In Kenya, standard early infant diagnosis (EID) with polymerase chain reaction (PCR) testing at 6-week postnatal achieves early treatment initiation (<12 weeks) in <20% of HIV+ infants. Kenya’s new early infant diagnosis guidelines tentatively proposed adding PCR testing at birth, pending results from pilot studies.We piloted birth testing at 4 Kenyan hospitals between November 2017 and November 2018. Eligible HIV-exposed infants were offered both point-of-care and PCR HIV testing at birth (window 0 to <4 weeks) and 6 weeks (window 4–12 weeks). We report the: proportion of infants tested at birth, 6-week, and both birth and 6-week testing; median infant age at results; seropositivity and antiretroviral therapy initiation.Final sample included 624 mother-infant pairs. Mean maternal age was 30.4 years, 73.2% enrolled during antenatal care and 89.9% had hospital deliveries. Among the 590 mother–infants pairs enrolled before 4 weeks postnatal, 452 (76.6%) completed birth testing before 4 weeks, with 360 (79.6%) testing within 2 weeks, and 178 (39.4%) before hospital discharge (0–2 days). Mothers were notified of birth PCR results at a median infant age of 5.4 weeks. Among all 624 enrolled infants, 575 (92.1%) were tested during the 6-week window; 417 (66.8%) received testing at both birth and 6-weeks; and 207 received incomplete testing (93.3% only 1 PCR and 6.7% no PCR). Four infants were diagnosed with HIV, and 3 infants were initiated on antiretroviral therapy early, before 12 weeks of age.Uptake of PCR testing at birth was high and a majority of infants received repeat testing at 6 weeks of age. In Kenya, infants with HIV initiate ART between 3.7 and 5.9 months of age.7 In contrast, high-income countries test infants exposed to HIV at birth, to expedite treatment for infants infected in-utero. Such immediate ART initiation has been associated with smaller viral reservoir development8 and faster time to viral suppression.9 In a pilot study in Lesotho, adding birth HIV PCR testing reduced the median age at ART initiation from 14.8 to 6.4 weeks.10 In South Africa, routine birth PCR testing for all infants exposed to HIV <4 weeks of age has increased the proportion of neonates diagnosed with HIV and initiated on ART,13 with 93% of infants in 1 district initiating ART within the first month of life.13 There is some concern, however, that return for subsequent infant testing may be too low. A study in Free State, South Africa found that after the receipt of birth PCR test results, only 44% of uninfected infants returned for a second PCR test at 10 weeks.14 Implementation studies are critical to better assess the impact of birth testing on infant outcomes and engagement in the EID continuum of services.The traditional approach to early infant diagnosis (EID) programs in lower resource settings is laboratory-based HIV polymerase chain reaction (PCR) testing between 4 and 6 weeks postnatal, when PCR sensitivity and specificity are optimal to identify cases of both intrauterine and intrapartum HIV transmission.16 Kenya was among the countries which engaged in pilot projects to assess the feasibility and impact of PoC testing for infants exposed to HIV.19 At the same time, Kenya revised the guidelines for EID to include PCR testing at birth, 6-week, 6 months and 12 months with antibody testing at 18 months.20 The recommendation for birth PCR testing was provisional, pending results of pilot projects. To date, birth PCR testing is not yet implemented as standard of care across Kenya. We report findings from a larger pilot study of simultaneous infant HIV testing strategies (PCR and PoC) at birth and 6 weeks of age to assess the feasibility and impact of implementation in Kenya. This paper details findings from the implementation of birth and 6-week HIV testing using laboratory-based PCR.With the introduction of diagnostic strategies for infant point of care (PoC) HIV testing in 2016,21This pilot study occurred in 4 Kenyan government hospitals with medium to high patient volume (mean of 8–15 infants exposed to HIV per month). Study hospitals were located in varied regions of the country; 1 in the coastal region (urban), 1 in the central region (urban) and 2 in the western region of Kenya (1 urban and 1 peri-urban) with pediatric HIV infection rates ranging from 3.4% to 4.2%.17 The study was approved by the Institutional Review Boards at the Kenya Medical Research Institute (SSC 3390) and the University of Kansas Medical Center.Eligible participants included women living with HIV >18 years of age presenting for care at the study hospitals during (1) pregnancy , (2) delivery or (3) postnatal period (<12 weeks of infant age). Eligible participants were enrolled from June 2017 to November 2018; however, the period of analysis was limited to November 3, 2017 to November 3, 2018 to avoid conflating the impact of the nationwide nursing strike  on the pilot results. All eligible candidates were informed about the purpose of the research, potential benefits and risks, and the study procedures by trained research or clinical staff. Participants provided written informed consent before study enrollment. A detailed description of study procedures has been previously published.20; though, at the time of the pilot study, birth testing was not being routinely implemented. Established standard of care procedures were used for PCR test sample collection and processing: a dried blood spot sample was collected via heel stick and sent by courier to the hospital’s designated central laboratory, processed, and then paper-based results were mailed back to the hospital, where the mother was notified of the results at the next clinical encounter. At both testing time points, if the PCR result was positive, the infant was linked to the comprehensive care center for ART initiation, at which time a confirmatory PCR sample was drawn and processed. Infants continued receiving ART until the confirmatory PCR result determined the infant’s final HIV status.20 If the PCR result was negative, mothers were counseled on retesting requirements.Infants of mothers living with HIV enrolled in the study were eligible for PCR testing at 2 time points: at birth (0 to <4 weeks) and at 6 weeks of age (4–12 weeks). Those tested within the optimal window for each test were documented: at birth (0–2 weeks) and 6 weeks (4–8 weeks). These time points aligned with HIV PCR testing time targets outlined in the 2016 Kenyan National Guidelines for EIDThe primary outcomes were the proportion of infants who received a birth test and the proportion of infants who returned for a 6-week test. We also distinguished between the optimal window  and the broader window  for age-specific infant HIV testing. Retention outcomes included (1) no test received, (2) receipt of birth PCR only, (3) receipt of 6-week PCR only and (4) receipt of birth and 6-week PCR.Secondary outcomes included turnaround times (TATs) of services , PCR test results , and infant age at PCR testing and ART initiation. Missed opportunities included the number of infants who presented for care during the targeted testing windows but did not receive a PCR test. Missed opportunities for PCR testing were documented when known and summarized.We used descriptive statistics to characterize participant demographics, and calculated the proportion of infants tested with PCR at birth, 6-week, and birth and 6-week. We calculated the median number of days and interquartile range (IQR) from sample collection to PCR test results and from PCR result to mother notification for tests conducted at birth and at 6-weeks. Lastly, median infant age was calculated for age at sample collection, notification of results, and ART initiation (if indicated) for birth and 6-week testing.A total of 670 mother–infant pairs were enrolled during the targeted 1-year period for analyses. Forty-six participants were excluded for the following reasons: 11 mother–infant pairs without a documented maternal date of birth (to confirm eligibility >18 years), 2 with maternal age <18 years at enrollment, 2 presented for testing after 12 weeks of age, and 31 who were discharged early due to transfer/move to another facility (n=11), infant mortality (n=14), maternal mortality (n=1), miscarriage/stillbirth (n=4) or withdrew consent (n=1). Six hundred twenty-four enrolled mother-infant pairs were included in final analyses.Mean maternal age was 30.2 years, 72.6% of women were married or lived with their partner, and the majority traveled <60 minutes to reach the hospital for PMTCT services. Nearly three-quarters of the women initiated ART before the current pregnancy, and the majority of women (73.2%) enrolled in the study during antenatal care , with 89.9% delivering in the hospital, and 54.3% of infants were carried to ≥37 gestational weeks.The timing of infant PCR testing, the proportion diagnosed with HIV, infant age at ART initiation, and the retention categories for testing are outlined in Figure Among the 590 mother–infant pairs enrolled before 4 weeks postnatal, 452 (76.6%) were tested within the birth window of 0–4 weeks of age, and among those 360 of 452 (79.6%) were tested within the optimal window of 0–2 weeks of age. One hundred seventy-eight of 452 (39.4%) were tested before hospital discharge after delivery (0–2 days).Compared with birth testing, a higher proportion of infants  received testing within the traditional 6-week window, with 546 of 575 (95.0%) tested on time.In total, 417/624 (66.8%) received repeat PCR testing (a birth PCR test followed by a repeat PCR test at 6 weeks of infant age). Among these, 332 (79.6%) infants received the birth and 6-week testing sequence within the optimal/on-time windows. The proportion receiving birth and 6-week testing at the 3 urban hospitals averaged 64.0% and was 74.2% at the peri-urban hospital.A total of 207 (33.2%) infants exposed to HIV received incomplete PCR testing for the following reasons: 35 (5.6%) birth test only , 158 (25.3%) 6-week test only and 14 (2.2%) with no PCR at either time point.Of the 452 infants who received a birth PCR test, there were 448 (99.1%) valid test results (446 negatives and 2 positives) posted to facilities with a median TAT of 14 days (IQR 7–22). Four hundred forty-one (98.4%) mothers were notified after a median time of 3 days (IQR 0–21) of test result.Of the 575 infants who received a 6-week PCR test, there were 573 valid test results (571 negatives and 2 positives) posted to facilities with a median TAT of 13.5 days (IQR 7–21) from sample collection to return of result. Five hundred sixty-two (98.1%) mothers were notified of their infant’s results after a median of 5 days (IQR 0–20). The median therapeutic TAT of results (sample collection to notification of caregiver) was the same for infants tested at birth  and 6-week . Median infant age at birth PCR sample collection was 0.8 weeks (IQR 0.14–1.9) and mothers were notified of results at a median infant age of 5.4 weeks (IQR 2.6–6.3). Both infants diagnosed with HIV at birth were initiated on ART at 3.9 weeks. Among infants tested at 6 weeks, the median infant age at sample collection was 6.1 weeks (IQR 6.0–6.4), mothers were notified by 10.0 weeks (IQR 8.0–11.0), with ART initiation of 1 infant at 11.9 weeks. Infants initiating ART were diagnosed by PCR only; either due to a PoC machine error or provider hesitancy to initiate ART based on PoC results alone. One infant diagnosed by 6-week PCR was not initiated on ART. The mother was notified of the results, but did not return to the hospital, despite repeated efforts and a home visit by a community health worker.Of the 172 infants who did not receive a birth PCR test, 34 were enrolled after the birth test window (≥4 weeks of age). Of the remaining 138, 19 (13.7%) presented for testing but only received a birth PoC test, thus reflecting a missed opportunity to provide birth PCR. Approximately 20% (119 of 590) of those enrolled antenatally or at delivery did not return and present for EID early enough to be tested within the birth window.Of the 49 of 624 (7.8%) infants who did not receive PCR testing at the well-established 6-week period, only 1 infant showed a documented hospital visit at 6-week, reflecting a missed opportunity to provide PCR testing at the same time. Among those not tested at 6 weeks, 71.4% (35 of 49) had received a PCR test during the birth window; only 2.2% of enrolled infants did not receive any PCR test during the first 12 weeks of life.13 holds promise for relatively rapid uptake in similar settings. Similar to the experience in Eswatini,22 this pilot study in Kenya did not observe the concern that fewer infants tested at birth may return for retesting; with nearly all (92.3%) infants tested at birth returning for a follow-up 6-week PCR test. A similarly high proportion of infants who were not tested at birth received a 6-week test (91.9%), indicating the well-established protocol of 6-week infant testing. In total, 66.8% of the sample achieved repeat testing (birth and 6-week). Only 2.2% of infants did not return for testing at either time point.These promising data demonstrate that earlier and repeated testing within the first 2 months of life is feasible with the established PCR laboratory infrastructure in Kenya. Nearly three-quarters of mother–infant pairs received testing during the birth windows. South Africa’s high coverage of birth HIV testing after nationwide implementation,23 Thus, continuous and comprehensive counseling throughout pregnancy is necessary to shape women’s expectations for early infant testing within the first 2 weeks of life and prepare women for the complete EID cascade of care. While 0–2 weeks is the optimal target for birth testing, we included a more generous range of 0–4 weeks. This allowed a more flexible window for infants delivered at home, and with an average TAT of 10 days for PCR test results in Kenya,21 infants tested <4 weeks could still have PCR results available by the 6-week retest (median infant age at the notification of birth results in the pilot was 5.4 weeks). If test and treat guidelines are followed for birth testing, positive infants could be diagnosed and initiated on ART by their 6-week visit, achieving targets for early ART initiation. Among the 3 infants initiated on ART in our study, 2 were diagnosed during the birth window and both initiated within the first month of life, and the infant diagnosed at 6-week was initiated on ART before the 12-week target. Other studies evaluating birth PCR testing found age at ART initiation ranged from 9 days to 9.7 weeks,26 while studies evaluating at birth PoC testing found age at ART initiated ranged from 2 days to approximately 1 month of age.25Formative qualitative interviews with parents and HIV care providers conducted before implementation revealed that some parents feared an infant’s positive diagnosis at birth could hinder mother–infant bonding and thus preferred traditional 6-week testing.28 it may be more pragmatic at this time for policy makers to add the more familiar PCR test at birth, rather than investing in the infrastructure and training required for birth PoC testing. In our parallel pilot study of PoC testing at these same sites, we experienced higher rates of missed testing opportunities due to machine/stock outs or invalid results (23.3%),29 and delays in ART initiation still occurred largely due to the initial novelty of PoC in this setting.30 Other larger PoC studies have reported more favorable findings,31 and the benefit of PoC may be greater in settings with longer delays for laboratory-based PCR results. Furthermore, PCR HIV testing at birth and 6-week has been assessed as cost-effective, compared with EID at 6 weeks alone.32 Thus, the addition of birth PCR may be more feasible for nationalwide implementation in some countries.Given the success in early ART initiation that many birth PCR programs have achieved, the consistent TAT of 2 weeks for PCR results in Kenya, and the challenges to implementing and sustaining birth PoC testing ,33 Furthermore, the practice of delivering in a hospital but seeking infant postnatal services in a closer health facility, could complicate the ability to accurately document repeat testing. Thus, history of birth testing will be important for providers to assess when infants present for routine EID at 6 weeks.To ensure hospital readiness and maximize benefits, barriers to implementation of birth testing must be addressed. One very practical, system-level barrier identified in a parallel study with repeated focus groups with providers over the course of the birth PCR implementation period, was that infant IDs are not usually designated until a first postnatal visit after 2 weeks; thus, confusion around infant IDs for those tested in maternity before discharge hindered early implementation.14 Thus, after the initial birth test, structured interventions are needed to support the completion of EID services and quality of pediatric HIV management,34 recognizing that key patient-level psychosocial (HIV stigma and nondisclosure), financial, and logistical (childcare and transportation) barriers to EID retention remain.38The critical gains in neonatal diagnosis and ART initiation achieved by birth testing can be lost without strong systems to support pediatric ART adherence, viral loading monitoring, and retention in care, as cautioned by researchers in South Africa.,This pilot study has several limitations to consider. The sample size was relatively small with only 4 government hospitals included for a duration of 1 year. Given the advances in antenatal coverage of PMTCT services, the proportion of infants diagnosed with HIV were few (<1%). This limited the generalizability of findings specific to infants diagnosed with HIV, including the efficiency and infant age of ART initiation, which are priority outcomes when considering varied infant testing strategies. The findings specific to infants who were not diagnosed with HIV, which reflect the vast majority of infants enrolled in EID in Kenya, demonstrate the feasibility of birth PCR testing with actionable test results by the time repeat testing is due at 6 weeks of age. We also acknowledge that the wide window afforded for “6-week” testing in this study (4–12 weeks), exceeds the target of EID before 8 weeks of age. Our ability to accurately characterize missed opportunities for birth PCR testing was limited by incomplete documentation that failed to specify a reason for the lack of testing, thus we could not distinguish between cases in which the infant never presented for HIV testing before 4 weeks or the provider failed to request an early test during the visit. Lastly, these findings are limited to women seeking facility-based PMTCT and EID services in Kenya and the pilot study did not include a comprehensive cost-effectiveness analysis.Our data suggest that simply accelerating the timeline for infant HIV testing with traditional laboratory-based PCR testing at birth can reduce infant age at HIV diagnosis and does not hinder 6-week retesting, which remains necessary to diagnose early postnatal HIV transmission.The Kenya Medical Research Institute, Global Health Innovations, and Children’s Mercy Kansas City were collaborative partners in these efforts. We are grateful to the mother–infant pairs and hospital staff who participated in the study. We also acknowledge the critical role of our government partners at the Kenya National AIDS and STI Control Program (NASCOP) and County Ministers of Health. We thank the Director of KEMRI for permission to publish this manuscript.


Nulliparity is considered to be a risk factor of preterm birth (PTB), low birth weight (LBW) and small for gestational age (SGA). With the new two-child policy launched in 2016, more Chinese women have delivered their 2nd baby. Yet few studies have assessed the impact of parity on adverse birth outcomes in China. This study aimed to examine the association between parity and risks of PTB, LBW and SGA in a Chinese population. The combined effects of maternal age and parity on adverse birth outcomes were also assessed.This retrospective study included all non-malformed live births born during January 1, 2014 and December 31, 2018 in Chengdu, China. A total of 746,410 eligible live singletons with complete information were included in the analysis. Parity was classified into nulliparity (i.e. has never delivered a newborn before) and multiparity (i.e. has delivered at least one newborn before). Log-binomial regression analyses were applied to evaluate the association between parity and PTB, LBW and SGA. We further divided maternal age into different groups  to assess the combined effects of maternal age and parity on adverse birth outcomes.Multiparity was associated with reduced risks of PTB , LBW  and SGA  compared with nulliparity. In each age group, we observed that multiparity was associated with lower risks of adverse birth outcomes. Compared to nulliparous women aged between 25 and 29 years, women aged ≥35 years had greater risks of PTB and LBW, regardless of their parity status. In contrast, multiparous women aged ≥35 years  and those aged < 25 years  were at lower risk of SGA compared with nulliparous women aged between 25 and 29 years.Multiparity was associated with lower risks of all adverse birth outcomes. Special attention should be paid to nulliparous mothers and those with advanced age during antenatal care, in order to reduce the risks of adverse birth outcomes.The online version contains supplementary material available at 10.1186/s12884-021-03718-4. Preterm birth (PTB), low birth weight (LBW) and small for gestational age (SGA) are common adverse birth outcomes globally, which have become significant public health problems with increasing concerns –3. InfanEpidemiologic evidence has demonstrated that various maternal, paternal and environmental factors, such as advanced maternal and paternal age, maternal pre-pregnant obesity, poor nutrition during pregnancy and unqualified antenatal care, might lead to adverse birth outcomes –14. PariChina has altered its one-child policy to a two-child policy in 2016. With more Chinese women delivering their 2nd baby, a contemporary assessment of parity on adverse birth outcomes in Chinese women is needed. In addition, previous studies have established the “U-shaped” effects of maternal age on adverse birth outcomes , 20. A mn = 28,012, 2.76%), newborns without information of sex, height, weight and gestational age , as well as those without information on parity , a total of 746,410 singleton live births were included in the data analysis.A retrospective study was conducted in Chengdu, China. Data were obtained from the Chengdu Maternal and Child Health Information System, which covers information on antenatal care and birth records from all women delivering babies at any medical environment in Chengdu, China. During January 1, 2014 and December 31, 2018, 1,016,406 non-malformed live births records were extracted from the system. After excluding multiple births  and multiparous mothers (i.e. have delivered at least one newborn before).n = 33,047) and very PTB  for the sensitivity analyses. LBW was defined as birth weight less than 2500 g. SGA was defined as birth weight below the 10th centile for specific gestational age and sex based on the Chinese birth weight reference percentiles [Adverse birth outcomes in this study included PTB, LBW and SGA. Birth information was obtained from the electronic medical record system. Gestational age at birth was calculated as the period from the first day of the last menstrual cycle to the day of birth. PTB was defined as the gestational age at delivery < 37 weeks. We further divided it into moderate PTB  were recorded during the first antenatal visit. Maternal area of residence , immigrant status  and education levels  were also collected. Pre-pregnancy weight was self-reported by pregnant women during their first antenatal visit. The height was measured using a stadiometer. Pre-pregnancy body mass index (BMI) was calculated as maternal pre-pregnancy weight divided by the square of height. Maternal pre-pregnancy obesity was defined as pre-pregnancy BMI > 28 kg/min China .Characteristics between nulliparous and multiparous mothers was compared by independent student t-test for continuous variables and Chi-square test for categorical variables. The impact of parity on adverse birth outcomes was assessed with log-binomial regression models. In the adjusted models, parental age and race, maternal area of residence, immigrant status, education level and pre-pregnancy obesity, as well as newborn’s sex were controlled. The crude and adjusted relative risks (RRs) with 95% confidence intervals (95% CI) for PTB, LBW and SGA were calculated for multiparous mothers versus nulliparous mothers (reference), respectively. We further assessed the association between parity with MPTB and VPTB. The impact of parity on LBW and SGA was also evaluated separately in preterm and term neonates.To evaluate the possible impact of maternal age on the association between parity and adverse birth outcomes. We first assessed the associations in different maternal age groups . Then, the combined impact of maternal age and parity on adverse birth outcomes was evaluated, with nulliparous mothers aged between 25 and 29 years as the reference group in the multivariate log-binomial regression analyses.To graphically visualize the birth weight between neonates born to nulliparous and multiparous mothers at different gestational age, we constructed gestational age and sex-specific birth weight charts by parity (nulliparity and multiparity) based on Box-Cox power exponential (BCPE) method  using geAll statistical analyses were performed with R software Version 3.6.1 (R Development Core Team). We conducted 2-sided tests with alpha set at 5%.n = 427,986, 57.34%) than multiparous mothers . The comparison of maternal, paternal and newborn characteristics by parity was shown in Table After excluding 241,984 women with missing data, 746,410 were included in the final analysis. The comparison of excluded and included participants are presented in Additional file The gestational age and sex-specific birthweight charts according to parity were shown in Fig. The associations between parity and adverse birth outcomes were presented in Table The prevalence of adverse birth outcomes by parity in different maternal age groups was shown in Fig. In this retrospective study among Chinese women, birth weight for neonates born to multiparous mothers was greater than those born to nulliparous mothers, regardless of the gestational age and newborn’s sex. Compared to nulliparity, the risks of PTB, LBW and SGA in multiparous women have reduced by 9%, 26% and 33%, respectively. The association revealed in sensitivity analyses were consistent with our main findings for MPTB or in term/preterm births, except for the outcome of VPTB. We further found discrepant association between parity with PTB, LBW and SGA in different maternal age groups. Compared to nulliparous mother aged between 25 and 29 years, nulliparous women aged ≥35 years had the greatest risks of PTB and LBW, while the greatest risk of SGA was found in nulliparous women aged < 25 years and ≥ 35 years.Our results were consistent with several previous researches , 21, 27.The association between parity and adverse birth outcomes might be explained by fewer uteroplacental blood flow and smaller uterine cavity of women who never gave birth before –37. StudWe further observed a negative association between multiparity and adverse birth outcomes in every maternal age group, which were consistent with previous study . AdditioIn contrast to PTB and LBW, we found that the risk of SGA was also reduced among multiparous mothers aged ≥35 years compared with nulliparous women aged between 25 and 29 years, indicating different pathogenic mechanism of PTB, LBW and SGA. We speculated that PTB and LBW were more likely to be associated with placental and oocyte defectivity, while SGA was mainly linked to inadequacy of nutrition to fetus. However, additional studies are needed to confirm it. Additionally, due to insufficient sample size of women aged < 18 years in our study, we failed to explore the risks of adverse birth outcomes among nulliparous teenage. Further investigations are needed to figure out the potential association and mechanism.Although parity and maternal age could not be modified, using both information might help us identify mothers with high risk of adverse birth outcomes. Previous research has shown that intervening high-risk women with targeted interventions, such as prenatal education, nutrition supplements, smoking cessation and clinical treatments during pregnancy, could effectively reduce the risk of adverse birth outcomes –57. It mThe main strength of this retrospective study was the large sample size of singleton live births, which allowed us to conduct further subgroup and sensitivity analysis with enough power. The consistent findings in sensitivity analysis demonstrated the robustness of our study. We also plotted birthweight charts by sex of newborns in different parity categories, which enabled us to directly visualize the birthweight at different gestational age between newborns delivered by nulliparous and multiparous mothers.n = 48), which was less likely to affect the findings reported. Fourthly, although ultrasound examination might be a more reliable method to estimate gestational age [Nevertheless, the present study had several limitations. Firstly, the population included in our study was limited to one city in western China and nearly one quarter 23.59%) of the study population were excluded due to missing information. Most characteristics of the included and excluded population were significantly different, which could cause potential selection bias. Cautions should be taken when extending the findings of this research to other regions of China or other countries. In particular, the majority of the included women were living in rural area (67.06%), while those excluded from this study were more likely to be urban residents (58.58%). Previous studies have shown that pregnant women in rural areas might attended fewer antenatal care with poor quality , 63, whi.59% of tonal age , gestational age , we wereIn this retrospective study, a contemporary assessment of parity on adverse birth outcomes was conducted in China. We found that nulliparity was associated with increased risks of PTB, LBW and SGA. Compared to nulliparous women aged between 25 and 29 years, mothers with advanced age had increased risks of PTB and LBW, regardless of their parity status, while multiparity was consistently associated with reduced risk of SGA across different age groups. The findings suggested that more attention should be paid to nulliparous mothers, in order to reduce the risks of adverse birth outcomes. Additionally, regardless of their parity status, women with advanced age should be closely monitored or intervened to minimize the risks of PTB and LBW.Additional file 1: Table S1. Comparison of maternal, paternal, newborn characteristics and adverse birth outcomes between excluded and included data.Additional file 2: Table S2. Associations between parity and adverse birth outcomes, stratified by maternal age.Additional file 3: Table S3. Relative Risk (RR) for adverse birth outcomes by parity, among overall women and subgroups with missing data imputed.Additional file 4: Table S4. Associations between parity/maternal age and adverse birth outcomes with missing data imputed (adjusted RR and 95% CI).


Preterm birth is the leading cause of child mortality. This study aimed to develop and validate programmatically feasible and accurate approaches to estimate newborn gestational age (GA) in low resource settings.The WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) study recruited pregnant women from population-based cohorts in five countries . Women <20 weeks gestation by ultrasound-based dating were enrolled. Research staff assessed newborns for: (1) anthropometry, (2) neuromuscular/physical signs and (3) feeding maturity. Machine-learning techniques were used to construct ensemble models. Diagnostic accuracy was assessed by areas under the receiver operating curve (AUC) and Bland-Altman analysis.7428 liveborn infants were included . The Ballard examination was biased compared with ultrasound dating (mean difference: +9 days) with 95% limits of agreement (LOA) −15.3 to 33.6 days (precision ±24.5 days). A model including 10 newborn characteristics  estimated GA with no bias, 95% LOA ±17.3 days and an AUC=0.88 for classifying the preterm infant. A model that included last menstrual period (LMP) with the 10 characteristics had 95% LOA ±15.7 days and high diagnostic accuracy (AUC 0.91). An alternative simpler model including birth weight and LMP had 95% LOA of ±16.7 and an AUC of 0.88.The best machine-learning model  estimated GA within ±15.7 days of early ultrasound dating. Simpler models performed reasonably well with marginal increases in prediction error. These models hold promise for newborn GA estimation when ultrasound dating is unavailable. In low-middle income countries, the gestational age (GA) dating of pregnancies is commonly inaccurate or unknown prenatally, and the GA of the baby is estimated after birth.Several clinical neonatal assessments exist to estimate the GA of the newborn, ranging from 4 to 23 physical and neurological signs.A recent systematic review and meta-analysis demonstrated that the most commonly used clinical assessment, the 10 sign Ballard score, systematically overestimated GA (3 days) and dated 95% of newborns within ±27 days (3.9 weeks) of ultrasound-based dating.The 21 sign Dubowitz examination dated 95% of newborns within ±18 days (2.6 weeks) of best obstetrical estimate.In general, clinical newborn assessments with fewer signs tend to be less accurate.The WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) GA study is a multicountry study that is one of the largest, well-dated, prospective, population-based pregnancy cohorts in low-middle income countries that included 7428 newborns from five countries in Africa and Asia.We aimed to develop the most precise model to predict newborn GA with the fewest clinical signs using machine learning techniques.In the most precise model that included 10 newborn characteristics  and last menstrual period (LMP), the model predicted GA within ±15.7 days (2.2 weeks) of early ultrasound and had high diagnostic accuracy for identifying preterm births.It correctly classified 91% of infants as preterm or not.In a simpler model including only two signs (birth weight and LMP), the prediction of GA was within ±16.7 days (2.4 weeks) of ultrasound and correctly classified 88% of infants as preterm or not.The AMANHI GA models may be used in clinical practice to more accurately identify high-risk, preterm infants in low-income settings and improve their access to special care.Achieving meaningful declines in child mortality in the post-Millenium Development Goal era will require commitment and innovation to reduce mortality among babies born preterm (<37 weeks gestation). According to the latest WHO estimates, 14.8 million (10.6%) of newborns were born preterm worldwide in 2014.3In low-middle income countries (LMICs), the lack of available or accurate data on the gestational age (GA) of a pregnancy, and thus misclassification of infant as preterm or not, is a critical barrier to providing adequate care for these vulnerable babies and estimating the global burden of preterm birth. Improvement in GA dating is a key priority to provide improved clinical care of mothers and babies, and to improve epidemiological data on the burden of disease. In the most recent estimates of preterm birth by WHO,et al reported on a GA assessment including 21 external physical and neurological characteristics.et al described a simplified score that required only 10 signs.For decades, the physical and neurological maturity of the newborn has been used to estimate the GA of the infant after delivery. In 1970, Dubowitz The WHO Alliance for Maternal and Neonatal Health Improvement (WHO AMANHI) study is a multicountry collaboration formed of investigators of maternal–newborn health studies from Bangladesh, Ghana, Pakistan, Tanzania and Zambia.The AMANHI GA study was conducted in prospective pregnancy cohorts in five sites—two in south Asia (Bangladesh (Sylhet), Pakistan ) and three in sub-Saharan Africa (Ghana (Brong Ahafo), Tanzania (Pemba) and Zambia (Southern Province)).10.1136/bmjgh-2021-005688.supp1Supplementary dataFor all sites except Zambia, pregnancies were identified by population-based surveillance of women of reproductive age every 1–3 months. In Zambia, where over 96% of all pregnant women attend antenatal care clinics, the study recruited pregnant women from antenatal clinics. Women were considered eligible if they had a known LMP that suggested a GA of <20 weeks. Pregnant women were consented by field workers in the local language, and those consenting had an ultrasound scan for pregnancy dating.et al11The ultrasound standard operations procedure (SOP) was developed by the AMANHI team with a maternal–fetal medicine specialist (BW). The SOP specified standardised procedures for measuring fetal biometric parameters transabdominally. Crown–rump length (CRL) was measured first. If CRL was >95 mm, both biparietal diameter (BPD) and femur length (FL) were additionally measured. At least two separate measurements were performed for each parameter. Average values were used for duplicate measures; median values were used for triplicate measures. If pregnancies were identified at <8 weeks, a repeat scan was scheduled 4 weeks later. Women with pregnancies enrolling >20 weeks were excluded from the GA study. To assign the gold standard GA, for scans with CRL between 15 and 95 mm, GA was assigned by the INTERGROWTH-21st formula.All pregnancies were followed until delivery and a neonatal assessment was conducted.The neonatal examination included six neuromuscular signs of passive flexor tone or joint flexibility, and five physical signs from the original Ballard examination13The newborn examination was conducted in most sites by non-clinician field workers  and prior experience/training in maternal–newborn care . After proficiency was established for each trainee with direct observation, a standardisation exercise was performed. Trainees were certified only after scoring all of the physical and neuromuscular signs within 1 point of the expert trainer on at least five newborns.The WHO AMANHI coordinating team conducted central data review on a quarterly basis and conducted regular site visits to monitor field implementation and data collection. For ultrasound, a random selected 5% of images were sent for central review and feedback to an external maternal fetal medicine expert (BW). A standardised quality checklist of minimal acceptable quality standards for each biometric parameter was completed. For the newborn assessment, trained study coordinators independently conducted and/or directly observed a random 5% of neonatal assessments in the field to ensure maintenance of skill and quality.For each subset of predictors considered, an ensemble model was constructed using the Super Learner algorithmIt was not possible to fit ensemble models for all possible subsets of the 25 predictors available from the newborn assessments . A priori, we determined that 10 would be a maximum feasible number of signs to include in a newborn assessment for front-line health workers in LMICs. Predictors were prescreened using LASSO regularised regressionTo compare the accuracy of the test methods and machine learning models for GA estimation, Bland-Altman plots were generated to summarise the agreement of GA as predicted by the test method versus gold standard (ultrasound) across the range of GA. Receiver operating curves were generated for each test method/model and areas under the receiver operating curve (AUC) calculated for the diagnostic accuracy of classifying infants <37 and <34 weeks. We assessed diagnostic accuracy by fixing sensitivity at a threshold of 80%, our a priori determined minimum sensitivity clinical threshold for a screening test for identifying preterm births. We also report diagnostic accuracy for fixed sensitivity of 85%, 90%, 95% and at the maximum Youden index, reflecting highest test accuracy.In the AMANHI GA study, assuming that the simple machine learning models would detect a preterm prevalence of 10% with ±5% (absolute) precision and achieve 80% sensitivity and specificity to identify preterm infants in comparison to early pregnancy ultrasound dating, sample size was estimated to be 5740 pregnant women, an additional 2870 women were estimated to be required for validation of the machine learning model.10Members of the public were not involved in the design or conduct of the study. During the formative/pilot phase of the study, family members of patients were involved in providing critical feedback on components of the neonatal assessment and certain procedures were modified based on their inputs. Specific examination components were eliminated (square window sign) and methods to calm the newborn were incorporated into study procedures.>37 weeks, 666 34–<37 weeks and 187 <34 weeks gestation). Of these 7414 (87%) term infants, 507 (76%) 34–<37 weeks infants, 80 (43%) <34 weeks infants were assessed at <72 hours of life. An important reason for the differential assessment was death prior to assessment  and 28% in early preterm births (<34 weeks infants)). The majority (67%) of assessments were performed within the first 24 hours of life. Complete data on all examination components were found in 93% of assessed newborns and were included in the final analytic data set.From 1 January 2012 to 18 January 2017, a total of 11 662 pregnant women were enrolled, who had 10 581 live births . Among tBasic characteristics of infants included in the analysis across study sites are shown in We determined the accuracy of the LMP and Ballard examination dating compared with early ultrasound dating .The average bias of LMP was 1.7 days underestimation compared with ultrasound , with a The Ballard exam systematically overestimated GA by 9.2 days (95% CI 8.9 to 9.4), and had a 95% LOA  compared to early ultrasound dating. This bias towards GA overestimation was consistent in the country specific analysis . Using tUsing machine learning, a full prediction model was built that included all 25 characteristics assessed (data not shown). Simpler models using less signs had comparable performance and are presented below. >39 weeks , predicted GA values fell within ±17.3 days of early ultrasound GA (95% LOA), with an AUC of 0.88 to classify <37 week infants and 0.94 to classify <34 weeks. While the average bias was zero across all GAs, model A tended to predict higher GA compared with ultrasound dating prior to 39 weeks, and lower GA at 39 weeks . The sen39 weeks . The diaLMP was additionally included with model A to determine whether the model performance and diagnostic accuracy could be further improved. In model B, the precision was further improved to 95% LOA±15.7 days . The AUCIn this parsimonious model with only two characteristics (model C), the 95% LOA was ±16.7 days, which was between that of model B and model A . Model CIn this model with two best performing anthropometric measures, for use in cases when LMP may not be known (model D), 95% LOA of ±18.4 days. These LOA were marginally worse than that of models A, B and C, but substantially better than that of Ballard examination or LMP. At 80% sensitivity, model D had 72% specificity to identify preterm <37 weeks (93% specificity for <34 weeks)  .Overall, the methods had more negative bias among SGA infants compared with those born AGA. Ballard examination overestimated GA on average by 10.5 days in AGA, compared with 4.9 days in SGA infants . All macIn this large multicountry prospective pregnancy cohort with high quality early ultrasound dating (<20 weeks), we found that routine, existing methods to estimate GA, the LMP and Ballard examination, were biased and imprecise (±25–39 days). We developed a new machine learning model including 10 newborn characteristics  and LMP, that estimated GA within ±15.7 days of early ultrasound dating. Furthermore, a simpler machine learning model including only birth weight and LMP performed similarly with only marginally lower diagnostic accuracy, dating 95% of pregnancies within ±16.7 days of early ultrasound.LMP dating is still widely used for pregnancy dating in high-income countries. However, recall of LMP is less available and accurate among women of low literacy and socio-economic status.The Ballard examination is one of the most common clinical methods used to estimate newborn GA after birth. In our study the Ballard was significantly biased, consistently overestimating GA by 9 days. This bias was similar across all study sites and countries. Furthermore, the estimates were imprecise, dating most pregnancies within ±25 days. These data are in line with a prior systematic reviewet al used machine learning to develop an algorithm for predicting preterm birth in the Zambian Preterm Birth Prevention Study, with six parameters including LMP, birth weight, twin delivery, maternal height, hypertension in labour and HIV serostatus.et al26In the best AMANHI machine learning model (model B), including 10 characteristics and LMP, we were able to achieve high accuracy with an AUC of 0.91, indicating that the test could correctly classify preterm or not, 91% of the time. This model predicted GA within 15.7 days of early ultrasound for 95% of newborns. Machine learning has been used by other groups and investigators to develop algorithms for estimating GA or predicting preterm birth. Rittenhouse An important consideration and potential limitation of our 10 newborn characteristic model is the reliance on several measures of physical size, or anthropometric measures that reflect infant size rather than maturity. These indicators would be influenced by intrauterine growth restriction, with the exception of head circumference which is potentially less affected in cases of asymmetric intrauterine growth restriction with head sparing. The machine learning models included substantial input data from three sites with high rates of SGA , yet, still systematically underestimated GA among SGA infants by approximately 4–5 days. The identification and validation of novel physical or clinical characteristics to improve GA estimation among SGA and growth restricted infants is an important priority to improve GA estimation in settings where SGA prevalence is high.Given feasibility, training and human resources considerations in LMIC, we also developed simpler two-characteristic models (models C and D), as potential alternatives to identify vulnerable babies in settings with limited resources. When LMP is known, model C (birth weight and LMP) was accurate with only marginal reductions in diagnostic accuracy compared with the best AMANHI model A. However, availability and quality of birth weight and LMP data remain major challenges in LMICs. Half of infants born in sub-Saharan Africa and Asia do not have a recorded birth weight.There were several limitations to this study. Infants <34 weeks infants represented only 1% of this analysed cohort. About 28% of infants <34 weeks died before the assessment. Given the exclusion of critically ill infants, the effect of morbidities on model performance cannot be assessed. Another consideration is the timing of the assessment. Certain physical signs may vary after birth, such as the skin opacity or foot creases. In our study, the majority of assessments (80%) were conducted within 48 hours of birth. We had hypothesised that feeding maturity observations and signs may improve performance in estimating gestational maturity. However, we found feeding questions difficult to train and standardise across sites, and these variables dropped out of the modelling in early stages.The WHO AMANHI machine learning GA model including 10 newborn characteristics and LMP predicted GA within ±16 days of an early pregnancy ultrasound, and a simpler machine learning model including only birth weight and LMP performed well with modest reductions in prediction accuracy. This accuracy is similar to the traditional clinical 21-sign Dubowitz examination and substantially more accurate and less biased than the Ballard examination. These new machine learning models hold promise for accurate and timely identification of vulnerable, preterm infants -- the essential first step required in order to provide them with the special care needed to reduce global neonatal morbidity and mortality.


Aims: The aim of this study was to analyse associations between maternal country of birth and preterm birth among women giving birth in Norway. Methods: A population-based register study was conducted employing official national databases in Norway. All singleton births, with neonates without major anomalies, between 1999 and 2014 were included . We estimated odds ratios (ORs) for extremely preterm birth (<28 weeks gestation), very preterm birth (28–33 weeks gestation) and late preterm birth (34–36 weeks gestation) by maternal country of birth. We conducted multivariable regression analyses, adjusting for maternal, obstetric and socio-economic confounders. Results: For extremely preterm births (0.4% of the study population), women with an unknown country of birth (adjusted OR (aOR)=3.09; 95% confidence interval (CI) 2.26–4.22) and women born in sub-Saharan Africa  had the highest ORs compared to Norwegian-born women. For very preterm births (1.2% of the study population), women with an unknown country of birth  and women born in South Asia  had the highest ORs. For late preterm births (3.8% of the study population), women born in East Asia Pacific/Oceania  and South Asia  had the highest ORs. Conclusions: After adjusting for maternal, obstetric and socio-economic risk factors, maternal country of birth remained significantly associated with preterm birth. Women with an unknown country of birth and women born in sub-Saharan Africa were found to be at increased risk of extremely preterm birth. Preterm birth, defined as birth before 37 weeks’ gestation, is a major cause of neonatal mortality and morbidity worldwide. National preterm birth rates vary in the range of 5–18%, with low-income countries having the highest rates ,3. GestaImmigration, which is increasing worldwide, may be considered to be a composite social health determinant, with individual, cultural and structural factors affecting health outcomes . WhereasThe main aim of the study was to assess associations between extremely, very and late preterm birth and maternal country of birth among women giving birth in Norway. A secondary aim was to explore the effects of maternal, obstetric and socio-economic factors on associations between preterm birth and maternal country of birth.This was a population-based register study. Data obtained from two national registries – the Medical Birth Registry of Norway (MBRN) and Statistics Norway (SSB) – were merged. The MBRN was established in 1967, where registration of data on maternal and neonatal health became mandatory for all deliveries in Norway, including home births. Information is collected consecutively throughout pregnancy and birth. Midwives complete the notification to the MBRN when discharging the women after birth. SSB compiles official statistics about Norwegian society, including the country of birth and education levels of the residents of Norway.+0 and 33+6; and late preterm, birth between gestational week 34+0 and 36+6. The categorisation was based on clinical relevance. In line with World Health Organization, birth before week 28 is termed extremely preterm. Babies born extremely preterm have the highest mortality and morbidity risk. In contrast, babies born after week 33 are considered low risk. Norwegian clinical guidelines recommend antenatal corticosteroids and tocolytics until the end of week 33.The study sample consisted of 930,684 births in the gestational age range of 22–44 weeks that were registered between 1999 and 2014. Multiple births and births in which neonates had major anomalies were excluded, leaving a total sample size of 910,752 births. Since 1999, gestational age in the MBRN has been based on second-trimester ultrasound examination markers. More than 97% of pregnant women in Norway undergo an ultrasound examination between gestational weeks 17 and 20 offered free of charge. The outcome variable, preterm birth, was divided into three subgroups: extremely preterm, birth before gestational week 28; very preterm, birth between gestational week 28The main independent risk factor was maternal country of birth. Countries were divided into nine regions based on the World Bank’s classification scheme. The reference group consisted of women born in Norway. Europe was divided into countries in the European Economic Association (EEA), including Switzerland, and countries outside the EEA. Our sample included relatively low numbers of women from Transcaucasia, Central Asia and Oceania. Based on demographic factors, women born in Transcaucasia and Central Asia regions were merged into a single group with women born in non-EEA European countries. Women born in countries within the East Asia or Oceania regions were merged into a single East Asia Pacific/Oceania group .Risk factors for preterm birth were accounted for in analysis adjustments. Education and marital status were used as proxies for socio-economic status. The eight levels of education in the 2011 International Standard Classification of Education were simplified into four levels according to number of years of education. Women who completed some secondary education (11–14 years) were a reference group. Marital status was dichotomised into married/cohabiting/partner or single/widowed.Maternal age at the time of birth was divided into five groups with five-year intervals, with the 25- to 30-year-old age group serving as a reference group. First-trimester smoking was categorised as sometimes, daily and non-smoking. Patients with diabetes were designated as type 1, type 2 or gestational diabetes. Patients were designated as having preeclampsia, eclampsia, or HELLP syndrome or not, forming a single dichotomous variable. Parity was grouped into nulliparous, para 1 and para ⩾2; para 1 was used as the reference group. Gestational hypertension, placenta previa, in vitro fertilisation and obstetric history of a stillbirth or second-trimester abortion were considered conditions with possible associations with preterm birth. These variables were treated as dichotomous categories.Information on smoking was missing for 16% of the cases. We categorised these cases as non-smokers, in line with previous studies based on MBRN data . InformaThis population-based cohort study is part of the PURPLE Study approved by the Regional Committee for Medical Research Ethics in South East Norway in 2015 (2015/681) and the Institutional Personal Data Officer in Oslo University Hospital. The study was conducted in accordance with the Norwegian Health Research legislation. The researchers received only anonymised data.Continuous data were categorised. Crude logistic regression analyses were performed to identify significant risk factors, which were included in subsequent multivariable regression analyses. Two models encompassing maternal, obstetric and socio-economic variables were evaluated. Model 1 included maternal morbidity, age, obstetric history and pregnancy-related conditions. Model 2 consisted of the model 1 constituents plus socio-economic factors. We performed a separate multivariable regression analysis and obtained adjusted odds ratio (aORs) for each outcome. Births occurring before week 28 were excluded in our analyses of the very preterm birth group, and only births occurring after the start of week 34 were included in our analyses of the late preterm birth group. To assess how well study factors in each model explained outcome differences, we calculated the percentage differences in the models with the formulas (OR–aOR1)/(OR–1) and (aOR1–aOR2)/(aOR1–1). No interactions or multicollinearity were observed between independent variables. IBM SPSS Statistics for Windows v25  was used to perform the statistical analyses.n=183,698; 20.2%) were not born in Norway. The overall preterm birth rate for gestational age <37 weeks (i.e. extremely+very+late) was 5.3% . Overall, the preterm birth rate was highest among women with an unknown country of birth (7.7%), women born in South Asia (7.1%) and women born in East Asia Pacific/Oceania (6.6%). Among Norwegian-born women, the preterm birth rate was 5.3%.Maternal characteristics by gestational age at birth are shown in n=3429) for the study population. Extremely preterm rates were highest among women with an unknown country of birth (1.3%) and women born in sub-Saharan Africa  was 0.4%  was 1.2%  for the study population. Very preterm birth rates were highest among women with an unknown country of birth (1.9%) and women born in South Asia (1.7%). Compared to Norwegian-born women, we observed the greatest OR increases for very preterm birth among women with an unknown country of birth  and women born in South Asia  was 3.8%  in the study population. Late preterm birth rates were highest among women born in South Asia (4.9%) and East Asia Pacific/Oceania  among women from sub-Saharan Africa, South Asia and East Asia . Two stu13Our findings of increased late preterm birth risk among women born in South Asia and East Asia Pacific/Oceania are consistent with several prior studies assessing preterm birth before gestational week 37 in Norway ,16,17 anPreterm birth rate disparities among women born in different regions of the world who gave birth in Norway could not be explained by known maternal and obstetric risk factors. Our observation of an association between socio-economic factors and preterm birth fits well with the results of prior studies assessing associations between socio-economic factors  and preterm birth risk conducted in countries with social and health-care systems that are similar to those in Norway –22.Associations between maternal origin and preterm birth may differ in relation to risk factors related to immigrant status, country of origin and receiving country. Notably, content and timing of antenatal care has been associated with preterm birth . NorwegiThe mechanisms underlying the presently reported associations between maternal country of birth and preterm birth rates are unknown. Multiple factors may contribute. For example, preterm birth has been reported to be associated with some infections that have different incidence rates among women from different regions of the world , and somWith respect to limitations, potential registry data errors are possible. However, underreporting is the most likely type of error. Such underreporting does not cause false associations, but it could weaken statistical associations between variables and outcomes. Second, maternal medical histories of previous preterm births and infections are not registered in the MBRN. Therefore, we could not assess these risk factors as confounders.Maternal country of birth was associated with preterm birth among women giving birth in Norway, even after adjusting for socio-economic factors and well-known other maternal and obstetric factors. Compared to Norwegian-born women, women with an unknown country of birth and women born in sub-Saharan Africa were at increased risk for extremely preterm birth, whereas women born in South Asia were at increased risk for preterm birth in all gestational age groups. These results suggest that some immigrant women may benefit from targeted surveillance and interventions during pregnancy, such as cervical length measurements or progesterone administration during pregnancy.


It is known that neonates born by cesarean delivery (CD) may have higher referral rates than those born by vaginal delivery (VD) for newborn hearing screening (NHS). False-positive NHS results can increase costs and parental anxiety. This study analyzed the differences in NHS referral rates according to delivery methods in Level I, II, and III neonatal care units. A retrospective chart review was done for 2322 infants (4644 ears) with delivery records who underwent NHS between 2004 and 2017. The first NHS was performed immediately before discharge when the infant was in good condition via the automated auditory brainstem response (AABR) or automated otoacoustic emissions (AOAE). There were 98 neonates (196 ears) who underwent both AABR and AOAE simultaneously as the first NHS, 30 of which failed. We used a total of 4810 ears in this analysis. Of all enrolled ears, 2075 ears were of neonates born by CD, and 2735 ears were of neonates born by VD. A total of 2460 ears were from patients in Level III neonatal intensive care units (NICU) and 2350 ears were from Level I and II neonatal care units. The overall referral rate was higher in infants born via CD (4.5%) than VD (3.2%). In Level I and II neonatal intensive care units, the referral rate was significantly higher in those born via CD (3.0%) than via VD (1.4%). Further, based on the screening method, AABR (75.8%) was more frequently used than AOAE (24.2%), thereby revealing AABR’s higher referral rate in CD (2.9%) than in VD (1.2%). The referral rate of infants who underwent the NHS within three days of birth was higher in the CD group (3.0%) than in the VD group (1.3%). There was no significant difference in the referral rate depending on the delivery method when infants were hospitalized for more than four days or hospitalized in the NICU. The referral rate according to the delivery methods was significantly higher when the NHS test was performed for healthy newborns in the Level I and II neonatal care units born by CD within 72 h using AABR. Therefore, we recommend that the hearing screening test for newborns delivered by cesarean section be performed after 72 h of age. The results of this study may reduce the false-positive NHS results, unnecessary further tests, and parental anxiety. Early detection and intervention for newborn and infant hearing loss are crucial for age-appropriate language, communication, and cognitive development ,2,3. TheInternational and Korean NHS guidelines recommend that screening tests be performed from 34 weeks of gestational age and within one month of birth at the adjusted chronological age and 24–72 h after birth before discharge ,2,7,8. NCD is an important delivery method, especially in an emergency. Absolute maternal indications of CD include severe antepartum hemorrhage due to placenta previa or abruptio placentae, major cephalopelvic disproportion, transverse lie, and brow presentation . Fetal iParents may experience stress when NHS results are ‘referred’, and the false-positive NHS results incur economic burden as well as the cost of performing additional screening and confirmatory hearing tests. Existing guidelines and the literature recommend that NHS in infants born by CD be implemented at least 24–48 h after birth to allow external auditory canal debris to clear. Recently, due to medical advances and insurance issues, the maternal hospitalization period has been getting shorter. Earlier hearing screening tests may be attributed to shorter maternal hospital stays after delivery. As the rate of CD is increasing, it may not be possible to secure sufficient hospitalization time to reduce the NHS false-positive rate .The hospitalization period for newborns varies according to the neonatal care unit and characteristics of the newborn and accompanying diseases. In many countries, hospital-based neonatal care units are divided into different levels. A level I unit is referred to as a well newborn nursery, which provides basic neonatal care such as evaluation and postnatal care of healthy newborns and neonatal resuscitation. Level II includes specialty neonatal care of preterm infants with low-birth weight, resuscitation, and stabilization of preterm and ill-infants before transferring them to a neonatal intensive care unit (NICU) facility. Level III is the NICU for the subspecialty neonatal intensive care of infants who require mechanical ventilation, have undergone major surgery, or have severe congenital heart anomalies that require cardiopulmonary bypass . Since tThis study aimed to investigate the impact of delivery method  on the NHS referral rate in Level I and II neonatal care units and the Level III, NICU. We tried to analyze the factors associated with and the timing for an increased NHS pass rate in newborns born by CD.Long-term retrospective data were collected for 2322 infants hospitalized in the Hallym University Kangnam Sacred Heart Hospital with delivery records who had undergone NHS tests between 2004 and 2017. The first NHS was performed immediately before discharge if the infant was healthy with the automated auditory brainstem response (AABR)  or Automated Otoacoustic Emissions (AOAE) measurements . Two NHS devices were randomly used regardless of the neonatal level. In Level I and II neonatal care units, either AOAE or AABR was performed, and in Level III, AABR alone or AABR and AOAE were performed simultaneously. Since 2011, in Level III NICU newborns, we tried to perform two NHS tests simultaneously due to the possibility of auditory neuropathy, but this was not performed in all NICU newborns.AABR set a sound stimulus intensity of 35 dB nHL. A total of 98 neonates (196 ears) underwent both AABR and AOAE as the first NHS. For the total infants, 30 ears failed the NHS test due to their own problems, such as moving or crying. Therefore, a total of 4810 ears were included in this analysis. The results of the second and subsequent NHS results were excluded from this study.Eligible ears were divided into a VD group (2075 ears) and CD group (2735 ears). The following variables were obtained from the medical records of each group: NHS result (pass or refer), sex, birth weight, gestational weeks at birth, hospitalization location , admission duration, NHS days after birth, and NHS method (AABR or AOAE).All ears were classified into four subgroups according to gestational weeks and birth weight. The criterion gestational age of each subgroup was 35 weeks because AABR should be performed at least 34 weeks after birth based on the adjusted chronological age and the gestational age was ≥35 weeks per the criteria for discharge from the NICU by the Ministry of Health and Welfare . The birt-test. p-values < 0.05 were considered statistically significant.Quantitative variables such as birth weight and admission days were described by the number of non-missing values, mean, and standard deviation. Qualitative variables such as sex and NHS method were described with the number and percentage of ears. Missing values were not included in the calculation. All statistical analyses were performed using SPSS . Group comparison for qualitative data was performed by the Pearson chi-square test. For quantitative data, we used Student’s p > 0.05). The mean body weight at birth was 2.53 ± 0.86 kg. Birth weight was significantly lower in the CD group at 2.67 ± 0.81 kg than in the VD group, at 2.42 ± 0.88 kg (p < 0.0001). A total of 4810 ears were enrolled in this study. A total of 2075 ears (43.1%) were in the CD group, and 2735 ears (56.9%) in the VD group . Based op < 0.0001) (p < 0.05)  were admitted at the Level III, NICU, and a total of 1175 infants  were admitted at Level I and II neonatal care units, respectively. The proportion of CD in the Level III, NICU was significantly higher than that of Level I and II neonatal care units ( 0.0001) . For all < 0.05) .p = 0.003). On the other hand, the referral rates were not significantly different between two delivery methods in the other subgroups, such as ‘gestational weeks ≥35 and birth weight <2.9 kg’, ‘gestational weeks <35 and birth weight ≥2.9 kg’, and ‘gestational weeks <35 and birth weight <2.9 kg’ (p > 0.05) (p = 0.022)  and birth weight (≥2.9 kg or <2.9 kg), only the group of ‘≥35 weeks gestation and ≥2.9 kg birth weight’ had a significant difference in referral rate between the two delivery methods; the referral rate was significantly higher in the CD group (3.1%) than in the VD group (1.1%) ( > 0.05) . For all= 0.022) .p = 0.095). There were no differences in the referral rates in the AOAE cases  (p = 0.010)  . However= 0.010) .p = 0.007). However, the referral rates were not different in infants admitted into the NICU (5.8% in the CD group and 5.1% in the VD group (p > 0.05)  than in the VD group (1.4%) ( > 0.05) B.p = 0.035). However, the referral rate appeared to be higher in the CD group (3.1%), although it was not significantly different in the VD group (1.4%) among infants admitted in Level I and II neonatal care units who underwent the NHS more than four days after birth  in infants admitted in Level I and II neonatal care units who underwent the NHS within three days after birth than in the VD group (1.3%)  on the NHS referral rates among newborns born and admitted in Level I and II neonatal care units and Level III, NICU at a single university-based hospital. In this study, the rate of using AABR as an NHS test 75.8%) was higher than that of using AOAE 24.2%) for all enrolled infants. The reason for this is that the current international and Korean guidelines recommend the use of the AABR test, which has high specificity and sensitivity, for all neonates including newborns in the NICU, to avoid missing cases of auditory neuropathy ,2,8,15. 4.2% for % was higThe CD rate has been increasing worldwide ,17,18. TNeonates born by CD have higher NICU admission rates than those born by VD due to a high rate of respiratory morbidity, including respiratory distress syndrome or mild transient tachypnea, regardless of gestational age . Our resMany guidelines recommend the NHS test be performed at least 24 h after birth to decrease “false-positive” rates ,2,7,9. IOur study performed a subgroup analysis on newborns with over or below 35 weeks gestational age, considering the guidelines’ recommendations that newborns should be performed NHS with AABR test at the age of more than 34 gestational weeks. We also performed subgroup analysis on babies based on the 2.9 kg birth weights, which corresponds to the 25th percentile of the 2017 Korean National Growth Charts for children’s data . The resn = 560) or after 48 h (n = 566), this rate was significantly higher in the group tested within 48 h (20.5%) than in the group tested 48 h after birth (3.4%) [In a study comparing the referral rate between the first AOAE tested within 48 h (h (3.4%) . In our The rate of CD was higher in the NICU in our study, although the referral rates did not differ between babies born by CD or VD in babies admitted to the NICU. This may be because NICU babies typically stay in the hospital for more than three days, with mean hospital stays of 35.5 days in our study. Relatively long hospital stays allow the amniotic fluid or debris such as vernix caseosa to flow out from the ear canal. Transient otitis media can also be resolved during this time. These factors could be why there are no significant differences by the delivery method in reducing the high referral rate associated with CD. The high referral rate in babies born by CD in the Level I and II neonatal care units was noted in those who underwent the test within three days after birth in this study; however, the difference was not noted in babies in the Level I and II neonatal care units who underwent the test later than the fourth day after birth. Based on this result, we suggest that the optimal timing of NHS for babies in the WBN delivered by CD is at least 72 h after birth, a criterion longer than the previously recommended 24 or 48 h after birth.This study analyzed newborn babies delivered in a university-based hospital over 14 consecutive years. The limitations of our study were as follows. First, the number of babies who underwent NHS by the AOAE test was too small to evaluate the previously reported high referral rates associated with the AOAE test. Second, there were only some data regarding the second NHS results and formal confirmatory testing with diagnostic auditory brainstem response threshold test. We therefore could not calculate the false-positive rate. Further large-scale, multi-center studies will be needed to complement these limitations. However, this study can be meaningful to analyze the impact of the delivery methods on the referral rates of NHS, not only for the Level I and II neonatal care units, but also NICU, and to present the appropriate timing and circumstances to reduce the false-positive ‘refer’ results of the infants born through CD.In conclusion, the referral rate according to the delivery method was significantly higher when the NHS test was performed for newborns in Level I and II neonatal care units with CD within 3 days after birth using AABR. Therefore, we recommend that the hearing screening test for newborns delivered by cesarean section be performed after 72 h of age. The results of this study may help reduce the NHS false-positive, unnecessary testing, and parental anxiety.


These differences disappeared after adjusting for covariates (p = 0.489). Lower mean platelet counts in ROP infants are not directly related to ROP, but rather to the presence of other risk factors for ROP, such as culture-proven sepsis, blood transfusion and bronchopulmonary dysplasia.Platelets are a primary source of pro- and anti-angiogenic cytokines. However, the evidence of their role in retinopathy of prematurity (ROP) is controversial. This retrospective study aimed to compare mean weekly platelet counts between infants with and without ROP over the first 6 weeks of life. A total of 93 infants matched by gestational age and birth weight were recruited . Weekly mean platelet counts and other related risk factors were documented. The repeated measure analysis of variance (ANOVA) and the repeated measure analysis of covariance (ANCOVA) were used to compare mean platelet counts over time between the two groups, with and without adjusting for confounders. We found significant differences in the weekly mean platelet counts of infants with and without ROP over the first 6 weeks of life ( Retinopathy of prematurity (ROP) is a proliferative disorder of the retinal vasculature in premature infants. It is the leading cause of preventable blindness in children globally, with reported rates of blindness ranging from 10 to 40% ,3. The pTo date, the relationship between platelet counts and ROP remains poorly defined. Most studies observe an association between thrombocytopenia and ROP development or severity ,13,14, wThis was a retrospective study among preterm infants admitted to Hospital Universiti Sains Malaysia from September 2016 to December 2019. A total of 93 infants were included in this study. The study was approved by the Human Research Ethics Committee of Universiti Sains Malaysia (USM/JEPeM/18090441). The conduct of the study followed the tenets of the Declaration of Helsinki. Inclusion criteria included all premature infants with a gestational age of less than 32 weeks and a birth weight less than 1.5 kg. Infants with significant congenital abnormalities, infants with ocular defects and infants who died before their ROP status was known were excluded. Each ROP case was individually matched to two non-ROP cases (1:2), with birth weight within 100 g and gestational age within 1 week of the study subjects. Subjects with extremely small gestational age or birth weight who could not be matched were excluded. Subjects with individual or parental history of platelet-related diseases  were also excluded.Data collected included birth weight, gestational age, gender, ROP stage, treatment and weekly mean platelet cell count from birth to week 6 of life. ROP stages were categorized into five stages as follows: Stage 1—demarcation line, i.e., a thin line separating the avascular retina anteriorly from the vascularized retina posteriorly; Stage 2—ridge, a raised demarcation line with width and height; Stage 3—extraretinal fibrovascular proliferation, in which neovascularization extends from the ridge to the vitreous; Stage 4—partial retinal detachment, extrafoveal (Stage 4a) or foveal (Stage 4b); Stage 5—total retinal detachment, in which total retinal detachment may be exudative or tractional . AssociaSample size calculation was determined using G Power Software 2010. The calculation was based on the repeated measure ANCOVA, with an effect size of 0.25, alpha of 0.05 and power of 0.8. This provided a sample size of 74. By allowing for 20% missing data, the total sample size was 93. A 1:2 ratio was used as ROP is much less common than the absence of ROP in a normal population.t-test was used to determine the mean differences in numerical variables between the two groups. Forward stepwise multiple logistic regression was used to screen for confounding factors . Repeated measure analysis of variance (ANOVA) was performed to determine the mean differences in weekly platelet counts from birth to week 6 of life between infants with and without ROP. The mean platelet count was then adjusted for confounding factors identified during logistic regression using the repeated measure analysis of covariance (ANCOVA). The repeated measure ANCOVA between groups was used to compare intergroup differences in mean platelet counts at specific times, and repeated measure ANCOVA within–between groups was used to compare changes in mean platelet count across time between groups. A comparison of mean platelet counts between different stages of ROP was similarly performed.Statistical analyses were performed using IBM SPSS Statistics for Windows, Version 26.0 . A chi-square test was performed to determine the differences in categorical risk factors between infants with and without ROP. An independent A total of 93 infants were included in this study. The ROP group consisted of 31 infants and the group without ROP consisted of 62 infants. Of those with ROP, 8 (25.8%) had stage 1 ROP, 6 (19.3%) had stage 2 ROP, 16 (51.6%) had stage 3 ROP and only 1 (3.2%) had stage 4 ROP. The majority of these  required treatment. Other clinical characteristics of our study subjects are shown in In univariate analysis, mean birth weight , mean gestational age , amount of blood transfusion , duration of supplemental oxygenation , culture-proven sepsis  and bronchopulmonary dysplasia  were statistically significant risk factors for the development of ROP. However, multivariable analysis identified only blood transfusion , bronchopulmonary dysplasia  and culture-proven sepsis  as independent risk factors for ROP. p = 0.002), this significance was lost after adjusting for confounders (p = 0.489). The unadjusted and adjusted mean platelet count in each group is illustrated in p = 0.926 )  .Advances in neonatal care have contributed to improved survival of preterm infants, particularly in technologically developed regions ,19. The We observed that infants with ROP had significantly lower weekly unadjusted mean platelet counts from week 2 to week 6 of life, compared to their counterparts without ROP. Although this finding is consistent with the literature, limitations of previous approaches are that treating thrombocytopenia as a categorical variable  may be too general of an approach and that failure to adjust for the effect of other parameters on platelets may confound the results ,13,14. OThe change in mean platelet counts after adjustment may be attributed to the effect of the confounding factors  on ROP ,25,26,27Preterm infants often have immature hematopoietic systems with inefficient erythropoiesis. The frequent phlebotomies required in these infants place them at greater risk of requiring blood transfusions . Red bloIn bronchopulmonary dysplasia, anomalous lung development with altered alveolar microvasculature results in inefficient gas exchange ,40. In fPlatelet counts decrease within the first week of life and then increase over the next few weeks before they plateau. The increase in megakaryopoiesis is stimulated by increased thrombopoietin production during the first week of life . PlateleOur study’s findings may be extrapolated to similar populations, as we strictly adhered to guidelines for neonatal care, including policies for oxygen saturation monitoring, blood transfusion and ROP screening, and the mortality rate of the population of this study is comparable to that of other middle-income countries ,47. The Mean platelet counts over the first 6 weeks of life do not significantly differ between infants with and without ROP after adjusting for confounders. The lower mean platelet counts observed in ROP infants are attributed to the effect of ROP-associated factors, particularly culture-proven sepsis, blood transfusion and bronchopulmonary dysplasia. Clinicians should maintain a higher index of suspicion for ROP when screening premature infants with these risk factors.


In women with autoimmune rheumatic disorders (ARD), pregnancy complications or postpartum events are more frequent compared to the general population. Transplacental autoantibodies or cytokines influence various fetal and neonatal outcomes. We compared the growth patterns of babies born to mothers with ARD versus healthy mothers to assess the long-term growth outcomes of children born to women with ARD.This was a retrospective age-matched cohort analyses of babies born to mothers with ARD from the hospitals belonging to the Catholic University of Korea between 2010 and 2017. Demographic and autoimmune laboratory test data of the mothers and newborns were assessed. Neonatal growth was measured in terms of height and weight, measured at birth and follow-up examinations.We enrolled 142 infants from mothers with ARD and 149 infants from healthy mothers. There was no significant difference between mothers with ARD and healthy mothers in terms of delivery age, parity, abortion, and premature delivery history. The mothers with ARD were diagnosed with systemic lupus erythematosus (81%), Sjogren syndrome (6%), and other autoimmune phenomena (11%). The groups were significantly different in terms of neonatal characteristics such as prematurity, gestational age, birth weight, and height, but not in Apgar score and delivery type. For most neonates, autoimmune laboratory results were normalized within 1 year, except for anti-La/SSB antibody, which remained high in some. The height and weight for age z-score were lower than the normal age groups at birth but showed catch-up growth by 2 years of age.Low birthweight and prematurity at birth for neonates born to mothers with ARD could be caught up by 2 years of age, and maternal ARD does not affect the growth of their offspring. Autoimmune rheumatic disorders (ARD), including systemic lupus erythematosus (SLE), mostly affect women of childbearing age , 2. WomeIn women with ARD, higher pregnancy complications or postpartum events are more frequent compared to the general population , 5, 8. TChildren born small for gestational age (SGA) showed catch-up growth during the first 2 years of life, although premature SGA babies born under 32 weeks of gestation had a risk of not catching-up compared to full-term SGA babies , 13. SevIn this study, we compared the growth patterns of babies born to mothers with ARD versus healthy mothers to assess the long-term growth outcomes of children born to women with ARD.This was a retrospective cohort study investigating the growth outcomes of babies born from mothers with ARD compared to healthy women without any underlying diseases. The medical records were retrospectively reviewed, and demographic characteristics compared. The transplacental autoantibodies were assessed according to infant growth.The inclusion criteria for subjects were babies born from 1) mothers diagnosed with ARD during January 2010 to December 2017 at Seoul St. Mary’s Hospital and Yeouido St. Mary’s Hospital, and 2) gestational age-matched babies born from healthy women without any underlying diseases during the same period. A total of 291 neonates were enrolled as study participants; 142 infants born to mothers with ARD and 149 gestational age-matched babies from the 4,561 infants born to healthy mothers. The study was approved by the Institutional Review Board of the hospitals of the Catholic University of Korea (XC20WIDI0037K).Mothers with ARD were defined in this study using the International Classification of Disease (ICD-10) classification (P00.8) as ARD group. Gestational age-matched babies born to healthy mothers  during the study period were defined as a control group.Normal babies from healthy mothers were randomly selected according to gestational age matched cases for comparison with babies born to mothers with ARD. Babies that expired prior to 2 years of age from congenital condition such as genetic diseases and monogenic lupus were excluded from the study.Demographic data of mothers included age at delivery, parity, history of abortion and prematurity, and underlying disease in patients with autoimmune disorders. Newborn infants were compared for sex, prematurity, gestational age, delivery type, birth weight, birth height, and Apgar score at 1 and 5 min. We considered birth events significant if the Apgar score was less than 7 at 1 and 5 min. The babies from mothers with ARD were investigated for the immunological parameters several days after birth, including antinuclear antibody (ANA), anti-double stranded DNA antibody (Ab), anti-Ro/SSA Ab, anti-La/SSB Ab, C3 and C4 levels.Follow-up growth measurements of babies in both groups were retrieved at birth and at 1, 2, 5, 8, 12, and 24 months. At each time point, the age of premature infants was corrected for gestational age. Initial height and weight at birth and follow-up growth parameters were retrieved through the outpatient clinic setting when visits were made for routine child health examinations and vaccinations. Depending on the vaccination schedule, the measurement times varied from 1 − 2 months for each subject. Babies born to mothers with ARD were studied for follow-up autoantibody levels, if possible, at around 8 months of age. The growth parameters of premature babies were adjusted for corrected age. We calculated adjusted z-scores for postnatal weight and height of babies from both groups using the Korean National Growth Charts 2017 .P < 0.05.Statistical analyses were performed using SPSS  software . Student’s t-test was used to compare continuous variables, while the chi-square test was used to assess qualitative variables. The Cochran-Armitage trend test and linear mixed regression model were carried out to find the z-score differences at each time point. Statistical significance was set at The sex, maturity, gestational age, mean birth weight, mean birth height, delivery type, and Apgar scores of babies from the two groups were compared Table . There wTable The average (SD) age at delivery was 33.4 (3.28) years for mothers with ARD and 33.5 (4.2) years for healthy mothers. The parity , abortion history , and premature birth history  of the two groups showed no significant differences , 48 (5 months), 45 (8 months), 38 (12 months), and 22 (24 months), respectively.In comparison with Korean general population, the height-for-age z-score curve in ARD group is shown in Fig. Since the majority of maternal underlying disease was SLE (81%), we additionally compared growth parameters of babies born to mothers with SLE and other ARD group (data not shown). No significant differences in height and weight of babies of both subgroups, so we assessed the growth parameters of babies born to mothers with ARD including SLE.As maternal morbidity is known to influence fetal or neonatal outcomes , seriousIn our study, neonates born to mothers with ARD had a higher rate of prematurity and low birth weight and height. These results are consistent those of previous studies that investigated the perinatal outcomes in children of mothers with SLE , 6, 11. As the infants grew up, transplacental autoantibodies disappeared during the follow-up period, except for anti-La/SSB Ab. Although infants born to mothers with ARD had autoantibodies, including anti-Ro/SSA Ab, there were no neonatal lupus manifestations including congenital heart block in the neonatal screening or follow-up period. Anti-Ro/SSA and/or anti-La/SSB are known to contribute to congenital heart block or neonatal lupus development , 24, 25.In this study, among the enrolled mothers with ARD, some represented only positive autoantibodies, including ANA, anti-cardiolipin antibody, and anti-phospholipid antibody, even when they were diagnosed with ARD. Pregnancy represents a tolerating immune state due to paternal alloantigen presented by fetal tissue. Sex hormones and the placenta contribute to pregnancy maintenance by modifying T cell function, but changes in T cell immunity during pregnancy might be changed to produce autoantibodies . HoweverOur results suggest that catch-up growth in infants from ARD mothers took place around 2 years of age in comparison with a normal Korean baby. The z-scores of body weight and height progressively increased as the infants grew. Body weight increased up to 2 years of age in the present study. Lower body weight in infants born to mothers with ARD might be due to poor placental development and persistent clinical or subclinical inflammation with high levels of cytokines or autoantibody reaction –7. Body As our study included a relatively small number of subjects compared to other studies that assessed national data, further large scale studies are needed. Moreover, as we retrospectively reviewed patients’ charts, we were not able to obtain measurements at every time point for each neonate. Other developmental factors were not included in this study and require further investigation. We were unable to investigate more specific maternal demographics, such as disease activity and treatment received. The effect of maternal therapy on offspring’s growth development may provide more insight into the impact of maternal disease on neonatal outcomes , 22, 26.This study is the first longitudinal study to assess the growth parameters of infants born to mothers with ARD. Our results suggest that weight and height differences could be caught up by 2 years of age in children born from mothers with ARD, and most transplacental autoantibodies could be normalized as neonates grow up. This study favorably suggests that maternal ARD may not affect growth for up to 2 years.