Mining Association Rules for Neurobehavioral and Motor Disorders in Children Diagnosed with Cerebral Palsy

10-year follow-up study found that motor-free intelligence quotient declined in children with mild to moderate cerebral palsy

Aim

This 10‐year follow‐up study examined cognitive change in a cohort of children with cerebral palsy from preschool to adolescence at the group and individual levels.

Methods

The Wechsler Preschool and Primary Scale of Intelligence was administered to 80 children with cerebral palsy (mean = 4 years 6 months, standard deviation = 7 months) at baseline (Time 1). At 10‐year follow‐up (Time 2), 28 adolescents (mean = 14 years 6 months, standard deviation = 9 months) returned for assessment with the Wechsler Intelligence Scale for Children. Motor‐free intelligence quotient (IQ) scores were calculated and paired‐samples t‐tests and the Reliable Change Index (RCI) were used to investigate change in IQ over time.

Results

At the group level, nonverbal IQ scores declined significantly. At the individual level, RCI indicated nine and 11 children showed a clinically significant decline in Full Scale IQ (FSIQ) and nonverbal IQ scores, respectively. Decline in FSIQ was related to a history of seizures whereas decline in nonverbal IQ was associated with higher initial IQ.

Conclusion

Cognitive abilities in children with cerebral palsy evolve over time and selective deficits may not be observable until a later age, highlighting the importance of repeated cognitive assessment throughout childhood and adolescence.

WISC-V motor-free cognitive profile and predictive factors in adolescents with cerebral palsy

BACKGROUND

The most commonly used intelligence tests - the Wechsler Scales - do not provide standardised procedures for assessing children with motor impairment, and as a result, may underestimate the intelligence quotient (IQ) of young people with CP.

AIMS

To characterise a motor-free cognitive profile of adolescents with CP using the Wechsler Intelligence Scale for Children - Fifth edition (WISC-V) and explore the influence of clinical factors on cognitive abilities.

METHODS AND PROCEDURE

The WISC-V was used to assess cognitive abilities in 70 adolescents (M = 14 years 6 months, SD = 10 months). Sixty-six adolescents (Gross Motor Function Classification System (GMFCS) Level I, n = 26 ; II, n = 23; III, n = 15; IV, n = 1; V, n = 1) obtained either a Motor-free IQ or index score using the motor-free method.

OUTCOMES AND RESULTS

MFIQ and index scores fell below the normative data and rates of borderline and impaired cognitive abilities were significantly higher in the CP group. Scores showed an uneven cognitive profile with a relative strength in verbal abilities. Severity of motor impairment and small for gestational age (SGA) were associated with lower IQ scores. A history of seizures was related to lower verbal abilities.

CONCLUSIONS AND IMPLICATIONS

Cognitive abilities of adolescents with CP are significantly below expectation compared to normative data. Severity of motor impairment, SGA, and seizures need to be recognised by health professionals as risk factors for cognitive impairment. A substantial proportion of adolescents showed borderline cognitive abilities, constituting a group with CP which are relatively neglected in the literature.

Neuropsychological profiles of children with cerebral palsy

PURPOSE

To explore factors contributing to variability in cognitive functioning in children with cerebral palsy (CP).

METHOD

A geographical cohort of 70 children with CP was assessed with tests of language comprehension, visual-spatial reasoning, attention, working memory, memory, and executive functioning. Mean age was 9;9 years (range 5;1-17;7), 54.3% were girls, and 50.0% had hemiplegic, 25.7% diplegic, 12.9% quadriplegic, and 11.4% dyskinetic CP. For the participants with severe motor impairments, assessments were adapted for gaze pointing. A cognitive quotient (CQ) was computed.

RESULTS

Mean CQ was 78.5 (range 19-123). Gross motor functioning, epilepsy, and type of brain injury explained 35.5% of the variance in CQ (F = 10.643, p = .000).

CONCLUSION

Twenty-four percent had an intellectual disability, most of them were children with quadriplegic CP. Verbal comprehension and perceptual reasoning scores did only differ for the 21% with an uneven profile, of whom two-thirds had challenges with perceptual reasoning.

A Review of Emerging Technologies for the Management of Diabetes Mellitus

OBJECTIVE

High prevalence of diabetes mellitus (DM) along with the poor health outcomes and the escalated costs of treatment and care poses the need to focus on prevention, early detection and improved management of the disease. The aim of this paper is to present and discuss the latest accomplishments in sensors for glucose and lifestyle monitoring along with clinical decision support systems (CDSSs) facilitating self-disease management and supporting healthcare professionals in decision making.

METHODS

A critical literature review analysis is conducted focusing on advances in: 1) sensors for physiological and lifestyle monitoring, 2) models and molecular biomarkers for predicting the onset and assessing the progress of DM, and 3) modeling and control methods for regulating glucose levels.

RESULTS

Glucose and lifestyle sensing technologies are continuously evolving with current research focusing on the development of noninvasive sensors for accurate glucose monitoring. A wide range of modeling, classification, clustering, and control approaches have been deployed for the development of the CDSS for diabetes management. Sophisticated multiscale, multilevel modeling frameworks taking into account information from behavioral down to molecular level are necessary to reveal correlations and patterns indicating the onset and evolution of DM.

CONCLUSION

Integration of data originating from sensor-based systems and electronic health records combined with smart data analytics methods and powerful user centered approaches enable the shift toward preventive, predictive, personalized, and participatory diabetes care.

SIGNIFICANCE

The potential of sensing and predictive modeling approaches toward improving diabetes management is highlighted and related challenges are identified.

icuARM-II: improving the reliability of personalized risk prediction in pediatric intensive care units

Clinicians in intensive care units (ICUs) rely on standardized scores as risk prediction models to predict a patient's vulnerability to life-threatening events. Conventional Current scales calculate scores from a fixed set of conditions collected within a specific time window. However, modern monitoring technologies generate complex, temporal, and multimodal patient data that conventional prediction models scales cannot fully utilize. Thus, a more sophisticated model is needed to tailor individual characteristics and incorporate multiple temporal modalities for a personalized risk prediction. Furthermore, most scales models focus on adult patients. To address this needdeficiency, we propose a newly designed ICU risk prediction system, called icuARM-II, using a large-scaled pediatric ICU database from Children's Healthcare of Atlanta. This novel database contains clinical data collected in 5,739 ICU visits from 4,975 patients. We propose a temporal association rule mining framework giving clinicians a potential to perform predict risks prediction based on all available patient conditions without being restricted by a fixed observation window. We also develop a new metric that can rigidly assesses the reliability of all all generated association rules. In addition, the icuARM-II features an interactive user interface. Using the icuARM-II, our results demonstrated showed a use case of short-term mortality prediction using lab testing results, which demonstrated a potential new solution for reliable ICU risk prediction using personalized clinical data in a previously neglected population.