Prediction of long-term neurodevelopmental outcome in preterm infants using trajectories of general movement assessments

Automated Prediction of Infant Cognitive Development Risk by Video: A Pilot Study

OBJECTIVE

Cognition is an essential human function, and its development in infancy is crucial. Traditionally, pediatricians used clinical observation or medical imaging to assess infants' current cognitive development (CD) status. The object of pediatricians' greater concern is however their future outcomes, because high-risk infants can be identified early in life for intervention. However, this opportunity has not yet been realized. Fortunately, some recent studies have shown that the general movement (GM) performance of infants around 3-4 months after birth might reflect their future CD status, which gives us an opportunity to achieve this goal by cameras and artificial intelligence.

METHODS

First, infants' GM videos were recorded by cameras, from which a series of features reflecting their bilateral movement symmetry (BMS) were extracted. Then, after at least eight months of natural growth, the infants' CD status was evaluated by the Bayley Infant Development Scale, and they were divided into high-risk and low-risk groups. Finally, the BMS features extracted from the early recorded GM videos were fed into the classifiers, using late infant CD risk assessment as the prediction target.

RESULTS

The area under the curve, recall and precision values reached 0.830, 0.832, and 0.823 for two-group classification, respectively.

CONCLUSION

This pilot study demonstrates that it is possible to automatically predict the CD of infants around the age of one year based on their GMs recorded early in life.

SIGNIFICANCE

This study not only helps clinicians better understand infant CD mechanisms, but also provides an economical, portable and non-invasive way to screen infants at high-risk early to facilitate their recovery.

Predictive value of General Movements Assessment for developmental delay at 18 months in children with complex congenital heart disease

BACKGROUND

Infants with complex congenital heart disease are at increased risk of impaired fetal brain growth, brain injury, and developmental impairments. The General Movement Assessment (GMA) is a valid and reliable tool to predict cerebral palsy (CP), especially in preterm infants. Predictive properties of the GMA in infants with complex congenital heart disease (CCHD) are unknown.

AIM

To evaluate predictive properties of the GMA to predict developmental outcomes, including cerebral palsy (CP), at 18-months corrected age (CA) in children with CCHD undergoing heart surgery in the first month of life.

METHODS

A prospective cohort of 56 infants with CCHD (35 males, 21 females) was assessed with GMA at writhing age (0-6 weeks CA) and fidgety age (7-17 weeks CA) and the Bayley Scales of Infant Development at 18 months. GMA focused on markedly reduced GM-variation and complexity (definitely abnormal (DA) GM-complexity) and fidgety movements. Predictive values of GMA for specific cognitive, language and motor delay (composite scores <85th percentile) and general developmental delay (delay in all domains) were calculated at 18 months.

RESULTS

At fidgety age, all infants had fidgety movements and no child was diagnosed with CP. DA GM-complexity at fidgety age predicted general developmental delay at 18 months (71 % sensitivity, 90 % specificity), but predicted specific developmental delay less robustly. DA GM-complexity at writhing age did not predict developmental delay, nor did it improve prediction based on DA GM-complexity at fidgety age.

CONCLUSIONS

In infants with CCHD and fidgety movements, DA GM-complexity at fidgety age predicted general developmental delay.

A biopsychosocial model of NICU family adjustment and child development

BACKGROUND

Although infants in Neonatal Intensive Care Units (NICU) are at risk for developmental impairments and parents are at risk for emotional distress, factors that explain outcomes remain unknown. Here, we developed the first biopsychosocial model to explain family adjustment after NICU discharge.

METHODS

Participants included 101 families at The Children's Hospital of Philadelphia Neonatal Follow-Up Program who had been discharged 1.5-2.5 years prior. We gathered data using validated assessments, standardized assessments, and electronic medical records.

RESULTS

Our structural equation model, informed by the Double ABC-X Model, captured the dynamic relationships among infant, parent, couple, and family factors. Infant medical severity, posttraumatic stress, couple functioning, and family resources (e.g., time, money) were key for family adjustment and child development.

CONCLUSIONS

Interventions that target parental posttraumatic stress, couple dynamics, parental perception of time for themselves, and access to financial support could be key for improving NICU family outcomes.

Automated Movement Analysis to Predict Cerebral Palsy in Very Preterm Infants: An Ambispective Cohort Study

The General Movements Assessment requires extensive training. As an alternative, a novel automated movement analysis was developed and validated in preterm infants. Infants < 31 weeks’ gestational age or birthweight ≤ 1500 g evaluated at 3−5 months using the general movements assessment were included in this ambispective cohort study. The C-statistic, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for a predictive model. A total of 252 participants were included. The median gestational age and birthweight were 274/7 weeks (range 256/7−292/7 weeks) and 960 g (range 769−1215 g), respectively. There were 29 cases of cerebral palsy (11.5%) at 18−24 months, the majority of which (n = 22) were from the retrospective cohort. Mean velocity in the vertical direction, median, standard deviation, and minimum quantity of motion constituted the multivariable model used to predict cerebral palsy. Sensitivity, specificity, positive, and negative predictive values were 55%, 80%, 26%, and 93%, respectively. C-statistic indicated good fit (C = 0.74). A cluster of four variables describing quantity of motion and variability of motion was able to predict cerebral palsy with high specificity and negative predictive value. This technology may be useful for screening purposes in very preterm infants; although, the technology likely requires further validation in preterm and high-risk term populations.

Early prediction of neurodevelopmental outcomes at 12 years in children born extremely preterm

BACKGROUND

Extremely preterm (EPT) birth is a major risk factor for neurodevelopmental impairments. The aim was to evaluate the predictive value of Prechtl General Movement Assessment (GMA), including the Motor Optimality Score-Revised (MOS-R), at 3 months corrected age (CA) for adverse neurodevelopmental outcome at the age of 12 years.

METHODS

The GMA, including the MOS-R, was applied at 3 months CA and outcomes were assessed at 12 years by Touwen's neurological examination, the Movement Assessment Battery for Children-2, and chart reviews.

RESULTS

Fifty-three infants born EPT (33 boys, mean GA 25 weeks, mean body weight 805 ± 156 g) were included. Forty-two (79%) children participated in the follow-up (mean age 12.3 ± 0.4) and 62% of these had adverse outcomes. The MOS-R differed between groups (p = 0.007). The respective predictive values of GMA, aberrant FMs, and the MOS-R cut-off of 21 for adverse outcomes were positive predictive values (PPVs) of 1.00 and 0.77, negative predictive value of 0.47 and 0.63, sensitivity of 0.31 and 0.77, and specificity of 1.00 and 0.77.

CONCLUSIONS

Using the Prechtl GMA, including the MOS-R, at 3 months CA predicted an overall adverse neurodevelopment at 12 years, with a high PPV, specificity, and sensitivity in children born EPT.

IMPACT

The Prechtl GMA, including the MOS-R, can improve early identification of long-term adverse neurodevelopmental outcomes. This is the first study to investigate the predictive value of the MOS-R for neurodevelopmental outcome at mid-school age in children born EPT. Using the GMA, including the MOS-R, is suggested as one important part of the neurological assessment at 3 months CA in children born EPT. Aberrant FMs in combination with a MOS of <21 is an indicator of an increased risk of future adverse neurodevelopment in children born EPT.

Automated movement analysis to predict motor impairment in preterm infants: a retrospective study

OBJECTIVE

To apply automated movement analysis to the general movements assessment (GMA) to build a predictive model for motor impairment (MI).

STUDY DESIGN

A retrospective cohort study including infants ≤30^6/7 weeks GA or BW ≤1500 g seen at 3-5 months was conducted. Automated video analysis was used to develop a multivariable model to identify MI, defined as Bayley motor composite score <85 or cerebral palsy (CP).

RESULTS

One hundred and fifty two videos were analyzed. Median GA and BW were 27^5/7 weeks and 955 g, respectively. MI and CP rates were 22% (N = 33) and 14% (N = 22). Minimum, mean, and mean vertical velocity of the infant's silhouette correlated significantly with MI. Sensitivity, specificity, positive and negative predictive values, and accuracy of automated GMA were 79%, 63%, 37%, 91%, and 66%, respectively. C-statistic indicated good fit (C = 0.77).

CONCLUSIONS

Automated movement analysis predicts MI in preterm infants. Further refinement of this technology is required for clinical application.

Motor and Postural Patterns Concomitant with General Movements Are Associated with Cerebral Palsy at Term and Fidgety Age in Preterm Infants

General movements (GMs) in combination with neurological examination and magnetic resonance imaging at term age can accurately determine the risk of cerebral palsy. The present study aimed to assess whether 11 motor and postural patterns concomitant with GMs were associated with cerebral palsy. Video recordings performed after birth in 79 preterm infants were reviewed retrospectively. Thirty-seven infants developed cerebral palsy at 2 years corrected age and the remaining 42 showed typical development. GMs were assessed from preterm to fidgety age and GM trajectories were defined. The 11 motor and postural patterns were evaluated at each age and longitudinally, alone and in combination with GM trajectories. A logistic regression model was used to assess the association between GMs, concomitant motor and postural patterns, and cerebral palsy. We confirmed that high-risk GM trajectories were associated with cerebral palsy (odds ratio = 44.40, 95% confidence interval = 11.74-167.85). An association between concomitant motor and postural patterns and cerebral palsy was found for some of the patterns at term age and for all of them at fidgety age. Therefore, at term age, concomitant motor and postural patterns can support GMs for the early diagnosis of cerebral palsy.