Improving Artificial Intelligence-derived Algorithms for Estimating Length and Weight in NEonateS and infanTs up to 6 Months of Age
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 60
- 试验地点
- 1
- 主要终点
- To evaluate the accuracy of the algorithm to estimate length (in cm)
研究概览
简要总结
The NEST study is a prospective, observational research study designed to collect clinical measurements and image data to develop and evaluate artificial intelligence (AI)-derived algorithms for estimating anthropometric parameters in neonates and young infants. The study focuses on infants from birth up to 6 months of age and aims to assess the accuracy of AI-based estimations of length, weight, and head circumference using photographs and/or video recordings captured during routine clinical care. These AI-derived measurements will be compared against standard clinical measurements obtained by trained healthcare professionals in neonatal and infant care settings.
详细描述
The NEST study is a prospective, observational cohort study designed to collect paired clinical reference measurements, image data, and associated clinical information to support the development and proof-of-concept evaluation of artificial intelligence (AI)-based algorithms for estimating anthropometric parameters in neonates and young infants.
Standard clinical anthropometric measurements-including infant length, weight, and head circumference-are obtained by trained healthcare professionals in accordance with site-standard clinical procedures and established neonatal measurement practices. These measurements serve as the clinical reference standard for comparison with AI-derived estimates. All reference measurements collected as part of routine clinical care during the study period may be recorded.
In parallel with clinical measurements, non-invasive image data consisting of two-dimensional photographs and/or video recordings of the infant are captured using digital imaging devices. Image capture occurs under real-world clinical conditions and does not require additional physical contact beyond routine care. Image and video data may be collected at multiple timepoints for a given participant, including repeated assessments during hospitalization or follow-up, where applicable. Image-based measurements are not used for clinical decision-making.
AI-derived estimates are compared against standard clinical reference measurements using predefined analytical accuracy and agreement metrics.
Secondary and exploratory objectives include the evaluation of AI models for additional anthropometric parameters, such as weight and head circumference, as well as assessment of the feasibility of image capture in neonatal and infant care settings. Investigator- and parent-reported perceptions related to the usability and acceptability of image-based measurement approaches are also evaluated.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 0 Days 至 6 Months（Child）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Infants up from birth up to 6 months of postnatal age (including neonates) who have been admitted to the NICU or SCN at the time of screening
- •Parent(s) should be able to comprehend the content of the study and be willing for their child to undergo video and photo recording, and to allow access to their blood sampling results (haemoglobin) taken as part of standard clinical practice
- •Written consent from parents and/or legally acceptable representative
排除标准
- •Infants who were born with gestational age of less than 28 weeks of gestational age
- •Infants who are intubated (i.e., endotracheal, nasotracheal intubation) at the time of screening
- •The investigator considers for any reason that the participant would not be suitable for the study
- •The participant has an existing medical condition that would prevent standardised measurement of length and/or head circumference e.g. structural abnormality of the lower limbs, orthopaedic conditions, hydrocephalus
- •Employees and/or children/family members or relatives of employees of Danone Global Research & Innovation Center, Danone Asia Pacific Holdings Pte Ltd, or the participating site
研究组 & 干预措施
Very preterm infants, moderate to late preterm infants, and term infants
This cohort includes neonates and infants from birth up to 6 months of age, encompassing very preterm (28-31 weeks gestation), moderate to late preterm (32-36 weeks gestation), and term infants (≥37 weeks gestation). Participants are enrolled prospectively during their stay in neonatal or infant care settings. This is an observational study; no investigational product or therapeutic intervention is administered. Study procedures involve the collection of routine clinical anthropometric measurements (length, weight, and head circumference) and the capture of photographs and/or video recordings for the development and evaluation of artificial intelligence-derived algorithms. All data are collected in conjunction with standard clinical care.
结局指标
主要结局
To evaluate the accuracy of the algorithm to estimate length (in cm)
时间窗: From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks
The primary outcome is the proof-of-concept accuracy of an artificial intelligence (AI)-based algorithm for estimating infant length in a neonatal intensive care unit (NICU) or special care nursery (SCN) setting. AI-derived length estimates (in centimeters) obtained from supine images and/or videos are compared with standard clinical length measurements performed by trained investigators using World Health Organization (WHO)-recommended techniques. Accuracy is evaluated using a composite metric that includes bias, mean absolute error, mean absolute percentage error, and the distribution of absolute percentage errors at predefined thresholds.
次要结局
- To evaluate the mean absolute error of the algorithm to estimate weight (in kg)(From enrolment (after informed consent) until discharge from NICU/SCN, up to a maximum of 10 weeks)