A Digital Health Solution for Child Growth Monitoring at Home: Testing the Accuracy of a Novel “GrowthMonitor” Smartphone Application to Detect Abnormal Height and Body Mass Indices

Objective: To develop and evaluate a smartphone application that accurately measures height and provides notifications when abnormalities are detected. Patients and Methods: A total of 145 (75 boys) participants with a mean age ± SD of 8.7±4.5 years (range, 1.0-17.0 years), from the Children’s Hospital at Barts Health Trust, London, United Kingdom, were enrolled in the study. “GrowthMonitor” (UCL Creatives) iPhone application (GMA) measures height using augmented reality. Using population-based (UK-WHO) references, algorithms calculated height SD score (HSDS), distance from target height (THSDSDEV), and HSDS change over time (ΔHSDS). Pre-established thresholds discriminated normal/abnormal growth. The GMA and a stadiometer (Harpenden; gold standard) measured standing heights of children at routine clinic visits. A subset of parents used GMA to measure their child’s height at home. Outcome targets were 95% of GMA measurements within ±0.5 SDS of the stadiometer and the correct identification of abnormal HSDS, THSDSDEV, and ΔHSDS. Results: Bland-Altman plots revealed no appreciable bias in differences between paired study team GMA and stadiometer height measurements, with a mean of the differences of 0.11 cm with 95% limits of agreement of −2.21 to 2.42 cm. There was no evidence of greater bias occurring for either shorter/younger children or taller/older children. The 2 methods of measurements were highly correlated (R=0.999). GrowthMonitor iPhone application measurements performed by parents in clinic and at home were slightly less accurate. The κ coefficient indicated reliable and consistent agreement of flag alerts for HSDS (κ=0.74) and THSDSDEV (κ=0.88) between 83 paired GMA and stadiometer measurements. GrowthMonitor iPhone application yielded a detection rate of 96% and 97% for HSDS-based and THSDSDEV-based red flags, respectively. Forty-two (18 boys) participants had GMA calculated ΔHSDS using an additional height measurement 6-16 months later, and no abnormal flag alerts were triggered for ΔHSDS values. Conclusion: GrowthMonitor iPhone application provides the potential for parents/carers and health care professionals to capture serial height measurements at home and without specialized equipment. Reliable interpretation and flagging of abnormal measurements indicate the potential of this technology to transform childhood growth monitoring

Genetic evaluation supports differential diagnosis in adolescent patients with delayed puberty

Context: Pubertal delay can be the clinical presentation of both idiopathic hypogonadotropic hypogonadism (IHH) and self-limited delayed puberty (SLDP). Distinction between these conditions is a common but important diagnostic challenge in adolescents. Objective: To assess whether gene panel testing can assist with clinical differential diagnosis and to allow accurate and timely management of delayed puberty patients. Design: Retrospective study. Methods: Patients presenting with delayed puberty to UK Paediatric services, followed up to final diagnosis, were included. Whole-exome sequencing was analysed using a virtual panel of genes previously reported to cause either IHH or SLDP to identify rarely predicted deleterious variants. Deleterious variants were verified by in silico prediction tools. The correlation between clinical and genotype diagnosis was analysed. Results: Forty-six patients were included, 54% with a final clinical diagnosis of SLDP and 46% with IHH. Red flags signs of IHH were present in only three patients. Fifteen predicted deleterious variants in 12 genes were identified in 33% of the cohort, with most inherited in a heterozygous manner. A fair correlation between final clinical diagnosis and genotypic diagnosis was found. Panel testing was able to confirm a diagnosis of IHH in patients with pubertal delay. Genetic analysis identified three patients with IHH that had been previously diagnosed as SLDP. Conclusion: This study supports the use of targeted exome sequencing in the clinical setting to aid the differential diagnosis between IHH and SLDP in adolescents presenting with pubertal delay. Genetic evaluation thus facilitates earlier and more precise diagnosis, allowing clinicians to direct treatment appropriately

Whole-exome sequencing gives additional benefits compared to candidate gene sequencing in the molecular diagnosis of children with growth hormone or IGF-1 insensitivity

Ipsen UK!(HLS). Sandoz Pharmaceutical

Short stature and language development in the United Kingdom: a longitudinal analysis of children from the Millennium Cohort Study.

BACKGROUND: In low- and middle-income countries, poverty and impaired growth prevent children from meeting their cognitive developmental potential. There are few studies investigating these relationships in high-income settings. METHODS: Participants were 12,536 children born between 2000 and 2002 in the UK and participating in the Millennium Cohort Study (MCS). Short stature was defined as having a height-for-age 2 or more standard deviations below the median (≤ - 2 SDS) at age 3 years. Standardized British Abilities Scales II (BAS II) language measures, used to assess language development at ages 3, 5, 7 and 11 years, were the main outcome assessed. RESULTS: Children with short stature at age 3 years (4.1%) had language development scores that were consistently lower from ages 3 to 11 years (- 0.26 standard deviations (SD) (95% CI - 0.37, - 0.15)). This effect was attenuated but remained significant after adjustment for covariates. Trajectory analysis produced four distinct patterns of language development scores (low-declining, low-improving, average and high). Multinomial logistic regression models showed that children with short stature had a higher risk of being in the low-declining group, relative to the average group (relative risk ratio (RRR) = 2.11 (95% CI 1.51, 2.95)). They were also less likely to be in the high-scoring group (RRR = 0.65 (0.52, 0.82)). Children with short stature at age 3 years who had 'caught up' by age 5 years (height-for-age ≥ 2 SDS) did not have significantly different scores from children with persistent short stature, but had a higher probability of being in the high-performing group than children without catch-up growth (RRR = 1.84 (1.11, 3.07)). CONCLUSIONS: Short stature at age 3 years was associated with lower language development scores at ages 3 to 11 years in UK children. These associations remained significant after adjustment for socioeconomic, child and parental factors

Regional differences in short stature in England between 2006 and 2019: A cross-sectional analysis from the National Child Measurement Programme.

BACKGROUND: Short stature, defined as height for age more than 2 standard deviations (SDs) below the population median, is an important indicator of child health. Short stature (often termed stunting) has been widely researched in low- and middle-income countries (LMICs), but less is known about the extent and burden in high-income settings. We aimed to map the prevalence of short stature in children aged 4-5 years in England between 2006 and 2019. METHODS AND FINDINGS: We used data from the National Child Measurement Programme (NCMP) for the school years 2006-2007 to 2018-2019. All children attending state-maintained primary schools in England are invited to participate in the NCMP, and heights from a total of 7,062,071 children aged 4-5 years were analysed. We assessed short stature, defined as a height-for-age standard deviation score (SDS) below -2 using the United Kingdom WHO references, by sex, index of multiple deprivation (IMD), ethnicity, and region. Geographic clustering of short stature was analysed using spatial analysis in SaTScan. The prevalence of short stature in England was 1.93% (95% confidence interval (CI) 1.92-1.94). Ethnicity adjusted spatial analyses showed geographic heterogeneity of short stature, with high prevalence clusters more likely in the North and Midlands, leading to 4-fold variation between local authorities (LAs) with highest and lowest prevalence of short stature. Short stature was linearly associated with IMD, with almost 2-fold higher prevalence in the most compared with least deprived decile (2.56% (2.53-2.59) vs. 1.38% (1.35-1.41)). There was ethnic heterogeneity: Short stature prevalence was lowest in Black children (0.64% (0.61-0.67)) and highest in Indian children (2.52% (2.45-2.60)) and children in other ethnic categories (2.57% (2.51-2.64)). Girls were more likely to have short stature than boys (2.09% (2.07-2.10) vs. 1.77% (1.76-1.78), respectively). Short stature prevalence declined over time, from 2.03% (2.01-2.05) in 2006-2010 to 1.82% (1.80-1.84) in 2016-2019. Short stature declined at all levels of area deprivation, with faster declines in more deprived areas, but disparities by IMD quintile were persistent. This study was conducted cross-sectionally at an area level, and, therefore, we cannot make any inferences about the individual causes of short stature. CONCLUSIONS: In this study, we observed a clear social gradient and striking regional variation in short stature across England, including a North-South divide. These findings provide impetus for further investigation into potential socioeconomic influences on height and the factors underlying regional variation