Joppe Nijman

Objective: Pediatric patients with congenital heart disease (CHD) are at risk of non-cardiac complications that impact outcome. Early prognostication is necessary to tailor treatment and improve parent counseling. This systematic review assessed the prognostic value of perioperative near-infrared spectroscopy (NIRS) monitoring of regional oxygen saturation (rSO₂) with regard to brain injury, brain development, neurodevelopment, acute kidney injury (AKI), and necrotizing enterocolitis (NEC) in pediatric CHD patients. Data Sources: PubMed and Embase databases. Study Selection: We searched for original research articles published up to 2023 describing children (younger than 18 yr) with CHD using perioperative rSO₂ monitoring, and reporting their association with at least one of the following outcomes: AKI, NEC, brain injury, brain development, or neurodevelopment. Data Extraction: Ten studies, including a total of 562 patients, were included for brain injury, 4 studies with 229 patients for brain development, 15 studies with 1024 patients for neurodevelopment, 15 studies with 1168 patients for AKI, and 3 studies including 250 patients for NEC. The majority of the studies had a moderate to high risk of bias as assessed by the Cochrane Quality in Prognosis Studies tool. High heterogeneity in study populations and NIRS measurements was found. Data Synthesis: Of the studies we identified, 5 of 10 in brain injury, 3 of 4 in brain development, 10 of 15 in neurodevelopment, 9 of 15 in AKI, and 1 of 3 in NEC reported associations with rSO₂. No meta-analysis could be performed due to heterogeneity. Conclusions: Our findings highlight the need to improve methodological quality and reduce intra- and interstudy heterogeneity. Several methodological recommendations to improve future research were formulated.

Objective: Intraoperative sodium changes and new postoperative white matter injury are prevalent in neonates with congenital heart disease (CHD) who undergo cardiopulmonary bypass surgery. Rapid sodium correction in hyponatremia is associated with white matter injury in adults. This study examined the potential effects of a rapid intraoperative sodium increase on white matter microstructure in neonates with CHD. Methods: 83 neonates with CHD underwent postoperative diffusion weighted magnetic resonance imaging within three weeks of cardiopulmonary bypass surgery as part of routine clinical practice. Mean diffusivity, radial diffusivity, and axial diffusivity were calculated using Diffusion Tensor Imaging. Voxel-wise associations within the core of white matter tracts were assessed using tract-based spatial statistics. Serum sodium measurements were extracted from clinical notes. Maximum intraoperative sodium range was defined as the difference between the minimum and maximum serum sodium observations during surgery. The rate of sodium change was calculated as this range divided by the time interval in hours. Results: A larger maximum intraoperative sodium range was associated with lower axial diffusivity values in the right centrum semiovale, bilateral precentral white matter, right inferior longitudinal fasciculus, and right optic radiation (p<0.05, family wise error rate corrected). There were no other associations between diffusivities and sodium range or rate of change. Conclusions: A larger maximum intraoperative sodium range was associated with reduced axial diffusivity, possibly indicating axonal injury in neonates with CHD after cardiopulmonary bypass surgery. These findings underscore the importance of limiting perioperative osmotic stress to optimize white matter microstructural development. Central picture: White matter regions affected by intraoperative sodium range. Central message: Intraoperative serum sodium changes are associated with white matter microstructural alterations in neonates with congenital heart disease undergoing cardiac surgery with cardiopulmonary bypass. Perspective statement: Rapid sodium changes are common in neonatal congenital heart disease surgery and are associated with white matter injury in other clinical populations. This study shows altered white matter microstructure in neonates with larger intraoperative sodium ranges, emphasizing the importance of limiting perioperative osmotic stress to optimise white matter microstructural development in this population.

There are several causes of generalized edema in sick neonates. We describe two newborns that developed progressive and treatment‐resistant generalized edema. We suggest this is due to impaired lymphatic flow from the thoracic duct as a result of a central venous catheter in the left subclavian vein.

Unobtrusive monitoring of children’s heart rate (HR) and respiratory rate (RR) can be valuable for promoting the early detection of potential health issues, improving communication with healthcare providers and reducing unnecessary hospital visits. A promising solution for wireless vital sign monitoring is radar technology. This paper presents a novel approach for the simultaneous estimation of children’s RR and HR utilizing ultra-wideband (UWB) radar using a deep transfer learning algorithm in a cohort of 55 children. The HR and RR are calculated by processing radar signals via spectrogram from time epochs of 10 s (25 sample length of hamming window with 90% overlap) and then transforming the resultant representation into 2-dimensional images. These images were fed into a pre-trained Visual Geometry Group-16 (VGG-16) model (trained on ImageNet dataset), with weights of five added layers fine-tuned using the proposed data. The prediction on the test data achieved a mean absolute error (MAE) of 7.3 beats per minute (BPM < 6.5% of average HR) and 2.63 breaths per minute (BPM < 7% of average RR). We also achieved a significant Pearson’s correlation of 77% and 81% between true and extracted for HR and RR, respectively. HR and RR samples are extracted every 10 s.

Introduction Increasingly, hospitals rely on local clinical practice guidelines (CPGs) alongside national guidance to standardise clinical care. This study examines variation between national and local CPGs, using the example of acute paediatric asthma (APA) CPGs from the United Kingdom and the Netherlands. Methods Fifteen British and Dutch local CPGs were collected with the matching national guidance for the management of APA. The drug sequences, routes and methods of administration recommended for patients with severe APA were represented. Deviations from national guidance were measured. Variation in recommended doses of intravenous salbutamol was examined. CPG quality was assessed using the AGREE II instrument. Results British and Dutch national CPGs differed in the recommended drug choices, sequences, routes and methods of administration for severe APA. Local British CPGs diverged from national guidance for 23% of their recommended interventions compared to 8% for Dutch local CPGs. Variation in second-line recommendations was greater than for first-line recommendations across local CPGs from both countries. Recommended starting doses for salbutamol infusions varied by more than tenfold. The quality of the sampled local CPGs was low across five out of six AGREE domains (Conclusions Local CPGs for the management of severe APA featured substantial variation and frequently diverged from national guidance. Their methodological quality was low. Although limited to one condition, this study suggests that unmeasured variation across local CPGs may contribute to variation of care more broadly, potentially undermining healthcare quality.

Background: Critical congenital heart disease (cCHD)—requiring cardiac intervention in the first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs—especially the brain—may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention. Objective: This study aimed to develop a clinical deterioration detection algorithm for PICU patients with cCHD. Methods: Retrospectively, synchronous per-second data of cerebral regional oxygen saturation (rSO2) and 4 vital parameters (respiratory rate, heart rate, oxygen saturation, and invasive mean blood pressure) in neonates with cCHD admitted to the University Medical Center Utrecht, the Netherlands, between 2002 and 2018 were extracted. Patients were stratified based on mean oxygen saturation during admission to account for physiological differences between acyanotic and cyanotic cCHD. Each subset was used to train our algorithm in classifying data as either stable, unstable, or sensor dysfunction. The algorithm was designed to detect combinations of parameters abnormal to the stratified subpopulation and significant deviations from the patient’s unique baseline, which were further analyzed to distinguish clinical improvement from deterioration. Novel data were used for testing, visualized in detail, and internally validated by pediatric intensivists. Results: A retrospective query yielded 4600 hours and 209 hours of per-second data in 78 and 10 neonates for, respectively, training and testing purposes. During testing, stable episodes occurred 153 times, of which 134 (88%) were correctly detected. Unstable episodes were correctly noted in 46 of 57 (81%) observed episodes. Twelve expert-confirmed unstable episodes were missed in testing. Time-percentual accuracy was 93% and 77% for, respectively, stable and unstable episodes. A total of 138 sensorial dysfunctions were detected, of which 130 (94%) were correct. Conclusions: In this proof-of-concept study, a clinical deterioration detection algorithm was developed and retrospectively evaluated to classify clinical stability and instability, achieving reasonable performance considering the heterogeneous population of neonates with cCHD. Combined analysis of baseline (ie, patient-specific) deviations and simultaneous parameter-shifting (ie, population-specific) proofs would be promising with respect to enhancing applicability to heterogeneous critically ill pediatric populations. After prospective validation, the current—and comparable—models may, in the future, be used in the automated detection of clinical deterioration and eventually provide data-driven monitoring support to the medical team, allowing for timely intervention.

BACKGROUND Critical congenital heart disease (cCHD)—requiring cardiac intervention in the first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs—especially the brain—may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention. OBJECTIVE This study aimed to develop a clinical deterioration detection algorithm for PICU patients with cCHD. METHODS Retrospectively, synchronous per-second data of cerebral regional oxygen saturation (rSO2) and 4 vital parameters (respiratory rate, heart rate, oxygen saturation, and invasive mean blood pressure) in neonates with cCHD admitted to the University Medical Center Utrecht, the Netherlands, between 2002 and 2018 were extracted. Patients were stratified based on mean oxygen saturation during admission to account for physiological differences between acyanotic and cyanotic cCHD. Each subset was used to train our algorithm in classifying data as either stable, unstable, or sensor dysfunction. The algorithm was designed to detect combinations of parameters abnormal to the stratified subpopulation and significant deviations from the patient’s unique baseline, which were further analyzed to distinguish clinical improvement from deterioration. Novel data were used for testing, visualized in detail, and internally validated by pediatric intensivists. RESULTS A retrospective query yielded 4600 hours and 209 hours of per-second data in 78 and 10 neonates for, respectively, training and testing purposes. During testing, stable episodes occurred 153 times, of which 134 (88%) were correctly detected. Unstable episodes were correctly noted in 46 of 57 (81%) observed episodes. Twelve expert-confirmed unstable episodes were missed in testing. Time-percentual accuracy was 93% and 77% for, respectively, stable and unstable episodes. A total of 138 sensorial dysfunctions were detected, of which 130 (94%) were correct. CONCLUSIONS In this proof-of-concept study, a clinical deterioration detection algorithm was developed and retrospectively evaluated to classify clinical stability and instability, achieving reasonable performance considering the heterogeneous population of neonates with cCHD. Combined analysis of baseline (ie, patient-specific) deviations and simultaneous parameter-shifting (ie, population-specific) proofs would be promising with respect to enhancing applicability to heterogeneous critically ill pediatric populations. After prospective validation, the current—and comparable—models may, in the future, be used in the automated detection of clinical deterioration and eventually provide data-driven monitoring support to the medical team, allowing for timely intervention.

Background: Infants with congenital heart disease are at risk of brain injury and impaired neurodevelopment. The aim was to investigate risk factors for perioperative brain lesions in infants with congenital heart disease. Methods: Infants with transposition of the great arteries, single ventricle physiology, and left ventricular outflow tract and/or aortic arch obstruction undergoing cardiac surgery <6 weeks after birth from 3 European cohorts (Utrecht, Zurich, and London) were combined. Brain lesions were scored on preoperative (transposition of the great arteries N=104; single ventricle physiology N=35; and left ventricular outflow tract and/or aortic arch obstruction N=41) and postoperative (transposition of the great arteries N=88; single ventricle physiology N=28; and left ventricular outflow tract and/or aortic arch obstruction N=30) magnetic resonance imaging for risk factor analysis of arterial ischemic stroke, cerebral sinus venous thrombosis, and white matter injury. Results: Preoperatively, induced vaginal delivery (odds ratio [OR], 2.23 [95% CI, 1.06–4.70]) was associated with white matter injury and balloon atrial septostomy increased the risk of white matter injury (OR, 2.51 [95% CI, 1.23–5.20]) and arterial ischemic stroke (OR, 4.49 [95% CI, 1.20–21.49]). Postoperatively, younger postnatal age at surgery (OR, 1.18 [95% CI, 1.05–1.33]) and selective cerebral perfusion, particularly at ≤20 °C (OR, 13.46 [95% CI, 3.58–67.10]), were associated with new arterial ischemic stroke. Single ventricle physiology was associated with new white matter injury (OR, 2.88 [95% CI, 1.20–6.95]) and transposition of the great arteries with new cerebral sinus venous thrombosis (OR, 13.47 [95% CI, 2.28–95.66]). Delayed sternal closure (OR, 3.47 [95% CI, 1.08–13.06]) and lower intraoperative temperatures (OR, 1.22 [95% CI, 1.07–1.36]) also increased the risk of new cerebral sinus venous thrombosis. Conclusions: Delivery planning and surgery timing may be modifiable risk factors that allow personalized treatment to minimize the risk of perioperative brain injury in severe congenital heart disease. Further research is needed to optimize cerebral perfusion techniques for neonatal surgery and to confirm the relationship between cerebral sinus venous thrombosis and perioperative risk factors.

Neurodevelopmental disabilities are common in infants with critical congenital heart disease (CCHD). A prospective, longitudinal cohort study was conducted to establish the prevalence and early determinants of adverse motor outcomes in infants who underwent cardiac surgery with cardiopulmonary bypass before six months of age. Motor development was assessed in 147 preschoolers using the Movement Assessment Battery for children-II. Although the majority displayed an average motor development, 22% of preschool children with CCHD deteriorated in their motor developmental score compared to their previous assessment at 18 months, especially in those with an aortic arch anomaly (AAA) (35%). Individual stability over time appeared to be moderate and the number of children with a motor delay increased, up to 20% in children with AAA. Motor development up to 42 months was best predicted by gestational age, cardio pulmonary bypass time, aortic cross clamp time, number of heart catheterizations up to 18 months and early motor outcomes. The increase in number of preschool children with a motor delay underlines the importance of longitudinal screening of motor skills in children with CCHD at risk for adverse motor outcomes. Offering early interventions may protect their current and future cardiovascular health as motor development is an independent predictor of exercise capacity, physical activity and participation in daily living.