Adverse effect of lockdowns during the COVID-19 pandemic: increased incidence of pediatric crisis admissions due to eating disorders and adolescent intoxications.

During the COVID-19 pandemic, countries imposed (partial) lockdowns that reduced viral transmission. However, these interventions may have unfavorable effects on emotional and psychological well-being. The aim of this study was to quantify possible adverse effects of the COVID-19 pandemic on psychological wellbeing in children and adolescents. Hospital admission data between January 2017 and September 2021 from eight general hospitals in the Netherlands was collected, comparing the incidences of sub-categorized psychological diagnoses, more specifically eating disorders, intentional intoxications, accidental intoxications, and excessive crying, before (2017-2019) and during the pandemic (2020-2021). Data was summarized per month and per year, and the years 2020 and 2021 were compared to 2017-2019. The relative increase or decrease in diagnoses since the start of the pandemic was calculated. Overall pediatric hospital admissions decreased with 28% since the start of the pandemic. Non-infectious diagnoses showed a decrease of 8%. Of these non-infectious diagnoses, overall psychosocial admissions were increased (+ 9%), mostly caused by an increase in admissions for eating disorders (+ 64%) and intoxications in adolescents (+ 24%). In addition, the proportion of admissions due to psychosocial diagnoses increased post-pandemic (6% vs 4%, p < 0.001). Overall admissions for intoxications in children (- 3%) and excessive crying (- 1%) did not increase, although peaks in incidence were found at the start of the second lockdown. CONCLUSION: During the COVID-19 pandemic, admission rates for eating disorders and intentional intoxications showed a substantial increase, indicating a high burden of pediatric psychiatric diseases. WHAT IS KNOWN: • The COVID-19 pandemic has had an impact on psychosocial wellbeing in children and adolescents. WHAT IS NEW: • There was an increase in admissions due to psychosocial problems in the Netherlands in the period after the pandemic. • This was mainly caused by an increase in crisis admissions due to eating disorders and intoxications in adolescents.

Clinical validation of digital biomarkers for paediatric patients with asthma and cystic fibrosis: potential for clinical trials and clinical care.

BACKGROUND: 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 (FEV1) 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 FEV1 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 FEV1 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, FEV1 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.

Population pharmacokinetics of clonazepam in saliva and plasma: Steps towards noninvasive pharmacokinetic studies in vulnerable populations.

AIM: Traditional studies focusing on the relationship between pharmacokinetics (PK) and pharmacodynamics necessitate blood draws, which are too invasive for children or other vulnerable populations. A potential solution is to use noninvasive sampling matrices, such as saliva. The aim of this study was to develop a population PK model describing the relationship between plasma and saliva clonazepam kinetics and assess whether the model can be used to determine trough plasma concentrations based on saliva samples. METHODS: Twenty healthy subjects, aged 18-30, were recruited and administered 0.5 or 1 mg of clonazepam solution. Paired plasma and saliva samples were obtained until 48 hours post-dose. A population pharmacokinetic model was developed describing the PK of clonazepam in plasma and the relationship between plasma and saliva concentrations. Bayesian maximum a posteriori optimization was applied to estimate the predictive accuracy of the model. RESULTS: A two-compartment distribution model best characterized clonazepam plasma kinetics with a mixture component on the absorption rate constants. Oral administration of the clonazepam solution caused contamination of the saliva compartment during the first 4 hours post-dose, after which the concentrations were driven by the plasma concentrations. Simulations demonstrated that the lower and upper limits of agreements between true and predicted plasma concentrations were -28% to 36% with one saliva sample. Increasing the number of saliva samples improved these limits to -18% to 17%. CONCLUSION: The developed model described the salivary and plasma kinetics of clonazepam, and could predict steady-state trough plasma concentrations based on saliva concentrations with acceptable accuracy.

Theoretical Performance of Nonlinear Mixed-Effect Models Incorporating Saliva as an Alternative Sampling Matrix for Therapeutic Drug Monitoring in Pediatrics: A Simulation Study.

BACKGROUND: 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 (kSALIVA), 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 kSALIVA 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.

The impact of lockdown on pediatric ED visits and hospital admissions during the COVID19 pandemic: a multicenter analysis and review of the literature.

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.

Postdischarge Recovery after Acute Pediatric Lung Disease Can Be Quantified with Digital Biomarkers.

BACKGROUND: 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. METHODS: In this study, patients admitted due to pneumonia (n = 30), preschool wheezing (n = 30), and asthma exacerbation (AE; n = 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. RESULTS: 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. CONCLUSIONS: 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.

Pharmacokinetics of intravenous and inhaled salbutamol and tobramycin: An exploratory study to investigate the potential of exhaled breath condensate as a matrix for pharmacokinetic analysis.

Concentrations of drugs acting in the lungs are difficult to measure, resulting in relatively unknown local pharmacokinetics. The aim of this study is to assess the potential of exhaled breath condensate (EBC) as a matrix for pharmacokinetic analysis of inhaled and intravenous medication. A 4-way crossover study was conducted in 12 volunteers with tobramycin and salbutamol intravenously and via inhalation. EBC and plasma samples were collected postdose and analysed for drug concentrations. Sample dilution, calculated using urea concentrations, was used to estimate the epithelial lining fluid concentration. Salbutamol and tobramycin were largely undetectable in EBC after intravenous administration and were detectable after inhaled administration in all subjects in 50.8 and 51.5% of EBC samples, respectively. Correction of EBC concentrations for sample dilution did not explain the high variability. This high variability of EBC drug concentrations seems to preclude EBC as a matrix for pharmacokinetic analysis of tobramycin and salbutamol.

The Future of Clinical Trial Design: The Transition from Hard Endpoints to Value-Based Endpoints.

Clinical trials have been conducted since 500 BC. Currently, the methodological gold standard is the randomized controlled clinical trial, introduced by Austin Bradford Hill. This standard has produced enormous amounts of high-quality evidence, resulting in evidence-based clinical guidelines for physicians. However, the current trial paradigm needs to evolve because of the ongoing decrease of the incidence of hard endpoints and spiraling trial costs. While new trial designs, such as adaptive clinical trials, may lead to an increase in efficiency and decrease in costs, we propose a shift towards value-based trial design: a paradigm that mirrors value-based thinking in business and health care. Value-based clinical trials will use technology to focus more on symptoms and endpoints that patients care about, will incorporate fewer research centers, and will measure a state or consequence of disease at home or at work. Furthermore, they will measure the subjective experience of subjects in relation to other objective measurements. Ideally, the endpoints are suitable for individual assessment of the effect of an intervention. The value-based clinical trial of the future will have a low burden for participants, allowing for the inclusion of neglected populations such as children and the elderly, will be data-rich due to a high frequency of measurements, and can be conducted with technology that is already available.

Risk Factors, Treatment, and Immune Dysregulation in Autoimmune Cytopenia after Allogeneic Hematopoietic Stem Cell Transplantation in Pediatric Patients.

Autoimmune or alloimmune cytopenia (AIC) is a known rare complication of hematopoietic stem cell transplantation (SCT). AIC after SCT is considered difficult to treat and is associated with high morbidity and mortality. In this retrospective study in pediatric patients we evaluated incidence, outcome, potential risk factors, and current treatment strategies. A nested matched case-control study was performed to search for biomarkers associated with AIC. Of 531 consecutive SCTs at our center between 2000 and 2016, 26 were complicated by the development of AIC (cumulative incidence, 5.0%) after a median of 5 months post-SCT. Autoimmune hemolytic anemia was the most common AIC with 12 patients (46%). We identified nonmalignant disease, alemtuzumab serotherapy pre-SCT, and cytomegalovirus (CMV) reactivation as independently associated risk factors. The cytokine profile of patients at the time of AIC diagnosis appeared to skew toward a more pronounced Th 2 response compared with control subjects at the corresponding time point post-SCT. Corticosteroids and intravenous immunoglobulin as first-line treatment or a wait-and-see approach led to resolution of AIC in 35% of cases. Addition of step-up therapies rituximab (n = 15), bortezomib (n = 7), or sirolimus (n = 3) was associated with AIC resolution in 40%, 57%, and 100% of cases, respectively. In summary, we identified CMV reactivation post-SCT as a new clinical risk factor for the development of AIC in children. The cytokine profile during AIC appears to favor a Th 2 response. Rituximab, bortezomib, and sirolimus are promising step-up treatment modalities.

The use of intravenous pentamidine for the prophylaxis of Pneumocystis pneumonia in pediatric patients.

Pneumocystis jiroveci pneumonia was common in the immunocompromised host before the widespread use of prophylaxis. When trimethoprim-sulfamethoxazole is not tolerated, prophylaxis with intravenous pentamidine (IVP) may be initiated. We performed a retrospective analysis of all pediatric patients who received IVP regarding efficacy, safety, and reason for initiation. Of 106 patients included in our analysis, one patient tested positive for Pneumocystis DNA. Adverse events were reported in 18% of IVP courses, and main reason for initiation was cytopenia (59%). We found IVP to be effective and safe, and recommend the use of IVP in pediatric patients in whom first-line prophylaxis is contraindicated.

Optimization of ß-Lactam Dosing Regimens in Neonatal Infections: Continuous and Extended Administration versus Intermittent Administration.

BACKGROUND AND OBJECTIVE: In neonates, ß-Lactam antibiotics are almost exclusively administered by intermittent infusion. However, continuous or prolonged infusion may be more beneficial because of the time-dependent antibacterial activity. In this pharmacokinetic/pharmacodynamic simulation study, we aimed to compare treatment with continuous, extended and intermittent infusion of ß-lactam antibiotics for neonates with infectious diseases. METHODS: We selected population pharmacokinetic models of penicillin G, amoxicillin, flucloxacillin, cefotaxime, ceftazidime and meropenem, and performed a Monte Carlo simulation with 30,000 neonates. Four different dosing regimens were simulated: intermittent infusion in 30 min, prolonged infusion in 4 h, continuous infusion, and continuous infusion with a loading dose. The primary endpoint was 90% probability of target attainment (PTA) for 100% ƒT>MIC during the first 48 h of treatment. RESULTS: For all antibiotics except cefotaxime, continuous infusion with a loading dose resulted in a higher PTA compared with other dosing regimens. Sufficient exposure (PTA >90%) using continuous infusion with a loading dose was reached for amoxicillin (90.3%), penicillin G (PTA 98.4%), flucloxacillin (PTA 94.3%), cefotaxime (PTA 100%), and ceftazidime (PTA 100%). Independent of dosing regimen, higher meropenem (PTA for continuous infusion with a loading dose of 85.5%) doses might be needed to treat severe infections in neonates. Ceftazidime and cefotaxime dose might be unnecessarily high, as even with dose reductions, a PTA > 90% was retained. CONCLUSIONS: Continuous infusion after a loading dose leads to a higher PTA compared with continuous, intermittent or prolonged infusion, and therefore has the potential to improve treatment with ß-lactam antibiotics in neonates.

Validation of the pharmacokinetic model for anti- TNFα clearance in infants exposed to anti- TNFα during pregnancy.

BACKGROUND AND AIMS: ECCO guideline recommend postponing live attenuated vaccines in infants exposed to anti-Tumor Necrosis Factor alpha (anti-TNFα) in utero until drug clearance. The aim was to validate the predictive performance of the anti-TNFα clearance model. METHODS: Newborns and anti-TNFα concentrations from the prospective PETIT cohort were included. The anti-TNFα clearance model was used to predict all measured concentrations in the PETIT cohort, based on the measured cord blood concentration and the mean population clearance described in the model. Bayesian maximum a posteriori optimization was used to estimate the value of drug monitoring. Predictive capability and drug monitoring were assessed through Mean Absolute Error (MAE), Root mean Squared Prediction Error and Limits of Agreement according to Bland and Altman. RESULTS: Observed drug concentrations after birth were within the 80% prediction interval in 94% of adalimumab samples and 93% of infliximab samples. The anti-TNFα clearance model accurately predicted the concentration at six months after birth with an MAE of 0.03 (SD 0.03) µg/mL for adalimumab and 0.11 (SD 0.18) µg/mL for infliximab based on cord blood concentrations. Addition of an additional sample between 1 and 4 months after birth improved the predictive accuracy for infliximab (MAE 0.05 (SD 0.09)) but not for adalimumab. Guidance for use in clinical practice was formulated. CONCLUSIONS: The validity of the anti-TNFα clearance model is high, and hence can be used to guide clinicians regarding timing of live vaccines in infants exposed to adalimumab or infliximab in utero.

Effect of lockdowns on the epidemiology of pediatric respiratory disease-A retrospective analysis of the 2021 summer epidemic.

BACKGROUND: 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.

Mitochondrial function, grip strength, and activity are related to recovery of mobility after a total knee arthroplasty.

Low muscle quality and a sedentary lifestyle are indicators for a slow recovery after a total knee arthroplasty (TKA). Mitochondrial function is an important part of muscle quality and a key driver of sarcopenia. However, it is not known whether it relates to recovery. In this pilot study, we monitored activity after TKA using a wrist mounted activity tracker and assessed the relation of mitochondrial function on the rate of recovery after TKA. Additionally, we compared the increase in activity as a way to measure recovery to traditional outcome measures. Patients were studied 2 weeks before TKA and up to 6 months after. Activity was monitored continuously. Baseline mitochondrial function (citrate synthase and complex [CP] 1-5 abundance of the electron transport chain) was determined on muscle tissue taken during TKA. Traditional outcome measures (Knee Injury and Osteoarthritis Outcome Score [KOOS], timed up-and-go [TUG] completion time, grip, and quadriceps strength) were performed 2 weeks before, 6 weeks after, and 6 months after TKA. Using a multivariate regression model with various clinical baseline parameters, the following were significantly related to recovery: CP5 abundance, grip strength, and activity (regression weights 0.13, 0.02, and 2.89, respectively). During recovery, activity correlated to the KOOS-activities of daily living (ADL) score (r = 0.55, p = 0.009) and TUG completion time (r = -0.61, p = 0.001). Mitochondrial function seems to be related to recovery, but so are activity and grip strength, all indicators of sarcopenia. Using activity trackers before and after TKA might give the surgeon valuable information on the expected recovery and the opportunity to intervene if recovery is low.

Development and technical validation of a smartphone-based pediatric cough detection algorithm.

INTRODUCTION: 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.

Objective Home-Monitoring of Physical Activity, Cardiovascular Parameters, and Sleep in Pediatric Obesity.

Introduction: 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. Methods: 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. Results: 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. Conclusion: 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.

Effect of INTELLiVENT-ASV versus Conventional Ventilation on Ventilation Intensity in Patients with COVID-19 ARDS-An Observational Study.

Driving pressure (ΔP) and mechanical power (MP) are associated with outcomes in critically ill patients, irrespective of the presence of Acute Respiratory Distress Syndrome (ARDS). INTELLiVENT-ASV, a fully automated ventilatory mode, controls the settings that affect ΔP and MP. This study compared the intensity of ventilation (ΔP and MP) with INTELLiVENT-ASV versus conventional ventilation in a cohort of COVID-19 ARDS patients in two intensive care units in the Netherlands. The coprimary endpoints were ΔP and MP before and after converting from conventional ventilation to INTELLiVENT-ASV. Compared to conventional ventilation, INTELLiVENT-ASV delivered ventilation with a lower ΔP and less MP. With conventional ventilation, ΔP was 13 cmH2O, and MP was 21.5 and 24.8 J/min, whereas with INTELLiVENT-ASV, ΔP was 11 and 10 cmH2O (mean difference -2 cm H2O (95 %CI -2.5 to -1.2 cm H2O), p < 0.001) and MP was 18.8 and 17.5 J/min (mean difference -7.3 J/Min (95% CI -8.8 to -5.8 J/min), p < 0.001). Conversion from conventional ventilation to INTELLiVENT-ASV resulted in a lower intensity of ventilation. These findings may favor the use of INTELLiVENT-ASV in COVID-19 ARDS patients, but future studies remain needed to see if the reduction in the intensity of ventilation translates into clinical benefits.

Development and Technical Validation of a Smartphone-Based Cry Detection Algorithm.

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.

Technical validity and usability of a novel smartphone-connected spirometry device for pediatric patients with asthma and cystic fibrosis.

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. 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.

Finding Suitable Clinical Endpoints for a Potential Treatment of a Rare Genetic Disease: the Case of ARID1B.

There is a lack of reliable, repeatable, and non-invasive clinical endpoints when investigating treatments for intellectual disability (ID). The aim of this study is to explore a novel approach towards developing new endpoints for neurodevelopmental disorders, in this case for ARID1B-related ID. In this study, twelve subjects with ARID1B-related ID and twelve age-matched controls were included in this observational case-control study. Subjects performed a battery of non-invasive neurobehavioral and neurophysiological assessments on two study days. Test domains included cognition, executive functioning, and eye tracking. Furthermore, several electrophysiological assessments were performed. Subjects wore a smartwatch (Withings® Steel HR) for 6 days. Tests were systematically assessed regarding tolerability, variability, repeatability, difference with control group, and correlation with traditional endpoints. Animal fluency, adaptive tracking, body sway, and smooth pursuit eye movements were assessed as fit-for-purpose regarding all criteria, while physical activity, heart rate, and sleep parameters show promise as well. The event-related potential waveform of the passive oddball and visual evoked potential tasks showed discriminatory ability, but EEG assessments were perceived as extremely burdensome. This approach successfully identified fit-for-purpose candidate endpoints for ARID1B-related ID and possibly for other neurodevelopmental disorders. Next, results could be replicated in different ID populations or the assessments could be included as exploratory endpoint in interventional trials in ARID1B-related ID.