Association of Early Antibiotic Exposure With Childhood Body Mass Index Trajectory Milestones

IMPORTANCE

Past studies have showed associations between antibiotic exposure and child weight outcomes. Few, however, have documented alterations to body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) trajectory milestone patterns during childhood after early-life antibiotic exposure.

OBJECTIVE

To examine the association of antibiotic use during the first 48 months of life with BMI trajectory milestones during childhood in a large cohort of children.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used electronic health record data from 26 institutions participating in the National Patient-Centered Clinical Research Network from January 1, 2009, to December 31, 2016. Participant inclusion required at least 1 valid set of same-day height and weight measurements at each of the following age periods: 0 to 5, 6 to 11, 12 to 23, 24 to 59, and 60 to 131 months (183 444 children). Data were analyzed from June 1, 2019, to June 30, 2020.

EXPOSURES

Antibiotic use at 0 to 5, 6 to 11, 12 to 23, 24 to 35, and 36 to 47 months of age.

MAIN OUTCOMES AND MEASURES

Age and magnitude of BMI peak and BMI rebound.

RESULTS

Of 183 444 children in the study (mean age, 3.3 years [range, 0-10.9 years]; 95 228 [51.9%] were boys; 80 043 [43.6%] were White individuals), 78.1% received any antibiotic, 51.0% had at least 1 episode of broad-spectrum antibiotic exposure, and 65.0% had at least 1 episode of narrow-spectrum antibiotic exposure at any time before 48 months of age. Exposure to any antibiotics at 0 to 5 months of age (vs no exposure) was associated with later age (β coefficient, 0.05 months [95% CI, 0.02-0.08 months]) and higher BMI (β coefficient, 0.09 [95% CI, 0.07-0.11]) at peak. Exposure to any antibiotics at 0 to 47 months of age (vs no exposure) was associated with an earlier age (-0.60 months [95% CI, -0.81 to -0.39 months]) and higher BMI at rebound (β coefficient, 0.02 [95% CI, 0.01-0.03]). These associations were strongest for children with at least 4 episodes of antibiotic exposure. Effect estimates for associations with age at BMI rebound were larger for those exposed to antibiotics at 24 to 35 months of age (β coefficient, -0.63 [95% CI, -0.83 to -0.43] months) or 36 to 47 (β coefficient, -0.52 [95% CI, -0.72 to -0.31] months) than for those exposed at 0 to 5 months of age (β coefficient, 0.26 [95% CI, 0.01-0.51] months) or 6 to 11 (β coefficient, 0.00 [95% CI, -0.20 to 0.20] months).

CONCLUSIONS AND RELEVANCE

In this cohort study, antibiotic exposure was associated with statistically significant, but small, differences in BMI trajectory milestones in infancy and early childhood. The small risk of an altered BMI trajectory milestone pattern associated with early-life antibiotic exposure is unlikely to be a key factor during prescription decisions for children.

Effects of ambient air pollution on childhood asthma exacerbation in the Philadelphia metropolitan Region, 2011-2014

Fine particulate matter (PM_2.5) and ozone (O₃) air pollutants are known risk factors for asthma exacerbation. We studied the association of these air pollutants with pediatric asthma exacerbation in the Philadelphia metropolitan region, and evaluated potential effect modification by children's characteristics (e.g., race/ethnicity, atopic conditions) and environmental factors (e.g., neighborhood tree canopy, meteorological factors, aeroallergens). We conducted a time-stratified case-crossover study of 54,632 pediatric (age ≤18 years) asthma exacerbation cases occurring from 2011 to 2014, identified through electronic health records (EHR) of the Children's Hospital of Philadelphia (CHOP) health system. We applied conditional logistic regression to estimate associations between air pollution and asthma exacerbation, using daily census-tract level pollutant concentrations estimated from the EPA Fused Air Quality Surface Using Downscaling (FAQSD) files. The associations were estimated within warm (Apr-Sep) and cold (Oct-Mar) months for unlagged exposure and for cumulative effects up to 5 days after exposure, with adjustment for temperature, relative humidity, and holidays. We found small increases in odds of asthma exacerbation with higher pollutant concentrations, with positive associations (OR, comparing concentrations of 75th to 25th percentile) observed for PM_2.5 during both warm (1.03, 95% CI: 0.98-1.08) and cold months (1.05, 95% CI: 1.02-1.07), and for O₃ during cold months (1.08, 95% CI: 1.02-1.14). The exposure-response relationship with PM_2.5 during the cold months was essentially linear, whereas thresholds of effect were observed for the other associations at low-medium pollutant concentrations. Results were robust to multi-pollutant modeling and adjustment for additional covariates. We found no effect modification by most children's characteristics, while effect sizes were higher on days with detected tree and grass pollens during warm months. Our results suggest that even small decreases in pollutant concentrations could potentially reduce risk of childhood asthma exacerbation - an important finding, given the high burden of childhood asthma and known disparities in asthma control.

Sleep Disturbance in School-Aged Children with Atopic Dermatitis: Prevalence and Severity in a Cross-Sectional Sample

BACKGROUND

Atopic dermatitis (AD) causes sleep disturbance but the epidemiology is not known.

OBJECTIVE

To estimate the US prevalence of sleep disturbance and its impact on psychological and neurocognitive function.

METHODS

We conducted a cross-sectional survey of 180 parent-child dyads with AD using stratified sampling based on disease severity (Patient Oriented Eczema Measure: mild [n = 30), moderate (n = 75) or severe (n = 75]), age, and race (White or Black or African American or other). Symptoms of sleep and psychologic health were assessed using the Patient-Reported Outcome Measurement Information System. To estimate the prevalence of sleep disturbance, we calculated weights using poststratification adjustment making marginal frequencies of AD severity, race, and age similar to marginal frequencies in the 2007 National Survey of Children's Health. Unweighted regression models examined associations with sleep disturbance.

RESULTS

In children age 5 to 17 years with AD, we estimated that sleep disturbance occurred in 66.9% (95% confidence interval, 53.3% to 80.5%; 3,116,305 children). The odds of severe sleep disturbance (worse than 95% of US children) were highest in moderate to severe versus mild AD (2.03 [1.00-4.10]; P = .0495; compared with 8.68 [1.82-41.49]; P = .0068). Predictors of parent proxy-reported sleep disturbance were itch intensity (adjusted β [95% confidence interval] 1.33 [0.62-2.04]) and low income (<$50,000: 6.64 [2.05-11.23]; and $50,000 to less than 100,000: 4.75 [0.35-9.14]). Controlling for disease severity, itch intensity, and significant sociodemographics-parent-proxy, reported sleep disturbance was associated with increased severity of sleep-related impairment, depression, fatigue, and anxiety, in addition to worse inattention and impulsivity. In fully adjusted models, children who self-reported sleep disturbance (T-score ≥60) had increased odds of sleep-related impairment (1.20 [1.11-1.29]), depression (1.13 [1.03, 1.24]), fatigue (1.28 [1.06-1.54]), and anxiety (1.16 [1.02-1.31]).

CONCLUSIONS

Sleep disturbance is a common symptom of AD. It affects about 3 million US children and is associated with neuropsychiatric impairment, including depression, anxiety, and inattention. Clinicians should screen for these symptoms in school-aged children, particularly those with moderate to severe AD.

Impact of the Early Phase of the COVID-19 Pandemic on US Healthcare Workers: Results from the HERO Registry

BACKGROUND

The HERO registry was established to support research on the impact of the COVID-19 pandemic on US healthcare workers.

OBJECTIVE

Describe the COVID-19 pandemic experiences of and effects on individuals participating in the HERO registry.

DESIGN

Cross-sectional, self-administered registry enrollment survey conducted from April 10 to July 31, 2020.

SETTING

Participants worked in hospitals (74.4%), outpatient clinics (7.4%), and other settings (18.2%) located throughout the nation.

PARTICIPANTS

A total of 14,600 healthcare workers.

MAIN MEASURES

COVID-19 exposure, viral and antibody testing, diagnosis of COVID-19, job burnout, and physical and emotional distress.

KEY RESULTS

Mean age was 42.0 years, 76.4% were female, 78.9% were White, 33.2% were nurses, 18.4% were physicians, and 30.3% worked in settings at high risk for COVID-19 exposure (e.g., ICUs, EDs, COVID-19 units). Overall, 43.7% reported a COVID-19 exposure and 91.3% were exposed at work. Just 3.8% in both high- and low-risk settings experienced COVID-19 illness. In regression analyses controlling for demographics, professional role, and work setting, the risk of COVID-19 illness was higher for Black/African-Americans (aOR 2.32, 99% CI 1.45, 3.70, p < 0.01) and Hispanic/Latinos (aOR 2.19, 99% CI 1.55, 3.08, p < 0.01) compared with Whites. Overall, 41% responded that they were experiencing job burnout. Responding about the day before they completed the survey, 53% of participants reported feeling tired a lot of the day, 51% stress, 41% trouble sleeping, 38% worry, 21% sadness, 19% physical pain, and 15% anger. On average, healthcare workers reported experiencing 2.4 of these 7 distress feelings a lot of the day.

CONCLUSIONS

Healthcare workers are at high risk for COVID-19 exposure, but rates of COVID-19 illness were low. The greater risk of COVID-19 infection among race/ethnicity minorities reported in the general population is also seen in healthcare workers. The HERO registry will continue to monitor changes in healthcare worker well-being during the pandemic.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT04342806.

Prediction of early childhood obesity with machine learning and electronic health record data

OBJECTIVE

This study compares seven machine learning models developed to predict childhood obesity from age > 2 to ≤ 7 years using Electronic Healthcare Record (EHR) data up to age 2 years.

MATERIALS AND METHODS

EHR data from of 860,510 patients with 11,194,579 healthcare encounters were obtained from the Children's Hospital of Philadelphia. After applying stringent quality control to remove implausible growth values and including only individuals with all recommended wellness visits by age 7 years, 27,203 (50.78 % male) patients remained for model development. Seven machine learning models were developed to predict obesity incidence as defined by the Centers for Disease Control and Prevention (age/sex adjusted BMI>95th percentile). Model performance was evaluated by multiple standard classifier metrics and the differences among seven models were compared using the Cochran's Q test and post-hoc pairwise testing.

RESULTS

XGBoost yielded 0.81 (0.001) AUC, which outperformed all other models. It also achieved statistically significant better performance than all other models on standard classifier metrics (sensitivity fixed at 80 %): precision 30.90 % (0.22 %), F1-socre 44.60 % (0.26 %), accuracy 66.14 % (0.41 %), and specificity 63.27 % (0.41 %).

DISCUSSION AND CONCLUSION

Early childhood obesity prediction models were developed from the largest cohort reported to date. Relative to prior research, our models generalize to include males and females in a single model and extend the time frame for obesity incidence prediction to 7 years of age. The presented machine learning model development workflow can be adapted to various EHR-based studies and may be valuable for developing other clinical prediction models.

Cross-Sectional Associations of Built and Social Neighborhood Environment Variables with Body Mass Index in a Large Sample of Urban Predominantly African American Children

Background and Objectives: Neighborhood environments may play a role in the development of child obesity by providing or limiting opportunities for children to be physically active and access healthy food near the home. This study quantifies associations between the neighborhood built and social environment and age- and sex- standardized body mass index (BMI) z-scores in a predominantly African American urban sample. Methods: Electronic health record data from a pediatric integrated delivery system (N = 26,460 children, 6 to 19 years old in Philadelphia in 2014) were linked to eight built and social neighborhood environment characteristics. Generalized estimating equations were used to obtain adjusted associations between neighborhood features and age- and sex-adjusted BMI Z-score. Interactions between built and social exposures were examined, as well as effect modification by age, sex, neighborhood socioeconomic status, and population density. Results: Of 26,460 children, 17% were overweight and 21% were obese. After adjustment for individual- and neighborhood-level confounders, higher neighborhood greenness and higher walkability were associated with lower BMI z-score [mean difference per standard deviation (SD): -0.069 (95% confidence interval: [-0.108 to -0.031] and -0.051 [-0.085, -0.017], respectively)]. Higher levels of neighborhood food and physical activity resources were associated with higher BMI z-score [mean difference per SD 0.031 (0.012 and 0.050)]. We observed no interaction between the built and social neighborhood measures. Conclusion: Policies to promote walkability and greening of urban neighborhoods may contribute to preventing obesity in children.

A maturity grid assessment tool for learning networks

BACKGROUND

The vision of learning healthcare systems (LHSs) is attractive as a more effective model for health care services, but achieving the vision is complex. There is limited literature describing the processes needed to construct such multicomponent systems or to assess development.

METHODS

We used the concept of a capability maturity matrix to describe the maturation of necessary infrastructure and processes to create learning networks (LNs), multisite collaborative LHSs that use an actor-oriented network organizational architecture. We developed a network maturity grid (NMG) assessment tool by incorporating information from literature review, content theory from existing networks, and expert opinion to establish domains and components. We refined the maturity grid in response to feedback from network leadership teams. We followed NMG scores over time for nine LNs and plotted scores for each domain component with respect to SD for one participating network. We sought subjective feedback on the experience of applying the NMG to individual networks.

RESULTS

LN leaders evaluated the scope, depth, and applicability of the NMG to their networks. Qualitative feedback from network leaders indicated that changes in NMG scores over time aligned with leaders' reports about growth in specific domains; changes in scores were consistent with network efforts to improve in various areas. Scores over time showed differences in maturation in the individual domains of each network. Scoring patterns, and SD for domain component scores, indicated consistency among LN leaders in some but not all aspects of network maturity. A case example from a participating network highlighted the value of the NMG in prompting strategic discussions about network development and demonstrated that the process of using the tool was itself valuable.

CONCLUSIONS

The capability maturity grid proposed here provides a framework to help those interested in creating Learning Health Networks plan and develop them over time.

Sleep practices in pediatric cancer patients: Indirect effects on sleep disturbances and symptom burden

OBJECTIVE

Sleep hygiene recommendations are commonly given to address patient-reported concerns about sleep, yet few studies have examined the relationship between sleep hygiene and sleep disturbances in the context of pediatric oncology. Because poor sleep may affect the patient's experience of cancer-related symptoms, understanding whether sleep hygiene practices influence sleep disturbances and symptoms may be important to improving symptom burden.

METHODS

One hundred and two caregivers of children ages 5-17 and 59 patients ages 8-17 receiving treatment for cancer completed parallel measures of child sleep, sleep hygiene, pain, fatigue, and nausea. Sleep hygiene practices were described, correlates between measures were examined, and the indirect relationship of sleep hygiene on symptom burden through sleep disturbances was tested using PROCESS.

RESULTS

Patients received adequate sleep for age but sleep timing was later than recommended for more than half of the sample and consistency in sleep times was poor. Sleep disturbances were moderately related to all symptoms, with the exception of patient-reported fatigue. Consistent sleep habits were indirectly related to fewer cancer-related symptoms of pain, fatigue, and nausea through sleep disturbances by caregiver report but not patient report.

CONCLUSION

Sleep disturbances are closely related to pain, fatigue, and nausea in pediatric cancer. Consistency in sleep/wake routines and schedules may be important to experiencing fewer sleep disturbances and lower symptom burden. Providing recommendations supporting consistent sleep habits broadly across pediatric oncology may be more effective than only presenting sleep hygiene recommendations to patients experiencing poor sleep.

Considerations to Support Use of Patient-Reported Outcomes Measurement Information System Pediatric Measures in Ambulatory Clinics

OBJECTIVE

To identify challenges to the use of Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric measures in the ambulatory pediatric setting and possible solutions to these challenges.

STUDY DESIGN

Eighteen semistructured telephone interviews of health system leaders, measurement implementers, and ambulatory pediatric clinicians were conducted. Five coders used applied thematic analysis to iteratively identify and refine themes in interview data.

RESULTS

Most interviewees had roles in leadership or the implementation of patient-centered outcomes; 39% were clinicians. Some had experience using PROMIS clinically (44%) and 6% were considering this use. Analyses yielded 6 themes: (1) selection of PROMIS measures, (2) method of administration, (3) use of PROMIS Parent Proxy measures, (4) privacy and confidentiality of PROMIS responses, (5) interpretation of PROMIS scores, and (6) using PROMIS scores clinically. Within the themes, interviewees illuminated specific unique considerations for using PROMIS with children, including care transitions and privacy.

CONCLUSIONS

Real-world challenges continue to hamper PROMIS use. Ongoing efforts to disseminate information about the integration of PROMIS measures in clinical care is critical to impacting the health of children.

Early Life Antibiotic Prescriptions and Weight Outcomes in Children 10 Years of Age

OBJECTIVE

We previously found that antibiotic use at <24 months of age was associated with slightly higher body weight at 5 years of age. In this study, we examine associations of early life antibiotic prescriptions with weight outcomes at 108 to 132 months of age ("10 years").

METHODS

We used electronic health record data from 2009 through 2016 from 10 health systems in PCORnet, a national distributed clinical research network. We examined associations of any (vs no) antibiotics at <24 months of age with body mass index z-score (BMI-z) at 10 years adjusted for confounders selected a priori. We further examined dose response (number of antibiotic episodes) and antibiotic spectrum (narrow and broad).

RESULTS

Among 56,727 included children, 57% received any antibiotics at <24 months; at 10 years, mean (standard deviation) BMI-z was 0.54 (1.14), and 36% had overweight or obesity. Any versus no antibiotic use at <24 months was associated with a slightly higher BMI-z at 10 years among children without a complex chronic condition (β 0.03; 95% confidence interval [CI] 0.01, 0.05) or with a complex chronic condition (β 0.09; 95% CI 0.03, 0.15). Any versus no antibiotic use was not associated with odds of overweight or obesity at 10 years among children without (odds ratio 1.02; 95% CI 0.97, 1.07) or with a complex chronic condition (odds ratio 1.07; 95% CI 0.96, 1.19).

CONCLUSIONS

The small and likely clinically insignificant associations in this study are consistent with our previous 5-year follow-up results, suggesting that, if this relationship is indeed causal, early increases in weight are small but maintained over time.

Assessment of 135 794 Pediatric Patients Tested for Severe Acute Respiratory Syndrome Coronavirus 2 Across the United States

IMPORTANCE

There is limited information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and infection among pediatric patients across the United States.

OBJECTIVE

To describe testing for SARS-CoV-2 and the epidemiology of infected patients.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective cohort study was conducted using electronic health record data from 135 794 patients younger than 25 years who were tested for SARS-CoV-2 from January 1 through September 8, 2020. Data were from PEDSnet, a network of 7 US pediatric health systems, comprising 6.5 million patients primarily from 11 states. Data analysis was performed from September 8 to 24, 2020.

EXPOSURE

Testing for SARS-CoV-2.

MAIN OUTCOMES AND MEASURES

SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) illness.

RESULTS

A total of 135 794 pediatric patients (53% male; mean [SD] age, 8.8 [6.7] years; 3% Asian patients, 15% Black patients, 11% Hispanic patients, and 59% White patients; 290 per 10 000 population [range, 155-395 per 10 000 population across health systems]) were tested for SARS-CoV-2, and 5374 (4%) were infected with the virus (12 per 10 000 population [range, 7-16 per 10 000 population]). Compared with White patients, those of Black, Hispanic, and Asian race/ethnicity had lower rates of testing (Black: odds ratio [OR], 0.70 [95% CI, 0.68-0.72]; Hispanic: OR, 0.65 [95% CI, 0.63-0.67]; Asian: OR, 0.60 [95% CI, 0.57-0.63]); however, they were significantly more likely to have positive test results (Black: OR, 2.66 [95% CI, 2.43-2.90]; Hispanic: OR, 3.75 [95% CI, 3.39-4.15]; Asian: OR, 2.04 [95% CI, 1.69-2.48]). Older age (5-11 years: OR, 1.25 [95% CI, 1.13-1.38]; 12-17 years: OR, 1.92 [95% CI, 1.73-2.12]; 18-24 years: OR, 3.51 [95% CI, 3.11-3.97]), public payer (OR, 1.43 [95% CI, 1.31-1.57]), outpatient testing (OR, 2.13 [1.86-2.44]), and emergency department testing (OR, 3.16 [95% CI, 2.72-3.67]) were also associated with increased risk of infection. In univariate analyses, nonmalignant chronic disease was associated with lower likelihood of testing, and preexisting respiratory conditions were associated with lower risk of positive test results (standardized ratio [SR], 0.78 [95% CI, 0.73-0.84]). However, several other diagnosis groups were associated with a higher risk of positive test results: malignant disorders (SR, 1.54 [95% CI, 1.19-1.93]), cardiac disorders (SR, 1.18 [95% CI, 1.05-1.32]), endocrinologic disorders (SR, 1.52 [95% CI, 1.31-1.75]), gastrointestinal disorders (SR, 2.00 [95% CI, 1.04-1.38]), genetic disorders (SR, 1.19 [95% CI, 1.00-1.40]), hematologic disorders (SR, 1.26 [95% CI, 1.06-1.47]), musculoskeletal disorders (SR, 1.18 [95% CI, 1.07-1.30]), mental health disorders (SR, 1.20 [95% CI, 1.10-1.30]), and metabolic disorders (SR, 1.42 [95% CI, 1.24-1.61]). Among the 5374 patients with positive test results, 359 (7%) were hospitalized for respiratory, hypotensive, or COVID-19-specific illness. Of these, 99 (28%) required intensive care unit services, and 33 (9%) required mechanical ventilation. The case fatality rate was 0.2% (8 of 5374). The number of patients with a diagnosis of Kawasaki disease in early 2020 was 40% lower (259 vs 433 and 430) than in 2018 or 2019.

CONCLUSIONS AND RELEVANCE

In this large cohort study of US pediatric patients, SARS-CoV-2 infection rates were low, and clinical manifestations were typically mild. Black, Hispanic, and Asian race/ethnicity; adolescence and young adulthood; and nonrespiratory chronic medical conditions were associated with identified infection. Kawasaki disease diagnosis is not an effective proxy for multisystem inflammatory syndrome of childhood.

Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm

OBJECTIVES

We propose a one-shot, privacy-preserving distributed algorithm to perform logistic regression (ODAL) across multiple clinical sites.

MATERIALS AND METHODS

ODAL effectively utilizes the information from the local site (where the patient-level data are accessible) and incorporates the first-order (ODAL1) and second-order (ODAL2) gradients of the likelihood function from other sites to construct an estimator without requiring iterative communication across sites or transferring patient-level data. We evaluated ODAL via extensive simulation studies and an application to a dataset from the University of Pennsylvania Health System. The estimation accuracy was evaluated by comparing it with the estimator based on the combined individual participant data or pooled data (ie, gold standard).

RESULTS

Our simulation studies revealed that the relative estimation bias of ODAL1 compared with the pooled estimates was <3%, and the ratio of standard errors was <1.25 for all scenarios. ODAL2 achieved higher accuracy (with relative bias <0.1% and ratio of standard errors <1.05). In real data analysis, we investigated the associations of 100 medications with fetal loss during pregnancy. We found that ODAL1 provided estimates with relative bias <10% for 85% of medications, and ODAL2 has relative bias <10% for 99% of medications. For communication cost, ODAL1 requires transferring p numbers from each site to the local site and ODAL2 requires transferring (p×p+p) numbers from each site to the local site, where p is the number of parameters in the regression model.

CONCLUSIONS

This study demonstrates that ODAL is privacy-preserving and communication-efficient with small bias and high statistical efficiency.

Development and Validation of the Pediatric Sleep Practices Questionnaire: A Self-Report Measure for Youth Ages 8-17 Years

Objective: To develop and evaluate the validity of a self-report measure of sleep practices for youth 8-17 years. Methods: Following recommended guidelines for the development of patient reported outcomes (PROs), sleep practice concepts were identified through expert (n = 8) and child (n = 28) concept elicitation interviews and a systematic literature review. Items were developed based on these concepts and tested in cognitive interviews with children (n = 32). Psychometric analyses were applied to item response data collected from a diverse sample of youth 8-17 years (n = 307). Construct validity was evaluated through tests of associations between sleep practices and sleep disturbance and sleep-related impairment. Finally, clinical validity of the tool was assessed by comparing scores of youth with and without a parent-identified sleep problem. Results: The final Pediatric Sleep Practices Questionnaire (PSPQ) included 15 items that were used to identify 5 sleep practices: sleep timing, sleep routines and consistency, technology use before bedtime, sleep environment, and the need for parental presence to fall asleep. A confirmatory factor analysis supported the hypothesized structure (all factor loadings ≥ 0.72) and PSPQ indices were significantly associated with self-reported sleep disturbances and sleep-related impairment. Finally, children with parent-reported sleep problems had shorter sleep opportunity, later bedtimes, greater need for parental presence, poorer bedtime routines, and more technology use than children without parent-reported sleep problems. Conclusions: The PSPQ was developed using best-practice PRO development methodology. The PSPQ can be used in clinical settings and for research assessment to capture modifiable sleep practices that may promote or interfere with healthy sleep.

International consensus on a standard set of outcome measures for child and youth anxiety, depression, obsessive-compulsive disorder, and post-traumatic stress disorder

A major barrier to improving care effectiveness for mental health is a lack of consensus on outcomes measurement. The International Consortium for Health Outcomes Measurement (ICHOM) has already developed a consensus-based standard set of outcomes for anxiety and depression in adults (including the Patient Health Questionnaire-9, the Generalised Anxiety Disorder 7-item Scale, and the WHO Disability Schedule). This Position Paper reports on recommendations specifically for anxiety, depression, obsessive-compulsive disorder, and post-traumatic stress disorder in children and young people aged between 6 and 24 years. An international ICHOM working group of 27 clinical, research, and lived experience experts formed a consensus through teleconferences, an exercise using an adapted Delphi technique (a method for reaching group consensus), and iterative anonymous voting, supported by sequential research inputs. A systematic scoping review identified 70 possible outcomes and 107 relevant measurement instruments. Measures were appraised for their feasibility in routine practice (ie, brevity, free availability, validation in children and young people, and language translation) and psychometric performance (ie, validity, reliability, and sensitivity to change). The final standard set recommends tracking symptoms, suicidal thoughts and behaviour, and functioning as a minimum through seven primarily patient-reported outcome measures: the Revised Children's Anxiety and Depression Scale, the Obsessive Compulsive Inventory for Children, the Children's Revised Impact of Events Scale, the Columbia Suicide Severity Rating Scale, the KIDSCREEN-10, the Children's Global Assessment Scale, and the Child Anxiety Life Interference Scale. The set's recommendations were validated through a feedback survey involving 487 participants across 45 countries. The set should be used alongside the anxiety and depression standard set for adults with clinicians selecting age-appropriate measures.

Provider Specialty and Receipt of Metabolic Monitoring for Children Taking Antipsychotics

BACKGROUND AND OBJECTIVES

Metabolic monitoring is important for children taking antipsychotic medication, given the risk for increased BMI, impaired glucose metabolism, and hyperlipidemia. The purpose was to examine the influence of provider specialty on the receipt of metabolic monitoring. Specifically, differences in the receipt of recommended care when a child receives outpatient care from a primary care provider (PCP), a mental health provider with prescribing privileges, or both was examined.

METHODS

Medicaid enrollment and health care and pharmacy claims data from 2 states were used in the analyses. Providers were assigned to specialties by using a crosswalk of the National Provider Identifier numbers to specialty type. A total of 41 078 children were included.

RESULTS

For both states, 61% of children saw ≥1 provider type and had adjusted odds ratios for receiving metabolic monitoring that were significantly higher than those of children seeing PCPs only. For example, children seeing a PCP and a mental health provider with prescribing privileges during the year had adjusted odds of receiving metabolic monitoring that were 42% higher than those seeing a PCP alone (P < .001).

CONCLUSIONS

Shared care arrangements significantly increased the chances that metabolic monitoring would be done. For states, health plans, and clinicians to develop meaningful quality improvement strategies, identifying the multiple providers caring for the children and potentially responsible for ordering tests consistent with evidence-based care is essential. Provider attribution in the context of shared care arrangements plays a critical role in driving quality improvement efforts.

Are there birth cohort effects in disparities in child obesity by maternal education?

BACKGROUND

Children belonging to the same birth cohort (i.e., born in the same year) experience shared exposure to a common obesity-related milieu during the critical early years of development-e.g., secular beliefs and feeding practices, adverse chemical exposures, food access and nutrition assistance policies-that set the stage for a shared trajectory of obesity as they mature. Fundamental cause theory suggests that inequitable distribution of recent efforts to stem the rise in child obesity may exacerbate cohort-based disparities over time.

METHODS

Data were from electronic health records spanning 2007-2016 linked to birth records for children ages 2-19 years. We used hierarchical age-period-cohort models to investigate cohort effects on disparities in obesity related to maternal education. We hypothesized that maternal education-based disparities in prevalence of obesity would be larger among more recent birth cohorts.

RESULTS

Sex-stratified models adjusted for race/ethnicity showed substantial obesity disparities by maternal education that were evident even at young ages: prevalence among children with maternal education < high school compared to maternal college degree was approximately three times as high among girls and twice as high among boys. For maternal education < high school, disparities compared to maternal college degree were higher in more recent birth cohorts. Among girls, this disparity cohort effect was evident at younger ages (at age 4, the disparity increased by 4 [0.1-8] percentage points per 5 birth years), while among boys it was larger at older ages (at age 16, the disparity increased by 7 [1-14] percentage points per 5 birth years).

CONCLUSIONS

There may be widening maternal education-based disparities in child obesity by birth cohort at some ages.

Ambient daily pollen levels in association with asthma exacerbation among children in Philadelphia, Pennsylvania

Pollen from trees, grasses, and weeds can trigger asthma exacerbation in sensitized individuals. However, there are gaps in knowledge about the effects, such as the relative risks from different plant taxa and threshold levels of effect. We aimed to describe the local association between pollen and asthma exacerbation among children in the City of Philadelphia, and to evaluate whether effects are modified by children's characteristics and clinical factors (e.g., child's age, race/ethnicity, comorbidities). We conducted a time-stratified case-crossover study of pediatric (age <18 years) asthma exacerbation, with cases identified through electronic health records (EHR) of the Children's Hospital of Philadelphia (CHOP) health system from March through October in the years 2011-2016. Daily pollen counts were obtained from the local National Allergy Bureau certified pollen counter. We applied conditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between the pollen level (vs. none detected) and odds of asthma exacerbation, adjusting for temperature, relative humidity, and holidays. We estimated same-day exposure effects, as well as effects from exposure lagged by up to 5 days. There were 35,040 asthma exacerbation events during the study period, with the majority occurring among black, non-Hispanic children (81.8%) and boys (60.4%). We found increased odds of asthma exacerbation among Philadelphia children in association with tree pollen, both for total tree pollen and most individual tree types. Increased odds from total tree pollen were observed at the lowest levels studied (≤5 grains/m³, unlagged, OR = 1.06, 95% CI: 1.02, 1.10), and exhibited a positive exposure-response pattern of effect; tree pollen levels above 1000 grains/m³ (unlagged) were associated with 64% increased odds of asthma exacerbation (95% CI: 1.45, 1.84). Grass pollen was associated with asthma exacerbation only at levels above the 99^th percentile (52 grains/m³), which occurred, on average, two days per year during the study period (with 2-day lag, OR = 1.38, 95% CI: 1.19, 1.60). There was an inverse association (reduced asthma exacerbation) with ragweed pollen that was consistent across analyses. Pollen from other weeds was associated with increased odds of asthma exacerbation, without a clear exposure-response pattern (2-day lag, significant increases ranging from 8% to 19%). Increased odds from tree pollen and weeds (other than ragweed) were higher among children with allergic rhinitis. While there are known benefits from urban vegetation for human health, there are risks as well. It is important to note, however, that pollen is released during a limited time frame each year, and advisories informed by local data can enable susceptible individuals to avoid outdoor exposure on high-risk days.

Using nationally representative percentiles to interpret PROMIS pediatric measures

PURPOSE

This study's aim was to use a representative sample of the US pediatric population to estimate percentiles for several PROMIS pediatric measures: Anger, Anxiety, Depressive Symptoms, Family Relationships, Fatigue, Global Health, Life Satisfaction, Meaning and Purpose, Pain Behavior, Pain Interference, Physical Activity, Physical Function Mobility, Physical Function Upper Extremity, Physical Stress Experiences, Positive Affect, Psychological Stress Experiences, Sleep Disturbance, Sleep Impairment, and Peer Relationships.

METHODS

We used two separate, nationally representative samples of parents and children aged 5-17 years drawn in different years from the GfK Knowledge Panel, a dual-frame online probability panel.

RESULTS

All measures that were developed using a representative sample had a median at or near the expected value of 50. For the other measures, the 50th percentile was often 10 points or more from 50. Several domains had high floors or low ceilings. No domain's percentiles completely corresponded to the percentiles associated with a normal distribution with a mean of 50 and standard deviation of 10.

CONCLUSIONS

This work allows users to interpret a child's self-reported quality of life relative to children in the US general population. When attempting to evaluate whether a child falls above or below other children in the US, one should use the values presented in this study. In addition, we recommend that users should focus on whether a child's score falls into one of a few broad severity groups rather than on specific percentile scores.

Pragmatic Health Assessment in Early Childhood: The PROMIS® of Developmentally Based Measurement for Pediatric Psychology

OBJECTIVE

To illustrate the integration of developmental considerations into person-reported outcome (PRO) measurement development for application in early childhood pediatric psychology.

METHODS

Combining the state-of-the-science Patient-Reported Outcome Measurement Information System (PROMIS®) mixed-methods instrument development approach with considerations from developmental measurement science, we developed 12 PROMIS early childhood (PROMIS EC) parent report measures to evaluate common mental, social, and physical health outcomes for ages 1-5. Through this interdisciplinary effort, we identified key considerations for early childhood PROs that enable reliable and valid assessment within the real-world constraints of clinical care settings.

RESULTS

Four key considerations are highlighted as key to this process: (a) Engage diverse content experts to identify meaningful and relevant constructs; (b) Balance salient features for early childhood with lifespan coherence of constructs; (c) Emphasize observable features across the typical/atypical spectrum; and (d) Ensure feasibility and relevancy for clinical and research application. Each consideration is discussed using exemplars from the PROMIS EC measurement development process.

CONCLUSIONS

PROMIS EC provides an illustration of how well-established PRO measures for youth can be adapted for younger children by incorporating developmental considerations. This process and resulting key considerations provide clinicians and researchers in the field of pediatric psychology with guidance for adapting PROs to early childhood, enabling critical continuity in domains of high salience to pediatric psychologists.

Development and evaluation of an EHR-based computable phenotype for identification of pediatric Crohn's disease patients in a National Pediatric Learning Health System

Objectives

To develop and evaluate the classification accuracy of a computable phenotype for pediatric Crohn's disease using electronic health record data from PEDSnet, a large, multi‐institutional research network and Learning Health System.

Study Design

Using clinician and informatician input, algorithms were developed using combinations of diagnostic and medication data drawn from the PEDSnet clinical dataset which is comprised of 5.6 million children from eight U.S. academic children's health systems. Six test algorithms (four cases, two non‐cases) that combined use of specific medications for Crohn's disease plus the presence of Crohn's diagnosis were initially tested against the entire PEDSnet dataset. From these, three were selected for performance assessment using manual chart review (primary case algorithm, n = 360, primary non‐case algorithm, n = 360, and alternative case algorithm, n = 80). Non‐cases were patients having gastrointestinal diagnoses other than inflammatory bowel disease. Sensitivity, specificity, and positive predictive value (PPV) were assessed for the primary case and primary non‐case algorithms.

Results

Of the six algorithms tested, the least restrictive algorithm requiring just ≥1 Crohn's diagnosis code yielded 11 950 cases across PEDSnet (prevalence 21/10 000). The most restrictive algorithm requiring ≥3 Crohn's disease diagnoses plus at least one medication yielded 7868 patients (prevalence 14/10 000). The most restrictive algorithm had the highest PPV (95%) and high sensitivity (91%) and specificity (94%). False positives were due primarily to a diagnosis reversal (from Crohn's disease to ulcerative colitis) or having a diagnosis of “indeterminate colitis.” False negatives were rare.

Conclusions

Using diagnosis codes and medications available from PEDSnet, we developed a computable phenotype for pediatric Crohn's disease that had high specificity, sensitivity and predictive value. This process will be of use for developing computable phenotypes for other pediatric diseases, to facilitate cohort identification for retrospective and prospective studies, and to optimize clinical care through the PEDSnet Learning Health System.

PCORnet® 2020: current state, accomplishments, and future directions

OBJECTIVE

To describe PCORnet, a clinical research network developed for patient-centered outcomes research on a national scale.

STUDY DESIGN AND SETTING

Descriptive study of the current state and future directions for PCORnet. We conducted cross-sectional analyses of the health systems and patient populations of the 9 Clinical Research Networks and 2 Health Plan Research Networks that are part of PCORnet.

RESULTS

Within the Clinical Research Networks, electronic health data are currently collected from 337 hospitals, 169,695 physicians, 3,564 primary care practices, 338 emergency departments, and 1,024 community clinics. Patients can be recruited for prospective studies from any of these clinical sites. The Clinical Research Networks have accumulated data from 80 million patients with at least one visit from 2009 to 2018. The PCORnet Health Plan Research Network population of individuals with a valid enrollment segment from 2009 to 2019 exceeds 60 million individuals, who on average have 2.63 years of follow-up.

CONCLUSION

PCORnet's infrastructure comprises clinical data from a diverse cohort of patients and has the capacity to rapidly access these patient populations for pragmatic clinical trials, epidemiological research, and patient-centered research on rare diseases.

Heavy precipitation and asthma exacerbation risk among children: A case-crossover study using electronic health records linked with geospatial data

Extreme precipitation events may be an important environmental trigger for asthma exacerbations in children. We used a time stratified case-crossover design and data from a large electronic health record database at the Children's Hospital of Philadelphia (CHOP) to estimate associations of daily heavy precipitation (defined as > 95th percentile of the summertime distribution) with asthma exacerbation among children. We defined control days as those falling on the same day of the week within the same month and year as the case. We restricted our primary analyses to the summer months in years 2011-2016 and used conditional logistic regression models to estimate associations between heavy precipitation and acute asthma exacerbations in both outpatient (primary care, specialty care, and emergency department) and inpatient settings. We investigated numerous individual-level (e.g., age, sex, eczema diagnosis) and environmental measures (e.g., greenspace, particulate matter) as potential effect modifiers. The analysis include 13,483 asthma exacerbations in 10,434 children. Odds of asthma exacerbation were 11% higher on heavy precipitation vs. no precipitation days (95% CI: 1.02-1.21). There was little evidence of effect modification by most measures. These results suggest that heavy summertime precipitation events may contribute to asthma exacerbations. Further research using larger datasets from other health systems is needed to confirm these results, and to explore underlying mechanisms.

Clinical validity of the PROMIS pediatric sleep short forms in children receiving treatment for cancer

BACKGROUND

Rates of sleep disturbances vary widely across pediatric cancer studies, partly due to differences in measurement tools. Patient-reported outcomes measurement information system (PROMIS) offers a rigorously developed, well-validated pair of pediatric sleep health instruments needed to advance sleep research and clinical practice in pediatric cancer. The current study evaluated the clinical validity of PROMIS pediatric sleep scales (sleep disturbances [SD] and sleep-related impairment [SRI]) among children in active cancer treatment.

PROCEDURE

Caregiver-patient dyads were enrolled during cancer treatment in 2-12 months after diagnosis: 45 children (ages 8-17 years) and 102 caregivers of children (ages 5-17 years) completed PROMIS SD and SRI 8-item short form self-report or caregiver-proxy scales, and caregivers reported the prior week's cancer treatments and blood counts.

RESULTS

Both scales demonstrated strong internal consistency reliability across reporters. SD and SRI were higher than the PROMIS general population calibration sample for caregivers and patients. Oncology caregivers reported lower SD and SRI than sleep clinic caregivers, but oncology patients were similar to sleep clinic patients. Convergent validity was evidenced through moderate correlations between scales by reporter and both scales being significantly higher in patients taking medications for sleep. There were no significant differences in SD or SRI by diagnostic group, receiving radiation, or having low blood counts.

CONCLUSION

The PROMIS SD and SRI short forms are promising measures for pediatric oncology, demonstrating strong internal consistency reliability and multiple indications of clinical validity. Although groups did not differ based on treatment variables, results suggest the need for universal screening for sleep problems during pediatric cancer treatment.

Better sleep, better life? How sleep quality influences children's life satisfaction

PURPOSE

To assess the association between children's sleep quality and life satisfaction; and to evaluate the underlying mechanisms of this relationship.

METHODS

Three pediatric cohorts in the National Institutes of Health (NIH) Environmental influences on Child Health (ECHO) Research Program administered Patient-Reported Outcome Measurement Information System (PROMIS®) parent-proxy measures to caregivers (n = 1111) who reported on their 5- to 9-year-old children's (n = 1251) sleep quality, psychological stress, general health, and life satisfaction; extant sociodemographic data were harmonized across cohorts. Bootstrapped path modeling of individual patient data meta-analysis was used to determine whether and to what extent stress and general health mediate the relationship between children's sleep quality and life satisfaction.

RESULTS

Nonparametric bootstrapped path analyses with 1000 replications suggested children's sleep quality was associated with lower levels of stress and better general health, which, in turn, predicted higher levels of life satisfaction. Family environmental factors (i.e., income and maternal mental health) moderated these relationships.

CONCLUSION

Children who sleep well have happier lives than those with more disturbed sleep. Given the modifiable nature of children's sleep quality, this study offers evidence to inform future interventional studies on specific mechanisms to improve children's well-being.

Development of the PROMIS Pediatric Physical Activity Item Banks

OBJECTIVE

The purpose of this study was to develop self-report and parent-proxy measures of children's physical activity for clinical research and practice and to demonstrate a valid and reliable instrument of children's lived experience of physical activity as reported by the children themselves or their parent proxies.

METHODS

This study involved qualitative development of item pools followed by 2 cross-sectional validity and reliability studies. The National Institutes of Health Patient Reported Outcome Measurement Information System (PROMIS) instrument development standards were applied to create child self-report and parent-proxy physical activity instruments from previously developed, content-valid pools of physical activity items. Each item used a 7-day recall period and had 5 response options. Item bank calibration was based on national samples totaling 3033 children aged 8 to 17 years and 2336 parents of children aged 5 to 17 years. Quantitative analyses included reliability assessments, factor analyses, item response theory calibration, differential item functioning, and construct validation.

RESULTS

The final item banks comprised 10 items each. The items were selected based on content and psychometric properties. The item banks appeared to be unidimensional and free from differential item functioning. They showed excellent reliability and a high degree of precision across the range of the latent variable. Child-report and parent-proxy 4- and 8-item fixed-length instruments were specified. The instruments showed moderate correlation with existing self-report measures of physical activity.

CONCLUSION

The PROMIS Pediatric Physical Activity instruments provide precise and valid measurement of children's lived experiences of physical activity.

IMPACT

The availability of the PROMIS Pediatric Physical Activity instruments will support advances in clinical practice and research that require measurement of pediatric physical activity by self- and parent-proxy report.