INTRODUCTION

Pediatric nephrolithiasis is a disease of increasing prevalence and economic burden, with data showing a rising trend among children and adolescents⁽¹⁾. Kidney stones in children tend to have a high recurrence rate related to underlying risk factors (RF), and the aim of evaluation should be to understand such causes so that targeted therapy can be provided to decrease recurrence and complications^(1-3).
As mentioned above, the recurrence rate is higher in pediatric population, seeing a 50% of relapse within 7 years from first episode^(4-6). Several RF have been implicated in the children’s nephrolithiasis pathogenesis, such as abnormalities related to metabolic, anatomic, genetic and environment conditions⁽⁷⁾. These last, and mainly metabolic abnormalities, are partly determining the type of kidney stone⁽⁸⁾. Hypercalciuria is the biochemical abnormality most frequently found in children with kidney stone and the presence of genetic mutations may be the cause in a group of patients^(9,10). Such findings are helpful to clarify etiologies, moreover, it is noticeable that reaching a metabolic diagnosis will allow us to optimize the treatment and prevent recurrence.
Nevertheless, there are few data on the familial predisposition to stone formation in childhood. A previous study conducted by Camacho Díaz et al. described that approximately 45% of children had a positive family history (FH)⁽¹¹⁾. Taking this into account, having information about FH could help us to identify kids at increased risk for inherited metabolic disorders.
Thus, due to the limited data available, the primary aim of this study was to identify the FH in children with kidney stone disease and a single urinary metabolic risk factor.

MATERIALS AND METHODS

Population studied
We have studied patients under 17 years of age with nephrolithiasis who had been referred to our institution between 2006 and 2019 for metabolic risk factor assessment. Referring physicians had confirmed the presence of lithiasis by spontaneous stone passage, renal ultrasound, abdominal X-rays, computed tomography, or surgical removal of lithiasis. Patients with kidney failure, genitourinary abnormalities, and/or immobilization; those who were taking drugs with a potential effect on mineral metabolism (corticosteroids, diuretics, and anticonvulsants); were not included in the study. Study protocol was approved by the Metabolic Research Institute review board. Informed consent was obtained from parents or legal responsible tutors.

Family history
All participants who entered to the study had to answer a questionnaire indicating family history of kidney stones and the degree of relationship. When the data were insufficient, they were contacted directly to inquire about the family antecedents. Only participants with single urinary metabolic risk factors were selected, then, they were grouped according to the degree of relation in 3 groups. Group 1: father, mother or siblings with history of kidney stones. Group 2: Grandparents, uncles or cousins ​​with history of kidney stones. Group 3: those that presented members of group 1 and 2.

Metabolic risk factor assessment
All patients included in the study were evaluated following an outpatient protocol⁽¹⁷⁾. Two 24-h urine samples were obtained, followed by a 2-h fasting urine sample collected by spontaneous voiding on the morning of the following day. Patients were asked to follow their usual diet and fluids consumption. Throughout the collection period, urine samples were kept refrigerated. Following the collection of urine samples, a blood sample was drawn. Blood samples were tested for creatinine, sodium, uric acid, phosphate, and calcium levels. Urine samples were tested for calcium, creatinine, sodium, potassium, uric acid, citrate, oxalate, cystine, and magnesium levels. Urine volume was measured for both 24-h urine collections. Urinary sediment and pH were determined in the 2-h fasting sample. For urinary pH values of <5.5, a repeat test was performed. Urine super saturation tests were conducted for persistently low urinary pH levels. All the patients underwent biochemical testing at least 1 month after the episode of renal colic or urinary tract infection to prevent biases related to any unknown procedure or treatment performed before entering the study and have baseline conditions similar to those of normal patients. The definition of a diagnosis of metabolic risk factor was based on criteria taken from the literature: idiopathic hypercalciuria (IH) >4 mg/kg per day; hyperoxaluria (HOx) >50 mg/1.73m2 BSA (body Surface area) per day; hypocitraturia (HC) < 400 mg/g creatinine; hypomagnesuria (HM) < 1.24 mg/kg/day; hyperuricosuria (HU) > 815 mg/1.73m2 BSA per day; persistently acidic urine pH as “unduly acidic urine” (UAU) when urinary pH was <5.5 in at least two different measurements on the same day, with increased risk of crystallization in a urine super saturation test. When metabolic alterations were not found, they were called «without or no metabolic activity (NMA). Serum calcium was measured by the ISE method using a Synchron CX3 Delta automated analyzer (Beckman, Beckman Instruments, Brea, CA); the same method was used for urinary calcium determination (performed on an acidified aliquot). Phosphate was measured by UV using CCX Spectrum automated analyzer (Abbott Laboratories, USA). Urinary magnesium was measured by Magnesium Reagent Synchron Systems (Calmagite) with a Synchron CX4 automated analyzer. Serum and urine creatinine levels were measured using the Jaffe kinetic method with the same automated analyzer. Urinary uric acid was measured in an alkalinized aliquot to prevent precipitation. Urinary citrate was determined by an enzymatic procedure using reagents from Sigma-Aldrich (St. Louis, MO). Urinary oxalate (measured in an acidified aliquot) was determined by an enzymatic procedure (Trinity Biotech, Bray Co., Wicklow, Ireland). Urinary pH was measured with a pH electrode in a 2-h fasting urine sample immediately after voiding. Brand’s reaction was used for the qualitative determination of cystine. We did not calculate urinary acidification defects. Urine saturation was calculated in repeated samples with urinary pH values < 5.5 using a computer program (ACTILIT) that evaluates the relative risk (RR) of crystallization of different salts. Following approval by the local institutional review board (IRB), written informed consent was obtained from the legal guardians of all participants for the use of their clinical and laboratory data for scientific purposes. Following the evaluation of all metabolic risk factors, the treatment and follow-up of patients were carried out by their referring physicians. Urologic treatments, types of dietary measures in children, and acidification defect assessments were not part of the objectives of this study.

Statistical analysis
The results are expressed as mean (X) ± standard deviation and/or percentages. When applicable, a 2-tailed paired “t” test and the Chi-square test were used, and p<0.05 was considered statistically significant. Baseline characteristics are expressed as mean and SD. Continuous numerical variables with normal distribution were analyzed using Student’s “t” and those without normal distribution with the Mann-Withney U (Wilcoxon rank sum test) test. The categorical variables were analyzed using the Chi-square test or Fisher’s exact test according to the sample size. A p≤0.05 was considered statistically significant. The analysis was carried out with the statistical program Statistix 7.0.

RESULTS

A total of 217 children were included in this study; 119 (55%) were males and 98 (45%) were females, calculating a ratio: 1.21:1.0. All patients included were Caucasian, which is the predominant ethnic group in our region.
There were no significant differences between the baseline characteristics between the two groups in terms of age, weight, height, BSA, and BMI (Table 1). From the total population, a family history of renal lithiasis was found in 47%, while the remaining 53% did not present it or referred it (Figure 1).

Table 1. Characteristics of children with kidney stones.

Body mass Index (BMI), Body Surface Area (BSA).

Figure 1. Overall prevalence of family history in children with kidney stone (n=217).

Similar to the observed in the general features, we did not find statistical differences between male and female and FH (51 vs 41%, p=0.12) (Table 2).The degree of kinship with FH (group 1, 2 and 3) was similar in both sexes, with group 2 being the most frequent between both (54% male and 52% female) (Table 2). The prevalence of FH varied according to the biochemical diagnosis found (Figure 2). IH represented the most frequent metabolic disorder n = 77 from which 52% (n = 40) had FH. Following the IH, the following were found: CIT, AUA, HU, OX, LUV, MG, CYS (figure 2)

Table 2. Prevalence of family history in children with kidney stone.

G1: father, mother or siblings with history of kidney stones. G2: Grandparents, uncles or cousins ​​with history of kidney stones. G3: those that presented members of group 1 and 2.

Figure 2. Family History according to biochemical diagnosis in patients with kidney stones.

This graph shows the number of individuals with the biochemical diagnosis in dark bars. In clear bars, the number of individuals who have a family history IH: IDIOPATIHC HYPERCALCIURIA, HC: HYPOCITRATURIANMA: NO METABOLIC ABNORMALITY, UAU: UNDULYACIDIC URINE pH, HU: HYPERURICOSURIA, HOx: HYPEROXALURIA, LUV: LOW URINARY VOLUME, CYS: CYSTINURIA, HM: HYPOMAGNESURIA.

The individuals were classified according to the presence or not of FH, no differences were found between the characteristics and the values of the determinations of the biochemical parameters according to each diagnosis (Table 3).

Table 3. Age, anthropometric and metabolic risk factorsin children with and without positive family history of stone disease

Body mass Index (BMI), Body Surface Area (BSA). *Non-parametric test: Median RIQ (distribution free test)

DISCUSSION

Data on prevalence of urolithiasis in paediatric patients are scares. In different parts of the world the estimated prevalence has been between 1%-15%⁽¹⁾. In our experience, the prevalence of kidney stones in children is 3%, with no differences between the sexes (unpublished data), in accordance with the 2% to 2.7% observed in Germany and Northern Italy^(12,13).
Tasian et al. has reported a growing incidence in children during the years 1997 to 2012, in whom frequency increased 23% per 5 years among boys, and 27% – 28% per 5 years among girls aged 10–19 years old⁽¹⁴⁾. Nephrolithiasis affects children of all ages and data on sex distribution varies by decades. In the first decade of life, boys were the most affected (1.2: 1 for 0–5 years and 1.3: 1 for 6–10 years) whereas in the second decade the prevalence is substantially higher in girls⁽¹⁵⁾. Often, in children it is more common to find metabolic disorders and recurrence of this disease^{(16 17)}.
Li et al demonstrated in a recent study that individuals whose first stone episode occurred prior to age 20 were more likely to suffer stone recurrence over their life time compared to those whose first episode occurred later in life⁽¹⁸⁾.
Recurrent stones in the pediatric population are associated with more severe complications, and unique genetic disorders are likely to be the cause for this severity⁽¹⁹⁾.
Although the molecular study is difficult due to the complexity of the process, in a recent study it was observed that those with a positive molecular diagnosis were more likely to be associated with a positive family history (OR 2.84, 95% CI 1.29-6.29), nephrocalcinosis (OR 10.6, 95% CI 3.06-36.6, p < 0.001), multiple stones (OR 13.9, 95% CI 6.39-30.2, p < 0.001), bilateral stones (OR 7.04, 95% CI 3.47-14.2, p < 0.001)⁽²⁰⁾.
Spivacow F.R et al. identified metabolic risk factors in almost 90% of children with nephrolithiasis. Of these, 56% had a single biochemical alteration and 36.6% had multiple risk factors⁽²¹⁾. Idiopathic hypercalciuria and hypocitraturia were the most frequent risk factors identified in that study⁽²¹⁾. These findings differ from those published by Kangur et al. where the metabolic disorder found was mainly hyperoxaluria⁽²²⁾.
On the other hand, the inheritance has a clear impact and a percentage of kidney stone formers have positive FH⁽¹⁸⁾. In adults with nephrolithiasis, FH was found in 27% to 50% and these results were independently of the biochemical alterations⁽²³⁾. All these data were also published by our group, but up to now FH in children from our country was unknown and missing.
In our series a FH of kidney stone frequency of 47% was observed. Additionally we have not found differences between male female and FH. The degree of kinship was similar in both sexes. The demographic characteristics of children with and without FH were similar. As far as we have awareness of; this is the first study carried out in our country that reports these backgrounds in children with a single metabolic diagnosis.
Therefore, we hope to provide epidemiological data for a better understanding of the pathology.