Circumstances, causes and timing of death in extremely preterm infants admitted to NICU: The EPIPAGE-2 study

AIM

To describe the circumstances, causes and timing of death in extremely preterm infants.

METHODS

We included from the EPIPAGE-2 study infants born at 24-26 weeks in 2011 admitted to neonatal intensive care units (NICU). Vital status and circumstances of death were used to define three groups of infants: alive at discharge, death with or without withholding or withdrawing life-sustaining treatment (WWLST). The main cause of death was classified as respiratory disease, necrotizing enterocolitis, infection, central nervous system (CNS) injury, other or unknown.

RESULTS

Among 768 infants admitted to NICU, 224 died among which 89 died without WWLST and 135 with WWLST. The main causes of death were respiratory disease (38%), CNS injury (30%) and infection (12%). Among the infants who died with WWLST, CNS injury was the main cause of death (47%), whereas respiratory disease (56%) and infection (20%) were the main causes in case of death without WWLST. Half (51%) of all deaths occurred within the first 7 days of life, and 35% occurred within 8 and 28 days.

CONCLUSION

The death of extremely preterm infants in NICU is a complex phenomenon in which the circumstances and causes of death are intertwined.

Multi-parametric quantitative MRI reveals three different white matter subtypes

INTRODUCTION

Magnetic resonance imaging (MRI) shows slight spatial variations in brain white matter (WM). We used quantitative multi-parametric MRI to evaluate in what respect these inhomogeneities could correspond to WM subtypes with specific characteristics and spatial distribution.

MATERIALS AND METHODS

Twenty-six controls (12 women, 38 ±9 Y) took part in a 60-min session on a 3T scanner measuring 7 parameters: R1 and R2, diffusion tensor imaging which allowed to measure Axial and Radial Diffusivity (AD, RD), magnetization transfer imaging which enabled to compute the Macromolecular Proton Fraction (MPF), and a susceptibility-weighted sequence which permitted to quantify R2* and magnetic susceptibility (χm). Spatial independent component analysis was used to identify WM subtypes with specific combination of quantitative parameters values.

RESULTS

Three subtypes could be identified. t-WM (track) mostly mapped on well-formed projection and commissural tracts and came with high AD values (all p < 10(-18)). The two other subtypes were located in subcortical WM and overlapped with association fibers: f-WM (frontal) was mostly anterior in the frontal lobe whereas c-WM (central) was underneath the central cortex. f-WM and c-WM had higher MPF values, indicating a higher myelin content (all p < 1.7 10(-6)). This was compatible with their larger χm and R2, as iron is essentially stored in oligodendrocytes (all p < 0.01). Although R1 essentially showed the same, its higher value in t-WM relative to c-WM might be related to its higher cholesterol concentration.

CONCLUSIONS

Thus, f- and c-WMs were less structured, but more myelinated and probably more metabolically active regarding to their iron content than WM related to fasciculi (t-WM). As known WM bundles passed though different WM subtypes, myelination might not be uniform along the axons but rather follow a spatially consistent regional variability. Future studies might examine the reproducibility of this decomposition and how development and pathology differently affect each subtype.

Infant and dyadic assessment in early community-based screening for autism spectrum disorder with the PREAUT grid

Background

The need for early treatment of autism spectrum disorders (ASD) necessitates early screening. Very few tools have been prospectively tested with infants of less than 12 months of age. The PREAUT grid is based on dyadic assessment through interaction and shared emotion and showed good metrics for predicting ASD in very-high-risk infants with West syndrome.

Methods

We assessed the ability of the PREAUT grid to predict ASD in low-risk individuals by prospectively following and screening 12,179 infants with the PREAUT grid at four (PREAUT-4) and nine (PREAUT-9) months of age. A sample of 4,835 toddlers completed the Checklist for Autism in Toddlers (CHAT) at 24 months (CHAT-24) of age. Children who were positive at one screening (N = 100) were proposed a clinical assessment (including the Children Autism Rating Scale, a Developmental Quotient, and an ICD-10-based clinical diagnosis if appropriate) in the third year of life. A randomly selected sample of 1,100 individuals who were negative at all screenings was followed by the PMI team from three to five years of age to identify prospective false negative cases. The clinical outcome was available for 45% (N = 45) of positive children and 52.6% (N = 579) of negative children.

Results

Of the 100 children who screened positive, 45 received a diagnosis at follow-up. Among those receiving a diagnosis, 22 were healthy, 10 were diagnosed with ASD, seven with intellectual disability (ID), and six had another developmental disorder. Thus, 50% of infants positive at one screening subsequently received a neurodevelopmental diagnosis. The PREAUT grid scores were significantly associated with medium and high ASD risk status on the CHAT at 24 months (odds ratio of 12.1 (95%CI: 3.0–36.8), p < 0.001, at four months and 38.1 (95%CI: 3.65–220.3), p < 0.001, at nine months). Sensitivity (Se), specificity, negative predictive values, and positive predictive values (PPVs) for PREAUT at four or nine months, and CHAT at 24 months, were similar [PREAUT-4: Se = 16.0 to 20.6%, PPV = 25.4 to 26.3%; PREAUT-9: Se = 30.5 to 41.2%, PPV = 20.2 to 36.4%; and CHAT-24: Se = 33.9 to 41.5%, PPV = 27.3 to 25.9%]. The repeated use of the screening instruments increased the Se but not PPV estimates [PREAUT and CHAT combined: Se = 67.9 to 77.7%, PPV = 19.0 to 28.0%].

Conclusions

The PREAUT grid can contribute to very early detection of ASD and its combination with the CHAT may improve the early diagnosis of ASD and other neurodevelopmental disorders.