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We introduce Experiencer, a newly developed Experience Sampling Method (ESM) software for commodity-level smartwatches. We designed this software mainly to address the compliance-related challenges, such as dropouts of study participants, that generations of ESM software solutions have faced. Dropouts are often caused by the inconvenient frequency and timing of the ESM prompts. This can partly be mitigated by utilizing physiological smartwatch sensors to learn which prompting moments are both convenient to the study participant and also relevant to the ESM study designer. Experiencer enables researchers to configure context-sensitive sampling protocols, providing access to raw sensor data, within the boundaries of European privacy legislation. In this paper, we describe the technical capabilities of our software, compare its features with the state-of-the-art, and showcase its application in studies that used Experiencer.

The introduction of rapid exome sequencing (rES) for critically ill neonates admitted to the neonatal intensive care unit has made it possible to impact clinical decision-making. Unbiased prospective studies to quantify the impact of rES over routine genetic testing are, however, scarce. We performed a clinical utility study to compare rES to conventional genetic diagnostic workup for critically ill neonates with suspected genetic disorders. In a multicenter prospective parallel cohort study involving five Dutch NICUs, we performed rES in parallel to routine genetic testing for 60 neonates with a suspected genetic disorder and monitored diagnostic yield and the time to diagnosis. To assess the economic impact of rES, healthcare resource use was collected for all neonates. rES detected more conclusive genetic diagnoses than routine genetic testing (20% vs. 10%, respectively), in a significantly shorter time to diagnosis (15 days (95% CI 10–20) vs. 59 days (95% CI 23–98, p < 0.001)). Moreover, rES reduced genetic diagnostic costs by 1.5% (€85 per neonate). Conclusion: Our findings demonstrate the clinical utility of rES for critically ill neonates based on increased diagnostic yield, shorter time to diagnosis, and net healthcare savings. Our observations warrant the widespread implementation of rES as first-tier genetic test in critically ill neonates with disorders of suspected genetic origin.What is Known:• Rapid exome sequencing (rES) enables diagnosing rare genetic disorders in a fast and reliable manner, but retrospective studies with neonates admitted to the neonatal intensive care unit (NICU) indicated that genetic disorders are likely underdiagnosed as rES is not routinely used.• Scenario modeling for implementation of rES for neonates with presumed genetic disorders indicated an expected increase in costs associated with genetic testing.What is New:• This unique prospective national clinical utility study of rES in a NICU setting shows that rES obtained more and faster diagnoses than conventional genetic tests.• Implementation of rES as replacement for all other genetic tests does not increase healthcare costs but in fact leads to a reduction in healthcare costs.

Background: Currently, in the majority of patients with stable angina pectoris (SAP) treatment consists of optimal medical treatment, potentially followed by coronary angiography and subsequent coronary revascularisation if necessary”. Recent work questioned the effectiveness of these invasive procedures in reducing re-events and improving prognosis. The potential of exercise-based cardiac rehabilitation on clinical outcomes in patients with coronary artery disease is well-known. However, in the modern era, no studies compared the effects of cardiac rehabilitation versus coronary revascularisation in patients with SAP. Methods: In this multicentre randomised controlled trial, 216 patients with stable angina pectoris and residual anginal complaints under optimal medical treatment will be randomised to: 1) usual care (i.e., coronary revascularisation), or 2) a 12-month cardiac rehabilitation (CR) programme. CR consists of a multidisciplinary intervention, including education, exercise training, lifestyle coaching and a dietary intervention with a stepped decline in supervision. The primary outcome will be anginal complaints (Seattle Angina Questionnaire-7) following the 12-month intervention. Secondary outcomes include cost-effectiveness, ischemic threshold during exercise, cardiovascular events, exercise capacity, quality of life and psychosocial wellbeing. Discussion: In this study, we will examine the hypothesis that multidisciplinary CR is at least equally effective in reducing anginal complaints as the contemporary invasive approach at 12-months follow-up for patients with SAP. If proven successful, this study will have significant impact on the treatment of patients with SAP as multidisciplinary CR is a less invasive and potentially less costly and better sustainable treatment than coronary revascularisations. Trial registration: Netherlands Trial Register, NL9537. Registered 14 June 2021.

Introduction: Supplemental oxygen therapy is a mainstay of modern neonatal intensive care for preterm infants. However, both insufficient and excess oxygen delivery are associated with adverse outcomes. Automated or closed loop FiO2 control has been developed to keep SpO2 within a predefined target range more effectively. Methods: The aim of this study was to investigate the feasibility of closed loop FiO2 control by Predictive Intelligent Control of Oxygenation (PRICO) on the Fabian ventilator in maintaining SpO2 within a target range (88/89-95%) in preterm infants on different modes of invasive and noninvasive respiratory support. In two tertiary neonatal intensive care units, preterm infants with an FiO2 >0.21 were included and received an 8 h nonblinded treatment period of closed loop FiO2 control by PRICO, flanked by two 8 h control periods of routine manual control (RMC1 and RMC2). Results: 32 preterm infants were included (median gestational age 26 + 5 weeks [IQR 25 + 5–27 + 6], median birthweight 828 grams [IQR 704–930]). Six patients received invasive respiratory support, while 26 received noninvasive respiratory support (18 CPAP, 4 DuoPAP, and 4 nasal IMV). The time percentage within the SpO2 target range was increased with PRICO (74.4% [IQR 67.8–78.5]) compared to RMC1 (65.8% [IQR 51.1–77.8]; p = 0.011) and RMC2 (60.6% [IQR 56.2–66.6]; p < 0.001) with an estimated median difference of 6.0% (95% CI 1.2–11.5) and 9.8% (95% CI 6.0–13.0), respectively. Conclusion: In preterm infants on invasive and noninvasive respiratory supports, closed loop FiO2 control by PRICO compared to RMC is feasible and superior in maintaining SpO2 within target ranges.

Late onset sepsis (LOS) is one of the main causes of death in preterm infants in a neonatal intensive care unit (NICU). LOS can be better treated with early detection, reducing its morbidity and mortality. In this study, an end-to-end deep learning model called DeepLOS was developed to predict LOS in preterm infants in a NICU. The model is based on a residual convolutional neural network (ResNet) with feature map (or channel) attention and uses RR intervals (i.e., interbeat intervals) as input. The model was trained and tested on a dataset composed of 128 preterm infants (60 blood-culture-proven LOS patients and 68 control patients). To minimize the possible age effect on modeling, we also considered an age-matched dataset including 32 LOS and 32 control patients from the full dataset. Prediction was done with a one-hour (non-overlapping) sliding window from 24 h before LOS to onset of LOS. We used 5-fold patient-independent cross validation and F-score to evaluate the model performance. The DeepLOS achieves an F-score of 0.72 for the full dataset and 0.73 for the matched dataset in LOS prediction for all one-hour segments, outperforming the baseline ResNet model without channel attention. F-score is generally higher (>0.75) when coming closer to the onset of LOS. Our study demonstrates the feasibility of deep learning for end-to-end LOS prediction in preterm infants. Furthermore, the model uses readily available RR intervals as input only; and is therefore vendor-processing independent and has the potential to be easily deployed in different NICUs.

Introduction: Less invasive surfactant administration (LISA) to preterm infants is associated with decreased risk for death or BPD. After LISA, a considerable proportion requires a second dose of surfactant because of ongoing respiratory distress syndrome, raising a clinical dilemma between intubation or performing a repeated LISA (re-LISA) procedure. We aim to assess efficacy of re-LISA in avoiding subsequent nasal continuous positive airway pressure failure (need for intubation in the first 72 h of life; CPAP-F), to identify factors associated with subsequent CPAP-F, and to compare short-term outcomes following re-LISA to surfactant retreatment by endotracheal intubation and mechanical ventilation. Methods: This was an observational retrospective study in two Dutch NICUs. Inclusion criterion was infants with gestational age Results: Of 209 infants requiring second surfactant dose, 132 received re-LISA. Subsequent CPAP-F was observed in 56 (42%) infants and was associated with extreme prematurity (OR 2.6, 95% CI: 1.2–5.8) and FiO2>0.5 (OR 5.4, 95% CI: 2.0–14.7). Infants receiving re-LISA had a lower risk of death or BPD compared to infants intubated for the second surfactant dose (OR 0.4, 95% CI: 0.2–0.9). Infants with CPAP-F after re-LISA had similar outcomes compared to those intubated for second surfactant dose. Conclusion: Re-LISA is effective in reducing CPAP-F and is associated with lower risk of death or BPD compared to retreatment via an endotracheal tube. Infants failing CPAP after re-LISA have similar outcomes compared to intubated infants. These findings support the use of re-LISA in preterm infants with ongoing RDS.

ObjectiveTo investigate the efficacy of automated control of inspired oxygen (FiO2) by Predictive Intelligent Control of Oxygenation (PRICO) on the Fabian ventilator in maintaining oxygen saturation (SpO2) in preterm infants on high flow nasal cannula (HFNC) support.DesignSingle-centre randomised two-period crossover study.SettingTertiary neonatal intensive care unit.Patients27 preterm infants (gestational age (GA) 0.25.InterventionA 24-hour period on automated FiO2-control with PRICO compared with a 24-hour period on routine manual control (RMC) to maintain a SpO2 level within target range of 88%–95% measured at 30 s intervals.Main outcome measuresPrimary outcome: time spent within target range (88%–95%). Secondary outcomes: time spent above and below target range, in severe hypoxia (SpO2 98%), mean SpO2 and FiO2 and manual FiO2 adjustments.Results15 patients received PRICO-RMC and 12 RMC-PRICO. The mean time within the target range increased with PRICO: 10.8% (95% CI 7.6 to 13.9). There was a decrease in time below target range: 7.6% (95% CI 4.2 to 11.0), above target range: 3.1% (95% CI 2.9 to 6.2) and in severe hypoxia: 0.9% (95% CI 1.5 to 0.2). We found no difference in time spent in severe hyperoxia. Mean FiO2 was higher during PRICO: 0.019 (95% CI 0.006 to 0.030). With PRICO there was a reduction of manual adjustments: 9/24 hours (95% CI 6 to 12).ConclusionIn preterm infants on HFNC support, automated FiO2-control by PRICO is superior to RMC in maintaining SpO2 within target range. Further validation studies with a higher sample frequency and different ventilation modes are needed.

Background and purpose: Treatment planning of radiotherapy for locally advanced breast cancer patients can be a time consuming process. Artificial intelligence based treatment planning could be used as a tool to speed up this process and maintain plan quality consistency. The purpose of this study was to create treatment plans for locally advanced breast cancer patients using a Convolutional Neural Network (CNN). Materials and methods: Data of 60 patients treated for left-sided breast cancer was used with a training, validation and test split of 36/12/12, respectively. The in-house built CNN model was a hierarchically densely connected U-net (HD U-net). The inputs for the HD U-net were 2D distance maps of the relevant regions of interest. Dose predictions, generated by the HD U-net, were used for a mimicking algorithm in order to create clinically deliverable plans. Results: Dose predictions were generated by the HD U-net and mimicked using a commercial treatment planning system. The predicted plans fulfilling all clinical goals while showing small (≤0.5 Gy) statistically significant differences (p < 0.05) in the doses compared to the manual plans. The mimicked plans show statistically significant differences in the average doses for the heart and lung of ≤0.5 Gy and a reduced D2% of all PTVs. In total, ten of the twelve mimicked plans were clinically acceptable. Conclusions: We created a CNN model which can generate clinically acceptable plans for left-sided locally advanced breast cancer patients. This model shows great potential to speed up the treatment planning process while maintaining consistent plan quality.

BACKGROUND AND OBJECTIVE: Apnea of prematurity is one of the most common diagnosis in neonatal intensive care units. Apneas can be classified as central, obstructive or mixed. According to the current international standards, minimal fluctuations or absence of fluctuations in the chest impedance (CI) suggest a central apnea (CA). However, automatic detection of reduced CI fluctuations leads to a high number of central apnea-suspected events (CASEs), the majority being false alarms. We aim to improve automatic detection of CAs by using machine learning to optimize detection of CAs among CASEs.METHODS: Using an optimized algorithm for automated detection, all CASEs were detected in a population of 10 premature infants developing late-onset sepsis and 10 age-matched control patients. CASEs were inspected by two clinical experts and annotated as CAs or rejections in two rounds of annotations. A total of 47 features were extracted from the ECG, CI and oxygen saturation signals considering four 30 s-long moving windows, from 30 s before to 15 s after the onset of each CASE, using a moving step size of 5 s. Consecutively, new CA detection models were developed based on logistic regression with elastic net penalty, random forest and support vector machines. Performance was evaluated using both leave-one-patient-out and 10-fold cross-validation considering the mean area under the receiver-operating-characteristic curve (AUROC).RESULTS: The CA detection model based on logistic regression with elastic net penalty returned the highest mean AUROC when features extracted from all four time windows were included, both using leave-one-patient-out and 10-fold cross-validation (mean AUROC of 0.88 and 0.90, respectively). Feature relevance was found to be the highest for features derived from the CI. A threshold for the false positive rate in the mean receiver-operating-characteristic curve equal to 0.3 led to a high percentage of correct detections for all CAs (78.2%) and even higher for CAs followed by a bradycardia (93.4%) and CAs followed by both a bradycardia and a desaturation (95.2%), which are more critical for the well-being of premature infants.CONCLUSIONS: Models based on machine learning can lead to improved CA detection with fewer false alarms.

Preterm infants in a neonatal intensive care unit (NICU) are continuously monitored for their vital signs, such as heart rate and oxygen saturation. Body motion patterns are documented intermittently by clinical observations. Changing motion patterns in preterm infants are associated with maturation and clinical events such as late-onset sepsis and seizures. However, continuous motion monitoring in the NICU setting is not yet performed. Video-based motion monitoring is a promising method due to its non-contact nature and therefore unobtrusiveness. This study aims to determine the feasibility of simple video-based methods for infant body motion detection. We investigated and compared four methods to detect the motion in videos of infants, using two datasets acquired with different types of cameras. The thermal dataset contains 32 hours of annotated videos from 13 infants in open beds. The RGB dataset contains 9 hours of annotated videos from 5 infants in incubators. The compared methods include background substruction (BS), sparse optical flow (SOF), dense optical flow (DOF), and oriented FAST and rotated BRIEF (ORB). The detection performance and computation time were evaluated by the area under receiver operating curves (AUC) and run time. We conducted experiments to detect motion and gross motion respectively. In the thermal dataset, the best performance of both experiments is achieved by BS with mean (standard deviation) AUCs of 0.86 (0.03) and 0.93 (0.03). In the RGB dataset, SOF outperforms the other methods in both experiments with AUCs of 0.82 (0.10) and 0.91 (0.05). All methods are efficient to be integrated into a camera system when using low-resolution thermal cameras.

In the first months of the COVID-19 pandemic in Europe, many patients were treated in hospitals using mechanical ventilation. However, due to a shortage of ICU ventilators, hospitals worldwide needed to deploy anesthesia machines for ICU ventilation (which is off-label use). A joint guidance was written to apply anesthesia machines for long-term ventilation. The goal of this research is to retrospectively evaluate the differences in measurable ventilation parameters between the ICU ventilator and the anesthesia machine as used for COVID-19 patients. In this study, we included 32 patients treated in March and April 2020, who had more than 3 days of mechanical ventilation, either in the regular ICU with ICU ventilators (Hamilton S1), or in the temporary emergency ICU with anesthetic ventilators (Aisys, GE). The data acquired during regular clinical treatment was collected from the Patient Data Management Systems. Available ventilation parameters (pressures and volumes: PEEP, Ppeak, Pinsp, Vtidal), monitored parameters EtCO2, SpO2, derived compliance C, and resistance R were processed and analyzed. A sub-analysis was performed to compare closed-loop ventilation (INTELLiVENT-ASV) to other ventilation modes. The results showed no major differences in the compared parameters, except for Pinsp. PEEP was reduced over time in the with Hamilton treated patients. This is most likely attributed to changing clinical protocol as more clinical experience and literature became available. A comparison of compliance between the 2 ventilators could not be made due to variances in the measurement of compliance. Closed loop ventilation could be used in 79% of the time, resulting in more stable EtCO2. From the analysis it can be concluded that the off-label usage of the anesthetic ventilator in our hospital did not result in differences in ventilation parameters compared to the ICU treatment in the first 4 days of ventilation.

ObjectiveIn the Netherlands, the threshold for offering active treatment for spontaneous birth was lowered from 25+0 to 24+0 weeks’ gestation in 2010. This study aimed to evaluate the impact of guideline implementation on survival and causes and timing of death in the years following implementation.DesignNational cohort study, using data from the Netherlands Perinatal Registry.PatientsThe study population included all 3312 stillborn and live born infants with a gestational age (GA) between 240/7 and 266/7 weeks born between January 2011 and December 2017. Infants with the same GA born between January 2007 and December 2009 (N=1400) were used as the reference group.Main outcome measuresSurvival to discharge, as well as cause and timing of death.ResultsAfter guideline implementation, there was a significant increase in neonatal intensive care unit (NICU) admission rate for live born infants born at 24 weeks’ GA (27%–69%, pConclusionsImplementation of the 2010 guideline resulted as expected in increased NICU admissions rate and postnatal survival of infants born at 24 weeks’ GA. In the years after implementation, a shift in cause of death was seen from respiratory insufficiency towards necrotising enterocolitis and sepsis.

Cardiorespiratory interaction (CRI) has been intensively studied in adult sleep, yet not in preterm infants, in particular across different sleep states including wake (W), active sleep (AS), and quiet sleep (QS). The aim of this study was to quantify the interaction between cardiac and respiratory activities in different sleep states of preterm infants. The postmenstrual age (PMA) of preterm infants was also taken into consideration. The CRI during sleep was analyzed using a visibility graph (VG) method, enabling the nonlinear analysis of CRI in a complex network. For each sleep state, parameters quantifying various aspects of the CRI characteristics from constructed VG network including mean degree (Dm) and its variability (Dsd), clustering coefficient (CCm) and its variability (CCsd), assortativity coefficient (AC) and complexity (DSE) were extracted from the CRI networks. The interaction effect of sleep state and PMA was found to be statistically significant on all CRI parameters but AC and DSE. The main effect between sleep state and CRI parameters was statistically significant except for CCm, and that between PMA and CRI parameters was statistically significant but DSE. In conclusion, the CRI of preterm infants is associated with sleep states and PMA in general. For preterm infants with a larger PMA, CRI has a more clustered pattern during different sleep states, where QS shows a more regular, stratified, and stronger CRI than other states. In the future, these parameters can be potentially used to separate sleep states in preterm infants.

Contains fulltext : 234074.pdf (Publisher’s version ) (Closed access) BACKGROUND: Doxapram is used for the treatment of apnea of prematurity in dosing regimens only based on bodyweight, as pharmacokinetic data are limited. This study describes the pharmacokinetics of doxapram and keto-doxapram in preterm infants. METHODS: Data (302 samples) from 75 neonates were included with a median (range) gestational age (GA) 25.9 (23.9-29.4) weeks, bodyweight 0.95 (0.48-1.61) kg, and postnatal age (PNA) 17 (1-52) days at the start of continuous treatment. A population pharmacokinetic model was developed using non-linear mixed-effects modelling (NONMEM®). RESULTS: A two-compartment model best described the pharmacokinetics of doxapram and keto-doxapram. PNA and GA affected the formation clearance of keto-doxapram (CL(FORMATION KETO-DOXAPRAM)) and clearance of doxapram via other routes (CL(DOXAPRAM OTHER ROUTES)). For a median individual of 0.95 kg, GA 25.6 weeks, and PNA 29 days, CL(FORMATION KETO-DOXAPRAM) was 0.115 L/h (relative standard error (RSE) 12%) and CL(DOXAPRAM OTHER ROUTES) was 0.645 L/h (RSE 9%). Oral bioavailability was estimated at 74% (RSE 10%). CONCLUSIONS: Dosing of doxapram only based on bodyweight results in the highest exposure in preterm infants with the lowest PNA and GA. Therefore, dosing may need to be adjusted for GA and PNA to minimize the risk of accumulation and adverse events. For switching to oral therapy, a 33% dose increase is required to maintain exposure. IMPACT: Current dosing regimens of doxapram in preterm infants only based on bodyweight result in the highest exposure in infants with the lowest PNA and GA. Dosing of doxapram may need to be adjusted for GA and PNA to minimize the risk of accumulation and adverse events. Describing the pharmacokinetics of doxapram and its active metabolite keto-doxapram following intravenous and gastroenteral administration enables to include drug exposure to the evaluation of treatment of AOP. The oral bioavailability of doxapram in preterm neonates is 74%, requiring a 33% higher dose via oral than intravenous administration to maintain exposure.

This paper studied the constraint mechanism for power device design based on perovskite quantum dots pumped by an electron beam. Combined with device designing, an experimental system of self-saturation luminescence and aging failure was designed for CsPbBr3 films. On this basis, we further completed the self-saturation luminescence and aging failure experiment and constructed a model of self-saturation luminescence and aging failure for CsPbBr3 device designing. Three constraints were proposed after analyzing and discussing the experimental data. Firstly, too high of a pumping current density makes it difficult to effectively promote the enhancement of luminescence efficiency. Secondly, radiation decomposition and aging failure of CsPbBr3 films are mainly related to the polarized degree of CsPbBr3 nanocrystals. Thirdly, by increasing the pumping electric field, the pumping energy can be effectively and widely delivered to the three-dimensional quantum dots film layer space, and there is a nonlinear relationship between the attenuation of the pumping energy density and the increment of the pumping electric field, which will effectively avoid the local high-energy density of instantaneous optical pumping.

Objective: To perform a temporal and geographical validation of a prognostic model, considered of highest methodological quality in a recently published systematic review, for predicting survival in very preterm infants admitted to the neonatal intensive care unit. The original model was developed in the UK and included gestational age, birthweight and gender. Design: External validation study in a population-based cohort. Setting: Dutch neonatal wards. Population or sample: All admitted white, singleton infants born between 23+0 and 32+6 weeks of gestation between 1 January 2015 and 31 December 2019. Additionally, the model’s performance was assessed in four populations of admitted infants born between 24+0 and 31+6 weeks of gestation: white singletons, non-white singletons, all singletons and all multiples. Methods: The original model was applied in all five validation sets. Model performance was assessed in terms of calibration and discrimination and, if indicated, it was updated. Main outcome measures: Calibration (calibration-in-the-large and calibration slope) and discrimination (c statistic). Results: Out of 6092 infants, 5659 (92.9%) survived. The model showed good external validity as indicated by good discrimination (c statistic 0.82, 95% CI 0.79–0.84) and calibration (calibration-in-the-large 0.003, calibration slope 0.92, 95% CI 0.84–1.00). The model also showed good external validity in the other singleton populations, but required a small intercept update in the multiples population. Conclusions: A high-quality prognostic model predicting survival in very preterm infants had good external validity in an independent, nationwide cohort. The accurate performance of the model indicates that after impact assessment, implementation of the model in clinical practice in the neonatal intensive care unit could be considered. Tweetable abstract: A high-quality model predicting survival in very preterm infants is externally valid in an independent cohort.

Background: Current knowledge regarding differences in verbal intelligence scores (VIQ) and performance intelligence scores (PIQ) in preterm born children is limited. As early motor performance may be essential for developing later visual-perceptual and visual-motor skills, early motor performance may be associated with PIQ. Aims: To evaluate whether in preterm born children motor performance at two years was associated with PIQ at eight years. Methods: Single-centre cohort study including 88 children born

AIM: To address alarm fatigue, a new alarm management system which ensures a quicker delivery of alarms together with waveform information on nurses' handheld devices was implemented and settings optimised. The effects of this clinical implementation on alarm rates and nurses' responsiveness were measured in an 18-bed single family rooms neonatal intensive care unit (NICU).METHODS: The technical implementation of the alarm management system was followed by clinical workflow optimisation. Alarms and vital parameters from October 2017 to December 2019 were analysed. Measures included monitoring alarms, nurses' response to alarms and time spent by patients in different saturation ranges. A survey among nurses was performed to evaluate changes in alarm rate and use of protocols.RESULTS: A significant reduction of monitoring alarms per patient days was detected after the optimisation phase (in particular for SpO2 ≤ 80%, P < .001). More time was spent by infants within the optimal peripheral oxygen saturation range (88% < SpO2 < 95%, P < .001). Results from the surveys showed that false alarms are less likely to cause an inappropriate response after the optimisation phase.CONCLUSION: The implementation of an alarm management solution and an optimisation programme can safely reduce the alarm burden inside of the NICU environment.

Respiration is monitored in neonatal wards using chest impedance (CI), which is obtrusive and can cause skin damage to the infants. Therefore, unobtrusive solutions based on infrared thermography are being investigated. This work proposes an algorithm to merge multiple thermal camera views and automatically detect the pixels containing respiration motion or flow using three features. The method was tested on 152 minutes of recordings acquired on seven infants. We performed a comparison with the CI respiration rate yielding a mean absolute error equal to 2.07 breaths/min. Merging the three features resulted in reducing the dependency on the window size typical of spectrum-based features.

ObjectiveTo find propofol doses providing effective sedation without side effects in neonates of different gestational ages (GA) and postnatal ages (PNA).Design and settingProspective multicentere dose-finding study in 3 neonatal intensive care units.PatientsNeonates with a PNA InterventionsNeonates were stratified into 8 groups based on GA and PNA. The first 5 neonates in every group received a dose of 1.0 mg/kg propofol. Based on sedative effect and side effects, the dose was increased or decreased in the next 5 patients until the optimal dose was found.Main outcome measuresThe primary outcome was the optimal single propofol starting dose that provides effective sedation without side effects in each age group.ResultsAfter inclusion of 91 patients, the study was prematurely terminated because the primary outcome was only reached in 13% of patients. Dose-finding was completed in 2 groups, but no optimal propofol dose was found. Effective sedation without side effects was achieved more often after a starting dose of 2.0 mg/kg (28%) than after 1.0 mg/kg (3%) and 1.5 mg/kg (9%). Propofol-induced hypotension occurred in 59% of patients. Logistic regression analyses showed that GA and PNA did not predict effective sedation or the occurrence of hypotension.ConclusionsEffective sedation without side effects is difficult to achieve with propofol and the optimal dose in different age groups of neonates could not be determined. The sedative effect of propofol and the occurrence of hypotension are unpredictable and show large inter-individual variability in the neonatal population.

This study in preterm infants was designed to characterize the prognostic potential of several features of heart rate variability (HRV), respiration, and (infant) motion for the predictive monitoring of late-onset sepsis (LOS). In a neonatal intensive care setting, the cardiorespiratory waveforms of infants with blood-culture positive LOS were analyzed to characterize the prognostic potential of 22 features for discriminating control from sepsis-state, using the Naïve Bayes algorithm. Historical data of the subjects acquired from a period sufficiently before the clinical suspicion of LOS was used as control state, whereas data from the 24 h preceding the clinical suspicion of LOS were used as sepsis state (test data). The overall prognostic potential of all features was quantified at three-hourly intervals for the period corresponding to test data by calculating the area under the receiver operating characteristics curve. For the 49 infants studied, features of HRV, respiration, and movement showed characteristic changes in the hours leading up to the clinical suspicion of sepsis, namely, an increased propensity toward pathological heart rate decelerations, increased respiratory instability, and a decrease in spontaneous infant activity, i.e., lethargy. While features characterizing HRV and respiration can be used to probe the state of the autonomic nervous system, those characterizing movement probe the state of the motor system-dysregulation of both reflects an increased likelihood of sepsis. By using readily interpretable features derived from cardiorespiratory monitoring, opportunities for pre-emptively identifying and treating LOS can be developed.

Apnea of prematurity (AOP) is a critical condition for preterm infants which can lead to several adverse outcomes. Despite its relevance, mechanisms underlying AOP are still unclear. In this work we aimed at improving the understanding of AOP and its physiologic responses by analyzing and comparing characteristics of real infant data and model-based simulations of AOP. We implemented an existing algorithm to extract apnea events originating from the central nervous system from a population of 26 premature infants (1248 h of data in total) and investigated oxygen saturation (SpO2) and heart rate (HR) of the infants around these events. We then extended a previously developed cardio-vascular model to include the lung mechanics and gas exchange. After simulating the steady state of a preterm infant, which successfully replicated results described in previous literature studies, the extended model was used to simulate apneas with different lengths caused by a stop in respiratory muscles. Apneas identified by the algorithm and simulated by the model showed several similarities, including a far deeper decrease in SpO2, with the minimum reached later in time, in case of longer apneas. Results also showed some differences, either due to how measures are performed in clinical practice in our neonatal intensive care unit (e.g. delayed detection of decline in SpO2 after apnea onset due to signal averaging) or to the limited number of very long apneas (≥80 s) identified in our dataset.

Lausanne : Frontiers Media 9, 793531 (2022). doi:10.3389/fped.2021.793531, Published by Frontiers Media, Lausanne

Vital signs are used in Neonatal Intensive Care Units (NICUs) to monitor the state of multiple patients at once. Alarms are triggered if a vital sign is below/above a predefined threshold. Numerous alarms sound each hour which could translate into an overload for the medical team, known as alarm fatigue. Yet many of these alarms do not require immediate clinical action of the caregivers.In this paper we automatically detect moments that need an immediate response (i.e. interaction with the patient) of the medical team in NICUs by using caregiver response to the patient, which is based on the interpretation of vital signs and of nonverbal cues (e.g. movements) delivered by patients. The ultimate goal of such approach is to reduce the overload of alarms while maintaining the patient safety.We use features extracted from the electrocardiogram (ECG) and pulse oxymetry (SpO2) sensors of the patient, as most unplanned interactions between patient and caregivers are due to deteriorations. Since in our unit an alarm can only be paused or silenced manually at the bedside, we used this information as a prior for caregiver response. We also propose different labeling schemes for classification, each representative of a possible interaction scenario within the nature of our problem.We accomplished a general detection of caregiver response with a mean AUC of 0.82. We also show that when trained only with stable and truly deteriorating (critical state) samples, the classifiers can better learn the difference between alarms that need no immediate response and those that do. In addition, we present an analysis of the posterior probabilities over time for different labeling schemes, and use it to speculate about the reasons behind some failure cases.

In neonatal intensive care units, respiratory traces of premature infants developing late onset sepsis (LOS) may also show episodes of apneas. However, since clinical patient monitors often underdetect apneas, clinical experts are required to investigate patients' traces looking for these events. In this work we present a method to optimize an existing algorithm for central apnea (CA) detection and how we used it together with human annotations to investigate the occurrence of CAs preceding LOS.The algorithm was optimized by using a previously-annotated dataset consisting of 90 hours, extracted from 10 premature infants. This allowed to double precision (19.7% vs 9.3%, median values per patient) without affecting recall (90.5% vs 94.5%) compared to the original algorithm. This choice caused the missed identification of just 1 additional CA (4 vs 3) in the whole dataset. The optimized algorithm was then used to annotate a second dataset consisting of 480 hours, extracted from 10 premature infants diagnosed with LOS. Annotations were corrected by two clinical experts.A significantly higher number of CA annotations was found in the 6 hours prior to sepsis onset (p-value < 0.05). The use of the optimized algorithm followed by human annotations proved to be a suitable, time-efficient method to annotate CAs before sepsis in premature infants, enabling future use in large datasets.

Motion patterns in newborns contain important information. Motion patterns change upon maturation and changes in the nature of motion may precede critical clinical events such as the onset of sepsis, seizures and apneas. However, in clinical practice, motion monitoring is still limited to observations by caregivers. In this study, we investigated a practical yet reliable method for motion detection using routinely used physiological signals in the patient monitor. Our method calculated motion measures with a continuous wavelet transform (CWT) and a signal instability index (SII) to detect gross-motor motion in 15 newborns using 40 hours of physiological data with annotated videos. We compared the performance of these measures on three signal modalities (electrocardiogram ECG, chest impedance, and photo plethysmography). In addition, we investigated whether their combinations increased performance. The best performance was achieved with the ECG signal with a median (interquartile range, IQR) area under receiver operating curve (AUC) of 0.92(0.87-0.95), but differences were small as both measures had a robust performance on all signal modalities. We then applied the algorithm on combined measures and modalities. The full combination outperformed all single-modal methods with a median (IQR) AUC of 0.95(0.91-0.96) when discriminating gross-motor motion from still. Our study demonstrates the feasibility of gross-motor motion detection method based on only clinically-available vital signs and that best results can be obtained by combining measures and vital signs.

Background: Preterm infants with pre- or postnatal growth restriction may have an additional risk of adverse neurodevelopmental outcome. Whereas reduced cognitive ability and behavioral problems have consistently been associated with prematurity, a more comprehensive evaluation is necessary to identify those preterm infants who are at increased risk for difficulties in school performance. This study evaluated the association between extremely low birth weight (ELBW) and the need for special education and determined if there is an additional risk for the need for special education among small for gestational age (SGA) children.Methods: This is a single-center cohort study including singleton children born below 30 weeks' gestation between 1990 and 2011 and followed into 2019. ELBW + was defined as a birth weight below 1,000 g, which was compared to ELBW–. Within all ELBW+ children, SGA+ was defined as a birth weight Results: In total, 609 children were eligible for follow-up, of whom 390 (64%) children were assessed at 8 years. Of these, 56 (14%) children needed special education, most often determined by cognitive deficiency (43%), behavioral problems (29%), or both (16%). Among the 191 ELBW+ children, 35 (18%) attended special education, compared to 21 (11%) among ELBW– children (p-value 0.041). A decreasing risk for the need for special education was found from 25% in ELBW+/SGA+ children to 16% in ELBW+/SGA– children and 11% in ELBW–/SGA– children (p-value 0.025). Multivariable logistic regression showed an odds ratio of 2.88 (95% CI 1.20–6.78) for ELBW+/SGA+ children vs. ELBW–/SGA– children for the need for special education.Conclusions: This study showed that ELBW children are at increased risk for the need for special education compared to non-ELBW children. In addition, children that are both ELBW and SGA do have the highest risk for the need for special education. Classifying children as ELBW and SGA can be useful in follow-up for identifying preterm children with an additional risk for adverse long-term outcome.

Both Respiratory Flow (RF) and Respiratory Motion (RM) are visible in thermal recordings of infants. Monitoring these two signals usually requires landmark detection for the selection of a region of interest. Other approaches combine respiratory signals coming from both RF and RM, obtaining a Mixed Respiratory (MR) signal. The detection and classification of apneas, particularly common in preterm infants with low birth weight, would benefit from monitoring both RF and RM, or MR, signals. Therefore, we propose in this work an automatic RF pixel detector not based on facial/body landmarks. The method is based on the property of RF pixels in thermal videos, which are in areas with a smooth circular gradient. We defined 5 features combined with the use of a bank of Gabor filters that together allow selection of the RF pixels. The algorithm was tested on thermal recordings of 9 infants amounting to a total of 132 min acquired in a neonatal ward. On average the percentage of correctly identified RF pixels was 84%. Obstructive Apneas (OAs) were simulated as a proof of concept to prove the advantage in monitoring the RF signal compared to the MR signal. The sensitivity in the simulated OA detection improved for the RF signal reaching 73% against the 23% of the MR signal. Overall, the method yielded promising results, although the positioning and number of cameras used could be further optimized for optimal RF visibility.

Introduction: Retinopathy of prematurity (ROP) remains an important cause for preventable blindness. Aside from gestational age (GA) and birth weight, risk factor assessment can be important for determination of infants at risk of (severe) ROP. Methods: Prospective, multivariable risk-analysis study (NEDROP-2) was conducted, including all infants born in 2017 in the Netherlands considered eligible for ROP screening by pediatricians. Ophthalmologists provided data of screened infants, which were combined with risk factors from the national perinatal database (Perined). Clinical data and potential risk factors were compared to the first national ROP inventory (NEDROP-1, 2009). During the second period, more strict risk factor-based screening inclusion criteria were applied. Results: Of 1,287 eligible infants, 933 (72.5%) were screened for ROP and matched with the Perined data. Any ROP was found in 264 infants (28.3% of screened population, 2009: 21.9%) and severe ROP (sROP) (stage ≥3) in 41 infants (4.4%, 2009: 2.1%). The risk for any ROP is decreased with a higher GA (odds ratio [OR] 0.59 and 95% confidence interval [CI] 0.54–0.66) and increased for small for GA (SGA) (1.73, 1.11–2.62), mechanical ventilation >7 days (2.13, 1.35–3.37) and postnatal corticosteroids (2.57, 1.44–4.66). For sROP, significant factors were GA (OR 0.37 and CI 0.27–0.50), SGA (OR 5.65 and CI 2.17–14.92), postnatal corticosteroids (OR 3.81 and CI 1.72–8.40), and perforated necrotizing enterocolitis (OR 7.55 and CI 2.29–24.48). Conclusion: In the Netherlands, sROP was diagnosed more frequently since 2009. No new risk factors for ROP were determined in the present study, apart from those already included in the current screening guideline.

ObjectiveTo evaluate incidence of minimally invasive surfactant therapy (MIST) failure, identify risk factors and assess the impact of MIST failure on neonatal outcome.DesignRetrospective cohort study. MIST failure was defined as need for early mechanical ventilation (SettingTwo tertiary neonatal intensive care centres in the Netherlands.PatientsInfants born between 24 weeks’ and 31 weeks’ gestational age (GA) (n=185) with MIST for respiratory distress syndrome.InterventionsMIST procedure with poractant alfa (100–200 mg/kg).Main outcome measuresContinuous positive airway pressure (CPAP) failure after MIST in the first 72 hours of life.Results30% of the infants failed CPAP after MIST. In a multivariate logistic regression analysis, four risk factors were independently associated with failure: GA Furthermore, MIST failure was independently associated with an increased risk of severe intraventricular haemorrhage.ConclusionWe observed moderate MIST failure rates in concordance with the results of earlier studies. Absence of corticosteroids and lower surfactant dose are risk factors for MIST failure that may be modifiable in order to improve MIST success and patient outcome.

Aim: To investigate the effects of a swaddling device known as the Hugsy (Hugsy, Eindhoven, the Netherlands) towards improving autonomic regulation. This device can be used both in the incubator and during Kangaroo care to absorb parental scent and warmth. After Kangaroo care, these stimuli can continue to be experienced by infants, while in the incubator. Additionally, a pre-recorded heartbeat sound can be played. Method: Autonomic regulation was compared in preterm infants before, during and after Kangaroo care with and without the use of a swaddling device in a within-subject study carried out in a level III neonatal intensive care unit. Descriptive statistics and effect sizes were calculated corresponding to changes in heart rate, respiratory rate, oxygen saturation, temperature and heart rate variability on intervention versus control days. Results: In this study of 20 infants with a median (interquartile range) gestational age of 28.4 (27-29.9) weeks, Kangaroo care was associated with a decrease in heart rate, respiratory rate and heart rate variability on both intervention and control days. There were no differences between intervention and control days. Conclusion: The use of an alternative swaddling device aimed at facilitating Kangaroo care did not enhance autonomic regulation, as measured by vital signs and heart rate variability.

In preterm infants, a better understanding and quantification of cardiorespiratory coupling may help improve caregiving by enabling the tracking of maturational changes and subclinical signatures of disease. Therefore, in a study of 20 preterm infants admitted to a neonatal intensive care unit, we analyzed the cardiac and respiratory regulatory mechanisms as well as the coupling between them. In particular, we selectively analyzed coupling from changes in heart rate to respiratory oscillations as well as coupling from respiratory oscillations to the heart rate. Furthermore, we stratified this coupling based on decelerations and accelerations of the heart rate and by inspiration and expiration during respiration while contrasting periods of kangaroo care, an intervention known to enhance autonomic regulation, with periods in the incubator. We identified that preterm infants exhibit cardiorespiratory coupling that is nonsymmetric with regard to the direction of coupling. We demonstrate coupling from decelerations and accelerations of the heart rate to exhalation and inhalation, respectively, both on a beat-to-beat basis as well as with sustained decelerations and accelerations. On the other hand, on average, we also observed coupling from both inspiration and expiration to marginal decelerations in the heart rate. These phenomena, especially coupling from the changes in the heart rate to respiratory oscillations, were sensitive to whether the infant was receiving kangaroo care. NEW & NOTEWORTHY Preterm infants exhibit cardiorespiratory coupling that is nonsymmetric with regard to the direction of coupling; coupling from fluctuations in the heart rate to respiratory oscillations and vice versa are asymmetric. On average, coupling is observable from decelerations or accelerations in the heart rate to inhalation or exhalation, respectively, whereas, on average, both peaks and troughs of respiration exhibit coupling to marginal decelerations in the heart rate.

IEEE access 7, 141766-141781 (2019). doi:10.1109/ACCESS.2019.2944531, Published by IEEE, New York, NY

Aim: Long-term outcome data in preterm children is often limited to cross-sectional measurement of neurodevelopmental impairment (NDI) at the corrected age of 24-36 months. However, impairments may only become overt during childhood or resolve with time, and individual trajectories in outcome over time may vary. The primary aim of this study was to describe NDI in very preterm born children at three subsequent ages of 2, 5, and 8 years of age. As a secondary aim, a longitudinal analysis was performed on the individual longitudinal trajectories in NDI from 2 to 8 years of age.Methods: Single-center prospective cohort study including children born between 1990 and 2011 below 30 weeks' gestation and followed into 2019. The outcome measurement was NDI assessed at 2, 5, and 8 years of age. NDI is a composite score that includes cognitive, neurological, visual, and auditory functions, in which problems were categorized as none, mild, moderate, or severe. Cognitive function measured as total DQ/IQ score was assessed by standardized psychometric tests. Neurological, visual, and auditory functions were assessed by the neonatologist.Results: In total, 921 children were eligible for follow-up, of whom 726 (79%) children were assessed. No NDI was seen in 54, 54, and 62%, mild NDI was seen in 31, 36, and 30%, and moderate-to-severe NDI was seen in 15, 9.2, and 8.6% of the children at 2, 5, and 8 years, respectively. From 2 to 8 years, 63% of the children remained in the same NDI category, 20% of the children improved to a better NDI category, and 17% deteriorated toward a worse NDI category. No differences were found in baseline characteristics of infants that improved or deteriorated. Extreme prematurity, male gender and low parental education were associated with worse NDI status at all time points. Although we observed considerable individual variation over time in NDI status, the course of the trajectories in NDI were not associated with gestation, gender, and parental education.Conclusions: Continued follow-up until school life is essential in order to provide optimal and individually focused referrals and care when needed.

CONTEXT Prediction models can be a valuable tool in performing risk assessment of mortality in preterm infants. OBJECTIVE Summarizing prognostic models for predicting mortality in very preterm infants and assessing their quality. DATA SOURCES Medline was searched for all articles (up to June 2020). STUDY SELECTION All developed or externally validated prognostic models for mortality prediction in liveborn infants born DATA EXTRACTION Data were extracted by 2 independent authors. Risk of bias (ROB) and applicability assessment was performed by 2 independent authors using Prediction model Risk of Bias Assessment Tool. RESULTS One hundred forty-four models from 36 studies reporting on model development and 118 models from 34 studies reporting on external validation were included. ROB assessment revealed high ROB in the majority of the models, most often because of inadequate (reporting of) analysis. Internal and external validation was lacking in 42% and 94% of these models. Meta-analyses revealed an average C-statistic of 0.88 (95% confidence interval [CI]: 0.83–0.91) for the Clinical Risk Index for Babies score, 0.87 (95% CI: 0.81–0.92) for the Clinical Risk Index for Babies II score, 0.86 (95% CI: 0.78–0.92) for the Score for Neonatal Acute Physiology Perinatal Extension II score and 0.71 (95% CI 0.61–0.79) for the NICHD model. LIMITATIONS Occasionally, an external validation study was included, but not the development study, because studies developed in the presurfactant era or general NICU population were excluded. CONCLUSIONS Instead of developing additional mortality prediction models for preterm infants, the emphasis should be shifted toward external validation and consecutive adaption of the existing prediction models.

The transformation procedure of deriving amplitude-integrated (a)EEG from raw EEG has been well described in a purely analog prototype, however the inherent specifications within the prototype are not established or disclosed. In this paper, we aim at providing an accessible and digitalized aEEG algorithm that is evaluated quantitatively and validated in clinical practice. The algorithms, especially the filter design and envelope detection methods, applied in the transformation procedure, are investigated. The effectiveness and feasibility of the filters namely, symmetric and asymmetric filters followed with four different envelope detection methods (low-pass filtering, squaring and low-pass filtering, Hilbert transform, and moving average) are evaluated on a clinical dataset collected at Children's Hospital of Fudan University which involves 30 infants. Compared to the outputs of the commercial available (a)EEG device NicoletOne, the Spearman rank correlations (SRs) of the upper/lower tracings of aEEG using the asymmetric filter and squaring and low-pass filtering-based envelope detection method can reach over 0.97. Meanwhile, the SRs of the upper and the lower margin amplitude of aEEG can achieve 0.98 and 0.97, respectively. Furthermore, the accuracy of the obtained aEEG tracings in identifying the aEEG background activities can achieve 100%. To our knowledge, this is the first work to present a digital procedure to transform the EEG into aEEG by assessing the impact of different filters and envelope detection methods. With the high performance of the proposed approach, this work can promote the standardization of aEEG transformation procedure and the exploration of the sophisticated automatic aEEG interpretation algorithms.

Aiming at continuous unobtrusive respiration monitoring, motion robustness is paramount. However, some types of motion can completely hide the respiration information and the detection of these events is required to avoid incorrect rate estimations. Therefore, this work proposes a motion detector optimized to specifically detect severe motion of infants combined with a respiration rate detection strategy based on automatic pixels selection, which proved to be robust to motion of the infants involving head and limbs. A dataset including both thermal and RGB (Red Green Blue) videos was used amounting to a total of 43 h acquired on 17 infants. The method was successfully applied to both RGB and thermal videos and compared to the chest impedance signal. The Mean Absolute Error (MAE) in segments where some motion is present was 1.16 and 1.97 breaths/min higher than the MAE in the ideal moments where the infants were still for testing and validation set, respectively. Overall, the average MAE on the testing and validation set are 3.31 breaths/min and 5.36 breaths/min, using 64.00% and 69.65% of the included video segments (segments containing events such as interventions were excluded based on a manual annotation), respectively. Moreover, we highlight challenges that need to be overcome for continuous camera-based respiration monitoring. The method can be applied to different camera modalities, does not require skin visibility, and is robust to some motion of the infants.

Context:There is an ongoing debate on the optimal management of patent ductus arteriosus (PDA) in preterm infants. Identifying subgroup of infants who would benefit from pharmacological treatment might help.Objective:To investigate the modulating effect of the differences in methodological quality, the rate of open-label treatment, and patient characteristics on relevant outcome measures in randomized controlled trials (RCTs).Data Sources:Electronic database search between 1950 and May 2020.Study Selection:RCTs that assessed pharmacological treatment compared to placebo/no treatment.Data Extraction:Data is extracted following the PRISMA guidelines. Outcome measures were failure to ductal closure, surgical ligation, incidence of necrotizing enterocolitis, bronchopulmonary dysplasia, sepsis, periventricular leukomalacia, intraventricular hemorrhage (IVH) grade ≥3, retinopathy of prematurity and mortality.Results:Forty-seven studies were eligible. The incidence of IVH grade ≥3 was lower in the treated infants compared to the placebo/no treatment (RR 0.77, 95% CI 0.64–0.94) and in the subgroups of infants with either a gestational age Limitations:Statistical heterogeneity caused by missing data and variable definitions of outcome parameters.Conclusions:Although the quality of evidence is low, this meta-analysis suggests that pharmacological treatment of PDA reduces severe IVH in extremely preterm, extremely low birth weight infants or if treatment with indomethacin was started

Objective: This study aims to evaluate outcome after conservative management (no pharmacological/surgical intervention other than fluid restriction, diuretics, or ventilator adjustments) compared with active (pharmacological and/or surgical) treatment for patent ductus arteriosus (PDA) in preterm infants and analyze differences in outcome between randomized controlled trials (RCTs) and cohort studies.Study Design: This is a systematic literature review using PubMed, EMBASE, and Cochrane library. RCTs and cohort studies comparing conservative management with active treatment were included. Meta-analysis was used to compare conservative management with any active (pharmacological and/or surgical), any pharmacological (non-prophylactic and prophylactic), and/or surgical treatment for mortality as primary and major neonatal morbidity as secondary outcome measure. Fixed-effect analysis was used, unless heterogeneity (I2) was >50%. Outcome is presented as relative risk (RR) with 95% confidence interval.Results: Twelve cohort studies and four RCTs were included, encompassing 41,804 and 720 patients, respectively. In cohort studies, conservative management for PDA was associated with a significantly higher risk for mortality (RR, 1.34 [1.12–1.62]) but a significantly lower risk for bronchopulmonary dysplasia (RR, 0.55 [0.46–0.65]), necrotizing enterocolitis (RR, 0.85 [0.77–0.93]), intraventricular hemorrhage (RR, 0.88 [0.83–0.95]), and retinopathy of prematurity (RR, 0.47 [0.28–0.79]) compared with any active PDA treatment. Meta-analysis of the RCTs revealed no significant differences in outcome between conservative management and active treatment.Conclusion: No differences in mortality or morbidity for conservative management compared with active treatment regimens were observed in RCTs. Findings from cohort studies mainly highlight the lack of high-quality evidence for conservative management for PDA in preterm infants.

We present an approach to interpret the response of audiences to live performances by processing mobile sensor data. We apply our method on three different datasets obtained from three live performances, where each audience member wore a single tri-axial accelerometer and proximity sensor embedded inside a smart sensor pack. Using these sensor data, we developed a novel approach to predict audience members' self-reported experience of the performances in terms of enjoyment, immersion, willingness to recommend the event to others and change in mood. The proposed method uses an unsupervised method to identify informative intervals of the event, using the linkage of the audience members' bodily movements, and uses data from these intervals only to estimate the audience members' experience. We also analyze how the relative location of members of the audience can affect their experience and present an automatic way of recovering neighborhood information based on proximity sensors. We further show that the linkage of the audience members' bodily movements is informative of memorable moments which were later reported by the audience.

Objective. Presence of a patent ductus arteriosus (PDA) in neonates is assessed by echocardiography. Echocardiographic assessment has disadvantages, primarily its discontinuous nature. We hypothesize that the continuously measured ratio of arterial blood pressures (ABP) at the borders of a window surrounding the systolic peak ratio discriminates non-PDA from PDA patients. Approach. Preterm infants (gestational age n = 8) and PDA patients (n = 22), the latter with a subset of patients with closed PDA after three doses Ibuprofen (n = 10). For each patient, a six-hour ABP segment from 12 AM to 6 AM on the day of echocardiographic assessment patency or closure of the DA was selected. The mean ratio of the ABP values a samples before and p samples after the systolic peak (R ABP) was calculated for each segment. If R ABP a and p with the least misclassifications were selected (−64 and +104 ms). Main results. R ABP was significantly lower in PDA patients (median 0.95, IQR 0.06) compared to controls (median 1.05, IQR 0.10; p = 0.0024). R ABP correctly predicted 19 out of 22 patients (86.4%) and six out of eight controls (75%). R ABP increased after closure in nine out of 10 patients (median 1.01, IQR 0.04; p = 0. 0182). Significance. R ABP may discriminate preterm PDA patients from non-PDA patients and can be calculated continuously from clinical data measured during standard of care.

PURPOSE: The cardiac output (CO) response to exercise is a useful marker to grade the prognosis and severity of chronic heart failure (CHF). The recovery of the oxygen pulse (OP) is a non-invasive parameter, which is related to exercise capacity in cardiac patients. However, the relation between OP recovery and the central haemodynamic response to exercise remains to be determined. We hypothesized that an impaired OP recovery is associated with a reduced CO response to exercise in CHF patients.METHODS: Sixty one CHF patients performed cardiopulmonary exercise test with simultaneous measurement of CO. Impaired OP recovery was defined as an overshoot during the first minute of recovery or OP at 1-min recovery as a percentage of peak OP (OPRR ).RESULTS: An OP overshoot was observed in 9% (n = 5) of patients. In these patients, peak CO and VO2 were significantly lower (peak CO 7.9 ± 0.8 versus 11.2 ± 4.3 L/min and peak VO2 14.1 ± 4.7 versus 19.6 ± 5.8 ml min-1 kg-1 ). Mean relative recovery of OP was 78 ± 20%. Slow OP recovery (negative OPRR ) was seen in 13% (n = 8). Peak CO and VO2 were significantly lower in the negative OPRR group (11 ± 4 versus 8 ± 0.7 L/min and 19.7 ± 5.9 versus 14.6 ± 3.7 ml kg min-1 ). There was a significant relation between OPRR and stroke volume (SV) RR (r = .57), as well as between OPRR and a-v O2 diff RR (rs = .4).CONCLUSION: An impaired OP recovery is associated with a reduced CO response to exercise and worse functional status. Therefore, the OP recovery can be used to grade the severity of CHF.

Chorioamnionitis and preeclampsia account for the majority of preterm births worldwide. Thus far, adequate methods for early detection or prevention of these diseases are lacking. In preeclampsia, accelerated villous maturation is believed to compensate placental insufficiency. However, little is known about the effects of placental inflammation in chorioamnionitis on villous maturation. Therefore, we established a set of morphological parameters to evaluate histological villous maturity in pregnancies complicated by chorioamnionitis and preeclampsia. Preterm placentas complicated by chorioamnionitis or preeclampsia were compared to idiopathic preterm placentas and term controls. Histological villous maturation was analyzed by means of 17 histological markers. Fourteen of these markers provided information on absolute and relative numbers of the terminal villi (TV), the extent of their vascularization (using CD31-stained sections) and their exchange capacities. In addition, the numbers of syncytial bridges, syncytial apoptotic knots and shed syncytiotrophoblasts were counted. Accelerated villous maturation in preeclampsia was demonstrated by means of histological villous remodeling and confirmed by 11 relevant markers. Chorioamnionitis, however, only showed increased area of fetal capillaries. In preeclampsia, placentas may transition from growth to maturation earlier than placentas in normal pregnancies, whereas in chorioamnionitis placental changes are more acute and therefore less elaborated at a structural level. Regression analysis suggests the number of all villi and the number of terminal villi as a percentage of all villi as parameters to evaluate histological villous maturity in preeclamptic placentas and to assist diagnosis. However, we would recommend to analyze all 11 relevant parameters to judge placental maturity in detail.

This paper presents a simple yet novel method to estimate the heart frequency (HF) of neonates directly from the ECG signal, instead of using the RR-interval signals as generally done in clinical practices. From this, the heart rate (HR) can be derived. Thus, we avoid the use of peak detectors and the inherent errors that come with them.Our method leverages the highest Power Spectral Densities (PSD) of the ECG, for the bins around the frequencies related to heart rates for neonates, as they change in time (spectrograms).We tested our approach with the monitoring data of 6 days for 52 patients in a Neonate Intensive Care Unit (NICU) and compared against the HR from a commercial monitor, which produced a sample every second. The comparison showed that 92.4% of the samples have a difference lower than 5bpm. Moreover, we obtained a median MAE (Mean Absolute Error) between subjects equal to 2.28 bpm and a median RMSE (Root Mean Square Error) equal to 5.82 bpm. Although tested for neonates, we hypothesize that this method can also be customized for other populations.Finally, we analyze the failure cases of our method and found a direct co-allocation of errors due to moments with higher PSD in the lower frequencies with the presence of critical alarms related to other physiological systems (e.g. desaturation).

A high fidelity baby manikin with a colour changing mechanism is required for medical training, especially for cyanosis skin colouration assessment in a newborn baby. However, commercially available baby manikin simulators do not have the real colour-change of cyanosis skin. The efforts in increasing the fidelity of the manikin might improve the accuracy of cyanosis evaluation among the novices, thus enhances the quality of the medical training. This study contributes towards designing a colour change actuator for central cyanosis simulation in a baby manikin for medical training. The actuation method of the 3D print photochromic PLA using a low-voltage UV LED and the evaluation of its colour properties using a colour measurement device are described. The colorimetric properties of the photochromic PLA were evaluated in CIE υ′ν′ colour space. Results are presented, showing a strong relationship between the colour intensity of the UV LED and the colour of the photochromic PLA. We reflect on the potential of the photochromic PLA as an actuator in imitating the cyanosis in a baby manikin. The specific PLA we used still cannot simulate the cyanosis well. However, the idea of using PLA photochromic is still considered promising.

Background In preterm infants with Respiratory Distress Syndrome (RDS), Less Invasive Surfactant Administration (LISA) has been established to reduce the need of mechanical ventilation and might improve survival rates without bronchopulmonary dysplasia. The aim of this study was to investigate whether NICU care has changed after introduction of less invasive surfactant administration (LISA), with regard to diagnostic and therapeutic procedures in the first week of life. Methods Infants with gestational age n = 169) were retrospectively compared to infants who received surfactant after intubation (January 2012 – May 2014, n = 155). Local protocols on indication for surfactant, early onset sepsis, blood transfusions and enteral feeding did not change between both study periods. Besides, as secondary outcome complications of prematurity were compared. Data was collected from electronic patient files and compared by univariate analysis through Students T-test, Mann Whitney-U test, Pearson Chi-Square test or Linear by Linear Association. Results All baseline characteristics of both groups were comparable. Compared to controls, LISA patients received a higher total surfactant dose (208 vs.160 mg/kg; p p = 0.023), but needed less mechanical ventilation (35.5% vs. 76.8%; p p p p = 0.024), blood transfusions (24.9% vs. 41.9%, p = 0.003) and had shorter duration of antibiotic therapy for suspected early onset sepsis (3.0 vs. 5.0 days, p p = 0.048) at day seven. There were no differences in complications of prematurity. Conclusion The introduction of LISA is associated with significantly fewer diagnostic and therapeutic procedures in the first week of life, which emphasizes the beneficial effects of LISA.

Preterm infant neuronal development is related to the distribution of their sleep states. The distribution changes throughout development. Automated sleep state monitoring can become a powerful aid for development monitoring in preterm infants. Three datasets including 34 preterm infants and a total of 18,018 30 s manually annotated sleep intervals (sleep-epochs) were analyzed in this study. The annotation of sleep states includes active sleep, quiet sleep, intermediate sleep, wake, and caretaking. Four different recurrent neuronal network architectures were compared for two-state, three-state, and all-state analysis. A sequential network was used to compare long- and short-term memory and gated recurrent unit models. The other network architectures were based on the popular ResNet and ResNext architectures utilizing residual connection for more depth. The most essential sleep states, active and quiet sleep, could be separated with a kappa of 0.43 ± 0.08. Quiet versus caretaking and wake showed a kappa of 0.44 ± 0.01. The three state classifications of active versus quiet versus intermediate sleep resulted in a kappa of 0.35 ± 0.07 and active versus quiet versus wake and caretaking resulted in a kappa of 0.33 ± 0.04. The all-state classification was underperforming with probably due to difficulty in separating subtle differences between all states and a lack of sufficient training data for the minority classes.

Pain or discomfort exposure during hospitalization of preterm infants has an adverse effect on brain development. Contactless monitoring has been considered to be a promising approach for detecting infant pain and discomfort moments continuously. In this study, our main objective is to develop an automated discomfort detection system based on video monitoring, allowing caregivers to provide timely and appropriate treatments. The system first employs the optical ow to estimate infant body motion trajectories across video frames. Following the movement estimation, Log Mel-spectrogram, Mel Frequency Cepstral Coefficients (MFCCs) and Spectral Subband Centroid Frequency (SSCF) features are calculated from the One-Dimensional (1D) motion signal. These features enable the representation of the 1D motion signals by Two-Dimensional (2D) time-frequency representations of the distribution of signal energy. Finally, deep Convolutional Neural Networks (CNNs) are applied on the 2D images for the binary - comfort/discomfort classification. The performance of the model is assessed using leave-one-infant- out cross-validation. Our algorithm was evaluated on a dataset containing 183 video segments recorded from 11 infants during 17 heel prick events, which is a pain stimulus associated with a routine care procedure. Experimental results showed an area under the receiver operating characteristic curve of 0.985 and an accuracy of 94.2%, which offers a promising possibility to deploy the proposed system in clinical practice.