INFANT Research Centre - Journal Articles

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Predicting admission to neonatal care unit at mid-pregnancy and delivery using data from a general obstetric population
(Springer Nature, 2024-10-17) Maher, Gillian M.; McKernan, Joye; O’Byrne, Laura; Walsh, Brian H.; Corcoran, Paul; Greene, Richard A.; Higgins, John R.; Khashan, Ali S.; McCarthy, Fergus P.; Health Research Board
Objectives: Development and validation of risk prediction models at mid-pregnancy and delivery to predict admission to the neonatal care unit. Methods: We used data from all singleton deliveries at Cork University Maternity Hospital (CUMH), Ireland during 2019. Admission to the neonatal care unit was assumed if length of stay in the unit was > 24 h. Multivariable logistic regression with backward stepwise selection was used to develop the models. Discrimination was assessed using the ROC curve C-statistic, and internal validation was assessed using bootstrapping techniques. We conducted temporal external validation using data from all singleton deliveries at CUMH during 2020. Results: Out of 6,077 women, 5,809 (95.6%) with complete data were included in the analyses. A total of 612 infants (10.54%) were admitted to the neonatal care unit for > 24 hours. Six variables were informative at mid-pregnancy: male infants, maternal smoking, advancing maternal age, maternal overweight/obesity, nulliparity and history of gestational diabetes (C-statistic: 0.600, 95% CI: 0.567, 0.614). Seven variables were informative at delivery: male infants, nulliparity, public antenatal care, gestational age < 39 weeks’, non-spontaneous vaginal delivery, premature rupture of membranes and time of birth between 17:01–07.59 h (C-statistic: 0.738, 95% CI: 0.715, 0.760). Using these predictors, we developed nomograms to calculate individualised risk of neonatal care unit admission. Bootstrapping indicated good internal performance and external validation suggested good reproducibility. Discussion: Our nomograms allow the user to quickly estimate individualised risk of neonatal care unit admission. Future research should aim to improve accuracy in early pregnancy to better assist counselling of parents.
Perinatal deaths in twin and singleton infants in Ireland: A comparison of characteristics and causes
(Springer Nature, 2024-11-04) O’Connor, Caroline; Leitao, Sara; Corcoran, Paul; O’Donoghue, Keelin; Irish Research Council
Introduction: Twin pregnancies are associated with significantly higher perinatal mortality (PM) rates compared to singletons, primarily due to complications like fetal growth restriction, preterm birth, and congenital anomalies. This study aimed to compare the characteristics associated with PM in twin pregnancies and compare maternal and obstetric factors and cause of death among twins and singletons in the Republic of Ireland. Materials and methods: Data spanning 2011 to 2022 from the National Perinatal Epidemiology Centre’s annual perinatal mortality clinical audit included 4494 perinatal deaths. Maternal characteristics, antenatal care factors and cause of death were analysed with relative risk calculated using national Hospital In-Patient Enquiry data. Pearson’s chi-squared tests studied the difference between mortality in twins and singletons. Results: Twins accounted for 10.4% of all perinatal deaths, despite representing only 3.6% of total births. The PM rate for twins was 17.3 per 1000 births, 3.1 times higher than for singletons. Early neonatal deaths (ENNDs) were more frequent in twins (54.2%), while stillbirths predominated among singletons (68.6%). Younger maternal age and lower BMI were associated with higher PM risks in twins. A considerable proportion of twin deaths with major congenital anomalies or birth before 28 weeks gestation occurred in non-tertiary hospitals, suggesting limitations in referral pathways to centres with appropriate neonatal expertise. Conclusion: Twin pregnancies pose a higher risk of perinatal mortality, particularly among younger mothers and preterm births. The findings highlight the need for updated guidelines that prioritise early risk assessment, targeted interventions, and improved referral systems.
A socio-cognitive perspective of knowledge integration in digital innovation networks
(Elsevier B.V., 2025) McCarthy, Stephen; O’Raghallaigh, Paidi; Kelleher, Carol; Adam, Frédéric; Science Foundation Ireland
Digital innovation is a complex process in which actors seek to create new value pathways by combining digital resources in a layered modular architecture. While IS scholarship has a rich tradition of research on developing and implementing digital artefacts within intra-organisational contexts, our understanding of knowledge integration across distributed innovation networks is nascent and under-theorised. This is an important area of research given the rising importance of digital innovation networks and the challenges faced in integrating specialised knowledge, especially given the greater diversity, speed, reach, and scope made possible by digital technologies. Drawing on in-depth case study findings from a health IoT project involving multiple organisations and disciplines, we explore how knowledge is integrated across boundaries during the initiation stage of a digital innovation network. Our findings point to boundaries related to the digital platform’s organising vision, resource allocation, delivery roadmap, technical architecture, and intellectual property, to name but a few challenges. We then reveal five socio-cognitive modes of knowledge integration which actors strategically enact to cross syntactic, semantic, and pragmatic boundaries: Signalling, Assembling, Contesting, Discounting, and Finalising. The choice of mode depends on the perceived knowledge status (‘what they know’) and social status (‘who they are’) of network actors, which highlight the salience of both social and cognitive dependencies for knowledge integration. We further discuss the contribution of design objects for overcoming differences and distinctions between specialist actors in a digital innovation network.
From early motor ability to global cognitive development 7 years after neonatal arterial ischemic stroke
(S. Karger AG, 2024) Giraud, Antoine; Garel, Pauline; Walsh, Brian; Chabrier, Stéphane; Région Auvergne-Rhône-Alpes
The developmental condition of children after neonatal arterial ischemic stroke (NAIS) is characterized by cognitive and motor impairments. We hypothesized that independent walking age would be a predictor of later global cognitive functioning in this population. Sixty-one children with an available independent walking age and full-scale intelligence quotient (IQ) score 7 years after NAIS were included in this study. Full-scale IQ was assessed using the fourth edition of the Wechsler Intelligence Scale for Children (WISC-IV). Independent walking age was negatively correlated with full-scale IQ score at 7 years of age (Pearson correlation coefficient of -0.27; 95% confidence interval from -0.48 to -0.01; p < 0.05). Early motor function is correlated with later global cognitive functioning in children after NAIS. Assessing and promoting early motor ability is essential in this population.
Determinants of receiving child protection and welfare services following initial assessment: A cross-sectional study from the Republic of Ireland
(Elsevier Ltd., 2024-05-13) O'Leary, Donna; Christie, Alistair; Perry, Ivan J.; Khashan, Ali S.; Irish Research Council; Child and Family Agency
Background: Children receive child protection and welfare services when an initial assessment concludes that their needs and care would be significantly compromised without intervention or support. Evidence is lacking on this decision to provide services in the Irish child protection and welfare system. Objective: To identify determinants of receiving services following an Initial Assessment. Participants and Setting: All children (n = 508) whose Initial Assessments were completed during the first quarter of 2016 in one of the four regions (spanning seven social work departments) of Tusla, the national Child and Family Agency. Methods: A cross-sectional study used data manually coded from social workers’ case records. Poisson regression analysis calculated incident rate ratios for receiving ongoing service, adjusting for demographic factors, family level and wider determinants of child welfare to investigate associations between predictor variables and the decision to provide services. Results: 38.5 % of children (n = 185) received ongoing child protection and welfare services. Risk factors for service provision included mother-perpetrated domestic violence (Incident Rate Ratio (IRR) 1.70 (95 % Confidence Interval (CI) 1.33, 2.19)), concerns about guidance and boundaries (IRR 1.66 (95 % CI 1.29, 1.14)), lack of emotional warmth (IRR 1.62 (95 % CI 1.30, 2.02)), prior abuse (IRR 1.59 (95 % CI 1.30, 1.95)), prior involvement (IRR 1.51 (95 % CI 1.15, 1.98)), intergenerational involvement (IRR 1.40 (95 % CI 1.10, 1.76)), health concerns (IRR 1.30 (95 % CI 1.07, 1.57)), and being aged 0–4 years (IRR 1.28 (95 % CI 1.03, 1.59)). Being reported by mandated professionals (IRR 0.71 (95 % CI 0.56, 0.90)), assessed by female social workers (IRR 0.72 (95 % CI 0.59, 0.89)), and, when separately examined, parental cooperation (IRR 0.64 (95 % CI 0.53, 0.77)) reduced the likelihood of receiving service. No differences were noted between departments. Conclusions: Service provision is largely driven by parental factors, prior involvement, and intergenerational abuse but gender disparities exist. Findings can be used to enhance decision strategies to improve outcomes for children and families.

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