Safety of discharge for children with cancer and febrile neutropenia off antibiotics using absolute neutrophil count threshold values as a surrogate marker for adequate bone marrow recovery.

BACKGROUND: Febrile neutropenia (F&N) is common among pediatric oncology patients. However, there is a lack of clarity regarding parameters whereby such patients have demonstrated adequate bone marrow recovery for hospital discharge and empiric antibiotic discontinuation. PROCEDURE: A retrospective review was performed for 350 episodes of F&N occurring at a single institution between 2007 and 2012 in pediatric oncology patients who were afebrile for 24 hr and had no bacterial source identified. Seven-day postdischarge outcomes were assessed and compared based on absolute neutrophil count (ANC) at discharge in order to identify an optimal threshold. RESULTS: Overall, 7-day readmission rates were low (17/350, 4.6%), with patients discharged with post-nadir ANC of 100-199/µl (2/51, 3.9%), 200-499/µl (5/125, 4.0%), and ≥500/µl (8/160, 5.0%), all having similar rates. Patients with a discharge ANC < 100/µl (2/14, 14.3%) had a higher readmission rate. A new bloodstream infection was identified upon readmission in one patient in each discharge ANC range except for ANC of 100-199/µl, in which none occurred. In a subset of 217 episodes where the ANC fell below 200/µl during the admission and subsequently rose above 100/µl, 94 episodes resulted in 126 additional hospital days while subjects awaited further count recovery. One death occurred in a patient whose ANC at discharge was 290/µl. This patient had received additional chemotherapy after count recovery and prior to discharge, and was readmitted with Clostridium tertium bacteremia. CONCLUSION: These results suggest that a post-nadir ANC > 100/µl is a safe threshold value for empiric antibiotic discontinuation and discharge home.

Differences in active commuting among younger and older adults.

The demonstrated health benefits of active commuting (AC) and low participation rates among older adults indicate a need to examine the socioecological correlates of AC by age category. An online survey of employed U.S. adults examined AC participation and individual, employment-related, community, and environmental variables. Participants were dichotomized by age (younger: 18-49 yr; n = 638, 64% and older: ≥ 50 yr; n = 359, 36%). Logistic-regression analyses examined differences in AC correlates by age. Older adults were less likely to be active commuters (13.4%) than younger adults (27.9%; p < .001) For older adults, analyses yielded a Nagelkerke R2 = .76, with perceived behavioral control, behavioral beliefs, household cars, and walking distance as predictors. Analyses for younger adults resulted in a Nagelkerke R2 = .79, with perceived behavioral control, coworker normative beliefs, parking problems at work, greater employer and community support for AC, and bad weather as predictors. Findings suggest age should be considered when examining and targeting AC behaviors.

An examination of the relationship of interpersonal influences with walking and biking to work.

UNLABELLED: Active commuting (AC) to the workplace is a successful strategy for incorporating more physical activity into daily life and is associated with health benefits. The purpose of this study was to understand the relationship between interpersonal influences and AC. METHODS: A cross-sectional online survey was delivered to workplaces in the mid-Atlantic region. A volunteer convenience sample of adults (N = 1234) completed questions about demographics, number of times per week actively commuting, spouse and coworker AC patterns, and spousal and coworker normative beliefs for AC. Basic descriptive and frequencies described the sample; bivariate correlations examined the relationship between AC and spouse and coworker variables. A multivariate regression analysis predicted the variance in AC with interpersonal independent variables. RESULTS: The sample was primarily middle-aged, white (92.7%), female (67.9%), and well-educated (83.3% college graduate or higher). Of those surveyed, 20.3% report AC to work at least once per week by means of walking or biking. The number of times per week of AC for spouse (P < .001) and coworkers (P = .006) and AC norms for spouse (P < .001) and coworker (P < .001) were positively related to AC. The multivariate regression model accounted for 37.9% of the variance in AC (F = 101.83, df = 4, P < .001). CONCLUSION: This study demonstrates that interpersonal influences are significantly related to actively commuting to work. Future interventions targeting AC should consider these interpersonal influences in addition to individual and environmental influences that have been previously documented.

Examining the link between public transit use and active commuting.

BACKGROUND: An established relationship exists between public transportation (PT) use and physical activity. However, there is limited literature that examines the link between PT use and active commuting (AC) behavior. This study examines this link to determine if PT users commute more by active modes. METHODS: A volunteer, convenience sample of adults (n = 748) completed an online survey about AC/PT patterns, demographic, psychosocial, community and environmental factors. t-test compared differences between PT riders and non-PT riders. Binary logistic regression analyses examined the effect of multiple factors on AC and a full logistic regression model was conducted to examine AC. RESULTS: Non-PT riders (n = 596) reported less AC than PT riders. There were several significant relationships with AC for demographic, interpersonal, worksite, community and environmental factors when considering PT use. The logistic multivariate analysis for included age, number of children and perceived distance to work as negative predictors and PT use, feelings of bad weather and lack of on-street bike lanes as a barrier to AC, perceived behavioral control and spouse AC were positive predictors. CONCLUSIONS: This study revealed the complex relationship between AC and PT use. Further research should investigate how AC and public transit use are related.

Health-related factors associated with mode of travel to work.

Active commuting (AC) to the workplace is a potential strategy for incorporating physical activity into daily life and is associated with health benefits. This study examined the association between health-related factors and mode of travel to the workplace. Methods. A volunteer convenience sample of employed adults completed an online survey regarding demographics, health-related factors, and the number of times/week walking, biking, driving, and using public transit to work (dichotomized as no walk/bike/drive/PT and walk/bike/drive/PT 1 + x/week). Logistic regression was used to predict the likelihood of each mode of transport and meeting PA recommendations from AC according to demographics and health-related factors. Results. The sample (n = 1175) was aged 43.5 ± 11.4 years and was primarily White (92.7%) and female (67.9%). Respondents reported walking (7.3%), biking (14.4%), taking public transit (20.3%), and driving (78.3%) to work at least one time/week. Among those reporting AC, 9.6% met PA recommendations from AC alone. Mode of travel to work was associated with several demographic and health-related factors, including age, number of chronic diseases, weight status, and AC beliefs. Discussion. Mode of transportation to the workplace and health-related factors such as disease or weight status should be considered in future interventions targeting AC.

Social ecological influences on work-related active commuting among adults.

OBJECTIVE: To examine influences on active commuting (AC) behavior using a social ecological framework. METHODS: Participants (N = 1234) responded to an online survey about AC patterns and social ecological influences on AC. Multiple regression analysis determined the relative influence of individual, interpersonal, institutional, community, and environmental levels on AC. RESULTS: Significant relationships were found between AC and individual, interpersonal, institutional, community, and environmental influences; 70% of the variance in AC was explained with the full model. CONCLUSIONS: The social ecological model provides a framework for understanding a range of influences on AC and should inform strategies to improve AC behavior.