Objective: Chronic kidney disease (CKD) is associated with growth retardation and delayed pubertal development in the pediatric population. This study aimed to investigate the impact of CKD on growth and pubertal development in children and adolescents by considering factors such as dialysis and transplantation. Methods:A cross-sectional retrospective study was conducted in a cohort of 52 pediatric patients aged 0-18 diagnosed with stages 2-5 CKD, undergoing dialysis treatment or kidney transplantation. Demographic information, clinical characteristics, pubertal development, and treatment methods were also collected. The relationships between these factors and pubertal development were also analyzed. Results:This study revealed significant delays in growth and pubertal development in children and adolescents with CKD. The mean age at menarche was 12.79, and 32.8% of the patients had primary amenorrhea. Patients on dialysis and those who underwent transplantation displayed further growth and pubertal outcomes. Factors such as the CKD stage (r = 0.35, p = 0.02) and age at diagnosis (r = -0.28, p = 0.01) significantly influenced the relationship between CKD and pubertal development. Results were associated with delayed pubertal growth in this population. Conclusion:Our findings underscore the significant impact of CKD on the growth and pubertal development of children and adolescents. Early detection, intervention, and comprehensive management of CKD and its complications could aid in improving growth and pubertal outcomes in this vulnerable population.

BackgroundFatigue is a common problem in patients with rheumatic disease. It may cause disability and poor quality of life (1). Although fatigue and its determinants are studied in several rheumatic diseases, there is no study in Familial Mediterranean Fever (FMF).ObjectivesThe aim of this study is to investigate fatigue in FMF patients as a disabiling symptom and its associations with clinical and demographic variables.MethodsFMF patients were recruited into the study according to FMF Tel Hashomer criteria (2). Control group composed of healthy individuals. Patients who were pregnant or who had concomitant medical illnesses such as cancer, fibromyalgia, or psychiatric conditions such as psychosis or bipolar disorder were excluded. Age, gender, disease duration, education, marital status were noted as demographic features. Number of attacks in the last year, type of attack, involvement of joints, dosage of colchicine, genotype, amyloidosis, and severity of FMF was assessed with PRAS score, visual analogue score of pain (VAS-pain) and VAS-fatigue were used as clinical parameters. Pittsburgh Sleep Quality Index (PSQI), Multidimensional Assessment of Fatigue (MAF), Nottingham Health Profile (NHP), Fatigue Severity Scale (FSS), Fatigue Impact Scale (FIS) and Hospital Anxiety and Depression Scale (HADS) were filled out by both control and study group. Assessment of normality was analyzed with Shapiro-Wilk test. Differences in the mean scores of control and study group were compared with independent samples Mann-Whitney U and Kruskal-Wallis test. Relationship between continuous variables was assessed with Spearman's correlation coefficient (rho).Results61 FMF patients and 61 age, gender (44 female, 17 male in each group) matched controls were enrolled into the study. Mean age of FMF and control group were 35.5±11.8 and 35.8±11.7 years, respectively. The mean disease duration was 82.5±81.7 months. Difference between mean of VAS-pain, VAS-fatigue, PSQI total score, MAF, all subsets of NHP, FSS, FIS, HADS scores of FMF patients were significantly higher than control group (p<0.0001). The correlations between scales assessing fatigue and other outcome measures in FMF patients was shown in Table.Spearman'sCorrelation (rho)VAS.fatigueMAFFSSFIS PSQI.TotalScore0.49***0.53***0.38**0.50***NHP.EnergyLevel0.43***0.65***0.54***0.55***NHP.Pain0.58***0.66***0.56***0.67***NHP.EmotionalReaction0.40**0.54***0.48***0.65***NHP.Sleep0.32*0.240.120.31*NHP.SocialIsolation0.27*0.39**0.50***0.54***NHP.PhysicalAbilities0.51***0.64***0.56***0.69***HADS.Anxiety0.43***0.55***0.52***0.75***HADS.Depression0.30*0.42***0.42***0.57******=p<0.001; **=p<0.01; *=p<0.05.ConclusionsThis study has shown that fatigue in FMF is associated with a number of psychological, sleep, quality of life and disease related factors. FMF group had increased pain, fatigue, sleep disturbance and decreased quality of life compared to control group. FMF patients with fatigue may benefit from pharmacological and psychological interventions which target these factors.References ...