IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i16p10270-d891489.html
   My bibliography  Save this article

Development of a Risk Score to Predict Sudden Infant Death Syndrome

Author

Listed:
  • Mounika Polavarapu

    (School of Population Health, The University of Toledo, HH 1010, Mail Stop 119, 2801 W. Bancroft St., Toledo, OH 43606, USA)

  • Hillary Klonoff-Cohen

    (Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

  • Divya Joshi

    (Department of Pediatrics, Johns Hopkins All Children’s Hospital, St. Petersburg, FL 33701, USA)

  • Praveen Kumar

    (Department of Pediatrics, Children’s Hospital of Illinois, Peoria, IL 61603, USA)

  • Ruopeng An

    (Brown School, Washington University in St. Louis, St. Louis, MO 63130, USA)

  • Karin Rosenblatt

    (Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

Abstract

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.

Suggested Citation

  • Mounika Polavarapu & Hillary Klonoff-Cohen & Divya Joshi & Praveen Kumar & Ruopeng An & Karin Rosenblatt, 2022. "Development of a Risk Score to Predict Sudden Infant Death Syndrome," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10270-:d:891489
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/16/10270/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/16/10270/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10270-:d:891489. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.