Development and Validation of a Risk Scoring Tool to Predict Respiratory Syncytial Virus Hospitalization in Premature Infants Born at 33 through 35 Completed Weeks of Gestation

John S. Sampalis, Joanne Langley, Xavier Carbonell-Estrany, Bosco Paes, Karel O'Brien, Upton Allen, Ian Mitchell, José Figueras Aloy, Carmen Pedraz and Andrea F. Michaliszyn
Additional contact information
John S. Sampalis: Department of Surgery and Medicine, McGill University and JSS Medical Research Inc., Montreal, Quebec, Canada
Joanne Langley: Departments of Pediatrics and Community Health and Epidemiology, Dalhousie University and the IWK Health Centre, Halifax, Nova Scotia, Canada
Xavier Carbonell-Estrany: Neonatology Service, Hospital Clinic, Institut Clinic Ginecologia Obstetricia i Neonatologia, Universidad de Barcelona, Barcelona, Spain
Bosco Paes: Division of Neonatology, Department of Pediatrics, McMaster Children's Hospital, Hamilton, Ontario, Canada
Karel O'Brien: Department of Pediatrics, University of Toronto and Mount Sinai Hospital, Toronto, Ontario, Canada
Upton Allen: Division of Infectious Diseases, Department of Pediatrics, Hospital for Sick Children, Toronto, Ontario, Canada
Ian Mitchell: Department of Pediatrics, Alberta's Children's Hospital and University of Calgary, Calgary, Alberta, Canada
José Figueras Aloy: Neonatology Service, Hospital Clinic, Institut Clinic Ginecologia Obstetricia i Neonatologia, Universidad de Barcelona, Barcelona, Spain
Carmen Pedraz: Neonatology Service, Hospital Clinico, Salamanca, Spain
Andrea F. Michaliszyn: Abbott Laboratories Limited, Montreal, Quebec, Canada

Medical Decision Making, 2008, vol. 28, issue 4, 471-480

Abstract: Objective. The purpose of the study was to develop and validate a clinical instrument predicting the risk of respiratory syncytial virus (RSV)-associated hospitalization (RSV-H) in premature infants born at 33 through 35 completed weeks of gestation (33 — 35GA). Design. An RSV risk scoring tool (RSV-RS) was developed by entering risk factors for RSV-H, determined in a Canadian prospective study, into a multiple logistic regression model. The scoring tool was then validated externally with data from a Spanish case-control study (FLIP). The Canadian cohort comprised 1758 RSV-positive infants born 33 — 35GA, of whom 66 (3.7%) had confirmed RSV-H. The FLIP data set comprised 186 (33.4%) RSV-H cases and 371 (66.7%) controls. Method. The primary outcome measure was RSV-H. The RSV-RS score was the sum of the weighted probabilities for each included risk factor multiplied by 100 and ranged from 0 to 100. Receiver operator characteristic curve analyses determined cutoff points to predict subjects at low, moderate, or high RSV-H risk. Results. The RSV-RS included 7 risk factors and cutoff scores of 0 — 48, 49 — 64, and 65 — 100 for low-, moderate-, and high-risk subjects, respectively. For the Canadian cohort, RSV-RS sensitivity in predicting RSV-H cases was 68.2%, with 71.9% specificity. With the FLIP data set, the RSV-RS had lower accuracy (61.3% sensitivity; 65.8% specificity) but showed significant positive association with increased risk for RSV-H. Conclusion. The RSV-RS accurately identified 33 — 35GA infants at increased risk for RSV-H in a Canadian cohort. External validation with Spanish case-control study data further confirmed that the scoring tool is appropriate for the estimation of RSV-H risk.

Keywords: hospitalization; prematurity; respiratory syncytial virus; risk assessment; risk factors; scoring tool. (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X08315238 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:28:y:2008:i:4:p:471-480

DOI: 10.1177/0272989X08315238

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().