The relationship between 24-h GH secretion, insulin-like growth factor (IGF) I serum levels, IGF-binding protein 3 (IGFBP-3) levels and height was studied in 114 healthy children and adolescents (147 tests). A significant correlation was found between the spontaneous GH secretion expressed as the area under the curve above baseline (AUCb) or the calculated 24-h GH secretion rate (GHb) and IGF-I (n = 147, r = 0.65, or 0.78, respectively, P < 0.001) or IGFBP-3 levels (r = 0.48 or 0.62, P < 0.001). Correlations were also significant within the various subgroups [females (n = 51), males (n = 96), prepubertal children (n = 75), pubertal children (n = 72)]. The slopes of the regression lines of IGF-I levels vs. AUCb or GHb were clearly steeper in pubertal children than in prepubertal ones; this was not as evident with IGFBP-3. In prepubertal children, a significant correlation was found between height (compared to Swedish reference values) standard deviation scores (SDS) and IGF-I SDS (n = 75, r = 0.66, P < 0.001) or IGFBP-3 SDS (r = 0.61, P < 0.001). The reproducibility during repeated testing (19 individuals, 6 prepubertal) was best with IGFBP-3 as compared to AUCb, GHb, or IGF-I which showed considerable variability. The data suggest: 1) that IGF-I and IGFBP-3 serum levels reflect spontaneous GH secretion in healthy individuals; 2) IGF-I levels are more sensitive to GH regulation than IGFBP-3; 3) in puberty, there may be increased sensitivity of IGF-I regulation by GH as compared to the prepubertal stage; 4) short children have low IGF-I and IGFBP-3 levels, whereas tall children have high levels, a fact which is likely to contribute to the understanding of height variability in a healthy population; 5) the good reproducibility of IGFBP-3 on repeated testing makes it an interesting parameter for the evaluation of the GH-IGF-axis. IGFBP-3 measurements may substitute for GH profiles in many cases, when the goal is an estimation of the GH secretion rate.
The relationship between height and amount of GH measured during a 24-h period was studied in 127 children who were growing at different rates. Of the children, 88 were prepubertal (3-16 yr old) and 39 were pubertal (10-16 yr old). The height of each child was expressed as the SD score, i.e. height in relation to the sex- and age-matched Swedish reference groups, and spontaneous GH secretion was estimated by taking integrated 20-min blood samples for a 24-h period, i.e. 72 samples/child. In a few children, discrete samples were taken in parallel with the integrated 20-min samples with virtually the same results. Plasma GH was estimated in each sample using a polyclonal RIA method. To compare different 24-h GH profiles, the profiles were analyzed using a computer program (Pulsar). One objective of the study was to determine if less frequent sampling and/or shorter sampling periods yielded the same information as that obtained by 20-min sampling for the whole 24-h period. To determine if less frequent sampling provided the same information as that obtained by the 20-min period, we simulated 40- and 60-min periods by pooling two or three consecutive samples. No difference was found between 20- and 40-min sampling, but with 60-min sampling the mean calculated baseline plasma GH concentrations increased, and the GH concentration within peaks [the area under the curve above the baseline (AUCb)] decreased markedly. A 30-min sampling interval thus seems to be a valid practical compromise. To determine if sampling periods shorter than 24 h provided the same information, we divided the profiles, which started at 0900 h, into two 12-h, three 8-h and four 6-h periods. A graded decrease in AUCb and a corresponding increase in the baseline was found with the shorter periods, indicating that the whole 24-h period is necessary for GH sampling. Another objective of the study was to determine whether there was a correlation between 24-h GH secretion and the height, age, and sex of the children. In the prepubertal children, the height (in SD scores) was highly correlated (r = 0.69; P less than 0.001) with GH AUCb during the 24-h period. Height also correlated with AUCb estimated over shorter time periods; the correlation diminished with decreasing time. In the pubertal children, a nonlinear correlation (r = 0.36; P less than 0.05) was found between height and 24-h GH (AUCb).(ABSTRACT TRUNCATED AT 400 WORDS)
The aim of the study was to develop and validate models that could predict the growth responses to GH therapy of individual children. Models for prediction of the initial one and 2-y growth response were constructed from a cohort of 269 prepubertal children (Model group) with isolated GH deficiency or idiopathic short stature, using a nonlinear multivariate data fitting technique. Five sets of clinical information were used. The "Basic model" was created using auxological data from the year before the start of GH treatment and parental heights. In addition to Basic model data, the other four models included growth data from the first 2 y of life, or IGF-I, or GH secretion estimated during a provocation test (AITT) or a spontaneous GH secretion profile.The performance of the models was validated by calculating the differences between predicted and observed growth responses in 149 new GH treated children (Validation group) who fulfilled the inclusion criteria used in the original cohort. The SD of these differences (SD res ) in the validation group was compared with the SD res for the model group. For the 1st y, the SD res for the Basic model was 0.28 SDscores. The lowest SD res (0.19 SDscores), giving the most narrow prediction interval, was achieved adding the 24h GH profile and data on growth from the first 2 y of life to the Basic model. The models presented permit estimation of GH responsiveness in children over a broad range in GH secretion, and with an accuracy of the models substantially better than when using maximal GH response during an provocation test. The predicted individual growth response, calculated using a computer program, can serve as a guide for evidence-based decisions when selecting children to GH treatment. Abbreviations GHD, GH deficiency GHI, GH insensitivity ISS, idiopathic short stature IGFBP-3, IGF binding protein 3 AITT, arginin-insulin tolerance test GH max , the estimated maximal GH levelThe diagnosis of severe GH deficiency (GHD) on the one hand or complete GH insensitivity (GHI) on the other, usually is obvious in the short child in whom appropriate studies have excluded other causes for growth failure. Among children forming the continuum between these two extremes, diagnosis is more challenging; that is, children with partial GHD or those considered to have partial GHI, who may be classified as idiopathic short stature (ISS). Despite investigations and discussions aimed at attaining consensus on the diagnostic discrimination between GHD and ISS (1, 2), none of the clinical measures used to date provide a reliable means for categorizing these patients and for predicting the value of GH therapy (3). The effect of the GH axis on statural growth in an individual child depends on the interaction between GH secretion and GH responsiveness. With better understanding of conditions causing GH resistance (4 -7), the need to consider responsiveness to GH, as well as secretion of GH when interpreting the growth of a child has become more apparent.Traditionally, the diagnosis of GHD relies ...
Urine and serum interleukin (IL)-6 and IL-8 responses were higher in children with febrile urinary tract infection (n = 61) than in those with asymptomatic bacteriuria (n = 39). By univariate analysis, cytokine levels were related to age, sex, reflux, renal scarring, urine leukocytes, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and bacterial properties (P fimbriae but not hemolysin). Multivariate modeling showed that urine IL-6 responses were higher in girls than boys, increased with age, and were positively associated with CRP, ESR, serum IL-6, and urine leukocyte counts. The urine IL-8 response was not influenced by age, but it was influenced by P fimbriae and was associated with ESR, CRP, urine leukocytes, and female sex. The results show that cytokine responses to urinary tract infection vary with the severity of infection and that cytokine activation is influenced by a variety of host and bacterial variables.
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