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  • 1
    In: European Journal of Pediatrics, Springer Science and Business Media LLC, Vol. 180, No. 7 ( 2021-07), p. 2271-2279
    Abstract: The coronavirus disease 2019 pandemic has enormous impact on society and healthcare. Countries imposed lockdowns, which were followed by a reduction in care utilization. The aims of this study were to quantify the effects of lockdown on pediatric care in the Netherlands, to elucidate the cause of the observed reduction in pediatric emergency department (ED) visits and hospital admissions, and to summarize the literature regarding the effects of lockdown on pediatric care worldwide. ED visits and hospital admission data of 8 general hospitals in the Netherlands between January 2016 and June 2020 were summarized per diagnosis group (communicable infections, noncommunicable infections, (probable) infection-related, and noninfectious). The effects of lockdown were quantified with a linear mixed effects model. A literature review regarding the effect of lockdowns on pediatric clinical care was performed. In total, 126,198 ED visits and 47,648 admissions were registered in the study period. The estimated reduction in general pediatric care was 59% and 56% for ED visits and admissions, respectively. The largest reduction was observed for communicable infections (ED visits: 76%; admissions: 77%), whereas the reduction in noninfectious diagnoses was smaller (ED visits 36%; admissions: 37%). Similar reductions were reported worldwide, with decreases of 30–89% for ED visits and 19–73% for admissions. Conclusion : Pediatric ED utilization and hospitalization during lockdown were decreased in the Netherlands and other countries, which can largely be attributed to a decrease in communicable infectious diseases. Care utilization for other conditions was decreased as well, which may indicate that care avoidance during a pandemic is significant. What is Known: • The COVID-19 pandemic had enormous impact on society. • Countries imposed lockdowns to curb transmission rates, which were followed by a reduction in care utilization worldwide. What is New : • The Dutch lockdown caused a significant decrease in pediatric ED utilization and hospitalization, especially in ED visits and hospital admissions because of infections that were not caused by SARS-CoV-2. • Care utilization for noninfectious diagnoses was decreased as well, which may indicate that pediatric care avoidance during a pandemic is significant.
    Type of Medium: Online Resource
    ISSN: 0340-6199 , 1432-1076
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2647723-3
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  • 2
    In: European Respiratory Journal, European Respiratory Society (ERS), Vol. 59, No. 6 ( 2022-06), p. 2100208-
    Abstract: Digital biomarkers are a promising novel method to capture clinical data in a home setting. However, clinical validation prior to implementation is of vital importance. The aim of this study was to clinically validate physical activity, heart rate, sleep and forced expiratory volume in 1 s (FEV 1 ) as digital biomarkers measured by a smartwatch and portable spirometer in children with asthma and cystic fibrosis (CF). Methods This was a prospective cohort study including 60 children with asthma and 30 children with CF (aged 6–16 years). Participants wore a smartwatch, performed daily spirometry at home and completed a daily symptom questionnaire for 28 days. Physical activity, heart rate, sleep and FEV 1 were considered candidate digital end-points. Data from 128 healthy children were used for comparison. Reported outcomes were compliance, difference between patients and controls, correlation with disease activity, and potential to detect clinical events. Analysis was performed with linear mixed effects models. Results Median compliance was 88%. On average, patients exhibited lower physical activity and FEV 1 compared with healthy children, whereas the heart rate of children with asthma was higher compared with healthy children. Days with a higher symptom score were associated with lower physical activity for children with uncontrolled asthma and CF. Furthermore, FEV 1 was lower and (nocturnal) heart rate was higher for both patient groups on days with more symptoms. Candidate biomarkers appeared able to describe a pulmonary exacerbation. Conclusions Portable spirometer- and smartwatch-derived digital biomarkers show promise as candidate end-points for use in clinical trials or clinical care in paediatric lung disease.
    Type of Medium: Online Resource
    ISSN: 0903-1936 , 1399-3003
    Language: English
    Publisher: European Respiratory Society (ERS)
    Publication Date: 2022
    detail.hit.zdb_id: 2834928-3
    detail.hit.zdb_id: 1499101-9
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  • 3
    In: Frontiers in Pediatrics, Frontiers Media SA, Vol. 9 ( 2021-4-13)
    Abstract: Introduction: The duration and frequency of crying of an infant can be indicative of its health. Manual tracking and labeling of crying is laborious, subjective, and sometimes inaccurate. The aim of this study was to develop and technically validate a smartphone-based algorithm able to automatically detect crying. Methods: For the development of the algorithm a training dataset containing 897 5-s clips of crying infants and 1,263 clips of non-crying infants and common domestic sounds was assembled from various online sources. OpenSMILE software was used to extract 1,591 audio features per audio clip. A random forest classifying algorithm was fitted to identify crying from non-crying in each audio clip. For the validation of the algorithm, an independent dataset consisting of real-life recordings of 15 infants was used. A 29-min audio clip was analyzed repeatedly and under differing circumstances to determine the intra- and inter- device repeatability and robustness of the algorithm. Results: The algorithm obtained an accuracy of 94% in the training dataset and 99% in the validation dataset. The sensitivity in the validation dataset was 83%, with a specificity of 99% and a positive- and negative predictive value of 75 and 100%, respectively. Reliability of the algorithm appeared to be robust within- and across devices, and the performance was robust to distance from the sound source and barriers between the sound source and the microphone. Conclusion: The algorithm was accurate in detecting cry duration and was robust to various changes in ambient settings.
    Type of Medium: Online Resource
    ISSN: 2296-2360
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2711999-3
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  • 4
    In: Pediatric Pulmonology, Wiley, Vol. 55, No. 9 ( 2020-09), p. 2463-2470
    Abstract: Diagnosis and follow‐up of respiratory diseases traditionally rely on pulmonary function tests (PFTs), which are currently performed in hospitals and require trained personnel. Smartphone‐connected spirometers, like the Air Next spirometer, have been developed to aid in the home monitoring of patients with pulmonary disease. The aim of this study was to investigate the technical validity and usability of the Air Next spirometer in pediatric patients. Methods Device variability was tested with a calibrated syringe. About 90 subjects, aged 6 to 16, were included in a prospective cohort study. Fifty‐eight subjects performed conventional spirometry and subsequent Air Next spirometry. The bias and the limits of agreement between the measurements were calculated. Furthermore, subjects used the device for 28 days at home and completed a subject‐satisfaction questionnaire at the end of the study period. Results Interdevice variability was 2.8% and intradevice variability was 0.9%. The average difference between the Air Next and conventional spirometry was 40 mL for forced expiratory volume in 1 second (FEV1) and 3 mL for forced vital capacity (FVC). The limits of agreement were −270 mL and +352 mL for FEV1 and −403 mL and +397 mL for FVC. About 45% of FEV1 measurements and 41% of FVC measurements at home were acceptable and reproducible according to American Thoracic Society/European Respiratory Society criteria. Parents scored difficulty, usefulness, and reliability of the device 1.9, 3.5, and 3.8 out of 5, respectively. Conclusion The Air Next device shows validity for the measurement of FEV1 and FVC in a pediatric patient population.
    Type of Medium: Online Resource
    ISSN: 8755-6863 , 1099-0496
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 1491904-7
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  • 5
    In: Therapeutic Drug Monitoring, Ovid Technologies (Wolters Kluwer Health), Vol. 43, No. 4 ( 2021-08), p. 546-554
    Abstract: Historically, pharmacokinetic (PK) studies and therapeutic drug monitoring (TDM) have relied on plasma as a sampling matrix. Noninvasive sampling matrices, such as saliva, can reduce the burden on pediatric patients. The variable plasma–saliva relationship can be quantified using population PK models (nonlinear mixed-effect models). However, criteria regarding acceptable levels of variability in such models remain unclear. In this simulation study, the authors aimed to propose a saliva TDM evaluation framework and evaluate model requirements in the context of TDM, with gentamicin and lamotrigine as model compounds. Methods: Two population pharmacokinetic models for gentamicin in neonates and lamotrigine in pediatrics were extended with a saliva compartment including a delay constant (k SALIVA ), a saliva:plasma ratio, and between-subject variability (BSV) on both parameters. Subjects were simulated using a realistic covariate distribution. Bayesian maximum a posteriori TDM was applied to assess the performance of an increasing number of TDM saliva samples and varying levels of BSV and residual variability. Saliva TDM performance was compared with plasma TDM performance. The framework was applied to a known voriconazole saliva model as a case study. Results: TDM performed using saliva resulted in higher target attainment than no TDM, and a residual proportional error 〈 25% on saliva observations led to saliva TDM performance comparable with plasma TDM. BSV on k SALIVA did not affect performance, whereas increasing BSV on saliva:plasma ratios by 〉 25% for gentamicin and 〉 50% for lamotrigine reduced performance. The simulated target attainment for voriconazole saliva TDM was 〉 90%. Conclusions: Saliva as an alternative matrix for noninvasive TDM is possible using nonlinear mixed-effect models combined with Bayesian optimization. This article provides a workflow to explore TDM performance for compounds measured in saliva and can be used for evaluation during model building.
    Type of Medium: Online Resource
    ISSN: 0163-4356
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 2048919-5
    SSG: 15,3
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  • 6
    In: Digital Biomarkers, S. Karger AG, Vol. 6, No. 1 ( 2022-3-31), p. 19-30
    Abstract: 〈 b 〉 〈 i 〉 Introduction: 〈 /i 〉 〈 /b 〉 Clinical research and treatment of childhood obesity is challenging, and objective biomarkers obtained in a home-setting are needed. The aim of this study was to determine the potential of novel digital endpoints gathered by a home-monitoring platform in pediatric obesity. 〈 b 〉 〈 i 〉 Methods: 〈 /i 〉 〈 /b 〉 In this prospective observational study, 28 children with obesity aged 6–16 years were included and monitored for 28 days. Patients wore a smartwatch, which measured physical activity (PA), heart rate (HR), and sleep. Furthermore, daily blood pressure (BP) measurements were performed. Data from 128 healthy children were utilized for comparison. Differences between patients and controls were assessed via linear mixed effect models. 〈 b 〉 〈 i 〉 Results: 〈 /i 〉 〈 /b 〉 Data from 28 patients (average age 11.6 years, 46% male, average body mass index 30.9) and 128 controls (average age 11.1 years, 46% male, average body mass index 18.0) were analyzed. Patients were recruited between November 2018 and February 2020. For patients, the median compliance for the measurements ranged from 55% to 100% and the highest median compliance was observed for the smartwatch-related measurements (81–100%). Patients had a lower daily PA level (4,597 steps vs. 6,081 steps, 95% confidence interval [CI] 862–2,108) and peak PA level (1,115 steps vs. 1,392 steps, 95% CI 136–417), a higher nighttime HR (81 bpm vs. 71 bpm, 95% CI 6.3–12.3) and daytime HR (98 bpm vs. 88 bpm, 95% CI 7.6–12.6), a higher systolic BP (115 mm Hg vs. 104 mm Hg, 95% CI 8.1–14.5) and diastolic BP (76 mm Hg vs. 65 mm Hg, 95% CI 8.7–12.7), and a shorter sleep duration (difference 0.5 h, 95% CI 0.2–0.7) compared to controls. 〈 b 〉 〈 i 〉 Conclusion: 〈 /i 〉 〈 /b 〉 Remote monitoring via wearables in pediatric obesity has the potential to objectively measure the disease burden in the home-setting. The novel endpoints demonstrate significant differences in PA level, HR, BP, and sleep duration between patients and controls. Future studies are needed to determine the capacity of the novel digital endpoints to detect effect of interventions.
    Type of Medium: Online Resource
    ISSN: 2504-110X
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2022
    detail.hit.zdb_id: 2906645-1
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  • 7
    In: Pediatric Pulmonology, Wiley, Vol. 57, No. 3 ( 2022-03), p. 761-767
    Abstract: Coughing is a common symptom in pediatric lung disease and cough frequency has been shown to be correlated to disease activity in several conditions. Automated cough detection could provide a noninvasive digital biomarker for pediatric clinical trials or care. The aim of this study was to develop a smartphone‐based algorithm that objectively and automatically counts cough sounds of children. Methods The training set was composed of 3228 pediatric cough sounds and 480,780 noncough sounds from various publicly available sources and continuous sound recordings of 7 patients admitted due to respiratory disease. A Gradient Boost Classifier was fitted on the training data, which was subsequently validated on recordings from 14 additional patients aged 0–14 admitted to the pediatric ward due to respiratory disease. The robustness of the algorithm was investigated by repeatedly classifying a recording with the smartphone‐based algorithm during various conditions. Results The final algorithm obtained an accuracy of 99.7%, sensitivity of 47.6%, specificity of 99.96%, positive predictive value of 82.2% and negative predictive value 99.8% in the validation dataset. The correlation coefficient between manual‐ and automated cough counts in the validation dataset was 0.97 ( p   〈  .001). The intra‐ and interdevice reliability of the algorithm was adequate, and the algorithm performed best at an unobstructed distance of 0.5–1 m from the audio source. Conclusion This novel smartphone‐based pediatric cough detection application can be used for longitudinal follow‐up in clinical care or as digital endpoint in clinical trials.
    Type of Medium: Online Resource
    ISSN: 8755-6863 , 1099-0496
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 1491904-7
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  • 8
    In: Pediatric Pulmonology, Wiley, Vol. 58, No. 4 ( 2023-04), p. 1229-1236
    Abstract: The imposition of lockdowns during the severe acute respiratory syndrome coronavirus‐2 pandemic led to a significant decrease in pediatric care utilization in 2020. After restrictions were loosened, a surge in pediatric respiratory disease was observed in pediatric wards. The aim of this study was to quantify the effect of the lockdown(s) on the incidence of pediatric respiratory disease. Methods For this multicenter retrospective study, emergency department (ED) visit and admission data between January 2017 and September 2021 was collected from eight general hospitals in the Netherlands. Clinical diagnoses were extracted and categorized in groups (“communicable infectious disease,” “all respiratory infections,” “upper respiratory tract infection,” “lower respiratory tract infection,” and “asthma/preschool wheezing”). The incidence of admissions and ED visits during 2020 and 2021 was compared to the incidence in 2017–2019. Results Successive lockdowns resulted in a maximum decrease of 61% and 57% in ED visits and admissions, respectively. After loosening restrictions during the summer of 2021, a 48% overall increase in ED visits and 31% overall increase in admission numbers was observed in July compared to the average July in 2017–2019. This was explained by a 381% increase in ED visits and a 528% increase in ward admissions due to overall respiratory infections, mainly due to lower respiratory tract infections. Conclusions Successive lockdowns in the spring and winter of 2020 and 2021 led to a decreased incidence of communicable infections, especially respiratory tract infections. The resulting lack of pediatric immunity resulted in an off‐season surge in care utilization at an unexpected moment.
    Type of Medium: Online Resource
    ISSN: 8755-6863 , 1099-0496
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1491904-7
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  • 9
    In: Respiration, S. Karger AG, Vol. 100, No. 10 ( 2021), p. 979-988
    Abstract: 〈 b 〉 〈 i 〉 Background: 〈 /i 〉 〈 /b 〉 Pediatric patients admitted for acute lung disease are treated and monitored in the hospital, after which full recovery is achieved at home. Many studies report in-hospital recovery, but little is known regarding the time to full recovery after hospital discharge. Technological innovations have led to increased interest in home-monitoring and digital biomarkers. The aim of this study was to describe at-home recovery of 3 common pediatric respiratory diseases using a questionnaire and wearable device. 〈 b 〉 〈 i 〉 Methods: 〈 /i 〉 〈 /b 〉 In this study, patients admitted due to pneumonia ( 〈 i 〉 n 〈 /i 〉 = 30), preschool wheezing ( 〈 i 〉 n 〈 /i 〉 = 30), and asthma exacerbation (AE; 〈 i 〉 n 〈 /i 〉 = 11) were included. Patients were monitored with a smartwatch and a questionnaire during admission, with a 14-day recovery period and a 10-day “healthy” period. Median compliance was calculated, and a mixed-effects model was fitted for physical activity and heart rate (HR) to describe the recovery period, and the physical activity recovery trajectory was correlated to respiratory symptom scores. 〈 b 〉 〈 i 〉 Results: 〈 /i 〉 〈 /b 〉 Median compliance was 47% (interquartile range [IQR] 33–81%) during the entire study period, 68% (IQR 54–91%) during the recovery period, and 28% (IQR 0–74%) during the healthy period. Patients with pneumonia reached normal physical activity 12 days postdischarge, while subjects with wheezing and AE reached this level after 5 and 6 days, respectively. Estimated mean physical activity was closely correlated with the estimated mean symptom score. HR measured by the smartwatch showed a similar recovery trajectory for subjects with wheezing and asthma, but not for subjects with pneumonia. 〈 b 〉 〈 i 〉 Conclusions: 〈 /i 〉 〈 /b 〉 The digital biomarkers, physical activity, and HR obtained via smartwatch show promise for quantifying postdischarge recovery in a noninvasive manner, which can be useful in pediatric clinical trials and clinical care.
    Type of Medium: Online Resource
    ISSN: 0025-7931 , 1423-0356
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2021
    detail.hit.zdb_id: 1464419-8
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