22
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Impact of antiretroviral treatment on height evolution of HIV infected children

      research-article

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Antiretroviral treatment (ART) has been shown to have a beneficial effect on the weight evolution but its effect on height remains unclear. We described patterns of height evolution and identified predictors of catch-up growth in HIV-infected children on ART.

          Methods

          To describe the height evolution from birth to adulthood, we developed a nonlinear mixed effect model using data from perinatally HIV-infected children who initiated ART from 1999 to 2013 in a prospective cohort study in Thailand. The main covariates of interest were: sex, ART regimen (dual nucleoside reverse-transcriptase inhibitor, non-nucleoside reverse transcriptase inhibitor (NNRTI)-, or protease inhibitor (PI)-based), baseline CD4 percentage, HIV-RNA load and CDC HIV Classification stage and occurrence of AIDS-defining events.

          Results

          A total 477 children (43% boys) contributed 18,596 height measurements over a median duration of 6.3 years on ART (interquartile range, 3.0 to 8.3). At ART initiation, median age was 6.2 years (1.8 to 9.6), 16% of children were underweight (weight-for-age z-score < − 2), 49% presented stunting (height-for-age z-score < − 2), and 7% wasting (weight-for-height z-score < − 2). The most frequent regimen at ART initiation was NNRTI-based (79%). A model with 4 components, birth length and 3 exponential functions of age accounting for the 3 growth phases was developed and show that the height-growth velocity was inversely associated with the age at ART initiation, the adult height was significantly lower in those who had experienced at least one AIDS-defining event while, as expected, the model found that adult height in females was lower than in males. Age at ART initiation, type of ART regimen, CDC stage, CD4 percentages, and HIV-RNA load were not associated with the final height.

          Conclusions

          The younger the children at ART initiation, the greater the effect on height-growth velocity, supporting the World Health Organization’s recommendation to start ART as early as possible. However, final adult height was not linked to the age at ART initiation.

          Electronic supplementary material

          The online version of this article (10.1186/s12887-019-1663-8) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references49

          • Record: found
          • Abstract: found
          • Article: not found

          Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models.

          Informative diagnostic tools are vital to the development of useful mixed-effects models. The Visual Predictive Check (VPC) is a popular tool for evaluating the performance of population PK and PKPD models. Ideally, a VPC will diagnose both the fixed and random effects in a mixed-effects model. In many cases, this can be done by comparing different percentiles of the observed data to percentiles of simulated data, generally grouped together within bins of an independent variable. However, the diagnostic value of a VPC can be hampered by binning across a large variability in dose and/or influential covariates. VPCs can also be misleading if applied to data following adaptive designs such as dose adjustments. The prediction-corrected VPC (pcVPC) offers a solution to these problems while retaining the visual interpretation of the traditional VPC. In a pcVPC, the variability coming from binning across independent variables is removed by normalizing the observed and simulated dependent variable based on the typical population prediction for the median independent variable in the bin. The principal benefit with the pcVPC has been explored by application to both simulated and real examples of PK and PKPD models. The investigated examples demonstrate that pcVPCs have an enhanced ability to diagnose model misspecification especially with respect to random effects models in a range of situations. The pcVPC was in contrast to traditional VPCs shown to be readily applicable to data from studies with a priori and/or a posteriori dose adaptations.
            • Record: found
            • Abstract: found
            • Article: not found

            Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: the npde add-on package for R.

            Pharmacokinetic/pharmacodynamic data are often analysed using nonlinear mixed-effect models, and model evaluation should be an important part of the analysis. Recently, normalised prediction distribution errors (npde) have been proposed as a model evaluation tool. In this paper, we describe an add-on package for the open source statistical package R, designed to compute npde. npde take into account the full predictive distribution of each individual observation and handle multiple observations within subjects. Under the null hypothesis that the model under scrutiny describes the validation dataset, npde should follow the standard normal distribution. Simulations need to be performed before hand, using for example the software used for model estimation. We illustrate the use of the package with two simulated datasets, one under the true model and one with different parameter values, to show how npde can be used to evaluate models. Model estimation and data simulation were performed using NONMEM version 5.1.
              • Record: found
              • Abstract: found
              • Article: not found

              Growth and pubertal development in children and adolescents: effects of diet and physical activity.

              The longitudinal growth of an individual child is a dynamic statement of the general health of that child. Measurements should be performed often and accurately to detect alterations from physiologic growth. Although any single point on the growth chart is not very informative, when several growth points are plotted over time, it should become apparent whether that individual's growth is average, a variant of the norm, or pathologic. Somatic growth and maturation are influenced by several factors that act independently or in concert to modify an individual's genetic growth potential. Linear growth within the first 2 y of life generally decelerates but then remains relatively constant throughout childhood until the onset of the pubertal growth spurt. Because of the wide variation among individuals in the timing of the pubertal growth spurt, there is a wide range of physiologic variations in normal growth. Nutritional status and heavy exercise training are only 2 of the major influences on the linear growth of children. In the United States, nutritional deficits result from self-induced restriction of energy intake. That single factor, added to the marked energy expenditure of training and competition for some sports, and in concert with the self-selection of certain body types, makes it difficult to identify the individual factors responsible for the slow linear growth of some adolescent athletes, for example, those who partake in gymnastics, dance, or wrestling.

                Author and article information

                Contributors
                patrinee@gmail.com
                saik.urien@cch.aphp.fr
                sophie.lecoeur@ined.fr
                sakulrats@yahoo.com
                nakkaratham@gmail.com
                skanjanavanit@gmail.com
                chaiwat008@gmail.com
                yuiwitree@gmail.com
                Nicole.Ngo-Giang-Huong@phpt.org
                marclallemant@gmail.com
                +66 5324 0910 , gonzague.jourdain@ird.fr
                Journal
                BMC Pediatr
                BMC Pediatr
                BMC Pediatrics
                BioMed Central (London )
                1471-2431
                17 August 2019
                17 August 2019
                2019
                : 19
                : 287
                Affiliations
                [1 ]ISNI 0000 0000 9039 7662, GRID grid.7132.7, Department of Statistics, Faculty of Science, , Chiang Mai University, ; Chiang Mai, Thailand
                [2 ]ISNI 0000 0001 2171 2558, GRID grid.5842.b, Pediatric and perinatal pharmacology, , Université de Paris, ; Paris, France
                [3 ]GRID grid.414461.2, Unité de Recherche Clinique Necker Cochin, , AP-HP, Hôpital Tarnier, ; Paris, France
                [4 ]ISNI 0000000121866389, GRID grid.7429.8, CIC1419 INSERM, Cochin-Necker, ; Paris, France
                [5 ]ISNI 0000000122879528, GRID grid.4399.7, Institut de recherche pour le développement (IRD) UMI 174-PHPT, ; Marseille, France
                [6 ]ISNI 0000 0000 9039 7662, GRID grid.7132.7, Faculty of Associated Medical Sciences, , Chiang Mai University, ; Chiang Mai, Thailand
                [7 ]Institut d’Etudes Démographiques, Paris, France
                [8 ]Kalasin Hospital, Kalasin, Thailand
                [9 ]GRID grid.477808.4, Sanpatong Hospital, ; Chiang Mai, Thailand
                [10 ]ISNI 0000 0004 0617 516X, GRID grid.477560.7, Nakornping Hospital, ; Chiang Mai, Thailand
                [11 ]ISNI 0000 0004 0576 179X, GRID grid.415153.7, Prapokklao Hospital, ; Chanthaburi, Thailand
                [12 ]Samutsakhon Hospital, Samutsakhon, Thailand
                [13 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard T.H. Chan School of Public Health, ; Boston, MA USA
                Author information
                http://orcid.org/0000-0002-3365-7020
                Article
                1663
                10.1186/s12887-019-1663-8
                6697969
                011b0edc-5b19-48b8-b345-d95d4fb766f6
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 28 March 2019
                : 7 August 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004417, Global Fund to Fight AIDS, Tuberculosis and Malaria;
                Award ID: PR-A-N-008
                Award Recipient :
                Funded by: Oxfam Great Britain, Thailand
                Award ID: THAA51
                Award Recipient :
                Funded by: Ministry of Public Health, Thailand
                Award ID: -
                Award Recipient :
                Funded by: Institut de Recherche pour le Développement (IRD), France
                Award ID: -
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Pediatrics
                asia, antiretroviral therapy, catch-up growth, height-growth velocity, hiv-infected children, thailand

                Comments

                Comment on this article

                Related Documents Log