Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study
This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV) hospitalization in preterm infants 33-35 weeks gestational age (WGA). The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy...
Gespeichert in:
| Veröffentlicht in: | PloS one 2013-03, Vol.8 (3), p.e59161-e59161 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e59161 |
|---|---|
| container_issue | 3 |
| container_start_page | e59161 |
| container_title | PloS one |
| container_volume | 8 |
| creator | Blanken, Maarten O Koffijberg, Hendrik Nibbelke, Elisabeth E Rovers, Maroeska M Bont, Louis |
| description | This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV) hospitalization in preterm infants 33-35 weeks gestational age (WGA).
The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227). In the validation cohort (n = 1,194), predicted versus actual RSV hospitalization rates were compared to determine validity of the model.
RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%). In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2), birth period (OR 2.6; 1.6-4.2), breastfeeding (OR 1.7; 1.0-2.7) and siblings or daycare attendance (OR 4.7; 1.7-13.1). The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping). External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74).
Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants. |
| doi_str_mv | 10.1371/journal.pone.0059161 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_1330898773</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A478300962</galeid><doaj_id>oai_doaj_org_article_b2ba98237f7f452ba4cdd0ae2e8d750f</doaj_id><sourcerecordid>A478300962</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-7765f7023dddffbd0053d24bed7048f5bcfba5c7b6a55e9f94cac12b94cb199f3</originalsourceid><addsrcrecordid>eNqNk1uL1DAUx4so7rr6DUQDgujDjGnSNq0PwrJ4GVhY8fYacp1mSZuapIPzPfzApk53mco-SB_SnPzO_-Sck5NlT3O4zjHJ31y70ffMrgfXqzWEZZNX-b3sNG8wWlUI4vtH_yfZoxCuE4TrqnqYnSBclkVTk9Ps92fvwqBENDsFdswayaJxPXAaMDB4t-1diEaAzkllgXYeeBUG41l0fg_Cvhf7aJgFO-PHALh3vWiNsyaaAEwPLIsqyaiofJf2mvUxvE3K3WiTquqTHXDjYwuEa52PIMRR7h9nDzSzQT2Z17Ps-4f33y4-rS6vPm4uzi9XompQXBFSlZpAhKWUWnM55SdRwZUksKh1yYXmrBSEV6wsVaObQjCRI55WnjeNxmfZ84PuYF2gc0EDzTGGdaoOwYnYHAjp2DUdvOmY31PHDP1rcH5LmU-ZWEU54qypESaa6KJMm0JICZlCqpakhFO0d3O0kXdKTtl7Zheiy5PetHTrdhSXTYnwdJlXs4B3P0cVIu1MEMpa1is3TvdGBa5Jam1CX_yD3p3dTG1ZSiC1x6W4YhKl5wWpMYRNhRK1voNKn1SdEen1aZPsC4fXC4fERPUrbtkYAt18_fL_7NWPJfvyiG0Vs7ENzo7Tgw1LsDiAIj3u4JW-LXIO6TQ8N9Wg0_DQeXiS27PjBt063UwL_gMQyxnz</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1330898773</pqid></control><display><type>article</type><title>Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Public Library of Science (PLoS)</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Blanken, Maarten O ; Koffijberg, Hendrik ; Nibbelke, Elisabeth E ; Rovers, Maroeska M ; Bont, Louis</creator><contributor>Semple, Malcolm Gracie</contributor><creatorcontrib>Blanken, Maarten O ; Koffijberg, Hendrik ; Nibbelke, Elisabeth E ; Rovers, Maroeska M ; Bont, Louis ; Dutch RSV Neonatal Network ; on behalf of the Dutch RSV Neonatal Network ; Semple, Malcolm Gracie</creatorcontrib><description>This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV) hospitalization in preterm infants 33-35 weeks gestational age (WGA).
The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227). In the validation cohort (n = 1,194), predicted versus actual RSV hospitalization rates were compared to determine validity of the model.
RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%). In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2), birth period (OR 2.6; 1.6-4.2), breastfeeding (OR 1.7; 1.0-2.7) and siblings or daycare attendance (OR 4.7; 1.7-13.1). The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping). External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74).
Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0059161</identifier><identifier>PMID: 23554987</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Age ; Analysis ; Asthma ; Atopy ; Birth weight ; Breast feeding ; Breastfeeding & lactation ; Bronchiolitis - diagnosis ; Bronchiolitis - virology ; Bronchopneumonia ; Cardiovascular disease ; Cohort analysis ; Cohort Studies ; Congenital diseases ; Cost analysis ; Daycare ; Derivation ; Down syndrome ; Families & family life ; Female ; Gestational age ; Hay fever ; Health aspects ; Hospitalization - statistics & numerical data ; Hospitals ; Humans ; Immunofluorescence ; Immunology ; Infant ; Infant, Newborn ; Infant, Premature ; Infant, Premature, Diseases - diagnosis ; Infant, Premature, Diseases - virology ; Infants ; Infections ; Infectious diseases ; Lung diseases ; Male ; Mathematical models ; Medical research ; Medicine ; Models, Statistical ; Newborn babies ; Parents & parenting ; Pediatrics ; Polymerase chain reaction ; Prediction models ; Premature birth ; Premature infants ; Prognosis ; Prophylaxis ; Regression analysis ; Respiratory diseases ; Respiratory syncytial virus ; Respiratory Syncytial Virus Infections - diagnosis ; Respiratory Syncytial Virus Infections - virology ; Respiratory Syncytial Viruses - isolation & purification ; Respiratory tract ; Respiratory tract diseases ; Risk analysis ; Risk Factors ; Severity of Illness Index ; Siblings ; Statistical analysis ; Survival Rate ; United Kingdom ; Viruses</subject><ispartof>PloS one, 2013-03, Vol.8 (3), p.e59161-e59161</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Blanken et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Blanken et al 2013 Blanken et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-7765f7023dddffbd0053d24bed7048f5bcfba5c7b6a55e9f94cac12b94cb199f3</citedby><cites>FETCH-LOGICAL-c692t-7765f7023dddffbd0053d24bed7048f5bcfba5c7b6a55e9f94cac12b94cb199f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3595233/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3595233/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2096,2915,23847,27905,27906,53772,53774,79349,79350</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23554987$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Semple, Malcolm Gracie</contributor><creatorcontrib>Blanken, Maarten O</creatorcontrib><creatorcontrib>Koffijberg, Hendrik</creatorcontrib><creatorcontrib>Nibbelke, Elisabeth E</creatorcontrib><creatorcontrib>Rovers, Maroeska M</creatorcontrib><creatorcontrib>Bont, Louis</creatorcontrib><creatorcontrib>Dutch RSV Neonatal Network</creatorcontrib><creatorcontrib>on behalf of the Dutch RSV Neonatal Network</creatorcontrib><title>Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV) hospitalization in preterm infants 33-35 weeks gestational age (WGA).
The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227). In the validation cohort (n = 1,194), predicted versus actual RSV hospitalization rates were compared to determine validity of the model.
RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%). In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2), birth period (OR 2.6; 1.6-4.2), breastfeeding (OR 1.7; 1.0-2.7) and siblings or daycare attendance (OR 4.7; 1.7-13.1). The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping). External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74).
Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants.</description><subject>Age</subject><subject>Analysis</subject><subject>Asthma</subject><subject>Atopy</subject><subject>Birth weight</subject><subject>Breast feeding</subject><subject>Breastfeeding & lactation</subject><subject>Bronchiolitis - diagnosis</subject><subject>Bronchiolitis - virology</subject><subject>Bronchopneumonia</subject><subject>Cardiovascular disease</subject><subject>Cohort analysis</subject><subject>Cohort Studies</subject><subject>Congenital diseases</subject><subject>Cost analysis</subject><subject>Daycare</subject><subject>Derivation</subject><subject>Down syndrome</subject><subject>Families & family life</subject><subject>Female</subject><subject>Gestational age</subject><subject>Hay fever</subject><subject>Health aspects</subject><subject>Hospitalization - statistics & numerical data</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Immunofluorescence</subject><subject>Immunology</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Infant, Premature</subject><subject>Infant, Premature, Diseases - diagnosis</subject><subject>Infant, Premature, Diseases - virology</subject><subject>Infants</subject><subject>Infections</subject><subject>Infectious diseases</subject><subject>Lung diseases</subject><subject>Male</subject><subject>Mathematical models</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Models, Statistical</subject><subject>Newborn babies</subject><subject>Parents & parenting</subject><subject>Pediatrics</subject><subject>Polymerase chain reaction</subject><subject>Prediction models</subject><subject>Premature birth</subject><subject>Premature infants</subject><subject>Prognosis</subject><subject>Prophylaxis</subject><subject>Regression analysis</subject><subject>Respiratory diseases</subject><subject>Respiratory syncytial virus</subject><subject>Respiratory Syncytial Virus Infections - diagnosis</subject><subject>Respiratory Syncytial Virus Infections - virology</subject><subject>Respiratory Syncytial Viruses - isolation & purification</subject><subject>Respiratory tract</subject><subject>Respiratory tract diseases</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>Severity of Illness Index</subject><subject>Siblings</subject><subject>Statistical analysis</subject><subject>Survival Rate</subject><subject>United Kingdom</subject><subject>Viruses</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk1uL1DAUx4so7rr6DUQDgujDjGnSNq0PwrJ4GVhY8fYacp1mSZuapIPzPfzApk53mco-SB_SnPzO_-Sck5NlT3O4zjHJ31y70ffMrgfXqzWEZZNX-b3sNG8wWlUI4vtH_yfZoxCuE4TrqnqYnSBclkVTk9Ps92fvwqBENDsFdswayaJxPXAaMDB4t-1diEaAzkllgXYeeBUG41l0fg_Cvhf7aJgFO-PHALh3vWiNsyaaAEwPLIsqyaiofJf2mvUxvE3K3WiTquqTHXDjYwuEa52PIMRR7h9nDzSzQT2Z17Ps-4f33y4-rS6vPm4uzi9XompQXBFSlZpAhKWUWnM55SdRwZUksKh1yYXmrBSEV6wsVaObQjCRI55WnjeNxmfZ84PuYF2gc0EDzTGGdaoOwYnYHAjp2DUdvOmY31PHDP1rcH5LmU-ZWEU54qypESaa6KJMm0JICZlCqpakhFO0d3O0kXdKTtl7Zheiy5PetHTrdhSXTYnwdJlXs4B3P0cVIu1MEMpa1is3TvdGBa5Jam1CX_yD3p3dTG1ZSiC1x6W4YhKl5wWpMYRNhRK1voNKn1SdEen1aZPsC4fXC4fERPUrbtkYAt18_fL_7NWPJfvyiG0Vs7ENzo7Tgw1LsDiAIj3u4JW-LXIO6TQ8N9Wg0_DQeXiS27PjBt063UwL_gMQyxnz</recordid><startdate>20130312</startdate><enddate>20130312</enddate><creator>Blanken, Maarten O</creator><creator>Koffijberg, Hendrik</creator><creator>Nibbelke, Elisabeth E</creator><creator>Rovers, Maroeska M</creator><creator>Bont, Louis</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20130312</creationdate><title>Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study</title><author>Blanken, Maarten O ; Koffijberg, Hendrik ; Nibbelke, Elisabeth E ; Rovers, Maroeska M ; Bont, Louis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-7765f7023dddffbd0053d24bed7048f5bcfba5c7b6a55e9f94cac12b94cb199f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Age</topic><topic>Analysis</topic><topic>Asthma</topic><topic>Atopy</topic><topic>Birth weight</topic><topic>Breast feeding</topic><topic>Breastfeeding & lactation</topic><topic>Bronchiolitis - diagnosis</topic><topic>Bronchiolitis - virology</topic><topic>Bronchopneumonia</topic><topic>Cardiovascular disease</topic><topic>Cohort analysis</topic><topic>Cohort Studies</topic><topic>Congenital diseases</topic><topic>Cost analysis</topic><topic>Daycare</topic><topic>Derivation</topic><topic>Down syndrome</topic><topic>Families & family life</topic><topic>Female</topic><topic>Gestational age</topic><topic>Hay fever</topic><topic>Health aspects</topic><topic>Hospitalization - statistics & numerical data</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Immunofluorescence</topic><topic>Immunology</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Infant, Premature</topic><topic>Infant, Premature, Diseases - diagnosis</topic><topic>Infant, Premature, Diseases - virology</topic><topic>Infants</topic><topic>Infections</topic><topic>Infectious diseases</topic><topic>Lung diseases</topic><topic>Male</topic><topic>Mathematical models</topic><topic>Medical research</topic><topic>Medicine</topic><topic>Models, Statistical</topic><topic>Newborn babies</topic><topic>Parents & parenting</topic><topic>Pediatrics</topic><topic>Polymerase chain reaction</topic><topic>Prediction models</topic><topic>Premature birth</topic><topic>Premature infants</topic><topic>Prognosis</topic><topic>Prophylaxis</topic><topic>Regression analysis</topic><topic>Respiratory diseases</topic><topic>Respiratory syncytial virus</topic><topic>Respiratory Syncytial Virus Infections - diagnosis</topic><topic>Respiratory Syncytial Virus Infections - virology</topic><topic>Respiratory Syncytial Viruses - isolation & purification</topic><topic>Respiratory tract</topic><topic>Respiratory tract diseases</topic><topic>Risk analysis</topic><topic>Risk Factors</topic><topic>Severity of Illness Index</topic><topic>Siblings</topic><topic>Statistical analysis</topic><topic>Survival Rate</topic><topic>United Kingdom</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Blanken, Maarten O</creatorcontrib><creatorcontrib>Koffijberg, Hendrik</creatorcontrib><creatorcontrib>Nibbelke, Elisabeth E</creatorcontrib><creatorcontrib>Rovers, Maroeska M</creatorcontrib><creatorcontrib>Bont, Louis</creatorcontrib><creatorcontrib>Dutch RSV Neonatal Network</creatorcontrib><creatorcontrib>on behalf of the Dutch RSV Neonatal Network</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Blanken, Maarten O</au><au>Koffijberg, Hendrik</au><au>Nibbelke, Elisabeth E</au><au>Rovers, Maroeska M</au><au>Bont, Louis</au><au>Semple, Malcolm Gracie</au><aucorp>Dutch RSV Neonatal Network</aucorp><aucorp>on behalf of the Dutch RSV Neonatal Network</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-03-12</date><risdate>2013</risdate><volume>8</volume><issue>3</issue><spage>e59161</spage><epage>e59161</epage><pages>e59161-e59161</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV) hospitalization in preterm infants 33-35 weeks gestational age (WGA).
The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227). In the validation cohort (n = 1,194), predicted versus actual RSV hospitalization rates were compared to determine validity of the model.
RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%). In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2), birth period (OR 2.6; 1.6-4.2), breastfeeding (OR 1.7; 1.0-2.7) and siblings or daycare attendance (OR 4.7; 1.7-13.1). The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping). External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74).
Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23554987</pmid><doi>10.1371/journal.pone.0059161</doi><tpages>e59161</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2013-03, Vol.8 (3), p.e59161-e59161 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1330898773 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Age Analysis Asthma Atopy Birth weight Breast feeding Breastfeeding & lactation Bronchiolitis - diagnosis Bronchiolitis - virology Bronchopneumonia Cardiovascular disease Cohort analysis Cohort Studies Congenital diseases Cost analysis Daycare Derivation Down syndrome Families & family life Female Gestational age Hay fever Health aspects Hospitalization - statistics & numerical data Hospitals Humans Immunofluorescence Immunology Infant Infant, Newborn Infant, Premature Infant, Premature, Diseases - diagnosis Infant, Premature, Diseases - virology Infants Infections Infectious diseases Lung diseases Male Mathematical models Medical research Medicine Models, Statistical Newborn babies Parents & parenting Pediatrics Polymerase chain reaction Prediction models Premature birth Premature infants Prognosis Prophylaxis Regression analysis Respiratory diseases Respiratory syncytial virus Respiratory Syncytial Virus Infections - diagnosis Respiratory Syncytial Virus Infections - virology Respiratory Syncytial Viruses - isolation & purification Respiratory tract Respiratory tract diseases Risk analysis Risk Factors Severity of Illness Index Siblings Statistical analysis Survival Rate United Kingdom Viruses |
| title | Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T11%3A20%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prospective%20validation%20of%20a%20prognostic%20model%20for%20respiratory%20syncytial%20virus%20bronchiolitis%20in%20late%20preterm%20infants:%20a%20multicenter%20birth%20cohort%20study&rft.jtitle=PloS%20one&rft.au=Blanken,%20Maarten%20O&rft.aucorp=Dutch%20RSV%20Neonatal%20Network&rft.date=2013-03-12&rft.volume=8&rft.issue=3&rft.spage=e59161&rft.epage=e59161&rft.pages=e59161-e59161&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0059161&rft_dat=%3Cgale_plos_%3EA478300962%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1330898773&rft_id=info:pmid/23554987&rft_galeid=A478300962&rft_doaj_id=oai_doaj_org_article_b2ba98237f7f452ba4cdd0ae2e8d750f&rfr_iscdi=true |