Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants
Identifieur interne : 000939 ( Pmc/Corpus ); précédent : 000938; suivant : 000940Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants
Auteurs : Mary T. Caserta ; Hongmei Yang ; Sanjukta Bandyopadhyay ; Xing Qiu ; Steven R. Gill ; James Java ; Andrew Mcdavid ; Ann R. Falsey ; David J. Topham ; Jeanne Holden-Wiltse ; Kristin Scheible ; Gloria PryhuberSource :
- The Journal of Pediatrics [ 0022-3476 ] ; 2019.
Abstract
To develop a valid research tool to measure infant respiratory illness severity using parent-reported symptoms.
Nose and throat swabs were collected monthly for 1 year and during respiratory illnesses for 2 years in a prospective study of term and preterm infants in the Prematurity, Respiratory Outcomes, Immune System and Microbiome study. Viral pathogens were detected using Taqman Array Cards. Parents recorded symptoms during respiratory illnesses using a Childhood Origins of Asthma (COAST) scorecard. The COAST score was validated using linear mixed effects regression modeling to evaluate associations with hospitalization and specific infections. A data-driven method was also used to compute symptom weights and derive a new score, the Infant Research Respiratory Infection Severity Score (IRRISS). Linear mixed effects regression modeling was repeated with the IRRISS illness data.
From April 2013 to April 2017, 50 term, 40 late preterm, and 28 extremely low gestational age (<29 weeks of gestation) infants had 303 respiratory illness visits with viral testing and parent-reported symptoms. A range of illness severity was described with 39% of illness scores suggestive of severe disease. Both the COAST score and IRRISS were associated with respiratory syncytial virus infection and hospitalization. Gestational age and human rhinovirus infection were inversely associated with both scoring systems. The IRRISS and COAST scores were highly correlated (r = 0.93;
Using parent-reported symptoms, we validated the COAST score as a measure of respiratory illness severity in infants. The new IRRISS score performed as well as the COAST score.
Url:
DOI: 10.1016/j.jpeds.2019.06.061
PubMed: 31377041
PubMed Central: 6815715
Links to Exploration step
PMC:6815715Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants</title><author><name sortKey="Caserta, Mary T" sort="Caserta, Mary T" uniqKey="Caserta M" first="Mary T." last="Caserta">Mary T. Caserta</name><affiliation><nlm:aff id="aff1">Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Yang, Hongmei" sort="Yang, Hongmei" uniqKey="Yang H" first="Hongmei" last="Yang">Hongmei Yang</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Bandyopadhyay, Sanjukta" sort="Bandyopadhyay, Sanjukta" uniqKey="Bandyopadhyay S" first="Sanjukta" last="Bandyopadhyay">Sanjukta Bandyopadhyay</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Qiu, Xing" sort="Qiu, Xing" uniqKey="Qiu X" first="Xing" last="Qiu">Xing Qiu</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Gill, Steven R" sort="Gill, Steven R" uniqKey="Gill S" first="Steven R." last="Gill">Steven R. Gill</name><affiliation><nlm:aff id="aff3">Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Java, James" sort="Java, James" uniqKey="Java J" first="James" last="Java">James Java</name><affiliation><nlm:aff id="aff3">Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Mcdavid, Andrew" sort="Mcdavid, Andrew" uniqKey="Mcdavid A" first="Andrew" last="Mcdavid">Andrew Mcdavid</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Falsey, Ann R" sort="Falsey, Ann R" uniqKey="Falsey A" first="Ann R." last="Falsey">Ann R. Falsey</name><affiliation><nlm:aff id="aff4">Department of Medicine-Infectious Diseases, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Topham, David J" sort="Topham, David J" uniqKey="Topham D" first="David J." last="Topham">David J. Topham</name><affiliation><nlm:aff id="aff5">Center for Vaccine Biology and Immunology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Holden Wiltse, Jeanne" sort="Holden Wiltse, Jeanne" uniqKey="Holden Wiltse J" first="Jeanne" last="Holden-Wiltse">Jeanne Holden-Wiltse</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation><affiliation><nlm:aff id="aff7">UR Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Scheible, Kristin" sort="Scheible, Kristin" uniqKey="Scheible K" first="Kristin" last="Scheible">Kristin Scheible</name><affiliation><nlm:aff id="aff1">Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Pryhuber, Gloria" sort="Pryhuber, Gloria" uniqKey="Pryhuber G" first="Gloria" last="Pryhuber">Gloria Pryhuber</name><affiliation><nlm:aff id="aff1">Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation><affiliation><nlm:aff id="aff6">Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">31377041</idno><idno type="pmc">6815715</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815715</idno><idno type="RBID">PMC:6815715</idno><idno type="doi">10.1016/j.jpeds.2019.06.061</idno><date when="2019">2019</date><idno type="wicri:Area/Pmc/Corpus">000939</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000939</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants</title><author><name sortKey="Caserta, Mary T" sort="Caserta, Mary T" uniqKey="Caserta M" first="Mary T." last="Caserta">Mary T. Caserta</name><affiliation><nlm:aff id="aff1">Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Yang, Hongmei" sort="Yang, Hongmei" uniqKey="Yang H" first="Hongmei" last="Yang">Hongmei Yang</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Bandyopadhyay, Sanjukta" sort="Bandyopadhyay, Sanjukta" uniqKey="Bandyopadhyay S" first="Sanjukta" last="Bandyopadhyay">Sanjukta Bandyopadhyay</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Qiu, Xing" sort="Qiu, Xing" uniqKey="Qiu X" first="Xing" last="Qiu">Xing Qiu</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Gill, Steven R" sort="Gill, Steven R" uniqKey="Gill S" first="Steven R." last="Gill">Steven R. Gill</name><affiliation><nlm:aff id="aff3">Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Java, James" sort="Java, James" uniqKey="Java J" first="James" last="Java">James Java</name><affiliation><nlm:aff id="aff3">Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Mcdavid, Andrew" sort="Mcdavid, Andrew" uniqKey="Mcdavid A" first="Andrew" last="Mcdavid">Andrew Mcdavid</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Falsey, Ann R" sort="Falsey, Ann R" uniqKey="Falsey A" first="Ann R." last="Falsey">Ann R. Falsey</name><affiliation><nlm:aff id="aff4">Department of Medicine-Infectious Diseases, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Topham, David J" sort="Topham, David J" uniqKey="Topham D" first="David J." last="Topham">David J. Topham</name><affiliation><nlm:aff id="aff5">Center for Vaccine Biology and Immunology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Holden Wiltse, Jeanne" sort="Holden Wiltse, Jeanne" uniqKey="Holden Wiltse J" first="Jeanne" last="Holden-Wiltse">Jeanne Holden-Wiltse</name><affiliation><nlm:aff id="aff2">Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation><affiliation><nlm:aff id="aff7">UR Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Scheible, Kristin" sort="Scheible, Kristin" uniqKey="Scheible K" first="Kristin" last="Scheible">Kristin Scheible</name><affiliation><nlm:aff id="aff1">Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author><author><name sortKey="Pryhuber, Gloria" sort="Pryhuber, Gloria" uniqKey="Pryhuber G" first="Gloria" last="Pryhuber">Gloria Pryhuber</name><affiliation><nlm:aff id="aff1">Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation><affiliation><nlm:aff id="aff6">Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY</nlm:aff></affiliation></author></analytic><series><title level="j">The Journal of Pediatrics</title><idno type="ISSN">0022-3476</idno><idno type="eISSN">1097-6833</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Objective</title><p>To develop a valid research tool to measure infant respiratory illness severity using parent-reported symptoms.</p></sec><sec><title>Study design</title><p>Nose and throat swabs were collected monthly for 1 year and during respiratory illnesses for 2 years in a prospective study of term and preterm infants in the Prematurity, Respiratory Outcomes, Immune System and Microbiome study. Viral pathogens were detected using Taqman Array Cards. Parents recorded symptoms during respiratory illnesses using a Childhood Origins of Asthma (COAST) scorecard. The COAST score was validated using linear mixed effects regression modeling to evaluate associations with hospitalization and specific infections. A data-driven method was also used to compute symptom weights and derive a new score, the Infant Research Respiratory Infection Severity Score (IRRISS). Linear mixed effects regression modeling was repeated with the IRRISS illness data.</p></sec><sec><title>Results</title><p>From April 2013 to April 2017, 50 term, 40 late preterm, and 28 extremely low gestational age (<29 weeks of gestation) infants had 303 respiratory illness visits with viral testing and parent-reported symptoms. A range of illness severity was described with 39% of illness scores suggestive of severe disease. Both the COAST score and IRRISS were associated with respiratory syncytial virus infection and hospitalization. Gestational age and human rhinovirus infection were inversely associated with both scoring systems. The IRRISS and COAST scores were highly correlated (r = 0.93; <italic>P</italic> < .0001).</p></sec><sec><title>Conclusions</title><p>Using parent-reported symptoms, we validated the COAST score as a measure of respiratory illness severity in infants. The new IRRISS score performed as well as the COAST score.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Monto, A S" uniqKey="Monto A">A.S. Monto</name></author><author><name sortKey="Malosh, R E" uniqKey="Malosh R">R.E. Malosh</name></author><author><name sortKey="Petrie, J G" uniqKey="Petrie J">J.G. Petrie</name></author><author><name sortKey="Thompson, M G" uniqKey="Thompson M">M.G. Thompson</name></author><author><name sortKey="Ohmit, S E" uniqKey="Ohmit S">S.E. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Pediatr</journal-id><journal-id journal-id-type="iso-abbrev">J. Pediatr</journal-id><journal-title-group><journal-title>The Journal of Pediatrics</journal-title></journal-title-group><issn pub-type="ppub">0022-3476</issn><issn pub-type="epub">1097-6833</issn><publisher><publisher-name>Mosby</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">31377041</article-id><article-id pub-id-type="pmc">6815715</article-id><article-id pub-id-type="publisher-id">S0022-3476(19)30825-X</article-id><article-id pub-id-type="doi">10.1016/j.jpeds.2019.06.061</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Measuring the Severity of Respiratory Illness in the First 2 Years of Life in Preterm and Term Infants</article-title></title-group><contrib-group><contrib contrib-type="author" id="au1"><name><surname>Caserta</surname><given-names>Mary T.</given-names></name><degrees>MD</degrees><email>mary_caserta@urmc.rochester.edu</email><xref rid="aff1" ref-type="aff">1</xref><xref rid="cor1" ref-type="corresp">∗</xref></contrib><contrib contrib-type="author" id="au2"><name><surname>Yang</surname><given-names>Hongmei</given-names></name><degrees>PhD</degrees><xref rid="aff2" ref-type="aff">2</xref></contrib><contrib contrib-type="author" id="au3"><name><surname>Bandyopadhyay</surname><given-names>Sanjukta</given-names></name><degrees>MS</degrees><xref rid="aff2" ref-type="aff">2</xref></contrib><contrib contrib-type="author" id="au4"><name><surname>Qiu</surname><given-names>Xing</given-names></name><degrees>PhD</degrees><xref rid="aff2" ref-type="aff">2</xref></contrib><contrib contrib-type="author" id="au5"><name><surname>Gill</surname><given-names>Steven R.</given-names></name><degrees>PhD</degrees><xref rid="aff3" ref-type="aff">3</xref></contrib><contrib contrib-type="author" id="au6"><name><surname>Java</surname><given-names>James</given-names></name><degrees>PhD</degrees><xref rid="aff3" ref-type="aff">3</xref></contrib><contrib contrib-type="author" id="au7"><name><surname>McDavid</surname><given-names>Andrew</given-names></name><degrees>PhD</degrees><xref rid="aff2" ref-type="aff">2</xref></contrib><contrib contrib-type="author" id="au8"><name><surname>Falsey</surname><given-names>Ann R.</given-names></name><degrees>MD</degrees><xref rid="aff4" ref-type="aff">4</xref></contrib><contrib contrib-type="author" id="au9"><name><surname>Topham</surname><given-names>David J.</given-names></name><degrees>PhD</degrees><xref rid="aff5" ref-type="aff">5</xref></contrib><contrib contrib-type="author" id="au10"><name><surname>Holden-Wiltse</surname><given-names>Jeanne</given-names></name><degrees>MPH</degrees><xref rid="aff2" ref-type="aff">2</xref><xref rid="aff7" ref-type="aff">7</xref></contrib><contrib contrib-type="author" id="au11"><name><surname>Scheible</surname><given-names>Kristin</given-names></name><degrees>MD</degrees><xref rid="aff1" ref-type="aff">1</xref></contrib><contrib contrib-type="author" id="au12"><name><surname>Pryhuber</surname><given-names>Gloria</given-names></name><degrees>MD</degrees><xref rid="aff1" ref-type="aff">1</xref><xref rid="aff6" ref-type="aff">6</xref></contrib></contrib-group><aff id="aff1"><label>1</label>Department of Pediatrics, University of Rochester Medical Center, Rochester, NY</aff><aff id="aff2"><label>2</label>Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY</aff><aff id="aff3"><label>3</label>Department of Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY</aff><aff id="aff4"><label>4</label>Department of Medicine-Infectious Diseases, University of Rochester Medical Center, Rochester, NY</aff><aff id="aff5"><label>5</label>Center for Vaccine Biology and Immunology, University of Rochester Medical Center, Rochester, NY</aff><aff id="aff6"><label>6</label>Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY</aff><aff id="aff7"><label>7</label>UR Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester, NY</aff><author-notes><corresp id="cor1"><label>∗</label>Reprint requests: Mary T. Caserta, MD, Division of Pediatric Infectious Diseases, 601 Elmwood Ave, Box 690, Rochester, NY 14642. <email>mary_caserta@urmc.rochester.edu</email></corresp></author-notes><pub-date pub-type="pmc-release"><day>31</day><month>7</month><year>2019</year></pub-date><pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="ppub"><month>11</month><year>2019</year></pub-date><pub-date pub-type="epub"><day>31</day><month>7</month><year>2019</year></pub-date><volume>214</volume><fpage>12</fpage><lpage>19.e3</lpage><history><date date-type="received"><day>4</day><month>3</month><year>2019</year></date><date date-type="rev-recd"><day>10</day><month>6</month><year>2019</year></date><date date-type="accepted"><day>25</day><month>6</month><year>2019</year></date></history><permissions><copyright-statement>© 2019 Elsevier Inc. All rights reserved.</copyright-statement><copyright-year>2019</copyright-year><copyright-holder>Elsevier Inc.</copyright-holder><license><license-p>Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.</license-p></license></permissions><related-article related-article-type="article-reference" id="d32e579" ext-link-type="doi" xlink:href="10.1016/j.jpeds.2019.09.039"></related-article><abstract id="abs0010"><sec><title>Objective</title><p>To develop a valid research tool to measure infant respiratory illness severity using parent-reported symptoms.</p></sec><sec><title>Study design</title><p>Nose and throat swabs were collected monthly for 1 year and during respiratory illnesses for 2 years in a prospective study of term and preterm infants in the Prematurity, Respiratory Outcomes, Immune System and Microbiome study. Viral pathogens were detected using Taqman Array Cards. Parents recorded symptoms during respiratory illnesses using a Childhood Origins of Asthma (COAST) scorecard. The COAST score was validated using linear mixed effects regression modeling to evaluate associations with hospitalization and specific infections. A data-driven method was also used to compute symptom weights and derive a new score, the Infant Research Respiratory Infection Severity Score (IRRISS). Linear mixed effects regression modeling was repeated with the IRRISS illness data.</p></sec><sec><title>Results</title><p>From April 2013 to April 2017, 50 term, 40 late preterm, and 28 extremely low gestational age (<29 weeks of gestation) infants had 303 respiratory illness visits with viral testing and parent-reported symptoms. A range of illness severity was described with 39% of illness scores suggestive of severe disease. Both the COAST score and IRRISS were associated with respiratory syncytial virus infection and hospitalization. Gestational age and human rhinovirus infection were inversely associated with both scoring systems. The IRRISS and COAST scores were highly correlated (r = 0.93; <italic>P</italic> < .0001).</p></sec><sec><title>Conclusions</title><p>Using parent-reported symptoms, we validated the COAST score as a measure of respiratory illness severity in infants. The new IRRISS score performed as well as the COAST score.</p></sec></abstract><kwd-group id="kwrds0010"><title>Abbreviations</title><kwd>AUC, Area under the curve</kwd><kwd>COAST, Childhood Origins of Asthma Study</kwd><kwd>ED, Emergency department</kwd><kwd>ELGANS, Extremely low gestational age newborns</kwd><kwd>hRV, Human rhinovirus</kwd><kwd>IRRISS, Infant Research Respiratory Infection Severity Score</kwd><kwd>LMER, Linear mixed effects regression modeling</kwd><kwd>PRISM, Prematurity, Respiratory Outcomes, Immune System and Microbiome</kwd><kwd>RSV, Respiratory syncytial virus</kwd></kwd-group></article-meta></front><body><p id="p0010">Respiratory infections are among the most common illnesses encountered in infancy and early childhood.<xref rid="bib1" ref-type="bibr">1</xref>, <xref rid="bib2" ref-type="bibr">2</xref> When symptomatic, these infections induce a range of disease severity, from mild congestion to severe respiratory distress requiring hospitalization. Respiratory infections in infancy have also been associated with respiratory morbidity in later childhood suggesting the importance of these infections to health and the need to fully understand how early infections relate to later disease.<xref rid="bib3" ref-type="bibr">3</xref>, <xref rid="bib4" ref-type="bibr">4</xref>, <xref rid="bib5" ref-type="bibr">5</xref></p><p id="p0015">Much has been learned about the epidemiology of respiratory pathogens causing early life infections owing to the introduction of molecular detection methods.<xref rid="bib6" ref-type="bibr">6</xref>, <xref rid="bib7" ref-type="bibr">7</xref> However, there is a significant need for a validated research assessment tool to measure the severity of respiratory illnesses among infants to understand disease risk as well as clinical and biological modifiers of respiratory disease severity. There are no widely accepted research tools to measure illness severity in infants with respiratory infections except those with bronchiolitis.<xref rid="bib8" ref-type="bibr">8</xref>, <xref rid="bib9" ref-type="bibr">9</xref>, <xref rid="bib10" ref-type="bibr">10</xref>, <xref rid="bib11" ref-type="bibr">11</xref>, <xref rid="bib12" ref-type="bibr">12</xref>, <xref rid="bib13" ref-type="bibr">13</xref> Most respiratory illnesses and infections in infants do not require hospitalization or medical intervention; thus, to measure the full range of respiratory symptom severity, a tool reflecting outpatient symptoms is needed.</p><p id="p0020">Physicians trust parents to be good judges of their child's health and to identify serious symptoms to seek care. Yet, the data for the accuracy of parental reports of respiratory symptoms are mixed.<xref rid="bib14" ref-type="bibr">14</xref>, <xref rid="bib15" ref-type="bibr">15</xref>, <xref rid="bib16" ref-type="bibr">16</xref>, <xref rid="bib17" ref-type="bibr">17</xref> The Childhood Origins of Asthma Study (COAST) developed a scorecard for parents of full term infants at risk for wheezing, asthma, and atopy to quantify respiratory symptoms to alert the study staff of a probable viral infection and the need for a research visit.<xref rid="bib18" ref-type="bibr">18</xref>, <xref rid="bib19" ref-type="bibr">19</xref>, <xref rid="bib20" ref-type="bibr">20</xref> Although the COAST score has been used as a measure of respiratory illness severity, it has not been fully validated. Additionally, the usefulness in measuring illness severity in preterm infants or those not at risk for atopy or allergy has not been demonstrated previously.</p><p id="p0025">We undertook a large, prospective cohort study of term and preterm infants focused on Prematurity, Respiratory Outcomes, Immune System and Microbiome, the PRISM study (<ext-link ext-link-type="uri" xlink:href="http://www.urmc.rochester.edu/respiratory-pathogens-research-center/projects.aspx" id="intref0010">www.urmc.rochester.edu/respiratory-pathogens-research-center/projects.aspx</ext-link>). One of the aims of PRISM is to identify symptomatic and asymptomatic respiratory infections over the first 2 years of life to understand the effect of repeated infections on respiratory morbidity in early childhood. The ability to measure respiratory illness symptomatology and severity is a key component of this aim and the subject of this report. As such, we first determined the validity of the COAST Scorecard for measuring illness severity in the PRISM birth cohort, including both term and preterm infants, selected without regard to risk of wheezing. As a secondary aim, we developed a new data-driven scoring system of disease severity based on the 10-day illness diary cards kept by parents for the PRISM infants and young children. We compared the new scoring system with the COAST score in an attempt to create a more broadly applicable, sensitive, and specific measure of respiratory illness severity to be used as a tool for research.</p><sec id="sec1"><title>Methods</title><p id="p0030">The PRISM study enrollment strategy has been previously published and registered at <ext-link ext-link-type="uri" xlink:href="http://ClinicalTrials.gov" id="intref0015">ClinicalTrials.gov</ext-link> (<ext-link ext-link-type="ClinicalTrials.gov" xlink:href="NCT01789268" id="intref0020">NCT01789268</ext-link>).<xref rid="bib21" ref-type="bibr"><sup>21</sup></xref> Briefly, preterm (<36 weeks of gestation) and term (≥37 weeks of gestation) newborns, ≤7 days of age, born at the University of Rochester Medical Center, Rochester, New York, were eligible for enrollment. Exclusion criteria included airway/chest wall abnormalities, neuromuscular or cardiac disorders (except patent ductus arteriosus or isolated atrial septal defect), genetic disorders of immune system or respiratory function, maternal HIV infection, and nonviability. The Research Subjects Review Board approved the study and all parents provided informed consent.</p><sec id="sec1.1"><title>Study Protocol</title><p id="p0035">Nose and throat swabs were obtained from each newborn on study day 1, weekly during hospitalization, monthly after discharge until 12 months corrected gestational age, and during respiratory illnesses after the birth hospitalization in the first 2 years of life. Additionally, the use of the COAST scorecard was reviewed with each family via a printed diary form before discharge from the birth hospitalization and at each visit. Families were reminded to begin filling out the scorecard and to notify the study team when their child developed respiratory symptoms resulting in a score of ≥3 and to continue completing the scorecard daily until 10 days had elapsed or the child's symptoms dropped below a score of 3.<xref rid="bib18" ref-type="bibr">18</xref>, <xref rid="bib19" ref-type="bibr">19</xref>, <xref rid="bib20" ref-type="bibr">20</xref> The scorecard assigns points to the presence or absence of fever ≥100°F, hoarseness, wheezing, retractions, tachypnea, cyanosis, apnea, being ill for >4 days, and the degree of cough and rhinorrhea. Maximal possible score is 31 with higher scores indicating more severe symptoms. The PRISM study sought to identify all respiratory infections with the full range of severity so a threshold score of 3 was chosen as a sensitive measure of illness. When parents reported a COAST score of ≥3, a study visit was completed and respiratory samples obtained. Staff followed up with families to ensure scorecard completion and also reviewed the 3 days before when a score of 3 was reached, so that the full range of illness was recorded. For participants with baseline respiratory symptoms such as retractions or wheezing, the families were instructed to assign points only when findings were greater than baseline.</p><p id="p0040">Hospitalizations and emergency department (ED) visits were recorded and chart review was completed only for those related to respiratory illnesses. Hospitalizations, ED visits, and research illness visits for respiratory illnesses were included in the analysis only if they occurred within 12 days of a parental COAST scorecard report and had respiratory pathogen testing completed. There had to be a minimum of 12 days between illnesses to count as a new event. The number of ED visits that met criteria were so small they were combined with research illness visits in the analyses. Results of clinical respiratory viral testing were included if obtained from 2 days before to 7 days after the first COAST scorecard entry.</p></sec><sec id="sec1.2"><title>Specimens</title><p id="p0045">Separate flocked swabs (Copan, FLOQSwabs catalog # 525CS01, Copan, Murrieta, California) were used to sample the nares and oropharynx/tonsillar region, combined in 3 mL of Universal Transport Media (UTM, Cat # 330CHL, Quidel [formerly Diagnostic Hybrids], Athens, Ohio), shaken, placed on ice, and transported to the laboratory.<xref rid="bib21" ref-type="bibr"><sup>21</sup></xref></p></sec><sec id="sec1.3"><title>Laboratory Methods: Real-Time Polymerase Chain Reaction</title><p id="p0050">TaqMan Array Card technology was used as previously described.<xref rid="bib21" ref-type="bibr"><sup>21</sup></xref> Targets included influenza A and B; respiratory syncytial virus (RSV); human metapneumovirus, parainfluenza virus 1, 2, and 3; human rhinovirus (hRV); enterovirus, human parechovirus, coronavirus 1-4 (229, NL63, OC43, and HKU1); adenovirus; and human bocavirus. The detection of the human RNase P gene was a positive control confirming the presence of cellular material.<xref rid="bib22" ref-type="bibr"><sup>22</sup></xref></p></sec><sec id="sec1.4"><title>Statistical Analyses</title><p id="p0055">Our first goal was to determine whether we could validate the COAST scorecard in our population of term and preterm infants. In the COAST study the detection of known viral respiratory pathogens was significantly associated with disease severity as measured by the scorecard.<xref rid="bib18" ref-type="bibr"><sup>18</sup></xref> Therefore, we used the identification of respiratory viruses as a validation measure. Because hospitalization is also a measure of disease severity, we chose it as an additional validation measure. The associations between the preterm and term cohorts and their characteristics, prevalence of hospitalizations, reported illnesses, and viruses identified were explored using the Pearson χ<sup>2</sup> test. The same approach was used to evaluate symptoms and validation measures.</p><p id="p0060">COAST scorecard data were summarized by using the maximum COAST score assigned by a parent or the area under the curve (AUC) of the daily score averaged over the full course of illness to control for different lengths of illness. Linear mixed effects regression modeling (LMER) was used to evaluate the associations between the detection of viral infections (RSV, hRV, and any other viral infections combined), hospitalization, and the maximum COAST score or the average AUC COAST score. Random intercepts were included in the model to account for between subject variations. Illness visits with >1 viral pathogen detected were included in the analysis of each virus (RSV, hRV, or other viral infections).</p><p id="p0065">Second, a novel, data-driven approach to severity scoring was developed to more precisely determine the contribution of the clinical information from each symptom to the overall score. With day 1 of reporting (score of ≥3) having the most abundant diary data, a factor analysis with polychoric correlation matrix of symptoms reported on day 1 was used to determine the symptom weights for cough, tachypnea, fever, hoarseness, retractions, rhinorrhea, sick for >4 days, and the presence of wheeze as reported on the scorecard. Cyanosis and apnea were rare, so were not considered. A value of 10 was added to each weighted score to produce all positive values. The first factor explained the largest amount of the variance in the data (51.2%) and was used to assign weights to the variables in the new Infant Research Respiratory Infection Severity Score (IRRISS). LMER models were again used to validate the IRRISS with the detection of a viral respiratory pathogen as well as hospitalization as measures of disease severity. Finally, severity scores were calculated similarly but separately for the term and preterm subjects to explore potential heterogeneity among age cohorts, and the performance of each score was compared with the IRRISS and COAST score.</p><p id="p0070">All LMER models were controlled for gestational age at birth, race, birthweight z-score, number of people in the household separated into 3 categories (2-3, 4-6, or 7-10), and a family history of asthma.</p></sec></sec><sec id="sec2"><title>Results</title><p id="p0075">From April 2013 to April 2017, 267 newborns were enrolled in the PRISM study including 64 born at <29 weeks of gestation or extremely low gestational age newborns (ELGANs), 84 late preterm (29-<36 weeks of gestation), and 119 term infants (≥37<sup>0/7</sup> weeks of gestation). To be included in the analyses, subjects had to have had a minimum of 1 follow-up visit ≥1 month after hospital discharge and ≥1 illness visit with an accompanying parent reported COAST score and viral testing data. During the study period there were 208 active subjects, 118 subjects (<xref rid="tbl1" ref-type="table">Table I</xref>), had a qualifying illness visit (1-12 per subject) resulting in a total of 346 illness visits. Of these, 303 visits (88%) had matching viral testing and parent reported COAST scorecards that form the basis of this report. Sixteen hospitalizations were included for 13 subjects; 89% of illness visits (269) with a matching COAST Scorecard reported ≥3 days of illness symptoms and 70% had ≥7-10 days of data. Twelve hospitalizations were in the ELGANS group, 2 in late preterm infants, and 2 in term infants with an overall hospitalization rate that was significantly higher in the ELGANS group (15.2%) than the late preterm (1.9%) or term infants (1.7%; <italic>P</italic> < .001; <xref rid="tbl2" ref-type="table">Table II</xref>).<table-wrap position="float" id="tbl1"><label>Table I</label><caption><p>Participant characteristics</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Characteristics</th><th>Term (n = 50)</th><th>Late preterm (n = 40)</th><th>ELGANs (n = 28)</th><th>Total (n = 118)</th><th><italic>P</italic> value</th></tr></thead><tbody><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> Female</td><td align="char">15 (30.0)</td><td align="char">19 (47.5)</td><td align="char">17 (60.7)</td><td align="char">51</td><td align="char">.025</td></tr><tr><td> Male</td><td align="char">35 (70.0)</td><td align="char">21 (52.5)</td><td align="char">11 (39.3)</td><td align="char">67</td><td></td></tr><tr><td>Race</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> African American</td><td align="char">6 (12.0)</td><td align="char">6 (15.0)</td><td align="char">8 (28.6)</td><td align="char">20</td><td align="char">.138</td></tr><tr><td> Other</td><td align="char">14 (28.0)</td><td align="char">5 (12.5)</td><td align="char">6 (21.4)</td><td align="char">25</td><td></td></tr><tr><td> White</td><td align="char">30 (60.0)</td><td align="char">29 (72.5)</td><td align="char">14 (50.0)</td><td align="char">73</td><td></td></tr><tr><td>Birth weight</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> Average for gestational age</td><td align="char">42 (84.0)</td><td align="char">34 (85.0)</td><td align="char">27 (96.4)</td><td align="char">103</td><td align="char">.086</td></tr><tr><td> Large for gestational age</td><td align="char">4 (8.0)</td><td align="char">0 (0.0)</td><td align="char">1 (3.6)</td><td align="char">5</td><td></td></tr><tr><td> Small for gestational age</td><td align="char">4 (8.0)</td><td align="char">6 (15.0)</td><td align="char">0 (0.0)</td><td align="char">10</td><td></td></tr><tr><td>Family history of asthma</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> No</td><td align="char">37 (74.0)</td><td align="char">29 (72.5)</td><td align="char">12 (42.9)</td><td align="char">78</td><td align="char">.012</td></tr><tr><td> Yes</td><td align="char">13 (26.0)</td><td align="char">11 (27.5)</td><td align="char">16 (57.1)</td><td align="char">40</td><td></td></tr><tr><td>No. of people in home</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> 2-3</td><td align="char">16 (32.0)</td><td align="char">8 (20.0)</td><td align="char">6 (21.4)</td><td align="char">30</td><td align="char">.397</td></tr><tr><td> 4-6</td><td align="char">33 (66.0)</td><td align="char">28 (70.0)</td><td align="char">20 (71.4)</td><td align="char">81</td><td></td></tr><tr><td> 7-10</td><td align="char">1 (2.0)</td><td align="char">4 (10.0)</td><td align="char">2 (7.1)</td><td align="char">7</td><td></td></tr></tbody></table><table-wrap-foot><fn><p>Values are number (%).</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="tbl2"><label>Table II</label><caption><p>Comparison of illness visits, hospitalizations, and respiratory viral infections in the term and preterm participants</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Variables</th><th>Term</th><th>Late preterm</th><th>ELGANs</th><th><italic>P</italic> value</th></tr></thead><tbody><tr><td>Total illness visits</td><td>121</td><td>103</td><td>79</td><td></td></tr><tr><td>Hospitalization</td><td align="char">2 (1.7)</td><td align="char">2 (1.9)</td><td align="char">12 (15.2)</td><td align="char"><.001</td></tr><tr><td>hRV infection</td><td align="char">47 (38.8)</td><td align="char">57 (55.3)</td><td align="char">37 (46.8)</td><td align="char">.048</td></tr><tr><td>RSV infection</td><td align="char">19* (15.7)</td><td align="char">15<sup>†</sup> (14.6)</td><td align="char">10<sup>‡</sup> (12.7)</td><td align="char">.836</td></tr><tr><td>Other than hRV/RSV</td><td align="char">38<sup>§</sup> (31.4)</td><td align="char">17 (16.5)</td><td align="char">17 (21.5)</td><td align="char">.029</td></tr><tr><td>Any virus infection</td><td align="char">102 (84.3)</td><td align="char">85 (82.5)</td><td align="char">62 (78.5)</td><td align="char">.572</td></tr></tbody></table><table-wrap-foot><fn id="tspara0025"><p>Values are number (%).</p></fn><fn id="tspara0030"><p>There were 7 hRV and RSV coinfections: *1 in a term baby, <sup>†</sup>4 in late preterm, <sup>‡</sup>2 in ELGANs, and <sup>§</sup>1 hRV and human bocavirus coinfection in a term baby.</p></fn></table-wrap-foot></table-wrap></p><p id="p0080">There were 249 samples (82%) from the 303 illness visits that had a viral respiratory pathogen identified with 8 viral co-detections including 7 with RSV and hRV and 1 with hRV and human bocavirus (<xref rid="tbl2" ref-type="table">Table II</xref>). The rate of viral detection at illness visits was significantly greater than at well visits (383 of 1114 well visits [34%]; <italic>P</italic> < .001). The rate of pathogen detection at illness visits did not differ by gestational age group with 79% of illness visits in the ELGANS, 83% in the late preterm group, and 84% in the term cohort associated with the detection of a viral pathogen (<italic>P</italic> = .57). In contrast, a respiratory virus was detected at 28% of well visits in ELGANs, 36% in the late preterm group, and 38% of well visits in term babies, suggesting that babies born at <29 weeks of gestation are significantly less likely to have asymptomatic viral respiratory infections (<italic>P</italic> = .03). The preterm cohorts were also more likely to have rhinovirus-associated illness visits (47% ELGANS and 55% late preterm) than term (39%) infants (<italic>P</italic> = .05; <xref rid="tbl2" ref-type="table">Table II</xref>). The percentage of illness visits associated with RSV infection was not different between the 3 groups (<italic>P</italic> = .84; <xref rid="tbl2" ref-type="table">Table II</xref>). In the PRISM study, 75% of ELGANS and 10% of late preterm infants received palivizumab prophylaxis. Of the 79 illness visits in ELGANS, 10 were due to RSV. Four hospitalizations and 5 illness visits occurred in subjects who received palivizumab, with 1 RSV illness visit in an ELGANS subject who had not received palivizumab. Nine illness visits occurred in late preterm subjects who received palivizumab, none of which were due to RSV infection, whereas 15 RSV illness visits occurred in late preterm infants who did not receive palivizumab, 1 of which was associated with hospitalization (<xref rid="tblEIII" ref-type="table">Table III</xref>; available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0025">www.jpeds.com</ext-link>).</p><sec id="sec2.1"><title>COAST Score</title><p id="p0085">Seven percent of illness visits had maximum COAST scores of ≤3, suggesting mild upper respiratory symptoms only. However, 39% of illnesses were associated with a maximal COAST score of >10, implying more severe disease. In general, ELGANS had a greater number of illness visits associated with higher scores (<xref rid="fig1" ref-type="fig">Figure 1</xref>).<fig id="fig1"><label>Figure 1</label><caption><p>Frequency distribution of the parent-reported maximal COAST score for respiratory illness visits by cohort.</p></caption><graphic xlink:href="gr1_lrg"></graphic></fig></p><p id="p0090">LMER models were used to examine associations between the detection of viral infections as a measure of disease severity and either the maximal COAST score or the average AUC COAST score. Results focus on the maximum scores for ease of presentation as the maximum scores and average AUC scores provided similar results. We chose to examine the associations with RSV, hRV, and other viral infections because the original COAST study showed an association between the identification of a respiratory pathogen and illness severity. The models were repeated using hospitalization as an alternative measure of construct validity.</p><p id="p0095">The presence of RSV in the respiratory sample during an illness visit was positively associated with the COAST score in each model (<xref rid="tbl4" ref-type="table">Table IV</xref>and <xref rid="tblEV" ref-type="table">Table V</xref> [available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0030">www.jpeds.com</ext-link>]). The detection of hRV was inversely associated with the COAST score (<xref rid="tbl4" ref-type="table">Tables IV</xref> and <xref rid="tblEV" ref-type="table">V</xref>). Hospitalization was also positively associated with the COAST score (<italic>P</italic> < .001). African American race was consistently positively associated with the COAST score and gestational age at birth was inversely associated.<table-wrap position="float" id="tbl4"><label>Table IV</label><caption><p>Results of the linear mixed effects regression models of the maximum COAST score and IRRISS</p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="2">Variables</th><th colspan="2">COAST score<hr></hr></th><th colspan="2">IRRISS<hr></hr></th></tr><tr><th>Estimate</th><th><italic>P</italic> value</th><th>Estimate</th><th><italic>P</italic> value</th></tr></thead><tbody><tr><td>Hospital admission</td><td></td><td></td><td></td><td></td></tr><tr><td> Hospitalization</td><td align="char">0.621</td><td align="char"><.001</td><td align="char">0.087</td><td align="char"><.001</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.022</td><td align="char"><.001</td><td align="char">−0.004</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.195</td><td align="char">.038</td><td align="char">0.027</td><td align="char">.110</td></tr><tr><td> Other race vs white</td><td align="char">0.054</td><td align="char">.551</td><td align="char">0.013</td><td align="char">.426</td></tr><tr><td> Family history of asthma</td><td align="char">0.088</td><td align="char">.253</td><td align="char">0.016</td><td align="char">.234</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.060</td><td align="char">.456</td><td align="char">−0.008</td><td align="char">.576</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.073</td><td align="char">.673</td><td align="char">0.004</td><td align="char">.899</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.072</td><td align="char">.075</td><td align="char">0.007</td><td align="char">.331</td></tr><tr><td>Other virus infection</td><td></td><td></td><td></td><td></td></tr><tr><td> Other than hRV/RSV</td><td align="char">0.159</td><td align="char">.022</td><td align="char">0.024</td><td align="char">.056</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.028</td><td align="char"><.001</td><td align="char">−0.005</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.216</td><td align="char">.023</td><td align="char">0.030</td><td align="char">.075</td></tr><tr><td> Other race vs white</td><td align="char">0.074</td><td align="char">.417</td><td align="char">0.016</td><td align="char">.326</td></tr><tr><td> Family history of asthma</td><td align="char">0.130</td><td align="char">.092</td><td align="char">0.023</td><td align="char">.098</td></tr><tr><td> 4-6 vs < 4 People in home</td><td align="char">−0.074</td><td align="char">.361</td><td align="char">−0.010</td><td align="char">.498</td></tr><tr><td> 7-10 vs < 4 People in home</td><td align="char">−0.143</td><td align="char">.416</td><td align="char">−0.006</td><td align="char">.854</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.096</td><td align="char">.019</td><td align="char">0.010</td><td align="char">.151</td></tr><tr><td>RSV infection</td><td></td><td></td><td></td><td></td></tr><tr><td> RSV infection</td><td align="char">0.253</td><td align="char">.002</td><td align="char">0.056</td><td align="char"><.001</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.029</td><td align="char"><.001</td><td align="char">−0.005</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.193</td><td align="char">.049</td><td align="char">0.025</td><td align="char">.141</td></tr><tr><td> Other race vs white</td><td align="char">0.045</td><td align="char">.636</td><td align="char">0.010</td><td align="char">.561</td></tr><tr><td> Family history of asthma</td><td align="char">0.123</td><td align="char">.121</td><td align="char">0.021</td><td align="char">.135</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.062</td><td align="char">.458</td><td align="char">−0.006</td><td align="char">.681</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.156</td><td align="char">.382</td><td align="char">−0.007</td><td align="char">.826</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.081</td><td align="char">.053</td><td align="char">0.007</td><td align="char">.318</td></tr><tr><td>hRV infection</td><td></td><td></td><td></td><td></td></tr><tr><td> hRV infection</td><td align="char">−0.159</td><td align="char">.007</td><td align="char">−0.026</td><td align="char">.013</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.029</td><td align="char"><.001</td><td align="char">−0.005</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.190</td><td align="char">.051</td><td align="char">0.026</td><td align="char">.131</td></tr><tr><td> Other race vs white</td><td align="char">0.058</td><td align="char">.534</td><td align="char">0.013</td><td align="char">.415</td></tr><tr><td> Family history of asthma</td><td align="char">0.130</td><td align="char">.098</td><td align="char">0.023</td><td align="char">.102</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.067</td><td align="char">.419</td><td align="char">−0.008</td><td align="char">.567</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.151</td><td align="char">.395</td><td align="char">−0.007</td><td align="char">.828</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.090</td><td align="char">.030</td><td align="char">0.010</td><td align="char">.189</td></tr></tbody></table></table-wrap></p></sec><sec id="sec2.2"><title>Development of a New Severity Score, the IRRISS</title><p id="p0100">Based on the respiratory symptom components of the COAST scorecard, we next performed a factor analysis to develop a data-driven severity scoring system. The aim was to develop an alternative system to accurately summarize the contribution of each respiratory symptom to disease severity to determine if this approach would improve upon the COAST score. Using the new score the associations with viral infection and hospitalization were reexamined.</p><p id="p0105">When developing the new scoring system we initially explored individual associations of symptoms with one another to evaluate the biological plausibility of including each one of the symptoms in the new scoring system. A cluster dendrogram based on a dissimilarity matrix classified the symptoms into 2 main groups—those more associated with lower respiratory tract infection such as retractions and tachypnea compared with those consistent with upper respiratory tract infection (<xref rid="figE2" ref-type="fig">Figure 2</xref>; available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0035">www.jpeds.com</ext-link>). Pearson χ<sup>2</sup> test analyses identified the presence of retractions, tachypnea, and wheeze as significantly associated with hospitalization (<xref rid="tblEVI" ref-type="table">Table VI</xref>; available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0040">www.jpeds.com</ext-link>). Cough was associated with the detection of RSV and hRV infection was associated with fever and a longer duration of illness (<xref rid="tblEVI" ref-type="table">Table VI</xref>). Viral infections other than hRV or RSV were also associated with fever and hoarseness. Next, a factor analysis was performed to compute weights for each of the 8 symptoms and to derive the new severity scoring system, the IRRISS, with a range of 9-14 (<xref rid="figE3" ref-type="fig">Figure 3</xref>; available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0045">www.jpeds.com</ext-link>).</p><p id="p0110">Repeating the LMER models using the IRRISS identified the presence of RSV infection and hospitalization to be positively associated with the IRRISS in both models (<xref rid="tbl4" ref-type="table">Table IV</xref> and <xref rid="tblEV" ref-type="table">Table V</xref>). Infection with hRV was inversely associated with the IRRISS when compared with all hRV-negative illness, visits which were predominantly due to RSV and other viral respiratory pathogens (<xref rid="tblEVII" ref-type="table">Table VII</xref>; available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0050">www.jpeds.com</ext-link>). Gestational age at birth was also negatively associated with the IRRISS. When comparing the IRRISS and the COAST score, they were highly correlated (r = 0.93; <italic>P</italic> < .0001; <xref rid="figE4" ref-type="fig">Figure 4</xref>; available at <ext-link ext-link-type="uri" xlink:href="http://www.jpeds.com" id="intref0055">www.jpeds.com</ext-link>).</p><p id="p0115">A sensitivity analysis was performed to confirm the associations between the IRRISS and COAST scores and hospitalization and specific viral infections with ELGANS subjects removed. RSV infection and hospitalization continued to be significantly associated with both the maximal COAST score and IRRISS with an inverse association with hRV infections. A family history of asthma was now significantly associated with the average AUC of the IRRISS in all analyses.</p><p id="p0120">Next, separate preterm and term infant severity scores were derived in a similar fashion as the IRRISS using factor analysis to determine if symptoms interacted differently between term and preterm infants. In the preterm cohort the COAST score, IRRISS and preterm factor score were consistently associated with RSV infection and hospitalization (<italic>P</italic> = .022 to <italic>P</italic> = .028 for RSV infection and <italic>P</italic> < .001 for hospitalization) and inversely associated with hRV infection (<italic>P</italic> = .002 to <italic>P</italic> = .002). Findings were not consistent when the full-term cohort was analyzed separately. There was an association between RSV infection and the maximal IRRISS score, but no association with the maximal COAST score or the maximal term factor score. Hospitalization was significantly associated with the COAST score, the average AUC of the term factor score and marginally significant with the average AUC of the IRRISS (<italic>P</italic> = .05) in term babies despite few hospitalizations in this cohort. No associations were noted for hRV.</p><p id="p0125">Despite these differences, the separate term and preterm factor scores were highly correlated with the IRRISS score (term score r = 0.97, preterm score r = 1; both <italic>P</italic> < .001) and the COAST score (term score, r = 0.94; preterm score, r = 0.93; both <italic>P</italic> < .0001; results not shown).</p></sec></sec><sec id="sec3"><title>Discussion</title><p id="p0130">In the PRISM study, we used parent reported symptom data included on the COAST scorecard to signal the need for a respiratory illness research visit and to quantitate the type and degree of symptoms throughout the illness as a measure of disease severity.<xref rid="bib18" ref-type="bibr">18</xref>, <xref rid="bib19" ref-type="bibr">19</xref> From these reports, we examined both the validity of the COAST score for measuring respiratory disease severity and developed ex nihilo data-driven severity scores, the IRRSS, and separate term and preterm factor scores, using the presence of RSV, hRV, and hospitalization to evaluate construct validity.</p><p id="p0135">As linear combinations of 8-10 separate symptoms clinically associated with acute respiratory illnesses, the COAST score and the newly derived scores demonstrate face validity. Evaluating individual components of the COAST score, we found associations between hospitalization and specific symptoms associated with lower tract disease. In addition, associations between RSV, hRV, and other viral infections with 7 of the 10 symptoms were identified. The cluster dendrogram linked 8 symptoms together, suggesting a physiologic relationship between them with differences possibly owing to predominant lower airway vs upper airway viral replication and injury. These 8 symptoms were then included in the development of alternative scores for assessing severity of respiratory illnesses up to 24 months of age. We also examined score performance relative to gestational age at birth.</p><p id="p0140">Prior reports demonstrated an association between the frequency of viral detection and the magnitude of the COAST score, categorized as mild (1-4), moderate (5-9), and severe disease (>9), which validated that the score was indeed identifying viral respiratory infections.<xref rid="bib18" ref-type="bibr">18</xref>, <xref rid="bib23" ref-type="bibr">23</xref> RSV infection causes more severe respiratory illness with a higher rate of hospitalization than other viral respiratory infections in infants.<xref rid="bib24" ref-type="bibr">24</xref>, <xref rid="bib25" ref-type="bibr">25</xref>, <xref rid="bib26" ref-type="bibr">26</xref> Houben et al found that term infants with RSV infection had greater disease severity using the COAST score than infants with other viral infections providing preliminary validation of the score.<xref rid="bib27" ref-type="bibr"><sup>27</sup></xref> Although modifications of the COAST score have been used in subsequent respiratory disease studies, further efforts to validate the score to measure disease severity have not been reported.<xref rid="bib28" ref-type="bibr">28</xref>, <xref rid="bib29" ref-type="bibr">29</xref> Marginal analysis of our data confirmed an association between a COAST score of ≥3 and the presence of a viral infection. Multivariate modeling analyses further demonstrated that the maximal COAST score reported over a 10-day period for each illness and the average AUC of the COAST score were both associated with the presence of a symptomatic RSV infection and hospitalization in our cohort. In addition, our analyses consistently identified an inverse association between the COAST score and infection with hRV, as compared with infections with other viruses. This finding is in keeping with hRV infections generally causing milder respiratory disease.<xref rid="bib26" ref-type="bibr">26</xref>, <xref rid="bib30" ref-type="bibr">30</xref> The COAST score was also consistently inversely related to gestational age at birth. These data provide validation of the COAST score to measure respiratory disease severity in the first 2 years of life in a new cohort of term and preterm infants.</p><p id="p0145">We further used the symptom components of the COAST score to develop the new IRRISS respiratory severity score. Our aim was to determine if the data would provide more accurate weightings of symptoms in measuring illness severity than the original investigator-assigned symptom weights. Additionally, we sought to develop a more accurate score that would be useful in the research setting with both preterm and term infants without regard to a family history of asthma or atopy, risk factors required in the COAST study. The IRRISS score demonstrated very good construct validity; it was significantly associated with RSV infections and hospitalization in both the maximal and average AUC scores, similar to the COAST score. Like the COAST score, the IRRISS score was also inversely associated with hRV infections. Separating the cohort into preterm and term sets and estimating individual factor models for each group did not provide consistent results. The COAST score and IRRISS also did not perform as well when applied only to the term infants included in our cohort, which may be due to the smaller number of subjects and illnesses in each group.</p><p id="p0150">Although both the COAST and IRRISS severity scores performed well in our cohort of preterm and term infants, gestational age at birth remained a significant variable in explaining respiratory illness severity, confirming prior reports of prematurity as a risk factor for severe, recurrent, respiratory disease, irrespective of the viral etiology.<xref rid="bib29" ref-type="bibr">29</xref>, <xref rid="bib31" ref-type="bibr">31</xref>, <xref rid="bib32" ref-type="bibr">32</xref> ELGANS not only had higher hospitalization rates, but they were also less likely to have asymptomatic respiratory viral infections in the current study and had higher COAST and IRRISS scores with respiratory illnesses. An additional consistent finding was that hRV infections were negatively associated with illness severity when compared with illness mostly owing to RSV and other viral respiratory infections. This finding is in keeping with prior reports of generally milder illness in infants with hRV infections, as noted.<xref rid="bib26" ref-type="bibr">26</xref>, <xref rid="bib30" ref-type="bibr">30</xref> Although previous research identified hRV as a cause of severe lower respiratory infections in infants, the association with disease severity seems to be due to underlying comorbidities such as prematurity, rather than virus type.<xref rid="bib30" ref-type="bibr">30</xref>, <xref rid="bib31" ref-type="bibr">31</xref>, <xref rid="bib33" ref-type="bibr">33</xref></p><p id="p0155">The strengths of this study include the prospective, 2-year longitudinal design in a large cohort with state-of-the-art molecular detection methods to identify respiratory pathogens. We also included preterm and term infants in our study without regard to a predisposition to atopy or asthma and were able to evaluate the characteristics of the severity scores on both groups, a novel contribution.</p><p id="p0160">Limitations include relying on caregivers to alert the study team with symptoms of respiratory illness, correctly using the COAST scorecard, and being available for a respiratory illness visit. We attempted to mitigate variability in parent report by frequent, typically monthly, contact and review of illness reporting. Study staff also reviewed the daily scoring of each illness with caregivers at the 10-day mark, which we believe enhanced information recovery and consistency. The staff also specifically taught caregivers the meaning of “wheeze” as chest sounds to be distinguished from upper airway noisy breathing. Despite these interventions, we acknowledge that illnesses may be underreported in our dataset.</p><p id="p0165">Although we did review electronic medical records, we did not include data from hospitalization or ED visits that were missing parent report. Although illness severity could be determined from the electronic medical record, we reasoned that the assessment of symptoms by health care workers is not necessarily comparable with that of parents and should not be included in an analysis of parental reports. We believe partnering with caregivers to identify significant respiratory symptoms is a clinically relevant and feasible approach in a research setting.</p><p id="p0170">Despite these limitations, our data suggest that parent-reported symptoms can be reasonably used to score respiratory disease severity in infants. The finding that the COAST score and the IRRISS were highly correlated is not unexpected, because they are based on the same constellation of symptoms. However, the IRRISS assigned weightings to symptoms based upon the data as a means to accurately capture the influence of each symptom on severity. However, these data-driven methods provided only marginal improvement over the original COAST score in this cohort. The ease of use of the COAST scorecard by parents makes it a simple tool for collecting symptom data in studies of respiratory illnesses in the first 2 years of life. 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The dendrogram was created with data from the dissimilarity matrix analyses of respiratory symptoms including wheeze, cough, hoarseness, tachypnea, retractions, sick for >4 days, runny nose and fever. It suggests a physiologic relationship among these 8 symptoms.</p></caption><graphic xlink:href="fx1_lrg"></graphic></fig><fig id="figE3"><label>Figure 3</label><caption><p>Computation of the IRRSS score. Respiratory symptom weights were computed via factor analysis with polychoric correlation matrix of symptoms. The final IRRSS was computed as: IRRSS = 0.07 × Severe runny nose today − 0.25 × Mild runny nose today + 0.08 × Fever >100°F today − 0.17 × Sick >4 days + 0.87 × Breathing fast today + 0.82 × Retractions today + 0.91 + Wheeze Today + 0.34 × Hoarse today + 0.71 × Severe cough today − 0.08 × Moderate cough today − 0.37 × Mild cough today + 10.</p></caption><graphic xlink:href="fx2_lrg"></graphic></fig><fig id="figE4"><label>Figure 4</label><caption><p>Correlation between the maximal COAST score and the maximal IRRSS. The scores were significantly correlated (r = 0.93; <italic>P</italic> < .0001).</p></caption><graphic xlink:href="fx3_lrg"></graphic></fig><table-wrap position="anchor" id="tblEIII"><label>Table III</label><caption><p>Illness visits and respiratory virus detection in preterm infants by palivizumab status</p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="3">Visits</th><th colspan="3">Late preterm<hr></hr></th><th colspan="3">ELGANS<hr></hr></th></tr><tr><th rowspan="2">All</th><th colspan="2">Palivizumab received<hr></hr></th><th rowspan="2">All</th><th colspan="2">Palivizumab received<hr></hr></th></tr><tr><th>No</th><th>Yes</th><th>No</th><th>Yes</th></tr></thead><tbody><tr><td>Total illness visits</td><td align="char">103</td><td align="char">94</td><td align="char">9</td><td align="char">79</td><td align="char">15</td><td align="char">64</td></tr><tr><td>Research illness visits</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> Illness visits</td><td align="char">101</td><td align="char">92</td><td align="char">9</td><td align="char">67</td><td align="char">14</td><td align="char">53</td></tr><tr><td> No virus identified</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> hRV−</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> RSV−</td><td align="char">18</td><td align="char">16</td><td align="char">2</td><td align="char">15</td><td align="char">–</td><td align="char">15</td></tr><tr><td> Virus infection identified</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> hRV−</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> RSV−</td><td align="char">16</td><td align="char">14</td><td align="char">2</td><td align="char">14</td><td align="char">4</td><td align="char">10</td></tr><tr><td> RSV+</td><td align="char">10</td><td align="char">10</td><td align="char">–</td><td align="char">5</td><td align="char">–</td><td align="char">5</td></tr><tr><td> hRV+</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> RSV−</td><td align="char">53</td><td align="char">48</td><td align="char">5</td><td align="char">32</td><td align="char">9</td><td align="char">23</td></tr><tr><td> RSV+</td><td align="char">4</td><td align="char">4</td><td align="char">–</td><td align="char">1</td><td align="char">1</td><td align="char">–</td></tr><tr><td>Hospital admission</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> Illness visits</td><td align="char">2</td><td align="char">2</td><td>–</td><td align="char">12</td><td align="char">1</td><td align="char">11</td></tr><tr><td> No virus identified</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> hRV−</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> RSV−</td><td>–</td><td>–</td><td>–</td><td align="char">2</td><td align="char">–</td><td align="char">2</td></tr><tr><td> Virus infection identified</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> hRV−</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> RSV−</td><td align="char">1</td><td align="char">1</td><td>–</td><td align="char">3</td><td align="char">1</td><td align="char">2</td></tr><tr><td> RSV+</td><td align="char">1</td><td align="char">1</td><td>–</td><td align="char">3</td><td>–</td><td align="char">3</td></tr><tr><td> hRV+</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td> RSV−</td><td>–</td><td>–</td><td>–</td><td align="char">3</td><td>–</td><td align="char">3</td></tr><tr><td> RSV+</td><td>–</td><td>–</td><td>–</td><td align="char">1</td><td>–</td><td align="char">1</td></tr></tbody></table></table-wrap><table-wrap position="anchor" id="tblEV"><label>Table V</label><caption><p>Results of the linear mixed effects regression models of the average AUC of the COAST score and the IRRISS</p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="2">Variables</th><th colspan="2">COAST score<hr></hr></th><th colspan="2">IRRISS<hr></hr></th></tr><tr><th>Estimate</th><th><italic>P</italic> value</th><th>Estimate</th><th><italic>P</italic> value</th></tr></thead><tbody><tr><td>Hospital admission</td><td></td><td></td><td></td><td></td></tr><tr><td> Hospitalization</td><td align="char">0.548</td><td align="char"><.001</td><td align="char">0.067</td><td align="char"><.001</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.018</td><td align="char">.002</td><td align="char">−0.003</td><td align="char">.003</td></tr><tr><td> African American vs white</td><td align="char">0.195</td><td align="char">.016</td><td align="char">0.028</td><td align="char">.029</td></tr><tr><td> Other race vs white</td><td align="char">0.077</td><td align="char">.326</td><td align="char">0.023</td><td align="char">.065</td></tr><tr><td> Family history of asthma</td><td align="char">0.080</td><td align="char">.227</td><td align="char">0.019</td><td align="char">.071</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.069</td><td align="char">.318</td><td align="char">−0.011</td><td align="char">.327</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.053</td><td align="char">.721</td><td align="char">−0.022</td><td align="char">.357</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.047</td><td align="char">.172</td><td align="char">0.005</td><td align="char">.314</td></tr><tr><td>Other virus infection</td><td></td><td></td><td></td><td></td></tr><tr><td> Other than hRV/RSV</td><td align="char">0.050</td><td align="char">.399</td><td align="char">0.002</td><td align="char">.845</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.023</td><td align="char"><.001</td><td align="char">−0.003</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.209</td><td align="char">.012</td><td align="char">0.029</td><td align="char">.023</td></tr><tr><td> Other race vs white</td><td align="char">0.091</td><td align="char">.255</td><td align="char">0.024</td><td align="char">.049</td></tr><tr><td> Family history of asthma</td><td align="char">0.115</td><td align="char">.087</td><td align="char">0.023</td><td align="char">.027</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.090</td><td align="char">.205</td><td align="char">−0.013</td><td align="char">.220</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.126</td><td align="char">.412</td><td align="char">−0.031</td><td align="char">.191</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.067</td><td align="char">.061</td><td align="char">0.008</td><td align="char">.154</td></tr><tr><td>RSV infection</td><td></td><td></td><td></td><td></td></tr><tr><td> RSV infection</td><td align="char">0.272</td><td align="char"><.001</td><td align="char">0.048</td><td align="char"><.001</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.024</td><td align="char"><.001</td><td align="char">−0.003</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.189</td><td align="char">.025</td><td align="char">0.026</td><td align="char">.042</td></tr><tr><td> Other race vs white</td><td align="char">0.064</td><td align="char">.426</td><td align="char">0.020</td><td align="char">.105</td></tr><tr><td> Family history of asthma</td><td align="char">0.108</td><td align="char">.113</td><td align="char">0.022</td><td align="char">.034</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.066</td><td align="char">.359</td><td align="char">−0.009</td><td align="char">.434</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.124</td><td align="char">.417</td><td align="char">−0.030</td><td align="char">.201</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.053</td><td align="char">.135</td><td align="char">0.006</td><td align="char">.309</td></tr><tr><td>hRV infection</td><td></td><td></td><td></td><td></td></tr><tr><td> hRV infection</td><td align="char">−0.103</td><td align="char">.040</td><td align="char">−0.017</td><td align="char">.032</td></tr><tr><td> Gestational age at birth</td><td align="char">−0.024</td><td align="char"><.001</td><td align="char">−0.003</td><td align="char"><.001</td></tr><tr><td> African American vs white</td><td align="char">0.194</td><td align="char">.021</td><td align="char">0.027</td><td align="char">.036</td></tr><tr><td> Other race vs white</td><td align="char">0.083</td><td align="char">.304</td><td align="char">0.023</td><td align="char">.063</td></tr><tr><td> Family history of asthma</td><td align="char">0.116</td><td align="char">.087</td><td align="char">0.023</td><td align="char">.026</td></tr><tr><td> 4-6 vs < 4 people in home</td><td align="char">−0.081</td><td align="char">.261</td><td align="char">−0.011</td><td align="char">.307</td></tr><tr><td> 7-10 vs < 4 people in home</td><td align="char">−0.124</td><td align="char">.417</td><td align="char">−0.030</td><td align="char">.207</td></tr><tr><td> Birth weight Z-score</td><td align="char">0.064</td><td align="char">.072</td><td align="char">0.007</td><td align="char">.176</td></tr></tbody></table></table-wrap><table-wrap position="anchor" id="tblEVI"><label>Table VI</label><caption><p>Correlations between respiratory symptoms and hospitalization, RSV, hRV, and other viral infections</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Variables</th><th>Hospitalization</th><th>hRV infection</th><th>RSV infection</th><th>Other than hRV/RSV</th></tr></thead><tbody><tr><td>Fever</td><td align="char">.303</td><td align="char">.003</td><td align="char">.065</td><td align="char"><.001</td></tr><tr><td>Rhinorrhea</td><td align="char">.358</td><td align="char">.055</td><td align="char">.812</td><td align="char">.257</td></tr><tr><td>Sick >4 days</td><td align="char">.211</td><td align="char">.016</td><td align="char">.056</td><td align="char">.524</td></tr><tr><td>Retractions</td><td align="char"><.001</td><td align="char">.436</td><td align="char">.167</td><td align="char">.293</td></tr><tr><td>Tachypnea</td><td align="char"><.001</td><td align="char">.315</td><td align="char">.403</td><td align="char">.438</td></tr><tr><td>Hoarseness</td><td align="char">.219</td><td align="char">.957</td><td align="char">.182</td><td align="char">.037</td></tr><tr><td>Cough</td><td align="char">.851</td><td align="char">.063</td><td align="char">.001</td><td align="char">.252</td></tr><tr><td>Wheeze</td><td align="char">.021</td><td align="char">.931</td><td align="char">.633</td><td align="char">.101</td></tr></tbody></table><table-wrap-foot><fn><p>Values are <italic>P</italic> values.</p></fn></table-wrap-foot></table-wrap><table-wrap position="anchor" id="tblEVII"><label>Table VII</label><caption><p>Viral respiratory pathogens identified other than hRV at illness visits included in the analyses</p></caption><table frame="hsides" rules="groups"><thead><tr><th>Target</th><th>Frequency</th></tr></thead><tbody><tr><td>Adenovirus</td><td align="char">15</td></tr><tr><td>Bocavirus</td><td align="char">25</td></tr><tr><td>Corona virus 2</td><td align="char">12</td></tr><tr><td>Corona virus 3</td><td align="char">14</td></tr><tr><td>Corona virus 4</td><td align="char">3</td></tr><tr><td>Enterovirus</td><td align="char">11</td></tr><tr><td>Influenza A</td><td align="char">7</td></tr><tr><td>Influenza B</td><td align="char">2</td></tr><tr><td>Parainfluenza virus 1</td><td align="char">3</td></tr><tr><td>Parainfluenza virus 2</td><td align="char">6</td></tr><tr><td>Parainfluenza virus 3</td><td align="char">17</td></tr><tr><td>Parechovirus</td><td align="char">5</td></tr><tr><td>RSV</td><td align="char">44</td></tr><tr><td>Metapneumovirus</td><td align="char">16</td></tr></tbody></table></table-wrap></p></sec><sec id="appsec2" sec-type="supplementary-material"><title>Supplementary Data</title><p id="p0190"><supplementary-material content-type="local-data" id="mmc1"><caption><title>Data Profile</title></caption><media xlink:href="mmc1.xml"></media></supplementary-material></p></sec><ack id="ack0010"><p>We are indebted to all of the children and families that participated in this study. We are also grateful to the URMC Obstetrics and NICU Nursing Teams, in addition to study team members Elizabeth Werner, Gerry Lofthus, Tanya Scalise, Dee Maffett, Amy Murphy, Lisa Denmark, Heidie Huyck, Jennifer Carnahan, Kenneth Schnabel, Lynne Shelley, Sara Misra, Emily Fitzgerald, Claire Wyman, and Jennifer Dutra for subject recruitment, sample collection, data management, and coordination.</p></ack><fn-group><fn id="d32e2433"><p id="ntpara0010">Funded in whole or in part with Federal funds from the <funding-source id="gs1">National Institute of Allergy and Infectious Diseases, National Institutes of Health</funding-source>, <funding-source id="gs3">Department of Health and Human Services</funding-source>, under Contract No. HHSN272201200005C, the <funding-source id="gs4">National Heart, Lung, and Blood Institute</funding-source> for the Prematurity and Respiratory Outcomes Program (U01 HL101813), and the <funding-source id="gs5">UR Clinical and Translational Science Institute</funding-source>, grant number UL1 TR002001. The authors declare no conflicts of interest.</p></fn></fn-group></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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