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| Name | Class |
|---|---|
| Barts & The London NHS Trust | OTHER |
| Child Growth Foundation | UNKNOWN |
| The Patients Association | UNKNOWN |
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The overarching objective of this research is to detect poor growth and delayed development early in childhood by developing an automated growth-screening algorithm. The screening algorithm will be created using cohort data and piloted for feasibility and acceptability in Tower Hamlets. The ultimate goals are to detect linear growth failure and delayed development early to identify two groups of children: first, children with serious underlying medical disorders, in whom earlier diagnosis and management would improve clinical outcomes; and second, children whose poor growth and/or delayed development is a manifestation of socioeconomic disadvantage, in whom targeted pre-school interventions may improve long term health and education outcomes.
Aim 1, Pilot an automated growth screening algorithm in Tower Hamlets
600 pre-school children at age 2-2.5 years will be enrolled into a pilot screening programme, following written informed parental consent. Children will be identified when they have their 2-2.5 year contact as part of the Healthy Child Programme. As per standard care, measures will be taken of the child's height using a stadiometer and weight using digital weighing scales. In addition to these measurements will be the child's head circumference, their height using a phone App and a record taken of previous anthropometric data including birthweight from the Personal Health Record. Parents' heights will also be recorded where possible. Next, families will be offered an additional height measurement at 3-3.5 years in the community, which is not currently part of standard care. Child height will then be recorded as part of the routine National Child Measurement Programme at 4-5 years of age, and linked to primary care data, enabling the growth-screening algorithm to be applied to these three data-points (2-2.5 years, 3-3.5 years and 4-5 years). At each height measurement the study team will identify the 2% of children with the poorest growth, in whom prior studies show a high prevalence (30-40%) of medical disorders and contact parents to offer referral to the paediatric endocrinology clinic at the Royal London Hospital. The study team will evaluate acceptability and feasibility of the screening and referral process, using parental and healthcare professional questionnaires. There will be an evaluation of the uptake by calculating the proportions screened, referred, investigated in clinic and diagnosed with medical disorders.
Focus group discussions will also be held with caregivers (one in English language and one in Sylheti) and with Health Visitors, to get an idea of how they feel about screening and identify potential barriers to a larger scale roll out.
Aim 2, Generate pilot data to investigate the best indicators to detect poor school readiness and/or developmental problems in early childhood.
As part of routine care, each child's development will be assessed using both the caregiver and professional components of the The Ages & Stages Questionnaire (ASQ-3). Following the 2-2.5 year contact, a subset of children (n = 150) will be invited to attend a separate appointment in the community to have a more detailed developmental assessment to measure gross motor, fine motor, social, language, visual-spatial and practical reasoning skills, conducted or supervised by a child psychologist. These data will be used to conduct sensitivity analyses to test the hypothesis that linear growth failure either alone or in combination with additional factors identifies children with reduced neurodevelopment, who are therefore at risk of poor school attainment.
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| Measure | Description | Time Frame |
|---|---|---|
| Feasibility and acceptability of the screening pilot | Feasibility will be assessed using Bowen et al.'s '8 areas of focus': acceptability, demand, implementation, practicality, adaptation, integration, expansion and limited-efficacy testing. To achieve this, a mixed methods evaluation will be employed including qualitative data collection using focus groups with caregivers and health visitors as well as questionnaires distributed to all caregiver participants in the study and all health visitors involved in growth and development assessments. Quantitative data will be collected on: uptake of growth measurements; number of successful growth and development measurements; number of referrals successfully completed (i.e. referred to child growth clinic with participant attending one clinic appointment); number of participants consenting to identification of their child's anthropometric data from National Child Measurement Programme; and uptake of the phone app. | 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| Linear Growth trajectory and child development | This will be assessed by child height measurements at age 2-2.5 years, age 3-3.5 years, and age 4-5 years, in combination with target parental height. Parents who make use of the app will provide additional longitudinal growth measurements between age 2-5 years. All measurements will be entered into an algorithm, developed using data from two longitudinal United Kingdom cohorts (Millennium Cohort Study and Born in Bradford), which will identify children with poor linear growth based on absolute height, growth velocity and distance from target height. |
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Inclusion Criteria:
Exclusion Criteria:
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Children randomly chosen from London borough of Tower Hamlets, based on Health Visitor records. All children will have height and weight measured as part of standard care by a Health Visitor or nursery nurse in the community, and caregivers are asked to complete a development questionnaire at age 2- 2.5 years as standard. Caregivers will be approached about taking part in the study and given information about what this involves.
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| Name | Affiliation | Role |
|---|---|---|
| Prof Andrew Prendergast, DPhil MRCPCH | Queen Mary | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Tower Hamlets GP Care Group | London | E1 4DG | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 7692826 | Background | Ahmed ML, Allen AD, Sharma A, Macfarlane JA, Dunger DB. Evaluation of a district growth screening programme: the Oxford Growth Study. Arch Dis Child. 1993 Sep;69(3):361-5. doi: 10.1136/adc.69.3.361. | |
| 6870335 | Background | Green AA, MacFarlane JA. Method for the earlier recognition of abnormal stature. Arch Dis Child. 1983 Jul;58(7):535-7. doi: 10.1136/adc.58.7.535. |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | Aug 17, 2023 | May 12, 2025 | Prot_001.pdf |
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| ID | Term |
|---|---|
| D006130 | Growth Disorders |
| ID | Term |
|---|---|
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| 3 years |
| 24731744 | Background | Rogol AD, Hayden GF. Etiologies and early diagnosis of short stature and growth failure in children and adolescents. J Pediatr. 2014 May;164(5 Suppl):S1-14.e6. doi: 10.1016/j.jpeds.2014.02.027. |
| 29375479 | Background | Maghnie M, Labarta JI, Koledova E, Rohrer TR. Short Stature Diagnosis and Referral. Front Endocrinol (Lausanne). 2018 Jan 11;8:374. doi: 10.3389/fendo.2017.00374. eCollection 2017. |
| 24026604 | Background | Sankilampi U, Saari A, Laine T, Miettinen PJ, Dunkel L. Use of electronic health records for automated screening of growth disorders in primary care. JAMA. 2013 Sep 11;310(10):1071-2. doi: 10.1001/jama.2013.218793. No abstract available. |
| 27333805 | Background | Jelenkovic A, Sund R, Hur YM, Yokoyama Y, Hjelmborg JV, Moller S, Honda C, Magnusson PK, Pedersen NL, Ooki S, Aaltonen S, Stazi MA, Fagnani C, D'Ippolito C, Freitas DL, Maia JA, Ji F, Ning F, Pang Z, Rebato E, Busjahn A, Kandler C, Saudino KJ, Jang KL, Cozen W, Hwang AE, Mack TM, Gao W, Yu C, Li L, Corley RP, Huibregtse BM, Derom CA, Vlietinck RF, Loos RJ, Heikkila K, Wardle J, Llewellyn CH, Fisher A, McAdams TA, Eley TC, Gregory AM, He M, Ding X, Bjerregaard-Andersen M, Beck-Nielsen H, Sodemann M, Tarnoki AD, Tarnoki DL, Knafo-Noam A, Mankuta D, Abramson L, Burt SA, Klump KL, Silberg JL, Eaves LJ, Maes HH, Krueger RF, McGue M, Pahlen S, Gatz M, Butler DA, Bartels M, van Beijsterveldt TC, Craig JM, Saffery R, Dubois L, Boivin M, Brendgen M, Dionne G, Vitaro F, Martin NG, Medland SE, Montgomery GW, Swan GE, Krasnow R, Tynelius P, Lichtenstein P, Haworth CM, Plomin R, Bayasgalan G, Narandalai D, Harden KP, Tucker-Drob EM, Spector T, Mangino M, Lachance G, Baker LA, Tuvblad C, Duncan GE, Buchwald D, Willemsen G, Skytthe A, Kyvik KO, Christensen K, Oncel SY, Aliev F, Rasmussen F, Goldberg JH, Sorensen TI, Boomsma DI, Kaprio J, Silventoinen K. Genetic and environmental influences on height from infancy to early adulthood: An individual-based pooled analysis of 45 twin cohorts. Sci Rep. 2016 Jun 23;6:28496. doi: 10.1038/srep28496. |
| 29758562 | Background | Hauer NN, Popp B, Schoeller E, Schuhmann S, Heath KE, Hisado-Oliva A, Klinger P, Kraus C, Trautmann U, Zenker M, Zweier C, Wiesener A, Abou Jamra R, Kunstmann E, Wieczorek D, Uebe S, Ferrazzi F, Buttner C, Ekici AB, Rauch A, Sticht H, Dorr HG, Reis A, Thiel CT. Clinical relevance of systematic phenotyping and exome sequencing in patients with short stature. Genet Med. 2018 Jun;20(6):630-638. doi: 10.1038/gim.2017.159. Epub 2017 Oct 12. |