Neonates

This protocol proposes a prospective observational study to develop and validate such a model, directly addressing a critical evidence gap identified by recent systematic reviews.

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.

Congenital heart disease (CHD) is a common condition affecting newborns that can be serious if not caught early. While echocardiograms are the best way to diagnose CHD, they are not always immediately available. Chest X-rays are widely available and are often the first test used when a newborn has breathing problems, a heart murmur, or a bluish skin tint. The purpose of this study is to determine how accurate standard chest X-rays are at finding congenital heart disease in newborns. Researchers will observe 60 newborns (up to 28 days old) admitted to the Neonatal Intensive Care Unit (NICU) who have signs or symptoms that suggest they might have a heart problem. Each baby in the study will receive a standard chest X-ray within 24 hours of their clinical presentation. Within 72 hours, they will also receive an echocardiogram, which is the standard, definitive test used to confirm if there is a heart defect. By comparing the initial chest X-ray results to the final echocardiogram results, researchers hope to figure out exactly which X-ray patterns are best at predicting specific heart diseases. This could help doctors make faster decisions about treating newborns, potentially reducing delays in diagnosis and improving care.

Background: Hypoxic-ischemic encephalopathy (HIE) is a neurological condition caused by poor oxygenation during the peripartum period. The main strategy to mitigate neurological damage is hypothermic therapy (HT), whose effectiveness-among other factors-depends on adequate pain management. Considering the prevalence of allodynia in this group of patients, routine nursing procedures can become sources of additional stress and pain. Music therapy is used in this population to promote self-regulation and relaxation, and may therefore help reduce pain levels after routine nursing procedures. Research question: What is the effect of an entrainment-based live music therapy intervention on pain levels in newborns with hypoxic-ischemic encephalopathy undergoing hypothermic therapy after routine nursing procedures? Methodology: A randomized, crossover pilot and feasibility study. Participants will be 22 newborns admitted to the Neonatal Intensive Care Unit (NICU) of the University Hospital Fundación Santa Fe de Bogotá. Participants will receive standard care plus a 15-minute live music therapy session after a routine nursing procedure, or standard care alone. The primary outcome is the Premature Infant Pain Profile-Revised (PIPP-R) scale, which will be assessed through video recordings. Secondary outcomes are vital signs, heart rate variability, and electroencephalography (EEG) recordings. Expected outcomes: Through this study, the aim is to improve the comfort and well-being of patients with HIE during TH. In addition, the safety and feasibility of music therapy in this population will be evaluated, seeking to contribute to current knowledge about the mechanisms of music therapy.

The aims of this study were to investigate underlying diseases associated with neonatal DIC diagnosed on the first 28 days of life, and whether DIC score could predict mortality in neonates.