Provider-ordered viral testing and antibiotic administration practices among children with acute respiratory infections across healthcare settings in Nashville, Tennessee.

Objective: Evaluate the association between provider-ordered viral testing and antibiotic treatment practices among children discharged from an ED or hospitalized with an acute respiratory infection (ARI). Design: Active, prospective ARI surveillance study from November 2017 to February 2020. Setting: Pediatric hospital and emergency department in Nashville, Tennessee. Participants: Children 30 days to 17 years old seeking medical care for fever and/or respiratory symptoms. Methods: Antibiotics prescribed during the child's ED visit or administered during hospitalization were categorized into (1) None administered; (2) Narrow-spectrum; and (3) Broad-spectrum. Setting-specific models were built using unconditional polytomous logistic regression with robust sandwich estimators to estimate the adjusted odds ratios and 95% confidence intervals between provider-ordered viral testing (ie, tested versus not tested) and viral test result (ie, positive test versus not tested and negative test versus not tested) and three-level antibiotic administration. Results: 4,107 children were enrolled and tested, of which 2,616 (64%) were seen in the ED and 1,491 (36%) were hospitalized. In the ED, children who received a provider-ordered viral test had 25% decreased odds (aOR: 0.75; 95% CI: 0.54, 0.98) of receiving a narrow-spectrum antibiotic during their visit than those without testing. In the inpatient setting, children with a negative provider-ordered viral test had 57% increased odds (aOR: 1.57; 95% CI: 1.01, 2.44) of being administered a broad-spectrum antibiotic compared to children without testing. Conclusions: In our study, the impact of provider-ordered viral testing on antibiotic practices differed by setting. Additional studies evaluating the influence of viral testing on antibiotic stewardship and antibiotic prescribing practices are needed.

Immunophenotypic predictors of influenza vaccine immunogenicity in pediatric hematopoietic cell transplant recipients.

ABSTRACT: Pediatric hematopoietic cell transplant (HCT) recipients exhibit poor serologic responses to influenza vaccination early after transplant. To facilitate the optimization of influenza vaccination timing, we sought to identify B- and T-cell subpopulations associated with influenza vaccine immunogenicity in this population. We used mass cytometry to phenotype peripheral blood mononuclear cells collected from pediatric HCT recipients enrolled in a multicenter influenza vaccine trial comparing high- and standard-dose formulations over 3 influenza seasons (2016-2019). We fit linear regression models to estimate relationships between immune cell subpopulation numbers before vaccination and prevaccination to postvaccination geometric mean fold rises in antigen-specific (A/H3N2, A/H1N1, and B/Victoria) serum hemagglutination inhibition antibody titers (28-42 days, and ∼6 months after 2 doses). For cell subpopulations identified as predictive of a response to all 3 antigens, we conducted a sensitivity analysis including time after transplant as an additional covariate. Among 156 HCT recipients, we identified 33 distinct immune cell subpopulations; 7 significantly predicted responses to all 3 antigens 28 to 42 days after a 2-dose vaccine series, irrespective of vaccine dose. We also found evidence that baseline absolute numbers of naïve B cells, naïve CD4+ T cells, and circulating T follicular helper cells predicted peak and sustained vaccine-induced titers irrespective of dose or timing of posttransplant vaccine administration. In conclusion, several B- and T-cell subpopulations predicted influenza vaccine immunogenicity in pediatric HCT recipients. This study provides insights into the immune determinants of vaccine responses and may help guide the development of tailored vaccination strategies for this vulnerable population.

Clinical prediction model: Multisystem inflammatory syndrome in children versus Kawasaki disease.

BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious complication of severe acute respiratory syndrome coronavirus 2 infection. Features of MIS-C overlap with those of Kawasaki disease (KD). OBJECTIVE: The study objective was to develop a prediction model to assist with this diagnostic dilemma. METHODS: Data from a retrospective cohort of children hospitalized with KD before the coronavirus disease 2019 pandemic were compared to a prospective cohort of children hospitalized with MIS-C. A bootstrapped backwards selection process was used to develop a logistic regression model predicting the probability of MIS-C diagnosis. A nomogram was created for application to individual patients. RESULTS: Compared to children with incomplete and complete KD (N = 602), children with MIS-C (N = 105) were older and had longer hospitalizations; more frequent intensive care unit admissions and vasopressor use; lower white blood cell count, lymphocyte count, erythrocyte sedimentation rate, platelet count, sodium, and alanine aminotransferase; and higher hemoglobin and C-reactive protein (CRP) at admission. Left ventricular dysfunction was more frequent in patients with MIS-C, whereas coronary abnormalities were more common in those with KD. The final prediction model included age, sodium, platelet count, alanine aminotransferase, reduction in left ventricular ejection fraction, and CRP. The model exhibited good discrimination with AUC 0.96 (95% confidence interval: [0.94-0.98]) and was well calibrated (optimism-corrected intercept of -0.020 and slope of 0.99). CONCLUSIONS: A diagnostic prediction model utilizing admission information provides excellent discrimination between MIS-C and KD. This model may be useful for diagnosis of MIS-C but requires external validation.

Sarcopenia defined by a computed tomography estimate of the psoas muscle area does not predict frailty in geriatric trauma patients.

INTRODUCTION: The aim of our study was to assess the correlation between frailty & sarcopenia and impact of each condition on outcomes in geriatric trauma patients. METHODS: We performed a four-year (2013-2016) secondary analysis of our prospectively maintained frailty database and included all trauma patients age ≥65 y who had CT-abdomen. Trauma-Specific-Frailty-Index (TSFI) was used to calculate frailty. Patients were classified as non-frail or frail. Sarcopenia was defined as the lowest sex-specific-quartile of total-psoas-index (TPI). Outcome measures included in-hospital complications, mortality and adverse disposition. RESULTS: 325 patients were included in the study, 36% (n = 117) were frail and 24.9% (n = 81) had sarcopenia. There was a weak correlation between frailty and sarcopenia (R2 = 0.04). The overall rate of complications and mortality was 19.4% and 7.7% respectively. On regression analysis, after controlling for possible confounding variables and frailty status, sarcopenia was associated with adverse disposition (OR:1.41,p = 0.01). However, it was not associated with in-hospital complications (OR:1.21,p = 0.54) or in-hospital mortality (OR:1.12,p = 0.73). CONCLUSION: Sarcopenia as an individual marker might not be an effective screening tool for risk assessment in geriatric-trauma patients. Frailty assessment should be a part of risk assessment and prognostication.