Mathematical Model Used to Project When Preemies Go Home
Using a new mathematical model, researchers have developed a new way to estimate when preemies will go leave the hospital to go home. Preemies are babies born weeks to months early.
The mathematical model was built from data gathered on 2,254 early preemies born at 16 U.S. sites in the Eunice Kennedy Shriver National Institute for Child Health and Human Development Neonatal Research Network. This model will enable doctors to better counsel infants’ families, help hospitals manage resources and provide targets for improving preemies’ medical care.
Susan Hintz, MD and colleagues have published their research online in the December issue of the journal Pediatrics. The preemies studied were born at 27 weeks or earlier gestation. All survived until hospital discharge. Normal human gestation lasts 40 weeks. On average, the preemies stayed in the hospital until the date which would have been their mother's original due date.
The researchers analyzed the data to determine which factors separated the infants who were discharged first from the infants with the longest hospital stays. The mathematical model found five key factors: birth weight less than 750 grams, need for surgery during hospitalization, infections in the bloodstream or digestive system, chronic lung problems, and severe problems with retinal development of the eyes. If an infant has more of these key factors present, then the infant is much more likely to have a long hospital stay.
Hintz stated, "The take-home message is that we can’t predict time to discharge very accurately from day one of hospitalization,." The research team zeroed in on a few key predictors that develop in the first weeks and months of a preemie’s life.
“It was encouraging that this very streamlined, five-factor model was as good as the much more complicated statistical model that we used to predict if a baby would be discharged early or late,” Hintz said. The five-factor model has the potential for development into a useful clinical tool, she added, since counting risk factors is much more practical for a bedside physician than complex statistical analyses.
The five key factors also provides important targets for improving preemies’ care. The research gives additional support to efforts already in place to reduce severe infections among preemies. In addition, because earlier research has shown that several of the key factors are linked with long-term neurological impairment, preventing these problems could also have lifelong benefits for preemies.
In addition to Hintz, the multi-center research team included the following Stanford/Packard scientists: David Stevenson, MD, director of the Johnson Center for Pregnancy and Newborn Services at Packard Children’s and professor of pediatrics and of obstetrics and gynecology at Stanford; Krisa Van Meurs, MD, neonatologist at Packard Children’s and professor of pediatrics at Stanford; Marian Adams, MD, neonatologist at Packard Children’s and clinical assistant professor of pediatrics at Stanford; and clinical research coordinator Bethany Ball.