Survival prediction modelling in extreme prematurity: are days important?

Schindler, T; Hayen, A; Tan, AHK; Bolisetty, S; Lui, K

Survival prediction modelling in extreme prematurity: are days important?

Schindler, T Hayen, A

Tan, AHK Bolisetty, S Lui, K

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Publisher:: SPRINGERNATURE
Publication Type:: Journal Article
Citation:: J Perinatol, 2022, 42, (2), pp. 177-180
Issue Date:: 2022-02

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Field	Value	Language
dc.contributor.author	Schindler, T
dc.contributor.author	Hayen, A https://orcid.org/0000-0003-4046-8030
dc.contributor.author	Tan, AHK
dc.contributor.author	Bolisetty, S
dc.contributor.author	Lui, K
dc.date.accessioned	2022-03-25T03:25:15Z
dc.date.available	2021-09-09
dc.date.available	2022-03-25T03:25:15Z
dc.date.issued	2022-02
dc.identifier.citation	J Perinatol, 2022, 42, (2), pp. 177-180
dc.identifier.issn	0743-8346
dc.identifier.issn	1476-5543
dc.identifier.uri	http://hdl.handle.net/10453/155545
dc.description.abstract	OBJECTIVE: To demonstrate that days are important in extreme prematurity when creating survival prediction models based on gestation. STUDY DESIGN: Prospectively collected data were analysed for all admitted infants born 23 + 0 to 27 + 6 weeks gestation in the Australian and New Zealand Neonatal Network from 2009 to 2016. The effect of days on observed survival rates was assessed using a non-parametric test for trend. Prediction models created based on gestational age in completed weeks only or weeks plus days were compared. RESULT: Seven thousand eight hundred and thirty-six extreme preterm infants were studied. Observed survival increased with days for 23, 24, 25, and 27 weeks gestational age (P = 0.01; P < 0.001; P = 0.003; P = 0.003) but not for 26 weeks (P = 0.19). A survival prediction model based on weeks and days performed better than completed weeks only (AUC 0.722 vs 0.712; P < 0.001). CONCLUSION: In extreme prematurity, survival estimate accuracy improves when survival prediction models include days in addition to weeks.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	SPRINGERNATURE
dc.relation.ispartof	J Perinatol
dc.relation.isbasedon	10.1038/s41372-021-01208-1
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	1103 Clinical Sciences, 1114 Paediatrics and Reproductive Medicine
dc.subject.classification	Pediatrics
dc.title	Survival prediction modelling in extreme prematurity: are days important?
dc.type	Journal Article
utslib.citation.volume	42
utslib.location.activity	United States
utslib.for	1103 Clinical Sciences
utslib.for	1114 Paediatrics and Reproductive Medicine
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
pubs.organisational-group	/University of Technology Sydney/Faculty of Health/Public Health
utslib.copyright.status	closed_access	*
dc.date.updated	2022-03-25T03:25:14Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	42
utslib.citation.issue	2

Abstract:

OBJECTIVE: To demonstrate that days are important in extreme prematurity when creating survival prediction models based on gestation. STUDY DESIGN: Prospectively collected data were analysed for all admitted infants born 23 + 0 to 27 + 6 weeks gestation in the Australian and New Zealand Neonatal Network from 2009 to 2016. The effect of days on observed survival rates was assessed using a non-parametric test for trend. Prediction models created based on gestational age in completed weeks only or weeks plus days were compared. RESULT: Seven thousand eight hundred and thirty-six extreme preterm infants were studied. Observed survival increased with days for 23, 24, 25, and 27 weeks gestational age (P = 0.01; P < 0.001; P = 0.003; P = 0.003) but not for 26 weeks (P = 0.19). A survival prediction model based on weeks and days performed better than completed weeks only (AUC 0.722 vs 0.712; P < 0.001). CONCLUSION: In extreme prematurity, survival estimate accuracy improves when survival prediction models include days in addition to weeks.

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http://hdl.handle.net/10453/155545