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Background Patient and Public Involvement (PPI) is a rich and valuable part of the process of planning, designing, carrying out and disseminating research. It is important to communicate PPI findings in detail so that the contributions of those involved are fully utilised and disseminated. The extended and iterative PPI process used within a neonatal randomised controlled trial related to the expression of breastmilk after very preterm birth is reported here. Methods Seven iterative stages of PPI were used. Stage 1 was informal PPI using historical interaction with parents and publicly available resources. Stage 2 was an online questionnaire open to parents of premature babies and advertised via a charity collaborator. Stage 3 was partnership with a charity collaborator. Stage 4 was a set of online panels focusing on study design and documents. Stage 5 was an interactive exercise to modify the trial intervention. Stage 6 is the presence of PPI contributors on the trial steering committee. Stage 7 is a dissemination panel. At each stage attention was paid to the diversity of participants involved, with strategies to increase the involvement of parents from under-reached groups. Results Six hundred and seventy-five participants responded at Stage 2, six parents were involved at Stage 4 and 12 parents at Stage 5. PPI contributed to the choice of study question, outcomes and produced a set of questions for future research. PPI impacted on the study design, with specific emphasis on reducing participant distress related to lactation, and reducing the burden of being involved in research at a time of significant stress. Conclusions PPI had a far-reaching influence on this neonatal randomised controlled trial during the planning and design phase, which reinforces the importance of PPI at the earliest stages of the research cycle. The online questionnaire format elicited an unexpectedly deep and broad pool of transferable insights, which will have an impact on future research focus and design in the area of lactation and prematurity. Approaches to increasing PPI involvement from under-reached populations are important and can be successful despite resource constraints.

Background Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by muscle atrophy and weakness. SMA type 1 (SMA1) is the most severe form: affected infants are unable to sit unaided; SMA type 2 (SMA2) children can sit, but are not able to walk independently. The Standards of Care has improved quality of life and the increasing availability of disease-modifying treatments is progressively changing the natural history; so, the clinical assessment of nutritional status has become even more crucial. Aims of this multicenter study were to present the growth pattern of treatment-naïve SMA1 and SMA2, and to compare it with the general growth standards. Results Body Weight (BW, kg) and Supine Length (SL, cm) were collected using a published standardized procedure. SMA-specific growth percentiles curves were developed and compared to the WHO reference data. We recruited 133 SMA1 and 82 SMA2 (48.8% females). Mean ages were 0.6 (0.4–1.6) and 4.1 (2.1–6.7) years, respectively. We present here a set of disease-specific percentiles curves of BW, SL, and BMI-for-age for girls and boys with SMA1 and SMA2. These curves show that BW is significantly lower in SMA than healthy peers, while SL is more variable. BMI is also typically lower in both sexes and at all ages. Conclusions These data on treatment-naïve patients point toward a better understanding of growth in SMA and could be useful to improve the clinical management and to assess the efficacy of the available and forthcoming therapies not only on motor function, but also on growth. Supplementary Information The online version contains supplementary material available at 10.1186/s13023-021-02015-9.

Objectives\ud To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment.\ud \ud Design\ud Individual participant data meta-analysis.\ud \ud Setting\ud Four population based cross sectional studies and a fifth study for external validation, United Kingdom.\ud \ud Participants\ud A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass.\ud \ud Main outcome measure\ud Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model’s predictive performance within the four development studies; external validation followed using the fifth dataset.\ud \ud Results\ud Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R2: 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R2: 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was −1.29 kg (95% confidence interval −1.62 to −0.96 kg).\ud \ud Conclusion\ud The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity.

IntroductionPreterm and small for gestational age (SGA) infants are at increased risk of poor growth, disability and delayed development. While growing up they are also at increased risk of obesity, diabetes and later heart disease. The risk of such adverse outcomes may be altered by how preterm and SGA infants are fed after birth. Faltering postnatal growth is common due to failure to achieve recommended high energy and protein intakes, and thus preterm and SGA infants are often provided with supplemental nutrition soon after birth. Enhanced nutrition has been associated with improved early growth and better cognitive development. However, limited evidence suggests that faster growth may increase the risk for later adiposity, metabolic and cardiovascular disease, and that such risks may differ between girls and boys.Methods and analysisWe will search Ovid MEDLINE, Embase, Cochrane CENTRAL, Cochrane Database of Systematic Reviews, controlled-trials.com, ClinicalTrials.gov and anzctr.org.au for randomised trials that studied the effects of macronutrient supplements for preterm and SGA infants on (i) developmental and metabolic and (ii) growth outcomes after hospital discharge. The outcomes will be (i) cognitive impairment and metabolic risk (co-primary) and (ii) body mass index. Individual participant data (IPD) from all available trials will be included using an intention-to-treat approach. A one-stage procedure for IPD meta-analysis (MA) will be used, accounting for clustering of participants within studies. Exploratory subgroup analyses will further investigate sources of heterogeneity, including sex and size of infants, different timing, duration and type of supplements.Ethics and disseminationThis IPD-MA is approved by the University of Auckland Human Participants Ethics Committee (reference number: 019874). Individual studies have approval from relevant local ethics committees. Results will be disseminated in a peer-reviewed journal and presented at international conferences.PROSPERO registration numberCRD42017072683