The effect of activity and face masks on exhaled particles in children.

Importance: Despite the high burden of respiratory infections among children, the production of exhaled particles during common activities and the efficacy of face masks in children have not been sufficiently studied. Objective: To determine the effect of type of activity and mask usage on exhaled particle production in children. Methods: Healthy children were asked to perform activities that ranged in intensity (breathing quietly, speaking, singing, coughing, and sneezing) while wearing no mask, a cloth mask, or a surgical mask. The concentration and size of exhaled particles were assessed during each activity. Results: Twenty-three children were enrolled in the study. Average exhaled particle concentration increased by intensity of activity, with the lowest particle concentration during tidal breathing (1.285 particles/cm3 [95% CI 0.943, 1.627]) and highest particle concentration during sneezing (5.183 particles/cm3 [95% CI 1.911, 8.455]). High-intensity activities were associated with an increase primarily in the respirable size (≤ 5 µm) particle fraction. Surgical and cloth masks were associated with lower average particle concentration compared to no mask (P = 0.026 for sneezing). Surgical masks outperformed cloth masks across all activities, especially within the respirable size fraction. In a multivariable linear regression model, we observed significant effect modification of activity by age and by mask type. Interpretation: Similar to adults, children produce exhaled particles that vary in size and concentration across a range of activities. Production of respirable size fraction particles (≤ 5 µm), the dominant mode of transmission of many respiratory viruses, increases significantly with coughing and sneezing and is most effectively reduced by wearing surgical face masks.

Standardizing the Evaluation and Management of Necrotizing Enterocolitis in a Level IV NICU.

OBJECTIVES: Necrotizing enterocolitis (NEC) is a severe intestinal inflammatory disease and a leading cause of morbidity and mortality in NICUs. Management of NEC is variable because of the lack of evidence-based recommendations. It is widely accepted that standardization of patient care leads to improved outcomes. This quality improvement project aimed to decrease variation in the evaluation and management of NEC in a Level IV NICU. METHODS: A multidisciplinary team investigated institutional variation in NEC management and developed a standardized guideline and electronic medical record tools to assist in evaluation and management. Retrospective baseline data were collected for 2 years previously and prospectively for 3.5 years after interventions. Outcomes included the ratio of observed-to-expected days of antibiotics and nil per os (NPO) on the basis of the novel guidelines and the percentage of cases treated with piperacillin/tazobactam. Balancing measures were death, surgery, and antifungal use. RESULTS: Over 5.5 years, there were 124 evaluations for NEC. Special cause variation was noted in the observed-to-expected antibiotic and NPO days ratios, decreasing from 1.94 to 1.18 and 1.69 to 1.14, respectively. Piperacillin/tazobactam utilization increased from 30% to 91%. There were no increases in antifungal use, surgery, or death. CONCLUSIONS: Variation in evaluation and management of NEC decreased after initiation of a guideline and supporting electronic medical record tools, with fewer antibiotic and NPO days without an increase in morbidity or mortality. A quality improvement approach can benefit patients and decrease variability, even in diseases with limited evidence-based standards.

Effect modification by age of the association between obstructive lung diseases, smoking, and COVID-19 severity.

INTRODUCTION: Obstructive lung diseases (asthma and chronic obstructive pulmonary disease (COPD)) and smoking are associated with greater risk of respiratory infections and hospitalisations, but conflicting data exist regarding their association with severity of COVID-19, and few studies have evaluated whether these associations differ by age. OBJECTIVES: To examine the associations between asthma, COPD and smoking on the severity of COVID-19 among a cohort of hospitalised patients, and to test for effect modification by age. METHODS: We performed a retrospective analysis of electronic health record data of patients admitted to Massachusetts General Hospital, assigning the maximal WHO Clinical Progression Scale score for each patient during the first 28 days following hospital admission. Using ordered logistic regression, we measured the association between maximal severity score and asthma, COPD and smoking and their interaction with age. MEASUREMENTS AND MAIN RESULTS: Among 1391 patients hospitalised with COVID-19, we found an increased risk of severe disease among patients with COPD and prior smoking, independent of age. We also found evidence of effect modification by age with asthma and current smoking; in particular, asthma was associated with decreased COVID-19 severity among older adults, and current smoking was associated with decreased severity among younger patients. CONCLUSIONS: This cohort study identifies age as a modifying factor for the association between asthma and smoking on severity of COVID-19. Our findings highlight the complexities of determining risk factors for COVID-19 severity, and suggest that the effect of risk factors may vary across the age spectrum.

The diagnosis of respiratory disease in children using a phone-based cough and symptom analysis algorithm: The smartphone recordings of cough sounds 2 (SMARTCOUGH-C 2) trial design.

The diagnosis of acute respiratory diseases in children can be challenging, and no single objective diagnostic test exists for common pediatric respiratory diseases. Previous research has demonstrated that ResAppDx, a cough sound and symptom-based analysis algorithm, can identify common respiratory diseases at the point of care. We present the study protocol for SMARTCOUGH-C 2, a prospective diagnostic accuracy trial of a cough and symptom-based algorithm in a cohort of children presenting with acute respiratory diseases. The objective of the study is to assess the performance characteristics of the ResAppDx algorithm in the diagnosis of common pediatric acute respiratory diseases.