A Bayesian approach to real-time spatiotemporal prediction systems for bronchiolitis

Heaton, Matthew J.; Ingersoll, Celeste; Berrett, Candace; Hartman, Brian; Sloan, Chantel D.

doi:10.1016/j.sste.2021.100434

Cited by 1 publication

(1 citation statement)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several of these previous algorithms also were developed using data only from preterm infants ( 16 , 17 ), thereby limiting their generalizability as compared to our MLA. As a preventive tool, Heaton et al developed an MLA to predict seasonal RSV outbreaks to allow for timely immunoprophylaxis injections for children predisposed to poor infection outcomes ( 18 ). Other studies using MLAs that predict suitable treatment courses ( 19 ) or patient outcomes ( 15 , 20 ) for bronchiolitis patients, a disease commonly caused by RSV, require a proper diagnosis prior to running the algorithm.…”

Section: Discussionmentioning

confidence: 99%

Machine learning early prediction of respiratory syncytial virus in pediatric hospitalized patients

et al. 2022

View full text Add to dashboard Cite

Respiratory syncytial virus (RSV) causes millions of infections among children in the US each year and can cause severe disease or death. Infections that are not promptly detected can cause outbreaks that put other hospitalized patients at risk. No tools besides diagnostic testing are available to rapidly and reliably predict RSV infections among hospitalized patients. We conducted a retrospective study from pediatric electronic health record (EHR) data and built a machine learning model to predict whether a patient will test positive to RSV by nucleic acid amplification test during their stay. Our model demonstrated excellent discrimination with an area under the receiver-operating curve of 0.919, a sensitivity of 0.802, and specificity of 0.876. Our model can help clinicians identify patients who may have RSV infections rapidly and cost-effectively. Successfully integrating this model into routine pediatric inpatient care may assist efforts in patient care and infection control.

show abstract