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https://doi.org/10.1186/s12887-017-0921-x
Title: | Comparing very low birth weight versus very low gestation cohort methods for outcome analysis of high risk preterm infants | Authors: | Koller-Smith, L.I.M Shah, P.S Ye, X.Y |
Keywords: | adult adverse outcome area under the curve Article brain injury chronic lung disease cohort analysis controlled study female gestational age human male mortality necrotizing enterocolitis population research prematurity retinopathy risk factor small for date infant validation study very low birth weight Australia benchmarking Canada comparative study decision support system epidemiology hospital mortality infant infant mortality New Zealand newborn newborn intensive care prognosis receiver operating characteristic retrospective study selection bias statistical model Sweden Area Under Curve Australia Benchmarking Canada Decision Support Techniques Female Gestational Age Hospital Mortality Humans Infant Infant Mortality Infant, Extremely Premature Infant, Newborn Infant, Premature Infant, Premature, Diseases Infant, Small for Gestational Age Infant, Very Low Birth Weight Intensive Care, Neonatal Male Models, Statistical New Zealand Prognosis Retrospective Studies Risk Factors ROC Curve Selection Bias Sweden |
Issue Date: | 2017 | Citation: | Koller-Smith, L.I.M, Shah, P.S, Ye, X.Y (2017). Comparing very low birth weight versus very low gestation cohort methods for outcome analysis of high risk preterm infants. BMC Pediatrics 17 (1) : 166. ScholarBank@NUS Repository. https://doi.org/10.1186/s12887-017-0921-x | Rights: | Attribution 4.0 International | Abstract: | Background: Compared to very low gestational age (<32 weeks, VLGA) cohorts, very low birth weight (<1500 g; VLBW) cohorts are more prone to selection bias toward small-for-gestational age (SGA) infants, which may impact upon the validity of data for benchmarking purposes. Method: Data from all VLGA or VLBW infants admitted in the 3 Networks between 2008 and 2011 were used. Two-thirds of each network cohort was randomly selected to develop prediction models for mortality and composite adverse outcome (CAO: mortality or cerebral injuries, chronic lung disease, severe retinopathy or necrotizing enterocolitis) and the remaining for internal validation. Areas under the ROC curves (AUC) of the models were compared. Results: VLBW cohort (24,335 infants) had twice more SGA infants (20.4% vs. 9.3%) than the VLGA cohort (29,180 infants) and had a higher rate of CAO (36.5% vs. 32.6%). The two models had equal prediction power for mortality and CAO (AUC 0.83), and similarly for all other cross-cohort validations (AUC 0.81-0.85). Neither model performed well for the extremes of birth weight for gestation (<1500 g and ≥32 weeks, AUC 0.50-0.65; ≥1500 g and <32 weeks, AUC 0.60-0.62). Conclusion: There was no difference in prediction power for adverse outcome between cohorting VLGA or VLBW despite substantial bias in SGA population. Either cohorting practises are suitable for international benchmarking. © 2017 The Author(s). | Source Title: | BMC Pediatrics | URI: | https://scholarbank.nus.edu.sg/handle/10635/181261 | ISSN: | 14712431 | DOI: | 10.1186/s12887-017-0921-x | Rights: | Attribution 4.0 International |
Appears in Collections: | Elements Staff Publications |
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