Pediatric Patients Discharged After Transfer to a Pediatric Emergency Department: Opportunities for Telehealth?

STUDY OBJECTIVE: Interemergency department pediatric transfers can be costly, involve risk, and may be disruptive to patients and families. Telehealth could be a way to safely reduce the number of transfers. We made an estimate of the proportion of transfers of pediatric patients to our emergency department (ED) that may have been avoidable using telehealth. METHODS: This was a retrospective analysis of electronic health record data of all pediatric patients (younger than 19 years) who were transferred to a single urban, academic medical center pediatric emergency department (PED) (annual pediatric volume approximately 15,000) between June 1, 2016, and December 29, 2021. We defined transfers as potentially avoidable with telehealth (the primary outcome) when the encounter at the receiving ED resulted in ED discharge and 1) met our definition of low-resource intensity (had no laboratory tests, diagnostic imaging, procedures, or consultations) or 2) could have used initial ED resources with telehealth guidance. RESULTS: Among 4,446 PED patients received in transfer during the study period, 406 (9%) were low-resource intensity. Of the non-low-resource intensity encounters, as many as another 1,103 (24.8%) potentially could have been avoided depending on available telehealth and initial ED resources, ranging from 210 (4.7%) with only telehealth specialty consultation to 538 (7.4%) with imaging and telehealth specialty consultation, and up to 1,034 (23.3%) with laboratory, imaging, and telehealth specialty consultation. CONCLUSION: Our results suggest that depending on available telehealth and initial ED resources, between 9% and 33% of pediatric inter-ED transfers may have been avoidable. This information may guide health system design and PED operations when considering implementing pediatric telehealth.

Does a lack of physical activity explain the rheumatoid arthritis lipid profile?

BACKGROUND: In rheumatoid arthritis (RA), cardiovascular risk is associated with paradoxical reductions in total cholesterol, low density lipoprotein-cholesterol (LDL-C), and high density lipoprotein-cholesterol (HDL-C). Concentrations of small LDL (LDL-P) and HDL (HDL-P) particles are also reduced with increased inflammation and disease activity in RA patients. Here we sought to identify which measure(s) of inflammation, disease activity and cardiometabolic risk contribute most to the RA-associated lipoprotein profile. METHODS: NMR lipoprotein measurements were obtained for individuals with RA (n = 50) and age-, gender-, and body mass index (BMI)-matched controls (n = 39). Groups were compared using 39 matched pairs with 11 additional subjects used in RA only analyses. Among RA patients, relationships were determined for lipoprotein parameters with measures of disease activity, disability, pain, inflammation, body composition, insulin sensitivity and exercise. Percentage of time spent in basal activity (<1 metabolic equivalent) and exercise (≥3 metabolic equivalents) were objectively-determined. RESULTS: Subjects with RA had fewer total and small LDL-P as well as larger LDL and HDL size (P < 0.05). Among RA patients, pain and disability were associated with fewer small HDL-P (P < 0.05), while interleukin (IL)-6, IL-18, and TNF-α were associated with LDL size (P < 0.05). BMI, waist circumference, abdominal visceral adiposity and insulin resistance were associated with more total and small LDL-P, fewer large HDL-P, and a reduction in HDL size (P < 0.05). Most similar to the RA lipoprotein profile, more basal activity (minimal physical activity) and less exercise time were associated with fewer small LDL-P and total and small HDL-P (P < 0.05). CONCLUSIONS: The RA-associated lipoprotein profile is associated with a lack of physical activity. As this was a cross-sectional investigation and not an intervention and was performed from 2008-13, this study was not registered in clinicaltrials.gov.

Molecular alterations in skeletal muscle in rheumatoid arthritis are related to disease activity, physical inactivity, and disability.

BACKGROUND: To identify molecular alterations in skeletal muscle in rheumatoid arthritis (RA) that may contribute to ongoing disability in RA. METHODS: Persons with seropositive or erosive RA (n = 51) and control subjects matched for age, gender, race, body mass index (BMI), and physical activity (n = 51) underwent assessment of disease activity, disability, pain, physical activity and thigh muscle biopsies. Muscle tissue was used for measurement of pro-inflammatory markers, transcriptomics, and comprehensive profiling of metabolic intermediates. Groups were compared using mixed models. Bivariate associations were assessed with Spearman correlation. RESULTS: Compared to controls, patients with RA had 75% greater muscle concentrations of IL-6 protein (p = 0.006). In patients with RA, muscle concentrations of inflammatory markers were positively associated (p < 0.05 for all) with disease activity (IL-1ß, IL-8), disability (IL-1ß, IL-6), pain (IL-1ß, TNF-α, toll-like receptor (TLR)-4), and physical inactivity (IL-1ß, IL-6). Muscle cytokines were not related to corresponding systemic cytokines. Prominent among the gene sets differentially expressed in muscles in RA versus controls were those involved in skeletal muscle repair processes and glycolytic metabolism. Metabolic profiling revealed 46% higher concentrations of pyruvate in muscle in RA (p < 0.05), and strong positive correlation between levels of amino acids involved in fibrosis (arginine, ornithine, proline, and glycine) and disability (p < 0.05). CONCLUSION: RA is accompanied by broad-ranging molecular alterations in skeletal muscle. Analysis of inflammatory markers, gene expression, and metabolic intermediates linked disease-related disruptions in muscle inflammatory signaling, remodeling, and metabolic programming to physical inactivity and disability. Thus, skeletal muscle dysfunction might contribute to a viscous cycle of RA disease activity, physical inactivity, and disability.

A novel inflammatory biomarker, GlycA, associates with disease activity in rheumatoid arthritis and cardio-metabolic risk in BMI-matched controls.

BACKGROUND: RA and CVD both have inflammation as part of the underlying biology. Our objective was to explore the relationships of GlycA, a measure of glycosylated acute phase proteins, with inflammation and cardiometabolic risk in RA, and explore whether these relationships were similar to those for persons without RA. METHODS: Plasma GlycA was determined for 50 individuals with mild-moderate RA disease activity and 39 controls matched for age, gender, and body mass index (BMI). Regression analyses were performed to assess relationships between GlycA and important markers of traditional inflammation and cardio-metabolic health: inflammatory cytokines, disease activity, measures of adiposity and insulin resistance. RESULTS: On average, RA activity was low (DAS-28 = 3.0 ± 1.4). Traditional inflammatory markers, ESR, hsCRP, IL-1ß, IL-6, IL-18 and TNF-α were greater in RA versus controls (P < 0.05 for all). GlycA concentrations were significantly elevated in RA versus controls (P = 0.036). In RA, greater GlycA associated with disease activity (DAS-28; RDAS-28 = 0.5) and inflammation (RESR = 0.7, RhsCRP = 0.7, RIL-6 = 0.3: P < 0.05 for all); in BMI-matched controls, these inflammatory associations were absent or weaker (hsCRP), but GlycA was related to IL-18 (RhsCRP = 0.3, RIL-18 = 0.4: P < 0.05). In RA, greater GlycA associated with more total abdominal adiposity and less muscle density (Rabdominal-adiposity = 0.3, Rmuscle-density = -0.3, P < 0.05 for both). In BMI-matched controls, GlycA associated with more cardio-metabolic markers: BMI, waist circumference, adiposity measures and insulin resistance (R = 0.3-0.6, P < 0.05 for all). CONCLUSIONS: GlycA provides an integrated measure of inflammation with contributions from traditional inflammatory markers and cardio-metabolic sources, dominated by inflammatory markers in persons with RA and cardio-metabolic factors in those without.

Adipose depots, not disease-related factors, account for skeletal muscle insulin sensitivity in established and treated rheumatoid arthritis.

OBJECTIVE: In prior reports, individuals with rheumatoid arthritis (RA) exhibited increased insulin resistance. However, those studies were limited by either suboptimal assessment methods for insulin sensitivity or a failure to account for important determinants such as adiposity and lack of physical activity. Our objectives were to carefully assess, compare, and determine predictors of skeletal muscle insulin sensitivity in RA, accounting for adiposity and physical activity. METHODS: Thirty-nine individuals with established (seropositive or erosions) and treated RA and 39 controls matched for age, sex, race, body mass index, and physical activity underwent a frequently sampled intravenous glucose tolerance test to determine insulin sensitivity. Inflammation, body composition, and physical activity were assessed with systemic cytokine measurements, computed tomography scans, and accelerometry, respectively. Exclusions were diabetes, cardiovascular disease, medication changes within 3 months, and prednisone use over 5 mg/day. This investigation was powered to detect a clinically significant, moderate effect size for insulin sensitivity difference. RESULTS: Despite elevated systemic inflammation [interleukin (IL)-6, IL-18, tumor necrosis factor-α; p < 0.05 for all], persons with RA were not less insulin sensitive [SI geometric mean (SD): RA 4.0 (2.4) vs control 4.9 (2.1)*10(-5) min(-1)/(pmol/l); p = 0.39]. Except for visceral adiposity being slightly greater in controls (p = 0.03), there were no differences in body composition or physical activity. Lower insulin sensitivity was independently associated with increased abdominal and thigh adiposity, but not with cytokines, disease activity, duration, disability, or disease-modifying medication use. CONCLUSION: In established and treated RA, traditional risk factors, specifically excess adiposity, play more of a role in predicting skeletal muscle insulin sensitivity than do systemic inflammation or other disease-related factors.