Néonatalogie | EPFL Graph Search

Neonatology is a subspecialty of pediatrics that consists of the medical care of newborn infants, especially the ill or premature newborn. It is a hospital-based specialty and is usually practised in neonatal intensive care units (NICUs). The principal patients of neonatologists are newborn infants who are ill or require special medical care due to prematurity, low birth weight, intrauterine growth restriction, congenital malformations (birth defects), sepsis, pulmonary hypoplasia, or birth asphyxia. Though high infant mortality rates were recognized by the medical community at least as early as the 1860s, advances in modern neonatal intensive care have led to a significant decline in infant mortality in the modern era. This has been achieved through a combination of technological advances, enhanced understanding of newborn physiology, improved sanitation practices, and development of specialized units for neonatal intensive care. Around the mid-19th century, the care of newborns was in its infancy and was led mainly by obstetricians; however, the early 1900s, pediatricians began to assume a more direct role in caring for neonates. The term neonatology was coined by Dr. Alexander Schaffer in 1960. The American Board of Pediatrics established an official sub-board certification for neonatology in 1975. In 1835, the Russian physician Georg von Ruehl developed a rudimentary incubator made from two nestled metal tubs enclosing a layer of warm water. By the mid-1850s, these "warming tubs" were in regular use at the Moscow Foundling Hospital for the support of premature infants. 1857, Jean-Louis-Paul Denuce was the first to publish a description of his own similar incubator design, and was the first physician to describe its utility in the support of premature infants in medical literature. By 1931, Dr. A Robert Bauer added more sophisticated upgrades to the incubator which allowed for humidity control and oxygen delivery in addition to heating capabilities, further contributing to improved survival in newborns.

Evaluation and extension of an automated system to diagnose the health of premature babies

Camille Joggi

Premature babies are not fully equipped to deal with the outside world. Their immature bodies make them highly at risk to a large number of physiological complications. Therefore, while they are still immature, premature babies are taken care of in neonatology intensive care units, where they are kept in a controlled and protective environment. In these units, the babies' vital parameters, such as their heart rate and temperature, are tightly monitored. The devices used to record this data are fitted with alarms that are triggered automatically when something wrong is detected. However, the alarm systems currently used are often unable to discriminate between real physiological problems and artefacts that should be ignored (e.g. when a measurement device drops-out). As a result, these systems produce a high rate of false alarms, where the alarm is triggered when nothing is clinically wrong. The can have unwanted consequences: first, it creates a noisy environment, which may disturb the babies; second, it can lead to the alarm being ignored when there is actually something wrong. In order to address this problem, my host laboratory has constructed a system that can automatically infer the state of health of premature babies in neonatology units, based on their recorded physiological data. The new system is designed to be able to deal with artefactual changes in the measurements, hopefully resulting in a reduced number of false alarms. In this thesis, I describe my contribution to this project, which is twofold. The first part deals with the problem of evaluating the performance of the system. To do this, I developed an online feedback process, where clinicians could provide information about the true clinical interpretation of the physiological data, which could be compared to the output of the system. The feedbacks provided by the clinicians were then analysed to investigate how the system could be improved. The second part of my thesis was motivated be early feedbacks from the clinicians, which indicated that the system was unable to deal with changes in the humidity measurements that occurred when the incubator door was opened and closed. To address this, I extended the current system, so that it was able to account for these changes, thereby increasing its capability to detect "true" physiological problems during the period after the incubator door is closed.

2011

Evaluation and extension of an automated system to diagnose the health of premature babies

Camille Joggi

2011