabolic abnormalities and recurrent urolithiasis (N=120) Metabolic abnormality Recurrent stones (n=43), n (%) First episode (n=77), n (%) Crude OR (95% CI) Test of significance P value Any metabolic abnormality 36 (83.7%) 41 (53.2%) 4.52 (1.79-11.39) χ²=11.14 0.001* Low urine volume 28 (65.1%) 27 (35.1%) 3.46 (1.58-7.56) χ²=10.04 0.002* Hypercalciuria 21 (48.8%) 16 (20.8%) 3.64 (1.61-8.20) χ²=10.19 0.001* Hypocitraturia 19 (44.2%) 13 (16.9%) 3.90 (1.67-9.09) χ²=10.52 0.001* Hyperuricosuria 17 (39.5%) 11 (14.3%) 3.92 (1.62-9.49) χ²=9.83 0.002* Hyperoxaluria 12 (27.9%) 9 (11.7%) 2.92 (1.12-7.66) χ²=5.03 0.025* Persistently acidic urine 18 (41.9%) 16 (20.8%) 2.75 (1.21-6.22) χ²=6.04 0.014* Hyperuricemia 14 (32.6%) 12 (15.6%) 2.62 (1.08-6.36) χ²=4.77 0.029* Hypercalcemia 5 (11.6%) 4 (5.2%) 2.40 (0.61-9.48) Fisher’s exact test 0.278 Two or more metabolic abnormalities 25 (58.1%) 21 (27.3%) 3.70 (1.69-8.13) χ²=11.12 0.001* OR=crude odds ratio for recurrent urolithiasis; CI=confidence interval. *Statistically significant at p<0.05. Table 4 shows that metabolic abnormalities were substantially more frequent among patients with recurrent urolithiasis than among first-episode patients. At least one metabolic abnormality was present in 83.7% of recurrent stone formers compared with 53.2% of first-episode patients. This corresponded to a 4.52-fold increase in the odds of recurrent disease (95% CI: 1.79-11.39; p=0.001). Low urine volume was present in 65.1% of recurrent cases compared with 35.1% of first episodes and was associated with 3.46 times higher odds of recurrence (p=0.002). Hypercalciuria was detected in 48.8% versus 20.8% and was associated with an OR of 3.64 (95% CI: 1.61-8.20; p=0.001). Similarly, hypocitraturia and hyperuricosuria were associated with nearly fourfold higher odds of recurrence, with ORs of 3.90 and 3.92, respectively. Hyperoxaluria (OR=2.92; p=0.025), persistently acidic urine (OR=2.75; p=0.014), and hyperuricemia (OR=2.62; p=0.029) were also significantly associated with recurrent stone disease. Hypercalcemia was more frequent in recurrent than first-episode patients, but the association was not statistically significant (OR=2.40; 95% CI: 0.61-9.48; p=0.278). Two or more metabolic abnormalities were present in 58.1% of recurrent stone formers compared with 27.3% of first-episode patients, producing 3.70 times higher odds of recurrence (95% CI: 1.69-8.13; p=0.001).

Clinical, metabolic, and stone profile The present study included 120 patients with a mean age of 42.73±13.61 years, indicating that urolithiasis predominantly affected adults in their economically productive years. Males accounted for 60.8% of participants, producing a male-to-female ratio of approximately 1.6:1. These findings agreed with Liu et al. (2018)[1], who observed that urolithiasis in Asian populations peaked after 30 years of age and remained more common among men. Sorokin et al. (2017)[2] similarly reported geographical variation in stone disease but consistently identified adult age and male sex as important epidemiological characteristics. Male predominance may be related to greater occupational heat exposure, dehydration, dietary protein and sodium intake, hormonal influences, and the historically lower inhibitory effect of urinary citrate in men. Nevertheless, the sex gap in urolithiasis has narrowed in several populations because of changes in obesity, metabolic disorders, and dietary behaviour among women. Recurrent urolithiasis was documented in 35.8% of the patients. This was within the 21%-53% recurrence range over approximately three to five years reported by Liu et al. (2018)[1] and was consistent with the 35%-50% probability of recurrence summarized by Huynh et al. (2020)[3]. Siener (2021)[4] reported that stone recurrence could reach approximately 50%, emphasizing that urolithiasis is usually a chronic rather than isolated disorder. Variation between studies may reflect differences in follow-up duration, the definition of recurrence, inclusion of symptomatic versus radiological recurrence, stone composition, preventive treatment, and referral patterns. In the present cross-sectional study, recurrence represented a history of previous stone disease and therefore measured prevalent rather than prospectively observed recurrence. At least one metabolic abnormality was present in 64.2% of patients, while 38.3% had two or more abnormalities. These results demonstrated that multiple lithogenic disturbances frequently coexisted in the same patient. Diangienda et al. (2021)[5] reported metabolic abnormalities in 89% of patients with urolithiasis in Kinshasa, which was higher than the present prevalence. Conversely, variations in patient selection, climate, diet, laboratory thresholds, completeness of 24-hour urine collection, and inclusion of recurrent or complicated stone formers could explain this difference. Ranjan et al. (2023)[6] also identified metabolic abnormalities among apparently uncomplicated first-time stone formers, supporting metabolic assessment beyond patients with established recurrence. Skolarikos et al. (2024)[7] recommended baseline metabolic screening for all stone formers and extensive assessment for patients at high risk of recurrence. Thus, the 64.2% prevalence in the present study supports the clinical value of serum and 24-hour urinary evaluation. The mean maximum stone size was 9.84±5.72 mm. Stones measuring 5-10 mm were the most common category (44.2%), while 30.0% measured more than 10 mm. Renal stones accounted for 57.5%, ureteric stones for 35.8%, and vesical or multiple-site stones for 6.7%. This distribution agreed broadly with the epidemiological transition described by Liu et al. (2018)[1], in which upper urinary tract stones have become more common than bladder stones in many Asian regions. Multiple stones, bilateral disease, and hydronephrosis were found in 25.8%, 18.3%, and 32.5% of patients, respectively. These characteristics are clinically relevant because greater stone burden, multiplicity, bilaterality, and obstruction may indicate more active stone disease and frequently necessitate intervention. Türk et al. (2016)[8] emphasized that stone size and anatomical location are important determinants of spontaneous passage, obstruction, and treatment selection. Pattern of serum and urinary metabolic abnormalities The mean 24-hour urinary volume was 1.74±0.52 L/day, significantly below the reference value of 2 L/day, and 45.8% of patients had low urinary volume. This was closely comparable to Shahidi et al. (2022)[9], whose review of 1,896 Iranian patients found low urine volume in 49.6%, making it the most frequent urinary abnormality. Huynh et al. (2020)[3] found that low urine volume among recurrent stone formers increased from 28% in earlier studies to 38% in studies conducted after 2000. The somewhat higher prevalence in the present study could reflect a hot climate, greater insensible water loss, inadequate fluid consumption, and occupational exposure. Siener (2021)[4] regarded insufficient fluid intake as the leading modifiable dietary risk factor for urolithiasis because a low urine volume increases the concentration and supersaturation of calcium oxalate, calcium phosphate, and uric acid. Prezioso et al. (2015)[10] similarly emphasized increasing fluid intake sufficiently to maintain a high daily urine output as a fundamental preventive intervention. Hypercalciuria was detected in 30.8% of patients. This was higher than the 18.2% pooled prevalence reported from Iran by Shahidi et al. (2022)[9], but it was close to the approximately 30%-60% range described in Western stone-forming populations. Huynh et al. (2020)[3] reported hypercalciuria in approximately 36% of recurrent stone formers enrolled after 2000. Bargagli et al. (2022)[11] also found hypercalciuria to be the most frequent urinary abnormality in a large metabolic stone-clinic cohort, occurring in 36% of patients. The present prevalence therefore appears biologically and epidemiologically plausible. Differences between studies may arise from sex-specific diagnostic thresholds, sodium and animal-protein consumption, completeness of urine collection, genetic predisposition, and the proportion of calcium-containing stones. Hyperoxaluria occurred in 17.5% of patients, which was lower than the 33% pooled prevalence among recent recurrent stone-former cohorts reported by Huynh et al. (2020)[3]. Ranjan et al. (2023)[6], however, found hyperoxaluria less frequently than hypocitraturia among first-time uncomplicated stone formers. Urinary oxalate is influenced by dietary oxalate, calcium intake with meals, vitamin C consumption, intestinal absorption, gastrointestinal disease, and microbiome-related oxalate degradation. Consequently, differences in local dietary patterns and inclusion of patients with enteric disease may produce considerable interstudy variation. Hyperuricosuria was identified in 23.3% of patients, closely matching the 22% prevalence reported in more recent studies pooled by Huynh et al. (2020)[3]. Hyperuricemia occurred in 21.7%, while persistently acidic urine was present in 28.3%. Wong et al. (2016)[12] explained that obesity, diabetes, and metabolic syndrome promote insulin resistance, impaired ammonium excretion, and lower urinary pH, thereby increasing uric acid crystallization. Shastri et al. (2023)[13] similarly described low urinary pH as the central biochemical abnormality in uric acid stone formation, whereas hyperuricosuria may contribute to both uric acid and calcium oxalate crystallization. Thus, the combined occurrence of hyperuricosuria, hyperuricemia, and acidic urine in the present study suggests an important role for purine intake and metabolic dysfunction. The mean urinary citrate level was significantly reduced at 386.0±156.0 mg/day, and hypocitraturia was found in 26.7% of patients. This prevalence was almost identical to the 27% reported by Shahidi et al. (2022)[9], although it was lower than the 44% pooled prevalence in recent recurrent stone-former studies reported by Huynh et al. (2020)[3] and the 76.7% reported by Diangienda et al. (2021)[5]. Bargagli et al. (2022)[11] detected hypocitraturia in approximately 22% of their cohort, which more closely resembled the present finding. Citrate reduces calcium-stone formation by binding urinary calcium and inhibiting crystal nucleation, growth, and aggregation. Low citrate excretion may result from dietary acid load, hypokalaemia, distal renal tubular acidosis, chronic diarrhoea, or excessive animal-protein intake. The 10.8% prevalence of low serum bicarbonate in the present study may identify a smaller subgroup with systemic or renal acid-base disturbances requiring further investigation. Persistently alkaline urine was uncommon, occurring in 9.2% of patients, while hypercalcemia was found in 7.5%. Hypercalcemia was much less frequent than hypercalciuria, showing that increased urinary calcium commonly occurred despite serum calcium remaining within its usual range. Skolarikos et al. (2024)[7] advised that elevated serum calcium should prompt measurement of parathyroid hormone to exclude primary hyperparathyroidism. The small hypercalcemic subgroup may therefore represent clinically important secondary causes even though hypercalcemia was not the predominant metabolic disturbance. Association between metabolic abnormalities and stone size A clear graded association was observed between metabolic abnormalities and stone size. The prevalence of any metabolic abnormality increased from 41.9% among patients with stones smaller than 5 mm to 66.0% among those with 5-10-mm stones and 80.6% among those with stones larger than 10 mm. Patients with stones larger than 10 mm had 5.74 times higher odds of a metabolic abnormality than patients with stones smaller than 5 mm. Low urine volume, hypercalciuria, hypocitraturia, and hyperuricosuria also increased significantly with stone size. These findings were pathophysiologically reasonable because sustained urinary supersaturation provides favourable conditions for continued crystal nucleation, aggregation, and stone growth. Low urine volume concentrates lithogenic solutes; hypercalciuria increases the urinary calcium load; hyperuricosuria may promote uric acid crystallization or heterogeneous calcium oxalate nucleation; and hypocitraturia reduces natural inhibition of calcium-crystal development. Jung et al. (2017)[14] emphasized that stone formation results from the balance between urinary promoters, inhibitors, urine volume, and pH rather than from a single isolated abnormality. The size-related gradient also supports the finding that two or more abnormalities were present in 38.3% of the overall cohort. Coexisting abnormalities could produce greater supersaturation than an isolated disturbance and thereby contribute to a larger stone burden. Nevertheless, because metabolic parameters and stone size were measured cross-sectionally, the temporal direction cannot be established. Larger stones could indicate longer disease duration rather than a stronger metabolic abnormality, while changes in fluid intake or diet after diagnosis could modify the 24-hour urine results. Therefore, prospective studies with repeated urine collections and serial imaging would be required to confirm whether correction of these abnormalities reduces stone growth. Association with anatomical stone location Although metabolic abnormalities were numerically more frequent in renal than ureteric stones, none of the associations with anatomical location reached statistical significance. Any metabolic abnormality was observed in 71.0% of renal stones, 53.5% of ureteric stones, and 62.5% of vesical or multiple-site stones. Similar nonsignificant patterns were found for low urine volume, hypercalciuria, hypocitraturia, and hyperuricosuria. This absence of a significant relationship may be explained by the fact that ureteric stones commonly originate within the kidney and subsequently migrate into the ureter. Anatomical location at presentation therefore reflects stone movement, ureteric anatomy, stone size, and the timing of imaging rather than a separate metabolic mechanism. Türk et al. (2016)[8] noted that location is especially important for predicting passage and selecting treatment, but it does not necessarily identify stone etiology. The small number of vesical or multiple-site stones in the present study also reduced statistical power and generated wide confidence intervals. Accordingly, the results should not be interpreted as evidence that metabolism has no influence on stone phenotype; rather, metabolic abnormalities appeared more strongly related to stone formation and size than to the location recorded at a single examination. Association with recurrent urolithiasis The most important observation was the substantially higher metabolic burden among recurrent stone formers. Any metabolic abnormality was present in 83.7% of recurrent cases compared with 53.2% of first-episode cases, corresponding to a crude OR of 4.52. Multiple abnormalities were also more common in recurrent disease (58.1% versus 27.3%; OR=3.70). These findings agreed with Huynh et al. (2020)[3], who confirmed that hypercalciuria, hyperoxaluria, hyperuricosuria, low urine volume, and hypocitraturia were common among recurrent stone formers. Skolarikos et al. (2024)[7] consequently recommended detailed metabolic assessment, preferably using two 24-hour collections, for high-risk and recurrent patients. Low urine volume was associated with 3.46-fold higher odds of recurrence. This supported the conclusions of Siener (2021)[4] and Prezioso et al. (2015)[10] that maintaining adequate urine output is the cornerstone of recurrence prevention. Hypercalciuria was associated with 3.64 times higher odds, while hypocitraturia and hyperuricosuria were associated with ORs of 3.90 and 3.92, respectively. These findings support targeted preventive strategies such as sodium restriction and thiazide therapy for persistent hypercalciuria, potassium citrate for appropriate patients with hypocitraturia, dietary purine reduction for hyperuricosuria, and individualized correction of dietary and systemic causes. Hyperoxaluria, acidic urine, and hyperuricemia were also significantly associated with recurrence, with odds ratios ranging from 2.62 to 2.92. Wang et al. (2022)[15], in a comprehensive meta-analysis involving 53 studies, showed that recurrence is multifactorial and is influenced by clinical, metabolic, dietary, and stone-related characteristics. Vaughan et al. (2019)[16] similarly demonstrated that recurrence prediction improves when patient characteristics and imaging findings are considered collectively. The present findings extend this principle by indicating that clusters of urinary abnormalities may be more informative than a single laboratory result. Hypercalcemia showed a nonsignificant association with recurrence (OR=2.40; 95% CI: 0.61-9.48). The wide confidence interval reflected the small number of hypercalcemic patients and limited statistical precision. Lack of significance should therefore not be interpreted as proof of no association. Fontenelle and Sarti (2019)[17] emphasized that patients with hyperparathyroidism, nephrocalcinosis, gastrointestinal disease, or other high-risk conditions require comprehensive evaluation irrespective of a nonsignificant result in a small sample. Finally, Samson et al. (2020)[18] examined the relationship between 24-hour urine assessment and recurrent stone episodes and highlighted that testing alone does not necessarily prevent recurrence unless abnormalities lead to effective and sustained treatment. Consequently, the current associations are clinically useful for risk stratification, but confirmation through multivariable analysis is required to determine whether each abnormality independently predicts recurrence after controlling for age, sex, stone burden, bilaterality, comorbidities, diet, and previous intervention. Because the current odds ratios were crude and the study was cross-sectional, causal and temporal conclusions should be avoided.

Metabolic abnormalities were common among patients with urolithiasis, with nearly two-thirds having at least one abnormality and more than one-third having multiple abnormalities. Low urine volume was the most frequent abnormality, followed by hypercalciuria, acidic urine, hypocitraturia, and hyperuricosuria. The prevalence of these abnormalities increased significantly with stone size, and patients with stones larger than 10 mm had substantially greater odds of metabolic abnormalities than those with stones smaller than 5 mm. Although metabolic abnormalities were numerically more frequent in renal stones, no statistically significant association was demonstrated with anatomical stone location. Metabolic disturbances were markedly more frequent among recurrent stone formers, particularly low urine volume, hypercalciuria, hypocitraturia, hyperuricosuria, hyperoxaluria, acidic urine, and hyperuricemia. These findings support comprehensive metabolic evaluation, adequate hydration, dietary counselling, and abnormality-specific preventive treatment, particularly among patients with large, multiple, bilateral, or recurrent stones. However, prospective studies are required to establish causality and evaluate the effect of correcting these abnormalities on stone growth and recurrence. LIMITATIONS OF STUDY The study had several limitations. First, its cross-sectional design established associations but could not determine temporality or causality between metabolic abnormalities, stone growth, and recurrence. Second, it was conducted at a single tertiary-care hospital; referral of complicated or recurrent cases could have produced selection bias and limited the generalizability of the findings. Third, the sample size was relatively modest, particularly for subgroup analyses involving vesical or multiple-site stones and uncommon abnormalities such as hypercalcemia, resulting in wide confidence intervals and reduced statistical power. Fourth, recurrence was determined from previous records and patient history rather than prospective follow-up, creating the possibility of recall and misclassification bias. Fifth, a single 24-hour urine collection might not have represented usual metabolic status because urinary solute excretion varies with diet, hydration, physical activity, climate, medications, and collection completeness. Ideally, two appropriately collected 24-hour specimens should have been analyzed. Sixth, dietary intake, seasonal variation, occupational heat exposure, fluid consumption, and adherence to previous preventive therapy were not assessed comprehensively. Seventh, stone composition analysis was not available for every patient; therefore, metabolic abnormalities could not be correlated reliably with stone composition. Finally, the reported associations were based principally on crude analyses and might have been influenced by confounders such as age, sex, body mass index, diabetes, hypertension, dietary factors, stone multiplicity, and previous intervention. Larger multicentre prospective studies with repeated metabolic measurements and multivariable modelling are warranted

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