Early prediction of poor outcome in extremely low birth weight infants by classification tree analysis.
J Pediatr
; 148(4): 438-444, 2006 Apr.
Article
in En
| MEDLINE
| ID: mdl-16647401
ABSTRACT
OBJECTIVE:
To predict death or neurodevelopmental impairment (NDI) in extremely low birth weight infants by classification trees with recursive partitioning and automatic selection of optimal cut points of variables. STUDYDESIGN:
Data from the Trial of Indomethacin Prophylaxis in Preterms were randomly divided into development (n=784) and validation sets (n=262). Three models were developed for the combined outcome of death (8 days to 18 months) or NDI (cerebral palsy, cognitive delay, deafness, or blindness at 18 months corrected age) antenatal antenatal data; early neonatal antenatal+first 3 days data; and first week antenatal, first 3 days, and 4th to 8th days data. Decision trees were tested on the validation set.RESULTS:
Variables associated with death/NDI in each model were Antenatal GestationCONCLUSIONS:
The ability to predict long-term morbidity/death in extremely low birth weight infants does not improve significantly over the first week of life. Effects of different variables depend on age.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Infant, Premature
/
Decision Trees
/
Infant, Very Low Birth Weight
/
Fetal Viability
Type of study:
Clinical_trials
/
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Female
/
Humans
/
Male
/
Newborn
Language:
En
Journal:
J Pediatr
Year:
2006
Document type:
Article
Affiliation country:
Estados Unidos