Title | Pattern Discrimination Software for Uncertainty Reduction in Neonatal Cardiovascular Risk Assessment |
Author(s) | Ramon C. Hermida; Artermio Mojon; Fernando Aguado; Diane E. Ayala |
Source | Proceedings of the 1994 IEEE Seventh Symposium on Computer-Based Medical Systems, Pages 299-304 |
ISBN | 0-8186-6257-3 |
Publisher | IEEE Computer Society Press |
Publication Date | 1994 |
Abstract | Genetic risk is a primary contributing factor to the predisposition of a newborn child to elevated blood pressure later in life. To determine whether there is a correlation between potential genetic risk as established by family history and measured physiologic variables in the neonate, the systolic and diastolic blood pressures and heart rates of 150 newborn babies were automatically monitored at about 30-minute intervals for 48 hours with a Nippon Colin device, starting early after birth. On the basis of questionnaires given to the parents, the neonates were assigned to a group of either a negative or positive family history of high blood pressure. Circadian characteristics (obtained by the least-squares fit of a 24-hour cosine curve to each individual series) and descriptive statistics of the three circulatory variables were used for classification by a so-called "monotest," an all-subsets variable selection technique for biomedical discriminant anlysis. For a particular combination of variables, the "monotest" performs as many steps of separate analyses as the total number of subjects, each subject's data being compared as a set with those of all others ("leave-one-out" approach). When the circadian amplitudes of systolic blood pressure and heart rate and the circadian range of heart rate were used as a combined classifier, the "monotest" yielded a 70% classification equivalent to prior criteria, the latter being based on a negative or positive family history of high blood pressure. The combined use of automatic hardware for time-specified sampling with proper software for signal processing and discriminant analysis allows us to recognize parmeters of blood pressure circadian variability as a source of information for neonatal classification according to cardiovascular risk. |