Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study

Abstract Background Gaining a better understanding of the probability, timing and prediction of rehospitalisation amongst preterm babies could help improve outcomes. There is limited research addressing these topics amongst extremely and very preterm babies. In this context, unplanned rehospitalisat...

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Main Authors: Robert Anthony Reed (Author), Andrei Scott Morgan (Author), Jennifer Zeitlin (Author), Pierre-Henri Jarreau (Author), Héloïse Torchin (Author), Véronique Pierrat (Author), Pierre-Yves Ancel (Author), Babak Khoshnood (Author)
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Published: BMC, 2019-11-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Robert Anthony Reed  |e author 
700 1 0 |a Andrei Scott Morgan  |e author 
700 1 0 |a Jennifer Zeitlin  |e author 
700 1 0 |a Pierre-Henri Jarreau  |e author 
700 1 0 |a Héloïse Torchin  |e author 
700 1 0 |a Véronique Pierrat  |e author 
700 1 0 |a Pierre-Yves Ancel  |e author 
700 1 0 |a Babak Khoshnood  |e author 
245 0 0 |a Assessing the risk of early unplanned rehospitalisation in preterm babies: EPIPAGE 2 study 
260 |b BMC,   |c 2019-11-01T00:00:00Z. 
500 |a 10.1186/s12887-019-1827-6 
500 |a 1471-2431 
520 |a Abstract Background Gaining a better understanding of the probability, timing and prediction of rehospitalisation amongst preterm babies could help improve outcomes. There is limited research addressing these topics amongst extremely and very preterm babies. In this context, unplanned rehospitalisations constitute an important, potentially modifiable adverse event. We aimed to establish the probability, time-distribution and predictability of unplanned rehospitalisation within 30 days of discharge in a population of French preterm babies. Methods This study used data from EPIPAGE 2, a population-based prospective study of French preterm babies. Only those babies discharged home alive and whose parents responded to the one-year survey were eligible for inclusion in our study. For Kaplan-Meier analysis, the outcome was unplanned rehospitalisation censored at 30 days. For predictive modelling, the outcome was binary, recording unplanned rehospitalisation within 30 days of discharge. Predictors included routine clinical variables selected based on expert opinion. Results Of 3841 eligible babies, 350 (9.1, 95% CI 8.2-10.1) experienced an unplanned rehospitalisation within 30 days. The probability of rehospitalisation progressed at a consistent rate over the 30 days. There were significant differences in rehospitalisation probability by gestational age. The cross-validated performance of a ten predictor model demonstrated low discrimination and calibration. The area under the receiver operating characteristic curve was 0.62 (95% CI 0.59-0.65). Conclusions Unplanned rehospitalisation within 30 days of discharge was infrequent and the probability of rehospitalisation progressed at a consistent rate. Lower gestational age increased the probability of rehospitalisation. Predictive models comprised of clinically important variables had limited predictive ability. 
546 |a EN 
690 |a Prematurity 
690 |a Newborn 
690 |a Neonatology 
690 |a Rehospitalisation 
690 |a Discharge 
690 |a Prediction 
690 |a Pediatrics 
690 |a RJ1-570 
655 7 |a article  |2 local 
786 0 |n BMC Pediatrics, Vol 19, Iss 1, Pp 1-11 (2019) 
787 0 |n http://link.springer.com/article/10.1186/s12887-019-1827-6 
787 0 |n https://doaj.org/toc/1471-2431 
856 4 1 |u https://doaj.org/article/f79556af7dce4dabb414bc932b4561e4  |z Connect to this object online.