Objectives: To describe medication management of children diagnosed with anxiety and depression by primary care providers. Study Design/Methods: We performed a retrospective cross-sectional analysis of electronic health record (EHR) structured data. All visits for pediatric patients seen at least twice during a four-year period within a network of primary care clinics in Northern California were included. Descriptive statistics summarized patient variables and most commonly prescribed medications. For each subcohort (anxiety, depression, and both (anxiety+depression)), logistic regression models examined the variables associated with medication prescription. Results: Of all patients (N=93,025), 2.8% (n=2635) had a diagnosis of anxiety only, 1.5% (n=1433) depression only, and 0.79% (n=737) both anxiety and depression (anxiety+depression); 18% of children with anxiety and/or depression had comorbid ADHD. A total of 14.0% with anxiety (n=370), 20.3% with depression (n=291), and 47.5% with anxiety+depression (n=350) received a psychoactive non-stimulant medication. For anxiety only and depression only, sertraline, citalopram, and fluoxetine were most commonly prescribed. For anxiety+depression, citalopram, sertraline, and escitalopram were most commonly prescribed. The top prescribed medications also included benzodiazepines. Logistic regression models showed that older age and having developmental or mental health comorbidities were independently associated with increased likelihood of medication prescription for children with anxiety, depression, and anxiety+depression. Insurance type and sex were not associated with medication prescription. Conclusions: PCPs prescribe medications more frequently for patients with anxiety+depression than for patients with either diagnosis alone. Medication choices generally align with current recommendations. Future research should focus on the use of benzodiazepines due to safety concerns in children.

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We compared determinations of anaerobic threshold (AT) made from measurements of arterial lactate concentration with AT determined from ventilatory response measurements of subjects with chronic airflow obstruction (CAO). Six untrained subjects with CAO performed incremental maximal cycle ergometer tests. Ventilation (V_E); O₂ uptake (V_O2), CO₂ output (V_co2); end-tidal CO₂ fraction (F_ETCO2); and end-tidal O₂ fraction (F_ETO2) were measured breath by breath. Arterial lactate concentration was sampled at rest and every 30 s during exercise from an indwelling arterial catheter. For three subjects with more severe airflow obstruction, plots of V_E/Vo₂ and F_ETO2 failed to detect AT. In contrast, a systematic increase of the respiratory gas exchange ratio across the lung (R) accompanied increasing arterial lactate concentrations in all 6 subjects. We conclude that progressive increases of V_E/V_O2 and F_ETO2 cannot be relied upon for the measurement of AT in patients with severe CAO. Progressive increases of R unaccompanied by decreasing F_ETCO2 detect AT in CAO

Objectives: (1) To assess continuity of care by primary-care provider (CoC), an established quality indicator, in children with asthma, autism spectrum disorder (ASD), and no chronic conditions, and (2) to determine patient factors that influenced CoC. Methods: Retrospective cohort study of electronic health records from all office visits of children under 9 years, seen >4 times between 2015 and 2019 in 10 practices of a community-based primary healthcare network in California. Three cohorts were constructed: (1)Asthma: >2 visits with asthma visit diagnoses; (2)ASD: same method; (3)Controls: no chronic conditions. CoC, using the Usual Provider of Care measure (range >0-1), was calculated for (1)total visits and (2)well care visits only. Fractional regression models examined CoC adjusting for patient age, medical insurance, practice affiliation, and number of visits. Results: Of 30,678 eligible children, 1875 (6.1%) were classified as Asthma, 294 (1.0%) as ASD, and 15,465 (50.4%) as Controls. Asthma and ASD had lower total CoC than Controls (Mean=0.58, SD 0.21, M=0.57, SD 0.20, M=0.66, SD 0.21). Differences among well CoC were smaller (Asthma M=0.80, ASD M=0.78, Controls M=0.82). In regression models, lower total CoC was found for Asthma (aOR 0.90, 95% CI 0.85-0.94). Lower total and well CoC were associated with public insurance (aOR 0.77, CI 0.74-0.81; aOR 0.64, CI 0.59-0.69). Conclusion: Children with asthma in this primary-care network had lower CoC compared to children without chronic conditions. Public insurance was the most prominent patient factor associated with low CoC. Quality initiatives should address disparities in CoC for children with chronic conditions.