<p><strong>OBJECTIVE: </strong>To evaluate change in the incidence of FTT based on selected growth percentile criteria and diagnostic codes before and after a switch in growth curves.</p>

<p><strong>METHODS: </strong>We performed a retrospective cohort study of children 2 to 24 months of age in a large primary care network that switched its default growth curve from the Centers for Disease Control (CDC) reference to the World Health Organization (WHO) standards in 2012. We compared the incidence of FTT defined by growth percentile criteria (using the default growth curve at the time of each measurement) and by ICD-9 codes in the three years before and after the CDC-WHO switch using an interrupted time series analysis. We performed these analyses stratified by age group (≤6 months and &gt;6-24 months).</p>

<p><strong>RESULTS: </strong>We evaluated 83,299 children. Among those ≤6 months, increases in FTT incidence were found in both growth-percentile and clinician-diagnosis criteria at the CDC-WHO switch (p&lt;0.05). Among those &gt;6-24 months, decreases in FTT incidence were found by growth-percentile criteria at the CDC-WHO switch (p&lt;0.05), but no significant changes were found in FTT incidence by diagnostic codes.</p>

<p><strong>CONCLUSIONS: </strong>When switching from the CDC to the WHO growth curves, changes in the incidence of FTT by growth-percentile and clinician-diagnosis criteria differed for younger versus older infants. Factors beyond growth likely influence the decision to diagnose a child as having FTT and may differ in younger compared to older infants.</p>

<p><strong>OBJECTIVE: </strong>The aim of this study was to identify emergency department (ED) heart rate (HR) values that identify children at elevated risk of ED revisit with admission.</p>

<p><strong>METHODS: </strong>We performed a retrospective cohort study of patients 0 to 18 years old discharged from a tertiary-care pediatric ED from January 2013 to December 2014. We created percentile curves for the last recorded HR for age using data from calendar year 2013 and used receiver operating characteristic (ROC) curves to characterize the performance of the percentiles for predicting ED revisit with admission within 72 hours. In a held-out validation data set (calendar year 2014 data), we evaluated test characteristics of last-recorded HR-for-age cut points identified as promising on the ROC curves, as well as those identifying the highest 5% and 1% of last recorded HRs for age.</p>

<p><strong>RESULTS: </strong>We evaluated 183,433 eligible ED visits. Last recorded HR for age had poor discrimination for predicting revisit with admission (area under the curve, 0.61; 95% confidence interval, 0.58-0.63). No promising cut points were identified on the ROC curves. Cut points identifying the highest 5% and 1% of last recorded HRs for age showed low sensitivity (10.1% and 2.5%) with numbers needed to evaluate of 62 and 50, respectively, to potentially prevent 1 revisit with admission.</p>

<p><strong>CONCLUSIONS: </strong>Last recorded ED HR discriminates poorly between children who are and are not at risk of revisit with admission in a pediatric ED. The use of single-parameter HR in isolation as an automated trigger for mandatory reevaluation prior to discharge may not improve revisit outcomes.</p>

<p><strong>Objective: </strong>Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data.</p>

<p><strong>Materials and Methods: </strong>Using deidentified data from 46 primary care sites, we developed an algorithm to identify weight and height values that should be excluded from analysis, including implausible values and values that were recorded repeatedly without remeasurement. The foundation of the algorithm is a comparison of each measurement, expressed as a standard deviation score, with a weighted moving average of a child's other measurements. We evaluated the performance of the algorithm by (1) comparing its results with the judgment of physician reviewers for a stratified random selection of 400 measurements and (2) evaluating its accuracy in a dataset with simulated errors.</p>

<p><strong>Results: </strong>Of 2 000 595 growth measurements from 280 610 patients 1 to 21 years old, 3.8% of weight and 4.5% of height values were identified as implausible or excluded for other reasons. The proportion excluded varied widely by primary care site. The automated method had a sensitivity of 97% (95% confidence interval [CI], 94-99%) and a specificity of 90% (95% CI, 85-94%) for identifying implausible values compared to physician judgment, and identified 95% (weight) and 98% (height) of simulated errors.</p>

<p><strong>Discussion and Conclusion: </strong>This automated, flexible, and validated method for preparing large datasets will facilitate the use of pediatric EHR growth datasets for research.</p>

<p><strong>IMPORTANCE: </strong>Early-life antibiotic exposure has been associated with increased adiposity in animal models, mediated through the gut microbiome. Infant antibiotic exposure is common and often inappropriate. Studies of the association between infant antibiotics and childhood weight gain have reported inconsistent results.</p>

<p><strong>OBJECTIVE: </strong>To assess the association between early-life antibiotic exposure and childhood weight gain.</p>

<p><strong>DESIGN AND SETTING: </strong>Retrospective, longitudinal study of singleton births and matched longitudinal study of twin pairs conducted in a network of 30 pediatric primary care practices serving more than 200,000 children of diverse racial and socioeconomic backgrounds across Pennsylvania, New Jersey, and Delaware.</p>

<p><strong>PARTICIPANTS: </strong>Children born between November 1, 2001, and December 31, 2011, at 35 weeks' gestational age or older, with birth weight of 2000 g or more and in the fifth percentile or higher for gestational age, and who had a preventive health visit within 14 days of life and at least 2 additional visits in the first year of life. Children with complex chronic conditions and those who received long-term antibiotics or multiple systemic corticosteroid prescriptions were excluded. We included 38,522 singleton children and 92 twins (46 matched pairs) discordant in antibiotic exposure. Final date of follow-up was December 31, 2012.</p>

<p><strong>EXPOSURE: </strong>Systemic antibiotic use in the first 6 months of life.</p>

<p><strong>MAIN OUTCOMES AND MEASURES: </strong>Weight, measured at preventive health visits from age 6 months through 7 years.</p>

<p><strong>RESULTS: </strong>Of 38,522 singleton children (50% female; mean birth weight, 3.4 kg), 5287 (14%) were exposed to antibiotics during the first 6 months of life (at a mean age of 4.3 months). Antibiotic exposure was not significantly associated with rate of weight change (0.7%; 95% CI, -0.1% to 1.5%; P = .07, equivalent to approximately 0.05 kg; 95% CI, -0.004 to 0.11 kg of added weight gain between age 2 years and 5 years). Among 92 twins (38% female; mean birth weight, 2.8 kg), the 46 twins who were exposed to antibiotics during the first 6 months of life received them at a mean age of 4.5 months. Antibiotic exposure was not significantly associated with a weight difference (-0.09 kg; 95% CI, -0.26 to 0.08 kg; P = .30).</p>

<p><strong>CONCLUSIONS AND RELEVANCE: </strong>Exposure to antibiotics within the first 6 months of life compared with no exposure was not associated with a statistically significant difference in weight gain through age 7 years. There are many reasons to limit antibiotic exposure in young, healthy children, but weight gain is likely not one of them.</p>

<p><strong>BACKGROUND: </strong>The test characteristics of head circumference (HC) measurement percentile criteria for the identification of previously undetected pathology associated with head enlargement in primary care are unknown.</p>

<p><strong>METHODS: </strong>Electronic patient records were reviewed to identify children age 3 days to 3 years with new diagnoses of intracranial expansive conditions (IEC) and metabolic and genetic conditions associated with macrocephaly (MGCM). We tested the following HC percentile threshold criteria: ever above the 95th, 97th, or 99.6th percentile and ever crossing 2, 4, or 6 increasing major percentile lines. The Centers for Disease Control and World Health Organization growth curves were used, as well as the primary care network (PCN) curves previously derived from this cohort.</p>

<p><strong>RESULTS: </strong>Among 74,428 subjects, 85 (0.11%) had a new diagnosis of IEC (n = 56) or MGCM (n = 29), and between these 2 groups, 24 received intervention. The 99.6th percentile of the PCN curve was the only threshold with a PPV over 1% (PPV 1.8%); the sensitivity of this threshold was only 15%. Test characteristics for the 95th percentiles were: sensitivity (CDC: 46%; WHO: 55%; PCN: 40%), positive predictive value (PPV: CDC: 0.3%; WHO: 0.3%; PCN: 0.4%), and likelihood ratios positive (LR+: CDC: 2.8; WHO: 2.2; PCN: 3.9). Test characteristics for the 97th percentiles were: sensitivity (CDC: 40%; WHO: 48%; PCN: 34%), PPV (CDC: 0.4%; WHO: 0.3%; PCN: 0.6%), and LR+ (CDC: 3.6; WHO: 2.7; PCN: 5.6). Test characteristics for crossing 2 increasing major percentile lines were: sensitivity (CDC: 60%; WHO: 40%; PCN: 31%), PPV (CDC: 0.2%; WHO: 0.1%; PCN: 0.2%), and LR+ (CDC: 1.3; WHO: 1.1; PCN: 1.5).</p>

<p><strong>CONCLUSIONS: </strong>Commonly used HC percentile thresholds had low sensitivity and low positive predictive value for diagnosing new pathology associated with head enlargement in children in a primary care network.</p>

<p><strong>OBJECTIVE: </strong>To develop and validate heart and respiratory rate percentile curves for hospitalized children and compare their vital sign distributions to textbook reference ranges and pediatric early warning score (EWS) parameters.</p>

<p><strong>METHODS: </strong>For this cross-sectional study, we used 6 months of nurse-documented heart and respiratory rates from the electronic records of 14,014 children on general medical and surgical wards at 2 tertiary-care children's hospitals. We developed percentile curves using generalized additive models for location, scale, and shape with 67% of the patients and validated the curves with the remaining 33%. We then determined the proportion of observations that deviated from textbook reference ranges and EWS parameters.</p>

<p><strong>RESULTS: </strong>We used 116,383 heart rate and 116,383 respiratory rate values to develop and validate the percentile curves. Up to 54% of heart rate observations and up to 40% of respiratory rate observations in our sample were outside textbook reference ranges. Up to 38% of heart rate observations and up to 30% of respiratory rate observations in our sample would have resulted in increased EWSs.</p>

<p><strong>CONCLUSIONS: </strong>A high proportion of vital signs among hospitalized children would be considered out of range according to existing reference ranges and pediatric EWSs. The percentiles we derived may serve as useful references for clinicians and could be used to inform the development of evidence-based vital sign parameters for physiologic monitor alarms, inpatient electronic health record vital sign alerts, medical emergency team calling criteria, and EWSs.</p>

<p><strong>OBJECT: </strong>Enlargement of the subarachnoid spaces has been theorized as a risk factor for the development of subdural hemorrhage (SDH). As the finding of unexplained SDH in children often raises suspicion for nonaccidental trauma, the possibility of increased risk of SDH in children with enlargement of the subarachnoid spaces has important clinical, social, and legal implications. Therefore, the authors evaluated the frequency of SDH in a cohort of children with enlargement of the subarachnoid spaces.</p>

<p><strong>METHODS: </strong>The authors identified children younger than 2 years of age who were diagnosed with enlargement of the subarachnoid spaces on MRI or CT scanning in a large primary care network between July 2001 and January 2008. The authors excluded children who had enlargement of the subarachnoid spaces diagnosed on imaging performed for trauma or developmental delay, as well as children with a history of prematurity, diagnosis of intracranial pathology, or metabolic or genetic disorders. Chart review recovered the following data: patient demographics, head circumference, history of head trauma, and head imaging results. For the subset of children with SDH, information regarding evaluation for other injuries, including skeletal survey, ophthalmological examination, and child protection team evaluation, was abstracted.</p>

<p><strong>RESULTS: </strong>There were 177 children with enlargement of the subarachnoid spaces who met the inclusion criteria. Subdural hemorrhage was identified in 4 (2.3%) of the 177 children. All of the children with SDH underwent evaluations for suspected nonaccidental trauma, which included consultation by the child protection team, skeletal survey, and ophthalmological examination. Additional injuries (healing rib fractures) were identified in 1 of 4 patients. None of the 4 children had retinal hemorrhages. Only the child with rib fractures was reported to child protective services due to concerns for abuse.</p>

<p><strong>CONCLUSIONS: </strong>Only a small minority of the patients with enlargement of the subarachnoid spaces had SDH. Evidence of additional injuries concerning for physical abuse were identified in a quarter of the children with enlargement of the subarachnoid spaces and SDH, suggesting that an evaluation for suspected nonaccidental trauma including occult injury screening should be performed in cases of SDH with enlargement of the subarachnoid spaces. In the absence of additional injuries, however, the presence of an unexplained SDH in the setting of enlargement of the subarachnoid spaces may be insufficient to support a diagnosis of nonaccidental trauma.</p>

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Heart rate (HR) is frequently used by clinicians in the hospital to assess a patient's severity of illness and make treatment decisions. We sought to develop percentiles that characterize the relationship of expected HR by age and body temperature in hospitalized children and to compare these percentiles with published references in both primary care and emergency department (ED) settings.</p>

<p><strong>METHODS: </strong>Vital sign data were extracted from electronic health records of inpatients &lt;18 years of age at 2 large freestanding children's hospitals from July 2011 to June 2012. We selected up to 10 HR-temperature measurement pairs from each admission. Measurements from 60% of patients were used to derive the percentile curves, with the remainder used for validation. We compared our upper percentiles with published references in primary care and ED settings.</p>

<p><strong>RESULTS: </strong>We used 60,863 observations to derive the percentiles. Overall, an increase in body temperature of 1°C was associated with an increase of ∼ 10 beats per minute in HR, although there were variations across age and temperature ranges. For infants and young children, our upper percentiles were lower than in primary care and ED settings. For school-age children, our upper percentiles were higher.</p>

<p><strong>CONCLUSIONS: </strong>We characterized expected HR by age and body temperature in hospitalized children. These percentiles differed from references in primary care and ED settings. Additional research is needed to evaluate the performance of these percentiles for the identification of children who would benefit from further evaluation or intervention for tachycardia.</p>