1,081 research outputs found

    ASSESSMENT OF RISK IN PRETERM INFANTS USING POINT PROCESS AND MACHINE LEARNING APPROACHES

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    Preemies, infants who are born too soon, have a higher incidence of Life-Threatening Events (LTE’s) such as apnea (cessation of breathing), bradycardia (slowing of heart rate) and hypoxemia (oxygen desaturation) also termed as ABD (Apnea, Bradycardia, and Desaturation) events. Clinicians at Neonatal Intensive Care Units (NICU) are facing the demanding task of assessing the risk of infants based on their physiological signals. The aim of this thesis is to develop a risk stratification algorithm using a machine-learning framework with the features related to pathological fluctuations derived from point process model that will be embedded into the current physiological recording system to assess the risk of life-threatening events well in advance of occurrence in individual infants in the NICU. We initially propose a point process algorithm of heart rate dynamics for risk stratification of preterm infants. Based on this analysis, point process indices were tested to determine whether they were useful as precursors for life-threatening events. Finally, a machine-learning framework using point process indices as precursors were designed and tested to classify the risk of preterm infants. This work helps to predict the number of bradycardia events, N, in the subsequent hours measuring point process indices for the current hour. The model proposed uses Quadratic Support Vector Machine (QSVM), a machine learning classifier, which can solve class optimization problems and execute data at an exponential speed with higher accuracy for risk assessment that might facilitate effective management and treatment for preterm infants in NICU. The findings are relevant to risk assessment by analyzing the fluctuations in physiological signals that can act as precursors for the future life-threatening events

    Monitoring the critical newborn:Towards a safe and more silent neonatal intensive care unit

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    Very Long Apnea Events in Preterm Infants

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    Apnea is nearly universal among very low birth weight (VLBW) infants, and the associated bradycardia and desaturation may have detrimental consequences. We describe here very long ( \u3e 60 s) central apnea events (VLAs) with bradycardia and desaturation, discovered using a computerized detection system applied to our database of over 100 infant years of electronic signals. Eighty-six VLAs occurred in 29 out of 335 VLBW infants. Eighteen of the 29 infants had a clinical event or condition possibly related to the VLA. Most VLAs occurred while infants were on nasal continuous positive airway pressure, supplemental oxygen, and caffeine. Apnea alarms on the bedside monitor activated in 66% of events, on average 28 s after cessation of breathing. Bradycardia alarms activated late, on average 64 s after cessation of breathing. Before VLAs oxygen saturation was unusually high, and during VLAs oxygen saturation and heart rate fell unusually slowly. We give measures of the relative severity of VLAs and theoretical calculations that describe the rate of decrease of oxygen saturation. A clinical conclusion is that very long apnea (VLA) events with bradycardia and desaturation are not rare. Apnea alarms failed to activate for about one-third of VLAs. It appears that neonatal intensive care unit (NICU) personnel respond quickly to bradycardia alarms but not consistently to apnea alarms. We speculate that more reliable apnea detection systems would improve patient safety in the NICU. A physiological conclusion is that the slow decrease of oxygen saturation is consistent with a physiological model based on assumed high values of initial oxygen saturation

    Continuous sensing and quantification of body motion in infants:A systematic review

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    Abnormal body motion in infants may be associated with neurodevelopmental delay or critical illness. In contrast to continuous patient monitoring of the basic vitals, the body motion of infants is only determined by discrete periodic clinical observations of caregivers, leaving the infants unattended for observation for a longer time. One step to fill this gap is to introduce and compare different sensing technologies that are suitable for continuous infant body motion quantification. Therefore, we conducted this systematic review for infant body motion quantification based on the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). In this systematic review, we introduce and compare several sensing technologies with motion quantification in different clinical applications. We discuss the pros and cons of each sensing technology for motion quantification. Additionally, we highlight the clinical value and prospects of infant motion monitoring. Finally, we provide suggestions with specific needs in clinical practice, which can be referred by clinical users for their implementation. Our findings suggest that motion quantification can improve the performance of vital sign monitoring, and can provide clinical value to the diagnosis of complications in infants.</p

    Automatic neonatal sleep stage classification:A comparative study

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    Sleep is an essential feature of living beings. For neonates, it is vital for their mental and physical development. Sleep stage cycling is an important parameter to assess neonatal brain and physical development. Therefore, it is crucial to administer newborn's sleep in the neonatal intensive care unit (NICU). Currently, Polysomnography (PSG) is used as a gold standard method for classifying neonatal sleep patterns, but it is expensive and requires a lot of human involvement. Over the last two decades, multiple researchers are working on automatic sleep stage classification algorithms using electroencephalography (EEG), electrocardiography (ECG), and video. In this study, we present a comprehensive review of existing algorithms for neonatal sleep, their limitations and future recommendations. Additionally, a brief comparison of the extracted features, classification algorithms and evaluation parameters is reported in the proposed study

    Neurodevelopmental Outcomes at Two Years of Age for Premature Infants Diagnosed With Neonatal Obstructive Sleep Apnea

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    STUDY OBJECTIVES: Neurocognitive deficits have been shown in school-aged children with sleep apnea. The effect of obstructive sleep apnea (OSA) on the neurodevelopmental outcome of preterm infants is unknown. METHODS: A retrospective chart review was performed for all preterm infants ( 1 event/h. Regression analyses were performed to find a relationship between PSG parameters and cognitive, language, and motor scores. RESULTS: Fifteen patients (males: n = 10) were eligible for the study. Median postmenstrual age at the time of the PSG was 41 weeks (37-46). Median AHI for the cohort was 17.4 events/h (2.2-41.3). Median cognitive, language, and motor scores were 90 (65-125), 89 (65-121), and 91 (61-112), respectively. Mean end-tidal CO2 (median 47 mm Hg [25-60]) negatively correlated with cognitive scores (P = .01) but did not significantly correlate with language or motor scores. AHI was not associated with cognitive, language, or motor scores. CONCLUSIONS: The median score for cognitive, language, and motor scores for preterm infants with neonatal OSA were within one standard deviation of the published norm. Mean end-tidal CO2, independent of AHI, may serve as a biomarker for predicting poor cognitive outcome in preterm infants with neonatal OSA

    Autonomic control in preterm infants - what we can learn from mathematical descriptions of vital signs

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    Background: Preterm birth is a major burden, affecting approximately 15 million infants each year. Recent advances in reproductive medicine increases that number even more. The population of preterm infants in particular suffers from autonomic dysregulation that manifests as temperature instability and poor control of heart rate and breathing. Thermal care, monitoring of vital signs in a neonatal intensive care unit, pharmacotherapy, and respiratory support over weeks to months is necessary. Improvements in neonatal care in the past years lead to a decrease in mortality, especially in very preterm infants. However, former preterm infants still are a high-risk population for acute and chronic sequelae as a result of the interruption of the physiological development. A better understanding of the pathophysiology of the autonomic dysregulation in that population would be very useful. Unfortunately, accurate diagnostic tools that objectively assess and quantify the immature autonomic control in neonates are lacking. Methods: In this PhD thesis we examined different effects of the immature autonomic control in very preterm infants under clinically relevant conditions. We conducted a prospective single center observational study, where we assessed fluctuations in body temperature, sleep behavior, and heart rate variability in very preterm infants. We described the different regulatory systems using distinct mathematical expressions, such as detrended fluctuation analysis and sample entropy. We assessed associations between these outcome parameters and relevant factors of the infant’s history, such as demographic parameters and co-morbidities. Besides that, we analyzed lung function measurements of preterm infants and healthy term controls at a comparable postconceptional age, to describe respiratory control. Results: This study is systematically assessing different physiological signals of autonomic dysregulation in preterm infants during their first days of life. We found associations between parameters describing the complexity of time series analysis and maturity or relevant co-morbidities of the infants. In the analysis of heart rate variability we even found that parameters derived from time series analysis, assessed during the infants first days of life, improve our ability to predict future evolution of the infants’ autonomic stability. Lastly, several weeks after the expected due date, tidal breathing pattern of preterm infants showed a different reaction in response to a sigh when compared to term born controls at equivalent postmenstrual age indicating that autonomic dysregulation in preterm infants is still present well beyond the expected due date. Conclusion: A better understanding about the resolution of autonomic dysregulation in this population is not only important for the infant and its family but has the potential to support resource allocation and identification of patients with elevated risk for future deterioration. We thus think that the insights about the immature autonomic control in preterm infants, gained through this PhD work, are of substantial scientific and clinical relevance
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