Factors Associated with Increased Risk of Early Severe Neonatal Morbidity in Late Preterm and Early Term Infants

Mengistu, Tesfaye S; Schreiber, Veronika; Flatley, Christopher; Fox, Jane; Kumar, Sailesh

doi:10.3390/jcm10061319

Cited by 10 publications

(19 citation statements)

References 45 publications

(58 reference statements)

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“…Several studies have demonstrated that maternal factors (such as sociodemographic factors, obesity, smoking, and hypertension) and neonatal factors (lower birth weight and earlier gestational age) are associated with neonatal morbidity and mortality. [13][14][15][16][17] Recognizing that maternal factors directly impact neonatal outcomes and that maternal risk systems are being adopted in clinical practice, we sought to determine if a single-risk stratification system could be used for both maternal and neonatal outcomes. Our findings supported our initial hypothesis and are consistent with prior studies that earlier gestational age and lower birth weight are associated with a higher risk of adverse neonatal outcome.…”

Section: Discussionmentioning

confidence: 99%

“…Our findings supported our initial hypothesis and are consistent with prior studies that earlier gestational age and lower birth weight are associated with a higher risk of adverse neonatal outcome. 14,15,17 Among neonates born at term gestation and those at low risk for complication, maternal risk scores constructed for maternal morbidity appear to provide little to no additional information on neonatal risk of low Apgar.…”

Section: Discussionmentioning

confidence: 99%

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Performance of a Maternal Risk Stratification System for Predicting Low Apgar Scores

Kishkovich,

James,

McCoy

et al. 2024

Am J Perinatol

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Objective: Maternal risk stratification systems are increasingly employed in predicting and preventing obstetric complications. These systems focus primarily on maternal morbidity, and few tools exist to stratify neonatal risk. We sought to determine if a maternal risk stratification score was associated with neonatal morbidity. Study Design: Retrospective cohort study of patients with liveborn infants born at ≥24 weeks at four hospitals in one health system between 1/1/2020-12/31/2020. The Expanded Obstetric Comorbidity Score (EOCS) used as the maternal risk score. The primary neonatal outcome was 5-minute Apgar <7. Logistic regression models determined associations between EOCS and neonatal morbidity. Secondary analyses were performed, including stratifying outcomes by gestational age and limiting analysis to “low-risk” term singletons. Model discrimination assessed using the area under the receiver operating characteristic curves (AUC) and calibration via calibration plots. Results: 14,497 maternal-neonatal pairs were included. 236 (1.6%) had 5-minute Apgar <7. EOCS were higher in 5-minute Apgar <7 group (median 41 vs. 11, p<0.001). AUC for EOCS in predicting Apgar <7 was 0.72 (95% CI 0.68, 0.75), demonstrating relatively good discrimination. Calibration plot revealed that those in the highest EOCS decile had higher risk of neonatal morbidity (7.6% vs. 1.7%, p<0.001). When stratified by gestational age, discrimination weakened with advancing gestational age: AUC 0.70 for <28 weeks, 0.63 for 28-31 weeks, 0.64 for 32-36 weeks, and 0.61 for ≥37 weeks. When limited to term low-risk singletons, EOCS had lower discrimination for predicting neonatal morbidity and was not well calibrated. Conclusions: A maternal morbidity risk stratification system does not perform well in most patients giving birth, at low risk for neonatal complications. The findings suggest the association between EOCS and 5-minute Apgar <7 likely reflects a relationship with prematurity. This study cautions against intentional or unintentional extrapolation of maternal morbidity risk for neonatal risk, especially for term deliveries.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Performance of a Maternal Risk Stratification System for Predicting Low Apgar Scores

Kishkovich,

James,

McCoy

et al. 2024

Am J Perinatol

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“…The prevalence of most neonatal diseases in infants in the NICU in Xiangxi significantly increased with decreased gestational age, especially jaundice. In addition, the delivery method of pregnancy had significant impact on neonatal disease (30). The prevalence of CD was significantly higher than that of VD (31).…”

Section: Discussionmentioning

confidence: 99%

The Disease Spectrum and Influencing Factors of NICU in Xiangxi, Underdeveloped Area of China: A 9-Year Retrospective Study

et al. 2022

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ObjectiveInvestigation of the basic conditions and disease spectrum in neonatal intensive care unit (NICU) from 2012 to 2020, in the underdeveloped area of Xiangxi, China.MethodsAll newborns (N = 16,094) admitted to the NICU of a hospital in the Xiangxi area from 2012 to 2020 were selected for the retrospective study.ResultsThe average male/female ratio was 1.43:1, with 9,482 males and 6,612 females admitted to the NICU. The sample comprised 41.02% premature infants, and 56.52% had been delivered via cesarean delivery (CD). The most prevalent diseases diagnosed in the NICU were jaundice (22.01%), respiratory (18.45%) and neurological diseases (17.54%). Over the 9-year study window, the prevalence of jaundice and cardiovascular diseases increased, while respiratory and neurological diseases became less frequent. The prevalence of the remaining diseases remained unchanged. Prevalence of neonatal diseases is influenced by gender, patient sources, delivery methods, gestational age and birth weight (P < 0.05). The prevalence of neonatal diseases was significantly higher in males, infants born via CD, and in infants of lower gestational age and birth weight.ConclusionThe study contributes in-depth information about infant characteristics in an NICU in an undeveloped region of China. In the past 9 years, the average proportion of premature infants in the NICU decreased to 37.38% in 2020, but this figure remains higher than the Chinese national average of 26.2%. Similarly, the CD rate is higher than the Chinese average. The spectrum of neonatal diseases in the NICU in Xiangxi area is drawn, included jaundice, respiratory and neurological diseases, primarily. Through statistical analysis, it is found that the types and prevalence of neonatal diseases are closely related to different gender, gestational age, patient sources, delivery methods, and birth weight (P < 0.05). Newborns of specific gestational age, birth weight and delivery method should be considered “at-risk” and targeted in the formulation of preventive measures. There is a great need to improve the diagnosis and treatment of neonatal diseases—and perinatal health care in general—to ensure improved outcomes for newborns admitted to NICUs in underdeveloped regions.

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“…[2][3][4] Several factors are impacted in adverse neonatal outcomes, although few studies have examined factors specifically associated with SNM. [5][6][7] Misra and colleagues (2003) proposed a multiple determinants framework for conceptualizing the complex relationships that influence perinatal (including neonatal) health, 8 and implicate interrelated distal social environmental factors (e.g., socioeconomic status, ethnicity), proximal biomedical (e.g., chronic diseases) and behavioural (e.g., smoking) responses, and intermediate diseases and pregnancy complications in the pathways to poor outcomes.…”

Section: Introductionmentioning

confidence: 99%

Disparities in severe neonatal morbidity and mortality between Aboriginal and non-Aboriginal births in Western Australia: a decomposition analysis

Adane

Bailey

Marriott

et al. 2021

J Epidemiol Community Health

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BackgroundThe health disadvantages faced by Australian Aboriginal peoples are evidenced in early life, although few studies have focused on the reasons for population-level inequalities in more severe adverse outcomes. This study aimed to examine the scale of disparity in severe neonatal morbidity (SNM) and mortality between Aboriginal and non-Aboriginal births and quantify the relative contributions of important maternal and infant factors.MethodA retrospective cohort study with singleton live births (≥32 weeks’ gestation) was conducted using Western Australia linked whole population datasets, from 1999 to 2015. Aboriginal status was determined based on the mothers’ self-reported ethnic origin. An Australian validated indicator was adapted to identify neonates with SNM. The Oaxaca-Blinder method was employed to calculate the contribution of each maternal and infant factor to the disparity in SNM and mortality.ResultsAnalyses included 425 070 births, with 15 967 (3.8%) SNM and mortality cases. The disparity in SNM and mortality between Aboriginal and non-Aboriginal births was 2.9 percentage points (95% CI 2.6 to 3.2). About 71% of this gap was explained by differences in modelled factors including maternal area of residence (23.8%), gestational age (22.2%), maternal age (7.5%) and antenatal smoking (7.2%).ConclusionsThere is a considerable disparity in SNM and mortality between Aboriginal and non-Aboriginal births in Western Australia with the majority of this related to differences in maternal sociodemographic factors, antenatal smoking and gestational age. Public health programmes targeting these factors may contribute to a reduction in early life health differentials and benefit Aboriginal population health through the life course.

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Factors Associated with Increased Risk of Early Severe Neonatal Morbidity in Late Preterm and Early Term Infants

Cited by 10 publications

References 45 publications

Performance of a Maternal Risk Stratification System for Predicting Low Apgar Scores

Performance of a Maternal Risk Stratification System for Predicting Low Apgar Scores

The Disease Spectrum and Influencing Factors of NICU in Xiangxi, Underdeveloped Area of China: A 9-Year Retrospective Study

Disparities in severe neonatal morbidity and mortality between Aboriginal and non-Aboriginal births in Western Australia: a decomposition analysis

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