BackgroundThe incidence of severe asthma exacerbations (SAE) requiring a pediatric intensive care unit (PICU) admission during the coronavirus disease 2019 (COVID-19) pandemic (and its association... Show moreBackgroundThe incidence of severe asthma exacerbations (SAE) requiring a pediatric intensive care unit (PICU) admission during the coronavirus disease 2019 (COVID-19) pandemic (and its association with public restrictions) is largely unknown. We examined the trend of SAE requiring PICU admission before, during, and after COVID-19 restrictions in Amsterdam, the Netherlands, and its relationship with features such as environmental triggers and changes in COVID-19 restriction measures.MethodsIn this single-center, retrospective cohort study, all PICU admissions of children aged >= 2 years for severe asthma at the Amsterdam UMC between 2018 and 2022 were included. The concentrations of ambient fine particulate matter (PM2.5) and pollen were obtained from official monitoring stations.ResultsBetween January 2018 and December 2022, 228 children were admitted to the PICU of the Amsterdam UMC for SAE. While we observed a decrease in admissions during periods of more stringent restriction, there was an increase in the PICU admission rate for SAE in some periods following the lifting of restrictions. In particular, following the COVID-19 restrictions in 2021, we observed a peak incidence of admissions from August to November, which was higher than any other peak during the indicated years. No association with air pollution or pollen was observed.ConclusionWe hypothesize that an increase in clinically diagnosed viral infections after lockdown periods was the reason for the altered incidence of SAE at the PICU in late 2021, rather than air pollution and pollen concentrations. Show less
Cavigioli, F.; Bresesti, I.; Peri, A. di; Cerritelli, F.; Gazzolo, D.; Gavilanes, A.W.D.; ... ; Lista, G. 2022
AimTo verify the added value of respiratory function monitor (RFM) to assess ventilation and the heart rate (HR) changes during stabilization of preterm infants. MethodsPreterm infants <32 weeks... Show moreAimTo verify the added value of respiratory function monitor (RFM) to assess ventilation and the heart rate (HR) changes during stabilization of preterm infants. MethodsPreterm infants <32 weeks' gestation, bradycardic at birth and in need for positive pressure ventilation (PPV) were included. The first 15 min of stabilization was monitored with RFM. Three time points were identified according to HR values (T0 the start of mask PPV; T1 the HR rise >100 bpm; T2 the delivery of the last PPV). For each inflation, PIP, PEEP, MAP, expired tidal volume/kg (Vte/kg), and mean dynamic compliance (Cdyn) were analyzed. ResultsPIP and MAP values were significantly higher at T1 (27.09 +/- 5.37 and 17.47 +/- 3.85 cmH(2)O) and at T2 (24.7 +/- 3.86 and 15.2 +/- 3.78 cmH(2)O) compared to T0 (24.05 +/- 2.27 and 15.85 +/- 2.77 cmH(2)O). PEEP at T1 was significantly higher (6.27 +/- 2.17 cmH(2)O) compared to T2 (5.61 +/- 1.50 cmH(2)O). Vte/kg showed significantly lower T0 values (3.57 +/- 2.14 ml/kg) compared to T1 (6.18 +/- 2.51 ml/kg) and T2 (6.89 +/- 2.40 ml/kg). There was a significant effect of time on Cdyn. ConclusionsA clear correspondence between HR rise and adequate Vte/kg during stabilization of very preterm infants was highlighted. RFM might be useful to tailor ventilation, following real-time changes of lung compliance. Show less
IntroductionCoughing 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... Show moreIntroductionCoughing 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.MethodsThe 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.ResultsThe 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.ConclusionThis novel smartphone-based pediatric cough detection application can be used for longitudinal follow-up in clinical care or as digital endpoint in clinical trials. Show less
Background The marked heterogeneity in cystic fibrosis (CF) disease complicates the selection of those most likely to benefit from existing or emergent treatments. Objective We aimed to predict the... Show moreBackground The marked heterogeneity in cystic fibrosis (CF) disease complicates the selection of those most likely to benefit from existing or emergent treatments. Objective We aimed to predict the progression of bronchiectasis in preschool children with CF. Methods Using data collected up to 3 years of age, in the Australian Respiratory Early Surveillance Team for CF cohort study, clinical information, chest computed tomography (CT) scores, and biomarkers from bronchoalveolar lavage were assessed in a multivariable linear regression model as predictors for CT bronchiectasis at age 5-6. Results Follow-up at 5-6 years was available in 171 children. Bronchiectasis prevalence at 5-6 was 134/171 (78%) and median bronchiectasis score was 3 (range 0-12). The internally validated multivariate model retained eight independent predictors accounting for 37% (adjusted R-2) of the variance in bronchiectasis score. The strongest predictors of future bronchiectasis were: pancreatic insufficiency, repeated intravenous treatment courses, recurrent lower respiratory infections in the first 3 years of life, and lower airway inflammation. Dichotomizing the resulting prediction score at a bronchiectasis score of above the median resulted in a diagnostic odds ratio of 13 (95% confidence interval [CI], 6.3-27) with positive and negative predictive values of 80% (95% CI, 72%-86%) and 77% (95% CI, 69%-83%), respectively. Conclusion Early assessment of bronchiectasis risk in children with CF is feasible with reasonable precision at a group level, which can assist in high-risk patient selection for interventional trials. The unexplained variability in disease progression at individual patient levels remains high, limiting the use of this model as a clinical prediction tool. Show less
Background: Long-COVID is a well-documented multisystem disease in adults. Far less is known about long-term sequelae of COVID in children. Here, we report on the occurrence of long-COVID in Dutch... Show moreBackground: Long-COVID is a well-documented multisystem disease in adults. Far less is known about long-term sequelae of COVID in children. Here, we report on the occurrence of long-COVID in Dutch children.Patients and Methods: We conducted a national survey asking Dutch pediatricians to share their experiences on long-COVID in children. We furthermore describe a case series of six children with long-COVID to explore the clinical features in greater detail.Results: With a response rate of 78% of Dutch pediatric departments, we identified 89 children, aged 2-18 years, suspected of long-COVID with various complaints. Of these children, 36% experienced severe limitations in daily function. The most common complaints were fatigue, dyspnea, and concentration difficulties with 87%, 55%, and 45% respectively. Our case series emphasizes the nonspecific and broad clinical manifestations seen in post-COVID complaints.Conclusion: Our study shows that long-COVID is also present in the pediatric population. The main symptoms resemble those previously described in adults. This novel condition demands a multidisciplinary approach with international awareness and consensus to aid early detection and effective management. Show less
Background Diagnosis and follow-up of respiratory diseases traditionally rely on pulmonary function tests (PFTs), which are currently performed in hospitals and require trained personnel.... Show moreBackground 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. Show less
