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Clinical Research 

Our products are developed based on extensive research in real-world population. We pride ourselves on a commitment to ongoing innovation, utilizing the most current knowledge to develop solutions that stand out for their excellence and relevance.

In crafting our products, we draw insights from the latest and most comprehensive studies available to date. Our approach harnesses the cutting-edge research conducted in Israel, leveraging its distinctive public health ecosystem that produces large-scale, real-world, and diverse population-based studies.

Published papers in peer-reviewed journals

link to JAMA Standardization of a Developmental Milestone Scale Using Data from children in israel

March 2022

The study conducted between 2014 and 2020 aimed to address the lack of strong normative data in developmental milestone assessments for children. Utilizing a population-based approach with 643,958 children aged 0 to 6 years, a new developmental scale was established - the Tipat Halav Israel Screening (THIS) Developmental Scale.

 

This scale, based on 3,774,517 developmental assessments, demonstrated high compatibility with other screening tests such as the Denver Developmental Screening Test II (67% match), the Alberta Infant Motor Scale (100% match), and the Centers for Disease Control and Prevention Developmental Assessment (53% match).

 

The study concludes that the THIS developmental scale, derived from the largest population evaluated to date, is recommended for further global evaluation due to its representation of a diverse, multicultural cohort.

link to article: assessing the attainment rates of updates cdc millstones using a new Israeli developmental scale

December 2022

The study aimed to compare a new Israeli evidence-based national developmental scale with the Centers for Disease Control and Prevention (CDC) checklists, focusing on nearly 4.5 million developmental assessments of 758,300 full-term born children aged 0 to 6 years.

 

In both the entire cohort (ALL-FT) and a subgroup of typically developing children (NORMAL-FT), 29 compatible milestones across gross motor, fine motor, language, and social domains were identified. The Israeli children consistently achieved these milestones earlier than the CDC-defined threshold age, with attainment rates exceeding 90% for 22 to 23 milestones.

 

The findings suggest that evidence-based analysis of developmental milestones can inform adjustments to developmental scales, offering potential for more personalized developmental surveillance.

link to article: a developmental surveillance score for quantitative monitoring of early childhood milestone attainment: algorithm development and validation.

March 2023

In this study, a new approach to developmental surveillance is introduced, aiming to provide a quantitative measure for tracking and monitoring child development.

 

The Developmental Surveillance Score (DSS) is presented as a simple-to-use tool that quantifies age-dependent severity levels of developmental milestone attainment, based on the Israeli developmental surveillance program.

 

The evaluation of the DSS on a nationwide cohort of over 1 million Israeli children (assessed between July 1, 2014, and September 1, 2021) revealed expected associations between developmental delays and known risk factors, such as preterm birth, gender, and maternal education levels.

 

Longitudinal analysis of the DSS trajectories for 294,000 children identified three main developmental patterns: children who successfully attain milestones, those who initially struggle but improve over time, and those whose difficulties tend to increase over time.

 

The DSS is proposed as a practical tool with potential applications in surveillance and research, offering insights into developmental trajectories. 

link to article: Early Prediction of Autistic Spectrum disorder using developmental surveillance data.

January 2024

This retrospective cohort study, spanning from January 1, 2014, to January 17, 2023, aimed to enhance early screening for autism spectrum disorder (ASD) by developing predictive models using routinely collected developmental surveillance data.

 

Analyzing data from 1,187,397 children assessed in nationwide maternal child health clinics, the study achieved fair accuracy in predicting ASD as early as 12 months of age.

 

A model combining longitudinal developmental milestone assessments and minimal demographic variables at 18 to 24 months demonstrated an area under the curve of 0.83, with 45.1% sensitivity and 95.0% specificity. Single-visit assessment models at the same age achieved an area under the curve of 0.81 with 41.2% sensitivity and 95.0% specificity.

 

These predictive models outperformed the Modified Checklist for Autism in Toddlers (M-CHAT) in similar studies, suggesting their potential seamless integration into clinical workflows for improved early identification and intervention for children at risk of ASD.

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