Growth in Virologically Suppressed HIV Positive Children on Antiretroviral Therapy: Individual and Population-Level References
Identifieur interne : 000C94 ( Pmc/Checkpoint ); précédent : 000C93; suivant : 000C95Growth in Virologically Suppressed HIV Positive Children on Antiretroviral Therapy: Individual and Population-Level References
Auteurs : Olivia Keiser [Suisse] ; Nello Blaser [Suisse] ; Mary-Ann Davies [Afrique du Sud] ; Patrick Wessa [Belgique] ; Brian Eley [Afrique du Sud] ; Harry Moultrie [Afrique du Sud] ; Helena Rabie [Afrique du Sud] ; Karl Technau [Afrique du Sud] ; James Ndirangu [Afrique du Sud] ; Daniela Garone [Afrique du Sud] ; Janet Giddy [Afrique du Sud] ; Ashraf Grimwood [Afrique du Sud] ; Thomas Gsponer [Suisse] ; Matthias Egger [Suisse, Afrique du Sud]Source :
- The Pediatric infectious disease journal [ 0891-3668 ] ; 2015.
Abstract
Combination antiretroviral therapy (ART) suppresses viral replication in HIV-infected children. The growth of virologically suppressed children on ART has not been well documented. We aimed to develop dynamic reference curves for weight-for-age z scores (WAZ) and height-for-age z scores (HAZ).
Children aged <11 years at ART initiation with continuously undetectable viral loads (<400 copies/ml) treated at seven South African ART programs with routine viral load monitoring were included. We used multilevel models to define trajectories of WAZ and HAZ up to 3 years and developed a web application to monitor trajectories in individual children.
A total of 4,876 children were followed for 7,407 person-years. Analyses were stratified by baseline z-scores and age, which were the most important predictors of growth response. The youngest children showed the most pronounced increase in weight and height initially but catch-up growth stagnated after 1–2 years. Three years after starting ART, WAZ ranged from −2.2 (95% Prediction interval −5.6 to 0.8) in children with baseline age >5 years and z-score <−3 to 0.0 (−2.7 to 2.4) in children with baseline age <2 years and WAZ >−1. For HAZ the corresponding range was −2.3 (−4.9 to 0.3) in children with baseline age>5 years and z-score <−3 to 0.3 (−3.1 to 3.4) in children with baseline age 2–5 years and HAZ >−1.
We have developed an online tool to calculate reference trajectories in fully suppressed children. The web application could help to define ‘optimal’ growth response and identify children with treatment failure.
Url:
DOI: 10.1097/INF.0000000000000801
PubMed: 26192393
PubMed Central: 4570854
Affiliations:
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<author><name sortKey="Moultrie, Harry" sort="Moultrie, Harry" uniqKey="Moultrie H" first="Harry" last="Moultrie">Harry Moultrie</name>
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<author><name sortKey="Rabie, Helena" sort="Rabie, Helena" uniqKey="Rabie H" first="Helena" last="Rabie">Helena Rabie</name>
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<author><name sortKey="Technau, Karl" sort="Technau, Karl" uniqKey="Technau K" first="Karl" last="Technau">Karl Technau</name>
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<author><name sortKey="Ndirangu, James" sort="Ndirangu, James" uniqKey="Ndirangu J" first="James" last="Ndirangu">James Ndirangu</name>
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<author><name sortKey="Garone, Daniela" sort="Garone, Daniela" uniqKey="Garone D" first="Daniela" last="Garone">Daniela Garone</name>
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<author><name sortKey="Giddy, Janet" sort="Giddy, Janet" uniqKey="Giddy J" first="Janet" last="Giddy">Janet Giddy</name>
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<author><name sortKey="Grimwood, Ashraf" sort="Grimwood, Ashraf" uniqKey="Grimwood A" first="Ashraf" last="Grimwood">Ashraf Grimwood</name>
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<country xml:lang="fr">Afrique du Sud</country>
<wicri:regionArea>Kheth’Impilo, Cape Town</wicri:regionArea>
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<author><name sortKey="Gsponer, Thomas" sort="Gsponer, Thomas" uniqKey="Gsponer T" first="Thomas" last="Gsponer">Thomas Gsponer</name>
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<author><name sortKey="Egger, Matthias" sort="Egger, Matthias" uniqKey="Egger M" first="Matthias" last="Egger">Matthias Egger</name>
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<front><div type="abstract" xml:lang="en"><sec id="S1"><title>Background</title>
<p id="P2">Combination antiretroviral therapy (ART) suppresses viral replication in HIV-infected children. The growth of virologically suppressed children on ART has not been well documented. We aimed to develop dynamic reference curves for weight-for-age z scores (WAZ) and height-for-age z scores (HAZ).</p>
</sec>
<sec id="S2"><title>Methods</title>
<p id="P3">Children aged <11 years at ART initiation with continuously undetectable viral loads (<400 copies/ml) treated at seven South African ART programs with routine viral load monitoring were included. We used multilevel models to define trajectories of WAZ and HAZ up to 3 years and developed a web application to monitor trajectories in individual children.</p>
</sec>
<sec id="S3"><title>Results</title>
<p id="P4">A total of 4,876 children were followed for 7,407 person-years. Analyses were stratified by baseline z-scores and age, which were the most important predictors of growth response. The youngest children showed the most pronounced increase in weight and height initially but catch-up growth stagnated after 1–2 years. Three years after starting ART, WAZ ranged from −2.2 (95% Prediction interval −5.6 to 0.8) in children with baseline age >5 years and z-score <−3 to 0.0 (−2.7 to 2.4) in children with baseline age <2 years and WAZ >−1. For HAZ the corresponding range was −2.3 (−4.9 to 0.3) in children with baseline age>5 years and z-score <−3 to 0.3 (−3.1 to 3.4) in children with baseline age 2–5 years and HAZ >−1.</p>
</sec>
<sec id="S4"><title>Conclusions</title>
<p id="P5">We have developed an online tool to calculate reference trajectories in fully suppressed children. The web application could help to define ‘optimal’ growth response and identify children with treatment failure.</p>
</sec>
</div>
</front>
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<contrib-group><contrib contrib-type="author"><name><surname>Keiser</surname>
<given-names>Olivia</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="author-notes" rid="FN1">*</xref>
<xref ref-type="aff" rid="A1">1</xref>
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<contrib contrib-type="author"><name><surname>Blaser</surname>
<given-names>Nello</given-names>
</name>
<degrees>MSc</degrees>
<xref ref-type="author-notes" rid="FN1">*</xref>
<xref ref-type="aff" rid="A1">1</xref>
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<contrib contrib-type="author"><name><surname>Davies</surname>
<given-names>Mary-Ann</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="A2">2</xref>
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<contrib contrib-type="author"><name><surname>Wessa</surname>
<given-names>Patrick</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Eley</surname>
<given-names>Brian</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Moultrie</surname>
<given-names>Harry</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A5">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Rabie</surname>
<given-names>Helena</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A6">6</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Technau</surname>
<given-names>Karl</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A7">7</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Ndirangu</surname>
<given-names>James</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A8">8</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Garone</surname>
<given-names>Daniela</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A9">9</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Giddy</surname>
<given-names>Janet</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A10">10</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Grimwood</surname>
<given-names>Ashraf</given-names>
</name>
<degrees>MBChBMPH</degrees>
<xref ref-type="aff" rid="A11">11</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Gsponer</surname>
<given-names>Thomas</given-names>
</name>
<degrees>PhD</degrees>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Egger</surname>
<given-names>Matthias</given-names>
</name>
<degrees>MD</degrees>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><collab>for IeDEA Southern Africa</collab>
</contrib>
</contrib-group>
<aff id="A1"><label>1</label>
Institute of Social and Preventive Medicine (ISPM), University of Bern, Switzerland</aff>
<aff id="A2"><label>2</label>
School of Public Health and Family Medicine, University of Cape Town, South Africa</aff>
<aff id="A3"><label>3</label>
Leuven Institute for Research on Information Systems, KU Leuven, Belgium</aff>
<aff id="A4"><label>4</label>
Red Cross War Memorial Children’s Hospital, Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa</aff>
<aff id="A5"><label>5</label>
Wits Reproductive Health and HIV Institute (Harriet Shezi Children’s Clinic, Chris Hani Baragwanath Hospital, Soweto) University of Witwatersrand, Johannesburg, South Africa</aff>
<aff id="A6"><label>6</label>
Tygerberg Academic Hospital, University of Stellenbosch, Stellenbosch, South Africa</aff>
<aff id="A7"><label>7</label>
Empilweni Services and Research Unit (Rahima Moosa Mother and Child Hospital, Johannesburg) and University of Witwatersrand, Johannesburg, South Africa</aff>
<aff id="A8"><label>8</label>
Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Somkhele, South Africa</aff>
<aff id="A9"><label>9</label>
Médecins Sans Frontières (MSF) South Africa, Khayelitsha, Cape Town, South Africa</aff>
<aff id="A10"><label>10</label>
Sinikithemba Clinic, McCord Hospital, Johannesburg, South Africa</aff>
<aff id="A11"><label>11</label>
Kheth’Impilo, Cape Town, South Africa</aff>
<author-notes><corresp id="cor1"><bold>Correspondence to:</bold>
Olivia Keiser, PhD, Institute of Social & Preventive Medicine, University of Bern, CH-3012 Bern, Switzerland, Tel. +41 31 631 35 15, <email>okeiser@ispm.unibe.ch</email>
</corresp>
<fn id="FN1" fn-type="equal"><label>*</label>
<p id="P1">equal contribution</p>
</fn>
</author-notes>
<pub-date pub-type="nihms-submitted"><day>14</day>
<month>6</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="ppub"><month>10</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>01</day>
<month>10</month>
<year>2016</year>
</pub-date>
<volume>34</volume>
<issue>10</issue>
<fpage>e254</fpage>
<lpage>e259</lpage>
<pmc-comment>elocation-id from pubmed: 10.1097/INF.0000000000000801</pmc-comment>
<abstract><sec id="S1"><title>Background</title>
<p id="P2">Combination antiretroviral therapy (ART) suppresses viral replication in HIV-infected children. The growth of virologically suppressed children on ART has not been well documented. We aimed to develop dynamic reference curves for weight-for-age z scores (WAZ) and height-for-age z scores (HAZ).</p>
</sec>
<sec id="S2"><title>Methods</title>
<p id="P3">Children aged <11 years at ART initiation with continuously undetectable viral loads (<400 copies/ml) treated at seven South African ART programs with routine viral load monitoring were included. We used multilevel models to define trajectories of WAZ and HAZ up to 3 years and developed a web application to monitor trajectories in individual children.</p>
</sec>
<sec id="S3"><title>Results</title>
<p id="P4">A total of 4,876 children were followed for 7,407 person-years. Analyses were stratified by baseline z-scores and age, which were the most important predictors of growth response. The youngest children showed the most pronounced increase in weight and height initially but catch-up growth stagnated after 1–2 years. Three years after starting ART, WAZ ranged from −2.2 (95% Prediction interval −5.6 to 0.8) in children with baseline age >5 years and z-score <−3 to 0.0 (−2.7 to 2.4) in children with baseline age <2 years and WAZ >−1. For HAZ the corresponding range was −2.3 (−4.9 to 0.3) in children with baseline age>5 years and z-score <−3 to 0.3 (−3.1 to 3.4) in children with baseline age 2–5 years and HAZ >−1.</p>
</sec>
<sec id="S4"><title>Conclusions</title>
<p id="P5">We have developed an online tool to calculate reference trajectories in fully suppressed children. The web application could help to define ‘optimal’ growth response and identify children with treatment failure.</p>
</sec>
</abstract>
<kwd-group><kwd>HIV</kwd>
<kwd>antiretroviral therapy</kwd>
<kwd>growth</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>Afrique du Sud</li>
<li>Belgique</li>
<li>Suisse</li>
</country>
<region><li>Canton de Berne</li>
</region>
<settlement><li>Berne</li>
</settlement>
<orgName><li>Université de Berne</li>
</orgName>
</list>
<tree><country name="Suisse"><region name="Canton de Berne"><name sortKey="Keiser, Olivia" sort="Keiser, Olivia" uniqKey="Keiser O" first="Olivia" last="Keiser">Olivia Keiser</name>
</region>
<name sortKey="Blaser, Nello" sort="Blaser, Nello" uniqKey="Blaser N" first="Nello" last="Blaser">Nello Blaser</name>
<name sortKey="Egger, Matthias" sort="Egger, Matthias" uniqKey="Egger M" first="Matthias" last="Egger">Matthias Egger</name>
<name sortKey="Gsponer, Thomas" sort="Gsponer, Thomas" uniqKey="Gsponer T" first="Thomas" last="Gsponer">Thomas Gsponer</name>
</country>
<country name="Afrique du Sud"><noRegion><name sortKey="Davies, Mary Ann" sort="Davies, Mary Ann" uniqKey="Davies M" first="Mary-Ann" last="Davies">Mary-Ann Davies</name>
</noRegion>
<name sortKey="Egger, Matthias" sort="Egger, Matthias" uniqKey="Egger M" first="Matthias" last="Egger">Matthias Egger</name>
<name sortKey="Eley, Brian" sort="Eley, Brian" uniqKey="Eley B" first="Brian" last="Eley">Brian Eley</name>
<name sortKey="Garone, Daniela" sort="Garone, Daniela" uniqKey="Garone D" first="Daniela" last="Garone">Daniela Garone</name>
<name sortKey="Giddy, Janet" sort="Giddy, Janet" uniqKey="Giddy J" first="Janet" last="Giddy">Janet Giddy</name>
<name sortKey="Grimwood, Ashraf" sort="Grimwood, Ashraf" uniqKey="Grimwood A" first="Ashraf" last="Grimwood">Ashraf Grimwood</name>
<name sortKey="Moultrie, Harry" sort="Moultrie, Harry" uniqKey="Moultrie H" first="Harry" last="Moultrie">Harry Moultrie</name>
<name sortKey="Ndirangu, James" sort="Ndirangu, James" uniqKey="Ndirangu J" first="James" last="Ndirangu">James Ndirangu</name>
<name sortKey="Rabie, Helena" sort="Rabie, Helena" uniqKey="Rabie H" first="Helena" last="Rabie">Helena Rabie</name>
<name sortKey="Technau, Karl" sort="Technau, Karl" uniqKey="Technau K" first="Karl" last="Technau">Karl Technau</name>
</country>
<country name="Belgique"><noRegion><name sortKey="Wessa, Patrick" sort="Wessa, Patrick" uniqKey="Wessa P" first="Patrick" last="Wessa">Patrick Wessa</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
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