The Standard Deviation Score: a novel similarity metric for data analysis

Cluster analysis is a technique for grouping a set of similar objects into one group so that they are not similar to objects in other groups. Cluster analysis is generally applied to objects with numeric data type. but in reality clustering also uses categorical data types. Clustering handling with mixed-type data can be done by applying the k-prototype algorithm, but the determination of cluster center initialization tends to be sensitive. To handle the determination of the initialization of the cluster center, can be applied an algorithm that is genetic algorithm. This study discusses the facilities and infrastructure and health workers in Poso Regency where the infrastructure and legal personnel in the district are adequate but the distribution is not evenly distributed in several areas. The results of this study indicate that in the k-prototype algorithm there are 8 clusters with cluster centers optimized using the genetic algorithm, namely 36,7,99,49,69,104,105,110.

Interpolation of point measurements using geostatistical techniques such as kriging can be used to estimate values at non-sampled locations in space. Traditional geostatistics are based on the spatial autocorrelation concept that nearby things are more related than distant things. In this study, additional information was used to modify the traditional Euclidean concept of distance into an adjusted distance metric that incorporates similarity in terms of quantifiable landscape characteristics such as topography or land use. This new approach was tested by interpolating soil moisture content, pH and carbon-to-nitrogen (C:N) ratio measured in both the mineral and the organic soil layers at a field site in central Sweden. Semivariograms were created using both the traditional distance metrics and the proposed adjusted distance metrics to carry out ordinary kriging (OK) interpolations between sampling points. In addition, kriging with external drift (KED) was used to interpolate soil properties to evaluate the ability of the adjusted distance metric to incorporate secondary data into interpolations. The new adjusted distance metric typically lowered the nugget associated with the semivariogram, thereby better representing small-scale variability in the measured data compared to semivariograms based on the traditional distance metric. The pattern of the resulting kriging interpolations using KED and OK based on the adjusted distance metric were similar because they represented secondary data and, thus, enhanced small-scale variability compared to traditional distance OK. This created interpolations that agreed better with what is expected for the real-world spatial variation of the measured properties. Based on cross-validation error, OK interpolations using the adjusted distance metric better fit observed data than either OK interpolations using traditional distance or KED.

The putative effects of diabetes and metabolic control on circulating levels of insulin-like growth factors (IGFs) and their binding proteins (IGFBPs) remain controversial. In the present study, serum levels of IGF-I and IGF-II and IGFBP-1, -2, and -3 were measured in 58 patients (age, 0.8-17 yr) with treated (51 subjects) or untreated (7 subjects) insulin-dependent diabetes mellitus (IDDM) and were compared with the levels in normal subjects. In the untreated patients IGF-I and IGF-II were decreased as compared with the healthy controls. In the treated diabetics IGF-I and IGF-II were reduced; IGFBP-2 (only in prepubertal subjects) and IGFBP-3 were increased. Furthermore, age-adjusted values of IGF-I, IGF-II, and IGFBP-3 were lower in prepubertal than in pubertal patients. Regression analysis revealed a negative correlation between hemoglobin (Hb)A1c and standard deviation scores (SDS) of IGF-I and a positive association between HbA1c and IGFBP-1 SDS or IGFBP-2 SDS. In the treated patients HbA1c was positively related to IGFBP-1 SDS and IGFBP-2 SDS when applying simple regression analysis and to IGFBP-2 SDS when using a multiple regression model. Strong correlations were observed between height SDS and IGF-I SDS, IGF-II SDS, and IGFBP-3 SDS in prepubertal subjects who had had IDDM for at least 2 yr, but not in adolescents. Such correlations have also been found in healthy children and adolescents. In conclusion; 1) IDDM is associated with alterations of the IGF-IGFBP system, which are partially accounted for by differences in metabolic control and pubertal status; 2) the lower plasma concentrations of serum IGF-I may play a role in the pathogenesis of growth impairment of poorly controlled prepubertal, but not pubertal, children and adolescents with IDDM; and 3) in addition, a potential role of the altered IGF-IGFBP system for the development of diabetic late complications is hypothesized.

Early diagnosis of Turner syndrome (TS) is necessary to facilitate appropriate management, including growth promotion. Not all girls with TS have overt short stature, and comparison with parental height (Ht) is needed for appropriate evaluation. We examined both the prevalence and diagnostic sensitivity of measured parental Ht in a dedicated TS clinic between 1989 and 2013. Lower end of parental target range (LTR) was calculated as mid-parental Ht (correction factor 12.5 cm minus 8.5 cm) and converted to standard deviation scores (SDS) using UK 1990 data, then compared with patient Ht SDS at first accurate measurement aged > 1 year. Information was available in 172 girls of whom 142 (82.6%) were short at first measurement. However, both parents had been measured in only 94 girls (54.6%). In 92 of these girls age at measurement was 6.93 ± 3.9 years, Ht SDS vs LTR SDS − 2.63 ± 0.94 vs − 1.77 ± 0.81 (p < 0.001), Ht SDS < LTR in 78/92 (85%). Eleven of the remaining 14 girls were < 5 years, while karyotype was 45,X/46,XX in 2 and 45,X/47,XXX in 3.Conclusion: This study confirms the sensitivity of evaluating height status against parental height but shows that the latter is not being consistently measured.What is Known:• Girls with Turner syndrome are short in relation to parental heights, with untreated final height approximately 20 cm below female population mean.• Measured parental height is more accurate than reported height.What is New:• In a dedicated Turner clinic, there was 85% sensitivity when comparing patient height standard deviation score at first accurate measurement beyond 1 year of age with the lower end of the parental target range standard deviation.• However, measured height in both parents had been recorded in only 54.6% of the Turner girls attending the clinic. This indicates the need to improve the quality of growth assessment in tertiary care.

Background: A stepwise increment of the GH dose is an approach aimed at avoiding adverse events. We investigated GH sensitivity by studying IGF-I and IGFBP-3 concentrations during the initial phase of GH treatment. Methods: Our investigation was part of the regular follow-up of prepubertal children with GH deficiency (GHD) (n = 31) and small for gestational age (SGA) (n = 23). Dosage was increased in three steps: one-third at the start, two-thirds after 14 days, and the full dose after 28 days (full dose: GHD = 28 µg/kg body weight (BW)/day; SGA = 60 µg/kg BW/day). Blood samples were taken on days 0, 14 and 28, as well as in conjunction with anthropometrical examinations after 3, 6 and 12 months. IGF-I and IGFBP-3 were measured by means of published in-house RIAs and age-related references were used to calculate standard deviation scores (SDS). Height velocity (cm/year) and Δ HT SDS were taken as growth response parameters. Results:Before GH treatment (GHD vs. SGA; median and p values): age (years) (6.6 vs. 6.0; n.s.), HT SDS (–2.6 vs. –3.2; p < 0.05); GH amount after stepping up (µg/kg BW/day) (28 vs. 60; p < 0.01); BW SDS (–0.5 vs. –2.9; p < 0.01); max. GH stimulated (µg/l) (5.6 vs. 10.8; p < 0.01); IGF-I SDS (–3.5 vs. –1.8; p < 0.01); IGFBP-3 SDS (–2.0 vs. 0.8; p < 0.01). After 1 year of GH therapy: HT velocity (cm/year) (9.8 vs. 9.6; n.s.), Δ HT SDS (0.9 vs. 0.9; n.s.); WT velocity (kg/year) (3.3 vs. 3.5; n.s.). Our results show that changes in growth similar to GHD could be induced in SGA by a dosage that was twice as high as the replacement dose given in GHD. GH dose and HT velocity did not correlate in both groups. IGF-I and IGFBP-3 increased as follows in GHD and SGA during stepping up of the dosage (ng/ml, GHD vs. SGA): at start, 54 vs. 89; at day 14, 78 vs. 132; at day 28, 90 vs. 167; at 3 months, 118 vs. 218. There was the same relationship between dose levels and absolute IGF-I concentrations in both groups. In terms of IGF-I SDS, the dose-response curve in SGA showed a shift to the right in comparison to GHD, thus indicating lower sensitivity to GH. The dynamics of IGF-I and IGFBP-3 differed, as IGFBP-3 peaked earlier (on day 28). In GHD, IGF-I SDS at 3 months was –0.7 vs. +0.9 in SGA. Near-identical levels were found for Δ IGF-I SDS and IGFBP-3 SDS above basal levels for each time-point investigated. First year HT velocity in GHD correlated negatively with basal IGF-I SDS (R² = 0.33; p <0.001) and basal IGFBP-3 (R² = 0.17; p <0.05) but did not correlate with the IGF-I increment during the 0- to 3-month period. Conversely, first year HT velocity correlated (+) in SGA with the IGF SDS increment during the 0- to 3-month period (R² = 0.26; p = <0.05). Height velocity in SGA, however, correlated neither with basal IGF-I and IGFBP-3 nor with the 0- to 3-month increments of IGFBP-3 SDS. Conclusions: IGFs increase during initial GH therapy, thus raising questions about short-term IGF generation tests. (I) In terms of IGF generation, substantially lower sensitivity to GH was observable in SGA. (II) Higher GH sensitivity during first year catch-up growth is associated with GHD, but in SGA it is attributable to increases in IGF. A wider range of GH dosages needs to be explored in order to gain further insight into the relationship between GH dose, IGF levels, and growth. Monitoring IGFs is a practical means for exploring GH sensitivity during dosage stepping up.

PurposeTo analyze the effects of clinical and laboratory factors, including insulin-like growth factor (IGF) levels, on the height velocity of normal prepubertal children.MethodsNinety-five healthy prepubertal children (33 boys, 62 girls) were enrolled. The mean chronological age was 6.3±1.4 years, with a height standard deviation score (SDS) of -0.88±0.70. IGF-1, IGF binding protein-3 (IGFBP-3), SDS for anthropometric measurements, and changes in SDS for anthropometric measurements were analyzed for 1 year, and their associations with 1-year height velocity were investigated.ResultsThe group of children with a 1-year height velocity of ≥6 cm were chronologically younger than the group with a 1-year height velocity of <6 cm (5.9±1.3 years vs. 6.7±1.3 years, P=0.004), with a lesser increase of SDS for body mass index (BMI) over 1 year (-0.18±0.68 vs. 0.13±0.53, P=0.014). There were no differences between the 2 groups in IGF-1 SDS and IGFBP-3 SDS. Multiple linear regression showed that baseline chronological age (r=0.243, P=0.026) and height SDS (r=0.236, P=0.030) were positively associated with IGF-1 SDS. Binomial logistic regression showed that an older chronologic age at referral (odds ratio [OR], 0.68; 95% confidence interval [CI], 0.47–0.99) and an increase of BMI SDS over 1 year (OR, 0.41; 95% CI, 0.18–0.89) were associated with a decreased growth possibility of an above-average height velocity (≥6 cm/yr).ConclusionsHeight velocity of normal prepubertal children is affected by an increase of BMI SDS and chronological age. Prepubertal IGF-1 SDS reflects height SDS at the time of measurement but is not associated with subsequent height velocity.

Aim: We determined whether subclassification of short small for gestational age (SGA) children according to birth anthropometrics could delineate different patterns in gestation, delivery, postnatal growth, response to growth hormone (GH) treatment and parental height. Methods: 201 short SGA children were divided into three groups, SGA_L, SGA_L+W and SGA_L+W+HC, according to birth length (L), weight (W) and head circumference (HC) ≤–2.00 standard deviation score (SDS). Results: SGA_L+W+HC children were born after the shortest gestational age and more often by caesarean section than SGA_L children (36.3 vs. 38.1 weeks, 68.4 vs. 24.4%). SGA_L+W children had an intermediate pattern and experienced most gestational hypertension (p = 0.01). At birth, SGA_L+W+HC children were shorter than SGA_L or SGA_L+W (–4.12 vs. –2.67 and –3.72 SDS, p ≤ 0.001). During the first 3 years of life, SGA_L+W+HC children exhibited an increased growth in height (0.98 SDS) and HC (1.28 SDS) than SGA_L (height, –0.06 SDS; HC, –0.30 SDS) and SGA_L+W (height, 0.62 SDS; HC, –0.31 SDS). However, HC SDS remained smaller for SGA_L+W+HC than the other groups at age 3. The groups did not differ in growth response during GH treatment. SGA_L children tended to have shorter parents and target height than SGA_L+W+HC children. Conclusions: Our study shows that subclassification of short SGA children might be a useful method for investigating SGA children as the subgroups revealed a different gestation, delivery and postnatal growth pattern. Response to GH treatment was not different between the groups.

Background/aimsChildren with idiopathic short stature (ISS) constitute a heterogenous group. Recombinant IGF-I (rhIGF-I) have been licensed for the treatment of severe short stature (height <−3 standard deviation scores (SDS)) in...

The primary issue in clustering analysis of multivariate data is the low accuracy resulting from a mismatch between the Distance Metric used and the characteristics of the data. This study aims to comprehensively evaluate the effect of eight Distance Metric in the KMeans algorithm integrated with the Principal Component Analysis (PCA)dimension reduction technique. The analysis process was conducted by transforming the data into two principal components using PCA, then applying K-Means to each Distance Metric. Performance evaluation was conducted based on five internal metrics: Silhouette Score, Davies-Bouldin Index, Sum of Squared Errors, Calinski-Harabasz Index, and Dunn Index. The results show that the Bray-Curtis formula provides the best performance, with a Silhouette Score of 0.4291 and SSE of 30.3673. This is followed by Euclidean and Minkowski, which yield the highest Calinski-Harabasz Index value of 2239.85 and Dunn Index of 0.0108, respectively. In contrast, Hamming’s formula yielded the lowest performance across all metrics, with a Silhouette Score of 0.0000 and an SSE of 1996.00. The ANOVA test revealed significant differences between the Distance Metric, with a p-value of ¡0.000 for all metrics, which was further supported by the Tukey HSD follow-up test results. The implications of these findings confirm the importance of selecting an appropriate Distance Metric in the clustering process to ensure the validity, efficiency, and interpretability of multivariate data analysis results.

BackgroundTrisomy 9p is an uncommon anomaly characterised by mental retardation, head and facial abnormalities, congenital heart defects, kidney abnormalities, and skeletal malformations. Affected children may also show growth and puberty retardation with delayed bone age. Auxological and endocrinological data are lacking for this syndrome.MethodsWe describe three girls and one boy with 9p trisomy showing substantial growth failure, and we evaluate the main causes of their short stature.ResultsThe target height was normal in all families, ranging from 0.1 and -1.2 standard deviation scores (SDS). The patients had a low birth-weight (from -1.2 to -2.4 SDS), birth length (from -1.1 to -3.2 SDS), and head circumference (from -0.5 to -1.6 SDS). All patients presented with substantial growth (height) retardation at the time of 9p trisomy diagnosis (from -3.0 to -3.8 SDS).The growth hormone stimulation test revealed a classic growth hormone (GH) deficiency (GHD) in patients 1, 3, and 4. In contrast, patient 2 was determined to have a GH neurosecretory dysfunction (GHNSD). The plasma concentrations of IGF-I and IGFBP-3 were low in all patients for their ages and sexes (from -2.0 to -3.4 SDS, and from -1.9 to -2.8 SDS, respectively).The auxological follow-up showed that those patients who underwent rhGH treatment exhibited a very good response to the GH therapy, whereas patients 3 and 4, whose families chose not to use rhGH treatment, did not experience any significant catch-up growth.ConclusionsGH deficiency appears to be a possible feature of patients with 9p trisomy syndrome. These patients, particularly those with growth delays, should be evaluated for GH secretion.

Context: The hypothesis that obese children are overdiagnosed with growth hormone deficiency (GHD) has not been adequately investigated in the context of adiposity-related differences in auxology.Aim: To investigate the differences in auxological parameters between short, prepubertal, obese children, and normal-weight peers who underwent growth hormone stimulation testing (GHST).Hypothesis: Over-weight/obese children with GHD [peak growth hormone (GH) < 10 μg/L] will have higher values for growth velocity (GV) standard deviation score (SDS), bone age minus chronological age (BA − CA), and child height SDS minus mid-parental height (MPTH) SDS when compared to normal-weight GHD peers.Subjects and Methods: A retrospective review of anthropometric and provocative GHST data of 67 prepubertal, GH-naïve children of age 10.21 ± 2.56 years (male n = 45, age 10.8 ± 2.60 years; female n = 22, age 8.94 ± 2.10). Inclusion criteria: GHST using arginine and clonidine. Exclusion criteria: hypopituitarism, abnormal pituitary magnetic resonance imaging scan, syndromic obesity, or syndromic short stature. Data were expressed as mean ± SD.Results: The over-weight/obese children with peak GH of <10 μg/L had significantly lower value for natural log (ln) peak GH (1.45 ± 0.09 vs. 1.83 ± 0.35, p = 0.022), but similar values for GV SDS, insulin-like growth factor-I, insulin-like growth factor binding protein-3, bone age, BA − CA, MPTH, and child height SDS minus MPTH SDS compared to normal-weight peers with GHD. After adjusting for covariates, the over-weight/obese children (BMI ≥ 85th percentile) were >7 times more likely than normal-weight subjects (BMI < 85th percentile) to have a peak GH of <10 μg/L, and 23 times more likely to have a peak GH of <7 μg/L (OR = 23.3, p = 0.021). There was a significant inverse relationships between BMI SDS and the ln of peak GH (β = −0.40, r2 = 0.26, p = 0.001), but not for BMI SDS vs. GV SDS, ln peak GH vs. BA, or ln peak GH vs. GV SDS.Conclusion: Subnormal peak GH levels in obese prepubertal children are not associated with unique pre-GHST auxological characteristics.

The risk of osteoporosis or osteopenia is known to increase after childhood cancer treatment. The purpose of this study was to evaluate patterns of bone mineral density (BMD) and factors related to decreased BMD in childhood cancer survivors. We studied 78 patients (34 males, 44 females) treated for acute lymphoblastic leukemia, acute myelogenous leukemia or chronic myelogenous leukemia during childhood. Clinical data, laboratory finding, bone age, lumbar BMD (LBMD) and femur neck BMD (FNBMD) were investigated. Chronological age at evaluation was 11.6±3.4 yr in males and 13.0±3.3 yr in females. Primary disease, chronological age at treatment, body mass index (BMI), method of treatment (chemotherapy, radiotherapy), endocrine function, presence of chronic graft-versus-host disease (cGVHD) and relevance of BMD standard deviation score (SDS) were evaluated. LBMD and FNBMD of the subjects were -0.91±1.41 and -1.13±1.79, respectively. Twenty (25.7%) patients had LBMD SDS lower than -2. Nineteen (24.4%) patients had FNBMD SDS lower than -2. The patients treated with hematopoietic stem cell transplantation had lower LBMD SDS (-1.17±1.39 vs -0.43±1.33, P=0.025). The risk of having LBMD SDS <-2 was higher in the patients treated with glucocorticoid for cGVHD (36.6% vs 13.5%; odds ratio [OR], 3.7; P=0.020). In multivariate logistic regression analysis, longer duration of glucocorticoid treatment (OR, 1.12; 95% confidence interval [CI], 1.03-1.22) and lower BMI SDS (OR, 0.42; 95% CI, 0.21-0.83) were associated with decreased LBMD SDS. These findings suggest that prolonged glucocorticoid use and reduction in BMI are risk factors for decreased BMD in childhood cancer survivors. Anticipatory follow-up and appropriate treatment are necessary, especially for the patients with risk factors.

This study evaluated renal swelling in infants with a first urinary tract infection (UTI) by correlating renal length and volume with C-reactive protein (CRP) and body temperature. Ultrasounds were carried out on 104 infants at The Queen Silvia Children's Hospital, Gothenburg, Sweden - 58 boys (mean age 3.3 months) and 46 girls (mean age 4.8 months) - during the acute phase of their UTI. A second scan was performed on 94 of them 4 weeks later. Renal length and volume were computed to standard deviation scores (SDS). The mean renal length and volume at the first ultrasound were 1.90 SDS (±1.54) and 1.67 SDS (±1.13) for the larger kidney and 0.86 SDS (±1.01) and 0.84 SDS (±0.90) for the smaller kidney. There was a significant decrease in renal length and volume between the two ultrasounds, with a mean difference of 0.96 SDS (±1.24) and 1.07 SDS (±1.10) for the larger kidney (p < 0.0001). The length and volume of the larger kidney correlated with CRP (p < 0.001), but only the renal length correlated with fever (p < 0.001). Early ultrasound determined renal swelling in infants with a UTI and may be a valuable noninvasive way of identifying infants with renal parenchymal involvement.

Electronic health records (EHRs) are an increasingly important source of information for healthcare professionals and researchers. However, EHRs are often fragmented, unstructured, and difficult to analyze due to the heterogeneity of the data sources and the sheer volume of information. Knowledge graphs have emerged as a powerful tool for capturing and representing complex relationships within large datasets. In this study, we explore the use of knowledge graphs to capture and represent complex relationships within EHRs. Specifically, we address the following research question: Can a knowledge graph created using the MIMIC III dataset and GraphDB effectively capture semantic relationships within EHRs and enable more efficient and accurate data analysis? We map the MIMIC III dataset to an ontology using text refinement and Protege; then, we create a knowledge graph using GraphDB and use SPARQL queries to retrieve and analyze information from the graph. Our results demonstrate that knowledge graphs can effectively capture semantic relationships within EHRs, enabling more efficient and accurate data analysis. We provide examples of how our implementation can be used to analyze patient outcomes and identify potential risk factors. Our results demonstrate that knowledge graphs are an effective tool for capturing semantic relationships within EHRs, enabling a more efficient and accurate data analysis. Our implementation provides valuable insights into patient outcomes and potential risk factors, contributing to the growing body of literature on the use of knowledge graphs in healthcare. In particular, our study highlights the potential of knowledge graphs to support decision-making and improve patient outcomes by enabling a more comprehensive and holistic analysis of EHR data. Overall, our research contributes to a better understanding of the value of knowledge graphs in healthcare and lays the foundation for further research in this area.

Poor growth in association with child abuse is well recognised, but the eventual outcome with respect to growth has not been clearly defined. In a study of 95 children who had suffered child abuse standard deviation (SD) scores for height and weight were significantly below the mean at presentation and improved at follow up. Sixty four children who remained at home showed significant increase in height SD scores only (p less than 0.01). Twenty children were either taken into long term fostercare or adopted and showed significant increases in height and weight SD scores (p less than 0.001 and p less than 0.01, respectively). The remaining 11 children, who were fostered for short periods only, showed little change in either index. Catch up growth for height defined as a change in SD scores of one or more occurred in seven (11%) of the children at home compared with 11 (55%) of those taken into long term fostercare (p less than 0.001). Catch up growth for weight occurred in 14 (22%) of those at home and 10 (50%) of those in long term fostercare (p less than 0.01). Children suffering child abuse show greater catch up growth when taken into long term fostercare. Growth patterns should be used to decided where these children are placed.