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Development of a Risk Score to Predict Sudden Infant Death Syndrome
Sudden Infant Death Syndrome (SIDS) is the third leading cause of death among infants younger than one year of age. Effective SIDS prediction models have yet to be developed. Hence, we developed a risk score for SIDS, testing contemporary factors including infant exposure to passive smoke, circumcis...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407916/ https://www.ncbi.nlm.nih.gov/pubmed/36011906 http://dx.doi.org/10.3390/ijerph191610270 |
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author | Polavarapu, Mounika Klonoff-Cohen, Hillary Joshi, Divya Kumar, Praveen An, Ruopeng Rosenblatt, Karin |
author_facet | Polavarapu, Mounika Klonoff-Cohen, Hillary Joshi, Divya Kumar, Praveen An, Ruopeng Rosenblatt, Karin |
author_sort | Polavarapu, Mounika |
collection | PubMed |
description | Sudden Infant Death Syndrome (SIDS) is the third leading cause of death among infants younger than one year of age. Effective SIDS prediction models have yet to be developed. Hence, we developed a risk score for SIDS, testing contemporary factors including infant exposure to passive smoke, circumcision, and sleep position along with known risk factors based on 291 SIDS and 242 healthy control infants. The data were retrieved from death certificates, parent interviews, and medical records collected between 1989–1992, prior to the Back to Sleep Campaign. Multivariable logistic regression models were performed to develop a risk score model. Our finalized risk score model included: (i) breastfeeding duration (OR = 13.85, p < 0.001); (ii) family history of SIDS (OR = 4.31, p < 0.001); (iii) low birth weight (OR = 2.74, p = 0.003); (iv) exposure to passive smoking (OR = 2.64, p < 0.001); (v) maternal anemia during pregnancy (OR = 2.07, p = 0.03); and (vi) maternal age <25 years (OR = 1.77, p = 0.01). The area under the curve for the overall model was 0.79, and the sensitivity and specificity were 79% and 63%, respectively. Once this risk score is further validated it could ultimately help physicians identify the high risk infants and counsel parents about modifiable risk factors that are most predictive of SIDS. |
format | Online Article Text |
id | pubmed-9407916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94079162022-08-26 Development of a Risk Score to Predict Sudden Infant Death Syndrome Polavarapu, Mounika Klonoff-Cohen, Hillary Joshi, Divya Kumar, Praveen An, Ruopeng Rosenblatt, Karin Int J Environ Res Public Health Article Sudden Infant Death Syndrome (SIDS) is the third leading cause of death among infants younger than one year of age. Effective SIDS prediction models have yet to be developed. Hence, we developed a risk score for SIDS, testing contemporary factors including infant exposure to passive smoke, circumcision, and sleep position along with known risk factors based on 291 SIDS and 242 healthy control infants. The data were retrieved from death certificates, parent interviews, and medical records collected between 1989–1992, prior to the Back to Sleep Campaign. Multivariable logistic regression models were performed to develop a risk score model. Our finalized risk score model included: (i) breastfeeding duration (OR = 13.85, p < 0.001); (ii) family history of SIDS (OR = 4.31, p < 0.001); (iii) low birth weight (OR = 2.74, p = 0.003); (iv) exposure to passive smoking (OR = 2.64, p < 0.001); (v) maternal anemia during pregnancy (OR = 2.07, p = 0.03); and (vi) maternal age <25 years (OR = 1.77, p = 0.01). The area under the curve for the overall model was 0.79, and the sensitivity and specificity were 79% and 63%, respectively. Once this risk score is further validated it could ultimately help physicians identify the high risk infants and counsel parents about modifiable risk factors that are most predictive of SIDS. MDPI 2022-08-18 /pmc/articles/PMC9407916/ /pubmed/36011906 http://dx.doi.org/10.3390/ijerph191610270 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Polavarapu, Mounika Klonoff-Cohen, Hillary Joshi, Divya Kumar, Praveen An, Ruopeng Rosenblatt, Karin Development of a Risk Score to Predict Sudden Infant Death Syndrome |
title | Development of a Risk Score to Predict Sudden Infant Death Syndrome |
title_full | Development of a Risk Score to Predict Sudden Infant Death Syndrome |
title_fullStr | Development of a Risk Score to Predict Sudden Infant Death Syndrome |
title_full_unstemmed | Development of a Risk Score to Predict Sudden Infant Death Syndrome |
title_short | Development of a Risk Score to Predict Sudden Infant Death Syndrome |
title_sort | development of a risk score to predict sudden infant death syndrome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407916/ https://www.ncbi.nlm.nih.gov/pubmed/36011906 http://dx.doi.org/10.3390/ijerph191610270 |
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