Relationship between large-for-gestational age and hospital readmission after postpartum discharge

Relationship between large-for-gestational age and hospital readmission after postpartum discharge | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationship between large-for-gestational age and hospital readmission after postpartum discharge M Nimal, C Ravel, S Nauleau, D Lapalus, O Bernard, C des Robert, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2397144/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Mar, 2023 Read the published version in European Journal of Pediatrics → Version 1 posted 7 You are reading this latest preprint version Abstract Objective To determine the association of small (SGA) and large (LGA) for gestational age at birth with hospital readmission after postpartum discharge for up to 28 days of delivery Methods Population-based linkage study using the French National Uniform Hospital Discharge Database. ‘Healthy’ singleton term infants born between January 1st, 2017 and November 30th, 2018 in the French South region were included. SGA and LGA were defined as birth weight 90th percentiles, respectively, according to sex and gestational age. A multivariable regression analysis was performed. Results Among 67,359 included infants, 2441 (3.6%) were re-admitted and 61% of them were hospitalized within 14 days postpartum. Hospitalized infants were more likely to be LGA at birth (10.3% vs. 8.6% in non-hospitalized infants, p < 0.01); the proportion of SGA infants did not differ between both groups. Compared to appropriate birth weight for GA (AGA) infants, LGA infants were more often hospitalized for infectious diseases (57.7% vs. 51.3%, p = 0.05). After regression analysis LGA infants had a 20% higher odds of being hospitalized than those born AGA (aOR(95%CI) = 1.21 (1.06–1.39)) while aOR(95%CI) for SGA was 1.11 (0.96–1.28). Conclusions In contrast to SGA, LGA was associated with hospital readmission during the first month of life. Follow-up protocols that include LGA should be evaluated. postpartum discharge LGA SGA infectious disease Figures Figure 1 Figure 2 What Is Known Newborns are at high risk of hospital re-admission during the post-partum period. Prematurity, male, siblings, young mother, living in deprived socioeconomic conditions, or discharged early after delivery are known risk factors. However, the influence of appropriateness for gestational age at birth, i.e. being born small-for-gestational age (SGA) or large-for-gestational age (LGA), has been little evaluated. What is knew: In contrast to SGA born infants, we found that infants born LGA were at high risk of hospital admission and the main cause was infectious diseases. This population should be considered at risk of early adverse outcomes and should require attentive medical follow-up after postpartum discharge. Introduction The post-partum period is a critical period for newborns. They are at high risk of hospital re-admission which can reach 10%; the principal causes are jaundice, feeding difficulties, dehydration, and infection ( 1 – 7 ). Infants who are immature at birth (up to 38 weeks of gestational age), male, have siblings, born to a young mother, living in deprived socioeconomic conditions, or discharged early after delivery are particularly vulnerable. However, the influence of trophicity at birth, i.e. being born small-for-gestational age (SGA) or large-for-gestational age (LGA), has not been thoroughly evaluated and requires further investigation. LGA is a growing public health concern worldwide. Its prevalence varies from 5–20%, and the number of LGA infants has increased over the last two decades and is expected to increase in several countries ( 8 – 12 ). These temporal trends are related to various factors, including the advancing age of pregnant women, increased maternal obesity and gestational diabetes, and social inequalities ( 8 , 11 – 15 ). LGA is known to increase the risk of numerous adverse perinatal and birth outcomes, including caesarean delivery, postpartum haemorrhage, shoulder dystocia, perinatal asphyxia, neonatal hypoglycaemia, hyperbilirubinemia, and neonatal respiratory distress disorders ( 13 , 16 , 17 ). Although SGA is associated with increased neonatal mortality and hospital readmission rates after the neonatal period, little is known about how SGA and LGA at birth influence outcomes in the postpartum period ( 18 – 20 ). Accordingly, this study aimed to determine whether SGA and LGA at birth were associated with hospital readmission for up to 28 days after delivery. The key sociodemographic and clinical confounding factors in a large population-based study using data from the French National Health Care Database system were studied. Methods Study design and population This population-based cohort study was a retrospective analysis of a prospective cohort using data from the French National Uniform Hospital Discharge Database ( Programme de Médicalisation du Système d’Information , [PMSI]), which systematically collects administrative and medical information, including obstetrical and infant characteristics. The PMSI database is based on diagnosis-related groups, using the International Classification of Diseases, Tenth Revision (ICD-10) ( 21 ). All data are fully anonymized and informed written patients consent are not required. In France all of the Regional Health Agencies are granted access to this database (Agence Technique d’Information sur l’Hospitalisation https://www.atih.sante.fr/ ), in compliance with French law after a deliberation of the French Commission for Data Protection and Liberties (CNIL) with the methodological reference MR005. The study population included all live singleton births within the Provence Alps Cote d’Azur (PACA) region between January 1st, 2017 and November 30th, 2018 with a gestational age (GA) above 36 weeks. Infants whose parents were domiciled outside the PACA region, with congenital anomalies or genetic disorders (Supplementary table), infants who were initially hospitalized or died during initial hospital stay, and infants requiring a prolonged initial maternity stay of ≥ 10 days were excluded (as mean maternity length of stay in France is about 4 to 5 days). We also excluded in-hospital stays with qualitative issues owing to linking problems (including absence or errors in mother to infant linkage), transfers from hospitals in another geographical area, charts without maternal address codes, cases in which the number of infants has not been specified, and infants with an aberrant weight for gestational age. Primary Outcome and sociodemographic data The primary outcome of interest was the hospital admission rate after postpartum discharge for up to 28 days after birth. The causes of hospitalization were determined according to ICD codes and classified as infectious disease, metabolic disorders (i.e. mainly jaundice P57–P59 and R17), digestive and nutrition/growth disorders (i.e. dehydration P74.1 and E86, feeding intolerance/insufficient feeding/, growth insufficiency, P92, P98 and E40–E46), neurologic abnormalities, non-infectious respiratory events, surgery and trauma and other causes (including social problems Z59, Z63, Z81) (Supplementary table). Maternal and obstetric data were obtained from the maternal hospital discharge database. Information on maternal age, obstetrical pathology, mode of delivery (i.e., caesarean section, ICD-10 code O82), and maternity level delivery were collected. Obstetric pathology was determined according to the presence of one of the following complications: preeclampsia (ICD-10 codes O12–O15), gestational diabetes (ICD-10 codes O24.4), placental abruption and previa (ICD-10 codes O44, O45), preterm premature rupture of membranes (O42), and chorioamnionitis (ICD-10 codes O41.1). GA, sex, and birth weight were also recorded. SGA, adapted-for-gestational (AGA), and LGA were respectively defined as a birth weight lower than the 10th percentile, within the 10th and 90th percentile, and higher than the 90th percentile for sex based on the national French growth chart (22). The length of stay in the maternity ward was also recorded. Early postpartum discharge was defined according to the recommendations of the French Health Care Authority ( Haute Autorité de Santé ) as less than 3 days for vaginal delivery and less than 4 days for caesarean delivery ( 23 ). Socioeconomic status was determined at the individual/family level based on health care insurance coverage and at the geographical level using a socioeconomic disadvantage index (SDI). Complementary health care insurance coverage, which provides universal health care coverage, is dedicated to the most disadvantaged families based on home income. SDI was calculated using five key socioeconomic and demographic variables extracted from the 2015 census data linked to each local residential municipality (French National Institute of Statistics and Economic Studies [Institut National de la Statistique et des Etudes Economiques]): median household income, unemployment rate, percentage of people aged ≥ 15 years who failed to graduate from high school, percentage of single-parent families, and percentage of families in rented accommodations. SDI scores ranged from Level 1 (affluent) to Level 5 (most disadvantaged) ( 24 ). The SDI score is based on the mother-commune postcode. In this study, we compared infants living in the most disadvantaged neighbourhoods to those living in affluent areas. Data analysis Univariate parametric and nonparametric analyses were performed using the χ 2 test or Fisher’s exact test for categorical variables, and the Student t t-test or Mann–Whitney U test was performed for quantitative variables, as appropriate. A stepwise multivariable regression analysis was performed to estimate the LGA and SGA factors for postpartum hospital admission for up to 28 days of delivery. Available variables were included in the final regression model. A two-sided P- value < 0.05 was considered statistically significant. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. Statistical analysis was performed using SAS 9·4 (SAS Institute). Results Between January 1st, 2017 and November 30th, 2018, 106,071 singleton newborns were born alive with a GA > 36 weeks in the PACA region. Of this population, 38,532 newborns were excluded; 24,773 were excluded based on the exclusion criteria, and 13,759 (12.9%) were excluded for various administrative, identification, and linkage errors (Fig. 1 ). Thus, 67,539 newborns were included in this analysis. During the study period, 2441 (3.6%) infants were hospitalized within the postpartum period for up to 28 days after birth. The mean (standard deviation [SD]) hospital length of stay and time from birth were 2.8 (2.5) days and 12.3 ( 7 ) days, respectively; 60.8% of infants were hospitalized within 14 days postpartum. The principal causes were infectious diseases (52%), digestive disorders (23%), and metabolic and growth disorders (4%) (i.e. mainly jaundice). The causes varied according to GA, especially for metabolic disorders, which decreased from 23–2% in infants with a GA of 36 weeks and 41 weeks, respectively (p < 0.001). Compared with AGA infants, LGA infants were more likely to be hospitalized for infectious diseases (57.7% vs. 51.3%, p = 0.05) and SGA infants tended to be more frequently hospitalized for nutrition/digestive disorders (28.1% vs.23.1%, p = 0.09) (Fig. 2 ). No differences were observed between SGA and AGA infants. Table 1 shows the perinatal characteristics of hospitalized infants. These infants were more likely to be born to young and socioeconomically deprived mothers, to be male, or born early (GA between 36 and 38 weeks, 26.7% vs. 20.4%; p < 0.001). The rate of LGA at birth was 20% higher in the hospitalized infant population (p < 0.01), whereas no difference was observed in the rate of SGA. The modes of delivery and maternity length of stay did not differ between the LGA and AGA infants. Table 1 Demographic characteristics of hospitalized infants Characteristics, n (%) Overall population n = 67 539 Hospitalized infants n = 2 441 Non-Hospitalized infants n = 65 098 P Obstetrical data Maternal age, years* 30.4 +/- 5.2 29.6 +/- 5.4 30,4 +/- 5.2 < 0.001 Maternal age, years < 25 y 8 751 (13.0) 423 (17.3) 8 328 (12.8) 35 y 14 932 (22.1) 461 (18.9) 14 471 (2.2) Maternal pathology, n (%) Pre-eclampsia Placenta praevia/abruptio Gestational diabetes Chorioamionitis/PPROM 18 857 (27.9) 1 941 (2.9) 383 (0.6) 6 282 (9.3) 10 251 (15.2) 726 (29.7) 85 (3.5) 15 (0.6) 239 (9.8) 387 (15.9) 18 131 (27.9) 1 856 (2.9) 368 (0.6) 6 043 (9.3) 9 864 (15.2) 0.10 IDS Score Low (Least disadvantaged) 3 644 (5.4) 115 (4.7) 3 529 (5.4) < 0.001 High (most disadvantaged) 6 786 (10.0) 315 (12.9) 6 471 (9.9) CHCI 12 855 (19.0) 613 (25.1) 12 242 (18.8) < 0.001 Maternity level Type I Type II Type III 20 133 (29.8) 40 480 (59.9) 6 926 (10.3) 656 (26.9) 1 499 (61.4) 286 (11.7) 19 477 (29.9) 38 981 (59.9) 6 640 (10.2) < 0.01 Vaginal delivery LOS, days* Early Discharge 55 349 (82.0) 3.6 +/- 0.9 3 480 (6.3) 2 007 (82.2) 3.6 +/- 1.0 136 (6.8) 53 342 (81.9) 3.6 +/- 0.9 3 344 (6.3) 0.73 0.45 0.36 Cesarean section LOS, days* Early discharge 12 004 (17.8) 4.5 +/- 0.9 614 (5.1) 427 (17.5) 4.6 +/- 1.0 26 (6.1) 11 571 (17.8) 4.6 +/- 0.8 588 (5.1) 0.71 0.12 0.35 Neonatal data GA, weeks* 39.4 +/- 1.2 39.2 +/- 1.3 39.4 +/- 1.2 < 0.001 GA, weeks 36 wks 884 (1.3) 60 (2.4) 824 (1.3) < 0.001 37 wks 3 233 (4.8) 173 (7.1) 3 060 (4.7) 38 wks 9 869 (14.6) 419 (17.2) 9 450 (14.5) 39 wks 20 222 (29.9) 704 (28.8) 19 518 (30.0) 40 wks 19 936 (29.5) 639 (26.2) 19 297 (29.6) ≥ 41 wks 13 395 (19.8) 446 (18.3) 12 949 (19.9) Female sexe 33 324 (49.3) 1 123 (46.0) 32 201 (49.5) < 0.001 Birthweight, gr* 3342 +/- 432 3339 +/- 452 3342 +/- 432 0.71 SGA 5 870 (8.7) 224 (9.2) 5 646 (8.7) 0.39 LGA 5 882 (8.7) 251 (10.3) 5 631 (8.6) 0.01 Medical visits 40 122 (59.4) 1 659 (68.0) 38 463 (59.1) < 0.001 Emergency department visits 4 513 (6.7) 457 (18.7) 4 056 (6.2) < 0.001 *Data expressed as mean +/- standard deviation; AGA: birthweight adapted for gestational age; LGA: large for gestational age; SGA: small for gestational age; SDI: socioeconomic disadvantage index; CHCI: Complementary health care insurance; LOS: maternity length of stay (days) After a multivariable regression logistic analysis, LGA infants had a 20% higher odds of being hospitalized than AGA infants, independent of GA, sex, maternal age, and socioeconomic status, with an adjusted OR of 1.21 (95% CI, 1.06, 1.39; p < 0.01). SGA at birth was not a significant risk factor (Table 2 ). The analysis also revealed that young maternal age, deprived socioeconomic conditions, and low GA were associated with hospitalization, whereas female sex was a protective factor. Table 2 Factors associated with newborn post-partum hospitalization Factors OR [IC95%] P Maternal age, years < 0.001 ≤ 25 y 1.33 [1.17, 1.50] 25–30 y 1.08 [0.98, 1.20] 30–35 y 1 [Référence] ≥ 35 y 0.88 [0.79, 0.99] Maternal pathology ‡ 1.01 [0.92, 1.11] 0.84 GA, weeks < 0.001 36 wks 2.12 [1.60, 2.80] 37 wks 1.59 [1.32, 1.90] 38 wks 1.26 [1.10, 1.44] 39 wks 1.02 [0.90, 1.15] 40 wks 0.94 [0.83, 1.06] 41 wks 1 [Référence] 42 wks 0.67 [0.38, 1.17] Female sex 0.77 [0.80, 0.95] < 0.01 Birthweight AGA 1 [Référence] SGA 1.11 [0.96, 1.28] 0.28 LGA 1.21 [1.06, 1.39] < 0.01 SDI score < 0.01 Low (Least disadvantaged) 1 [Référence] High (Most disadvantaged) 1.26 [1.01, 1.59] CHCI 1.30 [1.18, 1.43] < 0.001 Maternity Level Type I 1 [Référence] Type II 1.14 [1.03, 1.25] < 0.05 Type III 1.05 [0.90, 1.23] 0.89 Cesarean section 0.98 [0.87, 1.09] 0.50 Early postpartum discharge 0.89 [0.76, 1.05] 0.15 ‡ Maternel pathology: the presence of at least pre-eclampsia, gestational diabetes, placenta praevia/abruptio, chorioamniotitis or preterm premature rupture of membranes (PPROM); AGA: birthweight adapted for gestational age; LGA: large for gestational age; SGA: small for gestational age; SDI: socioeconomic disadvantage index; CHCI: Complementary health care insurance. Discussion In this regional population-based study of "healthy" newborns, we found that LGA at birth was associated with hospital re-admission after postpartum discharge for up to 28 days after birth, independent of common risk factors. Hospital admission rate did not differ between SGA and AGA infants. The association of LGA at birth with neonatal outcomes during the postpartum period has not been thoroughly investigated. LGA has been reported to be associated with various perinatal complications that occur during delivery or in the immediate neonatal period, such as shoulder dystocia, asphyxia, obstetric trauma, metabolic disorders (hypoglycaemia, hypocalcaemia, and severe jaundice), and respiratory disorders ( 13 , 16 , 17 ). However, data regarding hospital re-admission after postpartum discharge is scarce. Only two observational studies have confirmed our findings. In a regional perinatal medical network in the United States, LGA has been found to be associated with a 20% higher odds of re-hospitalization within 2 weeks of delivery (unadjusted OR, 1.20; 95% CI, 1.0, 1.6); the association was no longer significant for re-hospitalization between 3 and 52 weeks of life ( 25 ). In a large population-based record linkage study in New South Wales, Australia, term infants born LGA had a higher risk of hospital readmission during the first month of life than AGA infants, with an adjusted RR of 1.10 (95% CI, 1.05, 1.16) ( 26 ). However, the underlying mechanisms remain unknown. The fact that LGA infants were more likely to be hospitalized for infection than AGA infants may result from alterations in the immune system and inflammation acquired in utero. Maternal obesity and gestational diabetes, two principal factors of foetal macrosomia, are associated with foetal/placental inflammation and oxidative stress, which, consequently, may affect the structure and function of some systems ( 27 – 30 ). Furthermore, unlike SGA infants, those born LGA are usually considered to be at a low risk of adverse outcomes and, therefore, receive less regular medical follow-up after postpartum discharge. Altogether, these findings suggest that LGA infants are at a high risk of early adverse outcomes and require close medical follow-up after postpartum discharge. In the present study, we did not find out differences in hospital readmission rate between SGA and AGA infants. This is in agreement with a recent population-based study of term newborns in the United States ( 25 ). The absence of risk may be explained by the fact that infants born with severe SGA (i) are usually prematurely extracted and (ii) frequently receive specific medical follow-up. Therefore, infants born at term and SGA are less likely to be affected by severe placental insufficiency with consecutive neonatal morbidities than SGA infants born early. They also usually stay longer in the maternity ward, or in neonatal unit and receive specific medical follow-up during the post-partum period, preventing emergency department visits and hospital admissions. In our study, we excluded newborns with a prolonged initial hospital stay of at least 10 days (i.e. a marker of early severe morbidity) which might restrict the adverse effects of SGA or other neonatal morbidities after hospital discharge. However, this population still needs to be medically followed up because it is at an increased risk of mortality and adverse outcomes persisting in childhood ( 18 – 20 ). Strengths and limitations The French National Health Database System does not include some relevant individual factors, such as ethnicity, maternal BMI, breastfeeding, home environment (parental smoking, air pollution), siblings, educational status, and quality of parenting. Some comorbidities and clinical characteristics derived from ICD codes, such as maternal smoking or obesity, could be underreported. Thus, we were unable to identify how these factors and their severity mediate the associations of LGA or SGA on hospital admission after postpartum discharge. However, some of these factors are linked to socioeconomic status which was considered in the analysis. The French National Health Database System accurately registers data on hospitalized newborn and maternal health. All consecutive deliveries in private or public hospitals providing different levels of healthcare are collected in this registered database system, strengthening the findings of the study. We have excluded 12.9% of patients due to coding errors, maternal and neonatal linkage errors, or aberrant data to ensure an optimal quality cohort and to prevent potential selection bias. Finally, this population-based study of a large sample size of "healthy" singleton term newborns provides a relevant representation of a population usually cared for in maternity wards. Nevertheless, our findings need to be confirmed in other societies with different health care systems. Conclusion In this population-based linkage study that included a large population of "healthy" newborns, we found that LGA, unlike SGA, was associated with hospital readmission within the post-partum period for up to 28 days of birth, independent of known risk factors, including maternal age, family socioeconomic status, sex, gestational age, and maternity length of stay. Further investigations are required to determine the underlying mechanisms. LGA infants are an underestimated population at risk of early adverse outcomes and should require attentive medical follow-up within the postpartum period. Implementing follow-up protocols that include LGA infants should be addressed. Declarations Contributorship statement : Dr Nimal Marion and Camille Ravel designed the data collection, analysed the data, drafted the initial manuscript, and reviewed and revised the manuscript. Mr Steve Nauleau and David Lapidus designed the data collection instruments, collected data, carried out the initial analyses. Drs Clotilde Des Robert and Sophie Tardieu conceptualized and designed the study, Dr Farid Boubred conceptualized and designed the study drafted the initial manuscript, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. Ethics approval: This is an observational study using the data from the French National Uniform Hospital Discharge Database ( Programme de Médicalisation du Système d’Information , [PMSI]). All data are fully anonymized, informed written patients consent and ethical committee approval are not required in accordance of the French law after a deliberation of the French Commission for Data Protection and Liberties (CNIL) with the methodological reference MR005. Funding support: the study had no specific sponsors and funding Conflict of interest disclosures: the authors declare no conflict of interest to disclose Financial disclosures: the authors have no finantial relationship to disclose References Ellberg L, Högberg U, Lundman B, et al (2008). Maternity care options influence readmission of newborns. Acta Paediatrica 97:57983. Shakib J, Buchi K, Smith E, et al (2015). Timing of initial well-child visit and readmissions of newborns. Pediatrics 135:46974. Boubred F, Herlenius E, Andres V, et al (2016) Hospital readmission after postpartum discharge of term newborns in two maternity wards in Stockholm and Marseille. Archives de Pediatrie 23:234–40. Jones E, Stewart F, Taylor B, et al (2021) Early postnatal discharge from hospital for healthy mothers and term infants. Cochrane Database of Systematic Reviews 6:CD002958. Srinivasjois R, Slimings C, Einarsdottir K, et al (2015) Association of gestational age at birth with reasons for subsequent hospitalisation: 18 Years of follow-up in a Western Australian population study. PLoS One 10. Lain SJ, Nassar N, Bowen J, et al (2013) Risk factors and costs of hospital admissions in first year of life: a population-based study. The Journal of Pediatrics 163:10149. Batu ED, Yeni S, Teksam O (2015) The factors affecting neonatal presentations to the pediatric emergency department. The Journal of Emergency Medicine 48:5427. Surkan PJ, Hsieh CC, Johansson A, et al (2004) Reasons for increasing trends in large for gestational age births. Obstetrics and Gynecology 104:720–6. Henriksen T. The macrosomic fetus: a challenge in current obstetrics (2008) Acta Obstetricia Gynecologica Scandinavica 87:134–45. Chiavaroli V, Castorani V, Guidone P, et al (2016) Incidence of infants born small- and large-for-gestational-age in an Italian cohort over a 20-year period and associated risk factors. Italian Journal of Pediatrics 42:42. Ehrenberg HM, Mercer BM, Catalano PM (2004) The influence of obesity and diabetes on the prevalence of macrosomia. American Journal of Obstetrics & Gynecology 191:964–8. Bao C, Zhou Y, Jiang L, et al (2011) Reasons for the increasing incidence of macrosomia in Harbin, China: Increasing incidence of macrosomia in China. BJOG 118:938. Goldstein RF, Abell SK, Ranasinha S, et al (2017) Association of gestational weight gain with maternal and infant outcomes: a systematic review and meta-analysis. JAMA 317:2207–25. Kramer MS, Morin I, Yang H, et al (2002) Why are babies getting bigger? Temporal trends in fetal growth and its determinants. The Journal of Pediatrics 141:538–42. Boubred F, Pauly V, Romain F, et al (2020) The role of neighbourhood socioeconomic status in large for gestational age. PLoS One 15:e0233416. Weissmann-Brenner A, Simchen MJ, Zilberberg E, et al (2012) Maternal and neonatal outcomes of large for gestational age pregnancies. Acta Obstetricia and Gynecologica Scandinavica 91:844–9. Chauhan SP, Rice MM, Grobman WA, et al (2017) Neonatal morbidity of small- and large-forgestational-age neonates born at term in uncomplicated pregnancies. Obstetrics & Gynecology 130:5119. Ludvigsson JF, Lu D, Hammarström L, et al (2018) Small for gestational age and risk of childhood mortality: A Swedish population study. PLoS Med 15:e1002717. Paranjothy S, Dunstan F, Watkins WJ, et al (2013) Gestational age, birthweight, and risk of respiratory hospital admission in childhood. Pediatrics. Dec 132:e1562-9. Serrano-Lomelin J, Hicks A, Kumar M, et al (2021) Patterns of respiratory health services utilization from birth to 5 years of children who experienced adverse birth outcomes. PLoS One 16:e0247527. Boudemaghe T, Belhadj I (2017) Data resource profile: The french national uniform hospital discharge data set database (PMSI). International Journal of Epidemiology.;46:392-d. AUDIPOG: https://www.audipog.net/Courbes-morpho Hascoët JM, Petitprez K (2014) Maternal discharge: conditions and organization for mothers and newborns returning home. The French National Authority for Health recommendations update. Archives de Pediatrie 21:1053–9. Laugier O, Garcia P, Boucékine M, et al (2017) Influence of socioeconomic context on the rehospitalization rates of infants born preterm. Journal of Pediatrics 190:174–179.e1. Dietz PM, Rizzo JH, England LJ, et al (2013) Health care utilization in the first year of life among small- and large- for-gestational age term Infants. Maternal and Child Health Journal 17:101624. Khambalia AZ, Algert CS, Bowen JR, et al (2017) Long-term outcomes for large for gestational age infants born at term. Journal of Paediatrics and Child Health 53:876–881. Bedell S, Hutson J, de Vrijer B, et al (2021) Effects of maternal obesity and gestational diabetes mellitus on the placenta: current knowledge and targets for therapeutic interventions. Current Vascular Pharmacology 19:176–192. Parisi F, Milazzo R, Savasi VM, et al (2021) Maternal low-grade chronic inflammation and intrauterine programming of health and disease. International Journal of Molecular Sciences 22:1732. Vieira MC, McCowan LME, North RA, et al (2018) Antenatal risk factors associated with neonatal morbidity in large-for-gestational-age infants: an international prospective cohort study. Acta Obstetricia et Gynecologica Scandinavica 97:101524 Perez M, Robbins ME, Revhaug C, et al (2019) Oxygen radical disease in the newborn, revisited: Oxidative stress and disease in the newborn period. Free Radical Biology and Medicine 142:61–72. Additional Declarations No competing interests reported. Supplementary Files FBoubredSupplementarytableEJP.docx Cite Share Download PDF Status: Published Journal Publication published 04 Mar, 2023 Read the published version in European Journal of Pediatrics → Version 1 posted Editorial decision: Major revision 04 Feb, 2023 Reviews received at journal 28 Jan, 2023 Reviewers agreed at journal 04 Jan, 2023 Reviewers invited by journal 04 Jan, 2023 Editor assigned by journal 02 Jan, 2023 Submission checks completed at journal 02 Jan, 2023 First submitted to journal 20 Dec, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2397144","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":164457697,"identity":"c19eaab4-2053-4385-b82b-171d6463c96b","order_by":0,"name":"M Nimal","email":"","orcid":"","institution":"Hospital University La Conception","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"M","middleName":"","lastName":"Nimal","suffix":""},{"id":164457699,"identity":"62a6e9cc-4218-4fac-85cf-2f3bcced3683","order_by":1,"name":"C Ravel","email":"","orcid":"","institution":"Hospital University La Conception","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"C","middleName":"","lastName":"Ravel","suffix":""},{"id":164457700,"identity":"f722d144-3576-49a7-91d0-2b8bc830d2b8","order_by":2,"name":"S Nauleau","email":"","orcid":"","institution":"Regional Health Agency","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"S","middleName":"","lastName":"Nauleau","suffix":""},{"id":164457701,"identity":"6154727d-f551-4d6d-9dd0-33340d84d65e","order_by":3,"name":"D Lapalus","email":"","orcid":"","institution":"Regional Health Agency","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"D","middleName":"","lastName":"Lapalus","suffix":""},{"id":164457702,"identity":"b0abacfa-796b-4b8d-aa94-8cc535274450","order_by":4,"name":"O Bernard","email":"","orcid":"","institution":"Regional Health Agency","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"O","middleName":"","lastName":"Bernard","suffix":""},{"id":164457703,"identity":"7978143f-e6c9-45dd-b94c-cde0f47540a3","order_by":5,"name":"C des Robert","email":"","orcid":"","institution":"Hospital University La Conception","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"C","middleName":"","lastName":"des Robert","suffix":""},{"id":164457704,"identity":"23da5e28-0aaf-4f38-a397-8d7aebe7ab93","order_by":6,"name":"S Tardieu","email":"","orcid":"","institution":"Hospital University La Conception","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"S","middleName":"","lastName":"Tardieu","suffix":""},{"id":164457705,"identity":"60d288f3-10e9-426f-8503-608cf0443e46","order_by":7,"name":"F Boubred","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYBAC9gYGhgM8DAcYGCSAPJ4KBgijAo8WngMoWs5AtZwhoIUBroW3jRgt7GcfHnjDcEfO4Hbvwwdv59nlMUh3JzAc3INHC0+6wcE5DM+MDe4cNzacuy25mEHm7AaGA89wa7FnSGM4zMNwOHHDjTQ2ad5tzIn7b+RuYP5wAI8t/M/gWth/886pT2yQyAXagk+LBJItzLwNh4nR8ozh4ByDZ8aSd44xS845dryYAajlAF4t/GnMH95U3JHju93G+OFNTXUeUMvGB/i0QIABgpkAIghqQAEJJKkeBaNgFIyCEQEAK4hZYzfp1zQAAAAASUVORK5CYII=","orcid":"","institution":"Hospital University La Conception","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"F","middleName":"","lastName":"Boubred","suffix":""}],"badges":[],"createdAt":"2022-12-20 11:29:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2397144/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2397144/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00431-023-04908-2","type":"published","date":"2023-03-04T19:29:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":31186515,"identity":"d6c57c35-0eca-4d49-88be-2eac395b12c4","added_by":"auto","created_at":"2023-01-05 21:13:38","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77440,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Chart\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2397144/v1/49d37f5edb72ab52258a0854.jpg"},{"id":31186516,"identity":"c43cfab3-f66c-4906-828b-55e97bb4ff7d","added_by":"auto","created_at":"2023-01-05 21:13:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54504,"visible":true,"origin":"","legend":"\u003cp\u003eCauses of hospital admission within the postpartum period up to 28 days after birth\u003c/p\u003e\n\u003cp\u003eThe figure shows the hospitalization rates according to different causes and to birthweight characteristics. LGA infants are presented by black bars, AGA by white bars and SGA are in grey bars.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2397144/v1/45888793429ff58b15a51c38.jpg"},{"id":44721286,"identity":"fc76ff8c-7020-4610-ba8a-98de78a74514","added_by":"auto","created_at":"2023-10-16 19:33:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":419312,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2397144/v1/f732a18a-9eb7-4598-be68-d2fa59dad60e.pdf"},{"id":31185860,"identity":"53fc10f9-b7b7-4c9e-95d3-bea2795fdefe","added_by":"auto","created_at":"2023-01-05 21:05:38","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13027,"visible":true,"origin":"","legend":"","description":"","filename":"FBoubredSupplementarytableEJP.docx","url":"https://assets-eu.researchsquare.com/files/rs-2397144/v1/a316ef378dca66656c9e3b00.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship between large-for-gestational age and hospital readmission after postpartum discharge","fulltext":[{"header":"What Is Known","content":"\u003cp\u003eNewborns are at high risk of hospital re-admission during the post-partum period. Prematurity, male, siblings, young mother, living in deprived socioeconomic conditions, or discharged early after delivery are known risk factors. However, the influence of appropriateness for gestational age at birth, i.e. being born small-for-gestational age (SGA) or large-for-gestational age (LGA), has been little evaluated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is knew:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn contrast to SGA born infants, we found that infants born LGA were at high risk of hospital admission and the main cause was infectious diseases. This population should be considered at risk of early adverse outcomes and should require attentive medical follow-up after postpartum discharge.\u0026nbsp;\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe post-partum period is a critical period for newborns. They are at high risk of hospital re-admission which can reach 10%; the principal causes are jaundice, feeding difficulties, dehydration, and infection (\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Infants who are immature at birth (up to 38 weeks of gestational age), male, have siblings, born to a young mother, living in deprived socioeconomic conditions, or discharged early after delivery are particularly vulnerable. However, the influence of trophicity at birth, i.e. being born small-for-gestational age (SGA) or large-for-gestational age (LGA), has not been thoroughly evaluated and requires further investigation.\u003c/p\u003e \u003cp\u003eLGA is a growing public health concern worldwide. Its prevalence varies from 5\u0026ndash;20%, and the number of LGA infants has increased over the last two decades and is expected to increase in several countries (\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). These temporal trends are related to various factors, including the advancing age of pregnant women, increased maternal obesity and gestational diabetes, and social inequalities (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). LGA is known to increase the risk of numerous adverse perinatal and birth outcomes, including caesarean delivery, postpartum haemorrhage, shoulder dystocia, perinatal asphyxia, neonatal hypoglycaemia, hyperbilirubinemia, and neonatal respiratory distress disorders (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Although SGA is associated with increased neonatal mortality and hospital readmission rates after the neonatal period, little is known about how SGA and LGA at birth influence outcomes in the postpartum period (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccordingly, this study aimed to determine whether SGA and LGA at birth were associated with hospital readmission for up to 28 days after delivery. The key sociodemographic and clinical confounding factors in a large population-based study using data from the French National Health Care Database system were studied.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThis population-based cohort study was a retrospective analysis of a prospective cohort using data from the French National Uniform Hospital Discharge Database (\u003cem\u003eProgramme de M\u0026eacute;dicalisation du Syst\u0026egrave;me d\u0026rsquo;Information\u003c/em\u003e, [PMSI]), which systematically collects administrative and medical information, including obstetrical and infant characteristics. The PMSI database is based on diagnosis-related groups, using the International Classification of Diseases, Tenth Revision (ICD-10) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). All data are fully anonymized and informed written patients consent are not required. In France all of the Regional Health Agencies are granted access to this database (Agence Technique d\u0026rsquo;Information sur l\u0026rsquo;Hospitalisation \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.atih.sante.fr/\u003c/span\u003e\u003cspan address=\"https://www.atih.sante.fr/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), in compliance with French law after a deliberation of the French Commission for Data Protection and Liberties (CNIL) with the methodological reference MR005.\u003c/p\u003e \u003cp\u003eThe study population included all live singleton births within the Provence Alps Cote d\u0026rsquo;Azur (PACA) region between January 1st, 2017 and November 30th, 2018 with a gestational age (GA) above 36 weeks. Infants whose parents were domiciled outside the PACA region, with congenital anomalies or genetic disorders (Supplementary table), infants who were initially hospitalized or died during initial hospital stay, and infants requiring a prolonged initial maternity stay of \u0026ge;\u0026thinsp;10 days were excluded (as mean maternity length of stay in France is about 4 to 5 days). We also excluded in-hospital stays with qualitative issues owing to linking problems (including absence or errors in mother to infant linkage), transfers from hospitals in another geographical area, charts without maternal address codes, cases in which the number of infants has not been specified, and infants with an aberrant weight for gestational age.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Outcome and sociodemographic data\u003c/h2\u003e \u003cp\u003eThe primary outcome of interest was the hospital admission rate after postpartum discharge for up to 28 days after birth. The causes of hospitalization were determined according to ICD codes and classified as infectious disease, metabolic disorders (i.e. mainly jaundice P57\u0026ndash;P59 and R17), digestive and nutrition/growth disorders (i.e. dehydration P74.1 and E86, feeding intolerance/insufficient feeding/, growth insufficiency, P92, P98 and E40\u0026ndash;E46), neurologic abnormalities, non-infectious respiratory events, surgery and trauma and other causes (including social problems Z59, Z63, Z81) (Supplementary table).\u003c/p\u003e \u003cp\u003eMaternal and obstetric data were obtained from the maternal hospital discharge database. Information on maternal age, obstetrical pathology, mode of delivery (i.e., caesarean section, ICD-10 code O82), and maternity level delivery were collected. Obstetric pathology was determined according to the presence of one of the following complications: preeclampsia (ICD-10 codes O12\u0026ndash;O15), gestational diabetes (ICD-10 codes O24.4), placental abruption and previa (ICD-10 codes O44, O45), preterm premature rupture of membranes (O42), and chorioamnionitis (ICD-10 codes O41.1). GA, sex, and birth weight were also recorded. SGA, adapted-for-gestational (AGA), and LGA were respectively defined as a birth weight lower than the 10th percentile, within the 10th and 90th percentile, and higher than the 90th percentile for sex based on the national French growth chart (22). The length of stay in the maternity ward was also recorded. Early postpartum discharge was defined according to the recommendations of the French Health Care Authority (\u003cem\u003eHaute Autorit\u0026eacute; de Sant\u0026eacute;\u003c/em\u003e) as less than 3 days for vaginal delivery and less than 4 days for caesarean delivery (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSocioeconomic status was determined at the individual/family level based on health care insurance coverage and at the geographical level using a socioeconomic disadvantage index (SDI). Complementary health care insurance coverage, which provides universal health care coverage, is dedicated to the most disadvantaged families based on home income. SDI was calculated using five key socioeconomic and demographic variables extracted from the 2015 census data linked to each local residential municipality (French National Institute of Statistics and Economic Studies [Institut National de la Statistique et des Etudes Economiques]): median household income, unemployment rate, percentage of people aged\u0026thinsp;\u0026ge;\u0026thinsp;15 years who failed to graduate from high school, percentage of single-parent families, and percentage of families in rented accommodations. SDI scores ranged from Level 1 (affluent) to Level 5 (most disadvantaged) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The SDI score is based on the mother-commune postcode. In this study, we compared infants living in the most disadvantaged neighbourhoods to those living in affluent areas.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eUnivariate parametric and nonparametric analyses were performed using the χ\u003csup\u003e2\u003c/sup\u003e test or Fisher\u0026rsquo;s exact test for categorical variables, and the Student \u003cem\u003et\u003c/em\u003e t-test or Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test was performed for quantitative variables, as appropriate. A stepwise multivariable regression analysis was performed to estimate the LGA and SGA factors for postpartum hospital admission for up to 28 days of delivery. Available variables were included in the final regression model. A two-sided \u003cem\u003eP-\u003c/em\u003evalue\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. Statistical analysis was performed using SAS 9\u0026middot;4 (SAS Institute).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBetween January 1st, 2017 and November 30th, 2018, 106,071 singleton newborns were born alive with a GA\u0026thinsp;\u0026gt;\u0026thinsp;36 weeks in the PACA region. Of this population, 38,532 newborns were excluded; 24,773 were excluded based on the exclusion criteria, and 13,759 (12.9%) were excluded for various administrative, identification, and linkage errors (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Thus, 67,539 newborns were included in this analysis.\u003c/p\u003e \u003cp\u003eDuring the study period, 2441 (3.6%) infants were hospitalized within the postpartum period for up to 28 days after birth. The mean (standard deviation [SD]) hospital length of stay and time from birth were 2.8 (2.5) days and 12.3 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) days, respectively; 60.8% of infants were hospitalized within 14 days postpartum. The principal causes were infectious diseases (52%), digestive disorders (23%), and metabolic and growth disorders (4%) (i.e. mainly jaundice). The causes varied according to GA, especially for metabolic disorders, which decreased from 23\u0026ndash;2% in infants with a GA of 36 weeks and 41 weeks, respectively (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Compared with AGA infants, LGA infants were more likely to be hospitalized for infectious diseases (57.7% vs. 51.3%, p\u0026thinsp;=\u0026thinsp;0.05) and SGA infants tended to be more frequently hospitalized for nutrition/digestive disorders (28.1% vs.23.1%, p\u0026thinsp;=\u0026thinsp;0.09) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No differences were observed between SGA and AGA infants.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the perinatal characteristics of hospitalized infants. These infants were more likely to be born to young and socioeconomically deprived mothers, to be male, or born early (GA between 36 and 38 weeks, 26.7% vs. 20.4%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The rate of LGA at birth was 20% higher in the hospitalized infant population (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas no difference was observed in the rate of SGA. The modes of delivery and maternity length of stay did not differ between the LGA and AGA infants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of hospitalized infants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall population\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;67 539\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHospitalized infants\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;2\u0026nbsp;441\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-Hospitalized infants\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;65 098\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstetrical data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age, years*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.4 +/- 5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.6 +/- 5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30,4 +/- 5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age, years\u003c/p\u003e \u003cp\u003e\u0026lt; 25 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 751 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e423 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 328 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;30 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 872 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e775 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 097 (30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;35 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 984 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e782 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 202 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 35 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 932 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e461 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 471 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal pathology, n (%)\u003c/p\u003e \u003cp\u003ePre-eclampsia\u003c/p\u003e \u003cp\u003ePlacenta praevia/abruptio\u003c/p\u003e \u003cp\u003eGestational diabetes\u003c/p\u003e \u003cp\u003eChorioamionitis/PPROM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 857 (27.9)\u003c/p\u003e \u003cp\u003e1\u0026nbsp;941 (2.9)\u003c/p\u003e \u003cp\u003e383 (0.6)\u003c/p\u003e \u003cp\u003e6\u0026nbsp;282 (9.3)\u003c/p\u003e \u003cp\u003e10\u0026nbsp;251 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726 (29.7)\u003c/p\u003e \u003cp\u003e85 (3.5)\u003c/p\u003e \u003cp\u003e15 (0.6)\u003c/p\u003e \u003cp\u003e239 (9.8)\u003c/p\u003e \u003cp\u003e387 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 131 (27.9)\u003c/p\u003e \u003cp\u003e1\u0026nbsp;856 (2.9)\u003c/p\u003e \u003cp\u003e368 (0.6)\u003c/p\u003e \u003cp\u003e6\u0026nbsp;043 (9.3)\u003c/p\u003e \u003cp\u003e9\u0026nbsp;864 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDS Score\u003c/p\u003e \u003cp\u003eLow (Least disadvantaged)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 644 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 529 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (most disadvantaged)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 786 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315 (12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 471 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 855 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e613 (25.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 242 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternity level\u003c/p\u003e \u003cp\u003eType I\u003c/p\u003e \u003cp\u003eType II\u003c/p\u003e \u003cp\u003eType III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 133 (29.8)\u003c/p\u003e \u003cp\u003e40 480 (59.9)\u003c/p\u003e \u003cp\u003e6 926 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e656 (26.9)\u003c/p\u003e \u003cp\u003e1 499 (61.4)\u003c/p\u003e \u003cp\u003e286 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 477 (29.9)\u003c/p\u003e \u003cp\u003e38 981 (59.9)\u003c/p\u003e \u003cp\u003e6 640 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal delivery\u003c/p\u003e \u003cp\u003eLOS, days*\u003c/p\u003e \u003cp\u003eEarly Discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 349 (82.0)\u003c/p\u003e \u003cp\u003e3.6 +/- 0.9\u003c/p\u003e \u003cp\u003e3\u0026nbsp;480 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 007 (82.2)\u003c/p\u003e \u003cp\u003e3.6 +/- 1.0\u003c/p\u003e \u003cp\u003e136 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 342 (81.9)\u003c/p\u003e \u003cp\u003e3.6 +/- 0.9\u003c/p\u003e \u003cp\u003e3\u0026nbsp;344 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003cp\u003e0.45\u003c/p\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean section\u003c/p\u003e \u003cp\u003eLOS, days*\u003c/p\u003e \u003cp\u003eEarly discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 004 (17.8)\u003c/p\u003e \u003cp\u003e4.5 +/- 0.9\u003c/p\u003e \u003cp\u003e614 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e427 (17.5)\u003c/p\u003e \u003cp\u003e4.6 +/- 1.0\u003c/p\u003e \u003cp\u003e26 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 571 (17.8)\u003c/p\u003e \u003cp\u003e4.6 +/- 0.8\u003c/p\u003e \u003cp\u003e588 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003cp\u003e0.12\u003c/p\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeonatal data\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGA, weeks*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.4 +/- 1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.2 +/- 1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.4 +/- 1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGA, weeks\u003c/p\u003e \u003cp\u003e36 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e884 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e824 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 233 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 060 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 869 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e419 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 450 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 222 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e704 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 518 (30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 936 (29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e639 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 297 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 41 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 395 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e446 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 949 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sexe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 324 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 123 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 201 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirthweight, gr*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3342 +/- 432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3339 +/- 452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3342 +/- 432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 870 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 646 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 882 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e251 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 631 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026nbsp;122 (59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u0026nbsp;659 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u0026nbsp;463 (59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmergency department visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026nbsp;513 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e457 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u0026nbsp;056 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Data expressed as mean +/- standard deviation; AGA: birthweight adapted for gestational age; LGA: large for gestational age; SGA: small for gestational age; SDI: socioeconomic disadvantage index; CHCI: Complementary health care insurance; LOS: maternity length of stay (days)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter a multivariable regression logistic analysis, LGA infants had a 20% higher odds of being hospitalized than AGA infants, independent of GA, sex, maternal age, and socioeconomic status, with an adjusted OR of 1.21 (95% CI, 1.06, 1.39; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). SGA at birth was not a significant risk factor (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The analysis also revealed that young maternal age, deprived socioeconomic conditions, and low GA were associated with hospitalization, whereas female sex was a protective factor.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with newborn post-partum hospitalization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR [IC95%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; 25 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.33 [1.17, 1.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;30 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08 [0.98, 1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;35 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [R\u0026eacute;f\u0026eacute;rence]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 35 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 [0.79, 0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal pathology \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 [0.92, 1.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGA, weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.12 [1.60, 2.80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.59 [1.32, 1.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26 [1.10, 1.44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02 [0.90, 1.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 [0.83, 1.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [R\u0026eacute;f\u0026eacute;rence]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42 wks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67 [0.38, 1.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.77 [0.80, 0.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirthweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [R\u0026eacute;f\u0026eacute;rence]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11 [0.96, 1.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21 [1.06, 1.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow (Least disadvantaged)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [R\u0026eacute;f\u0026eacute;rence]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh (Most disadvantaged)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26 [1.01, 1.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.30 [1.18, 1.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternity Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 [R\u0026eacute;f\u0026eacute;rence]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.14 [1.03, 1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05 [0.90, 1.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98 [0.87, 1.09]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly postpartum discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89 [0.76, 1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e\u0026Dagger;\u003c/sup\u003e Maternel pathology: the presence of at least pre-eclampsia, gestational diabetes, placenta praevia/abruptio, chorioamniotitis or preterm premature rupture of membranes (PPROM); AGA: birthweight adapted for gestational age; LGA: large for gestational age; SGA: small for gestational age; SDI: socioeconomic disadvantage index; CHCI: Complementary health care insurance.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this regional population-based study of \"healthy\" newborns, we found that LGA at birth was associated with hospital re-admission after postpartum discharge for up to 28 days after birth, independent of common risk factors. Hospital admission rate did not differ between SGA and AGA infants.\u003c/p\u003e \u003cp\u003eThe association of LGA at birth with neonatal outcomes during the postpartum period has not been thoroughly investigated. LGA has been reported to be associated with various perinatal complications that occur during delivery or in the immediate neonatal period, such as shoulder dystocia, asphyxia, obstetric trauma, metabolic disorders (hypoglycaemia, hypocalcaemia, and severe jaundice), and respiratory disorders (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). However, data regarding hospital re-admission after postpartum discharge is scarce. Only two observational studies have confirmed our findings. In a regional perinatal medical network in the United States, LGA has been found to be associated with a 20% higher odds of re-hospitalization within 2 weeks of delivery (unadjusted OR, 1.20; 95% CI, 1.0, 1.6); the association was no longer significant for re-hospitalization between 3 and 52 weeks of life (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In a large population-based record linkage study in New South Wales, Australia, term infants born LGA had a higher risk of hospital readmission during the first month of life than AGA infants, with an adjusted RR of 1.10 (95% CI, 1.05, 1.16) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). However, the underlying mechanisms remain unknown. The fact that LGA infants were more likely to be hospitalized for infection than AGA infants may result from alterations in the immune system and inflammation acquired in utero. Maternal obesity and gestational diabetes, two principal factors of foetal macrosomia, are associated with foetal/placental inflammation and oxidative stress, which, consequently, may affect the structure and function of some systems (\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Furthermore, unlike SGA infants, those born LGA are usually considered to be at a low risk of adverse outcomes and, therefore, receive less regular medical follow-up after postpartum discharge. Altogether, these findings suggest that LGA infants are at a high risk of early adverse outcomes and require close medical follow-up after postpartum discharge.\u003c/p\u003e \u003cp\u003eIn the present study, we did not find out differences in hospital readmission rate between SGA and AGA infants. This is in agreement with a recent population-based study of term newborns in the United States (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The absence of risk may be explained by the fact that infants born with severe SGA (i) are usually prematurely extracted and (ii) frequently receive specific medical follow-up. Therefore, infants born at term and SGA are less likely to be affected by severe placental insufficiency with consecutive neonatal morbidities than SGA infants born early. They also usually stay longer in the maternity ward, or in neonatal unit and receive specific medical follow-up during the post-partum period, preventing emergency department visits and hospital admissions. In our study, we excluded newborns with a prolonged initial hospital stay of at least 10 days (i.e. a marker of early severe morbidity) which might restrict the adverse effects of SGA or other neonatal morbidities after hospital discharge. However, this population still needs to be medically followed up because it is at an increased risk of mortality and adverse outcomes persisting in childhood (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe French National Health Database System does not include some relevant individual factors, such as ethnicity, maternal BMI, breastfeeding, home environment (parental smoking, air pollution), siblings, educational status, and quality of parenting. Some comorbidities and clinical characteristics derived from ICD codes, such as maternal smoking or obesity, could be underreported. Thus, we were unable to identify how these factors and their severity mediate the associations of LGA or SGA on hospital admission after postpartum discharge. However, some of these factors are linked to socioeconomic status which was considered in the analysis. The French National Health Database System accurately registers data on hospitalized newborn and maternal health. All consecutive deliveries in private or public hospitals providing different levels of healthcare are collected in this registered database system, strengthening the findings of the study. We have excluded 12.9% of patients due to coding errors, maternal and neonatal linkage errors, or aberrant data to ensure an optimal quality cohort and to prevent potential selection bias. Finally, this population-based study of a large sample size of \"healthy\" singleton term newborns provides a relevant representation of a population usually cared for in maternity wards. Nevertheless, our findings need to be confirmed in other societies with different health care systems.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this population-based linkage study that included a large population of \"healthy\" newborns, we found that LGA, unlike SGA, was associated with hospital readmission within the post-partum period for up to 28 days of birth, independent of known risk factors, including maternal age, family socioeconomic status, sex, gestational age, and maternity length of stay. Further investigations are required to determine the underlying mechanisms. LGA infants are an underestimated population at risk of early adverse outcomes and should require attentive medical follow-up within the postpartum period. Implementing follow-up protocols that include LGA infants should be addressed.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eContributorship statement\u003c/em\u003e :\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr Nimal Marion and Camille Ravel designed the data collection, analysed the data, drafted the initial manuscript, and reviewed and revised the manuscript. Mr Steve Nauleau and David Lapidus designed the data collection instruments, collected data, carried out the initial analyses. Drs Clotilde Des Robert and Sophie Tardieu conceptualized and designed the study, Dr Farid Boubred conceptualized and designed the study drafted the initial manuscript, and reviewed and revised the manuscript. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis is an observational study using the data from the French National Uniform Hospital Discharge Database (\u003cem\u003eProgramme de M\u0026eacute;dicalisation du Syst\u0026egrave;me d\u0026rsquo;Information\u003c/em\u003e, [PMSI]). All data are fully anonymized, informed written patients consent and ethical committee approval are not required in accordance of the French law after a deliberation of the French Commission for Data Protection and Liberties (CNIL) with the methodological reference MR005.\u003c/p\u003e\n\u003cp\u003eFunding support: the study had no specific sponsors and funding\u003c/p\u003e\n\u003cp\u003eConflict of interest disclosures: the authors declare no conflict of interest to disclose\u003c/p\u003e\n\u003cp\u003eFinancial disclosures: the authors have no finantial relationship to disclose\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEllberg L, H\u0026ouml;gberg U, Lundman B, et al (2008). Maternity care options influence readmission of newborns. Acta Paediatrica 97:57983.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShakib J, Buchi K, Smith E, et al (2015). Timing of initial well-child visit and readmissions of newborns. Pediatrics 135:46974.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoubred F, Herlenius E, Andres V, et al (2016) Hospital readmission after postpartum discharge of term newborns in two maternity wards in Stockholm and Marseille. Archives de Pediatrie 23:234\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones E, Stewart F, Taylor B, et al (2021) Early postnatal discharge from hospital for healthy mothers and term infants. Cochrane Database of Systematic Reviews 6:CD002958.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrinivasjois R, Slimings C, Einarsdottir K, et al (2015) Association of gestational age at birth with reasons for subsequent hospitalisation: 18 Years of follow-up in a Western Australian population study. PLoS One 10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLain SJ, Nassar N, Bowen J, et al (2013) Risk factors and costs of hospital admissions in first year of life: a population-based study. The Journal of Pediatrics 163:10149.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBatu ED, Yeni S, Teksam O (2015) The factors affecting neonatal presentations to the pediatric emergency department. The Journal of Emergency Medicine 48:5427.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSurkan PJ, Hsieh CC, Johansson A, et al (2004) Reasons for increasing trends in large for gestational age births. Obstetrics and Gynecology 104:720\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenriksen T. The macrosomic fetus: a challenge in current obstetrics (2008) Acta Obstetricia Gynecologica Scandinavica 87:134\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiavaroli V, Castorani V, Guidone P, et al (2016) Incidence of infants born small- and large-for-gestational-age in an Italian cohort over a 20-year period and associated risk factors. Italian Journal of Pediatrics 42:42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEhrenberg HM, Mercer BM, Catalano PM (2004) The influence of obesity and diabetes on the prevalence of macrosomia. American Journal of Obstetrics \u0026amp; Gynecology 191:964\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBao C, Zhou Y, Jiang L, et al (2011) Reasons for the increasing incidence of macrosomia in Harbin, China: Increasing incidence of macrosomia in China. BJOG 118:938.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldstein RF, Abell SK, Ranasinha S, et al (2017) Association of gestational weight gain with maternal and infant outcomes: a systematic review and meta-analysis. JAMA 317:2207\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKramer MS, Morin I, Yang H, et al (2002) Why are babies getting bigger? Temporal trends in fetal growth and its determinants. The Journal of Pediatrics 141:538\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoubred F, Pauly V, Romain F, et al (2020) The role of neighbourhood socioeconomic status in large for gestational age. PLoS One 15:e0233416.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeissmann-Brenner A, Simchen MJ, Zilberberg E, et al (2012) Maternal and neonatal outcomes of large for gestational age pregnancies. Acta Obstetricia and Gynecologica Scandinavica 91:844\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChauhan SP, Rice MM, Grobman WA, et al (2017) Neonatal morbidity of small- and large-forgestational-age neonates born at term in uncomplicated pregnancies. Obstetrics \u0026amp; Gynecology 130:5119.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLudvigsson JF, Lu D, Hammarstr\u0026ouml;m L, et al (2018) Small for gestational age and risk of childhood mortality: A Swedish population study. PLoS Med 15:e1002717.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParanjothy S, Dunstan F, Watkins WJ, et al (2013) Gestational age, birthweight, and risk of respiratory hospital admission in childhood. Pediatrics. Dec 132:e1562-9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSerrano-Lomelin J, Hicks A, Kumar M, et al (2021) Patterns of respiratory health services utilization from birth to 5 years of children who experienced adverse birth outcomes. PLoS One 16:e0247527.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoudemaghe T, Belhadj I (2017) Data resource profile: The french national uniform hospital discharge data set database (PMSI). International Journal of Epidemiology.;46:392-d.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAUDIPOG: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.audipog.net/Courbes-morpho\u003c/span\u003e\u003cspan address=\"https://www.audipog.net/Courbes-morpho\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHasco\u0026euml;t JM, Petitprez K (2014) Maternal discharge: conditions and organization for mothers and newborns returning home. The French National Authority for Health recommendations update. Archives de Pediatrie 21:1053\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaugier O, Garcia P, Bouc\u0026eacute;kine M, et al (2017) Influence of socioeconomic context on the rehospitalization rates of infants born preterm. Journal of Pediatrics 190:174\u0026ndash;179.e1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDietz PM, Rizzo JH, England LJ, et al (2013) Health care utilization in the first year of life among small- and large- for-gestational age term Infants. Maternal and Child Health Journal 17:101624.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhambalia AZ, Algert CS, Bowen JR, et al (2017) Long-term outcomes for large for gestational age infants born at term. Journal of Paediatrics and Child Health 53:876\u0026ndash;881.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBedell S, Hutson J, de Vrijer B, et al (2021) Effects of maternal obesity and gestational diabetes mellitus on the placenta: current knowledge and targets for therapeutic interventions. Current Vascular Pharmacology 19:176\u0026ndash;192.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParisi F, Milazzo R, Savasi VM, et al (2021) Maternal low-grade chronic inflammation and intrauterine programming of health and disease. International Journal of Molecular Sciences 22:1732.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVieira MC, McCowan LME, North RA, et al (2018) Antenatal risk factors associated with neonatal morbidity in large-for-gestational-age infants: an international prospective cohort study. Acta Obstetricia et Gynecologica Scandinavica 97:101524\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerez M, Robbins ME, Revhaug C, et al (2019) Oxygen radical disease in the newborn, revisited: Oxidative stress and disease in the newborn period. Free Radical Biology and Medicine 142:61\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"postpartum discharge, LGA, SGA, infectious disease","lastPublishedDoi":"10.21203/rs.3.rs-2397144/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2397144/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo determine the association of small (SGA) and large (LGA) for gestational age at birth with hospital readmission after postpartum discharge for up to 28 days of delivery\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePopulation-based linkage study using the French National Uniform Hospital Discharge Database. \u0026lsquo;Healthy\u0026rsquo; singleton term infants born between January 1st, 2017 and November 30th, 2018 in the French South region were included. SGA and LGA were defined as birth weight\u0026thinsp;\u0026lt;\u0026thinsp;10th and \u0026gt;\u0026thinsp;90th percentiles, respectively, according to sex and gestational age. A multivariable regression analysis was performed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 67,359 included infants, 2441 (3.6%) were re-admitted and 61% of them were hospitalized within 14 days postpartum. Hospitalized infants were more likely to be LGA at birth (10.3% vs. 8.6% in non-hospitalized infants, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01); the proportion of SGA infants did not differ between both groups. Compared to appropriate birth weight for GA (AGA) infants, LGA infants were more often hospitalized for infectious diseases (57.7% vs. 51.3%, p\u0026thinsp;=\u0026thinsp;0.05). After regression analysis LGA infants had a 20% higher odds of being hospitalized than those born AGA (aOR(95%CI)\u0026thinsp;=\u0026thinsp;1.21 (1.06\u0026ndash;1.39)) while aOR(95%CI) for SGA was 1.11 (0.96\u0026ndash;1.28).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn contrast to SGA, LGA was associated with hospital readmission during the first month of life. Follow-up protocols that include LGA should be evaluated.\u003c/p\u003e","manuscriptTitle":"Relationship between large-for-gestational age and hospital readmission after postpartum discharge","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-05 21:05:34","doi":"10.21203/rs.3.rs-2397144/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-02-04T16:32:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-01-28T08:54:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37153ff7-cf85-49dd-a0fd-e102ce5db043","date":"2023-01-04T21:49:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-01-04T21:24:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-01-03T03:35:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-01-03T03:35:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2022-12-20T11:15:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"92a02396-b887-44f2-bdce-728276dd26f6","owner":[],"postedDate":"January 5th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T19:31:11+00:00","versionOfRecord":{"articleIdentity":"rs-2397144","link":"https://doi.org/10.1007/s00431-023-04908-2","journal":{"identity":"european-journal-of-pediatrics","isVorOnly":false,"title":"European Journal of Pediatrics"},"publishedOn":"2023-03-04 19:29:21","publishedOnDateReadable":"March 4th, 2023"},"versionCreatedAt":"2023-01-05 21:05:34","video":"","vorDoi":"10.1007/s00431-023-04908-2","vorDoiUrl":"https://doi.org/10.1007/s00431-023-04908-2","workflowStages":[]},"version":"v1","identity":"rs-2397144","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2397144","identity":"rs-2397144","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}