Predicting hospital-onset Clostridium difficile using patient mobility data: A network approach

This is the final version. Available from Cambridge University Press via the DOI in this record. Objective: To examine the relationship between unit-wide Clostridium difficile infection (CDI) susceptibility and inpatient mobility and to create contagion centrality as a new predictive measure of CDI. Design: Retrospective cohort study. Methods: A mobility network was constructed using 2 years of patient electronic health record data for a 739-bed hospital (n = 72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (ie, edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and were compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility. Results: Closeness centrality was a statistically significant measure associated with unit susceptibility (P< .05), highlighting the importance of incoming patient mobility in CDI prevention at the unit level. Contagion centrality (CC) was calculated using inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. The contagion centrality measure was statistically significant (P< .05) with our outcome of hospital-onset CDI cases, and it captured the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create easily interpretable clinical tools showing this relationship as well as the risk of hospital-onset CDI in real time, and these tools can be implemented in hospital EHR systems Conclusions: Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak and, thus, provide clinicians and infection prevention staff with advanced warning and specific location data to inform prevention efforts.University of Rochester Clinical and Translational Science InstituteNational Institutes of HealthBurroughs Wellcome Fund Institutional Program Unifying Population and Laboratory Based Science

The epidemiology of injuries across the weight-training sports

Background: Weight-training sports, including weightlifting, powerlifting, bodybuilding, strongman, Highland Games, and CrossFit, are weight-training sports that have separate divisions for males and females of a variety of ages, competitive standards, and bodyweight classes. These sports may be considered dangerous because of the heavy loads commonly used in training and competition. Objectives: Our objective was to systematically review the injury epidemiology of these weight-training sports, and, where possible, gain some insight into whether this may be affected by age, sex, competitive standard, and bodyweight class. Methods: We performed an electronic search using PubMed, SPORTDiscus, CINAHL, and Embase for injury epidemiology studies involving competitive athletes in these weight-training sports. Eligible studies included peer-reviewed journal articles only, with no limit placed on date or language of publication. We assessed the risk of bias in all studies using an adaption of the musculoskeletal injury review method. Results: Only five of the 20 eligible studies had a risk of bias score ≥75 %, meaning the risk of bias in these five studies was considered low. While 14 of the studies had sample sizes >100 participants, only four studies utilized a prospective design. Bodybuilding had the lowest injury rates (0.12–0.7 injuries per lifter per year; 0.24–1 injury per 1000 h), with strongman (4.5–6.1 injuries per 1000 h) and Highland Games (7.5 injuries per 1000 h) reporting the highest rates. The shoulder, lower back, knee, elbow, and wrist/hand were generally the most commonly injured anatomical locations; strains, tendinitis, and sprains were the most common injury type. Very few significant differences in any of the injury outcomes were observed as a function of age, sex, competitive standard, or bodyweight class. Conclusion: While the majority of the research we reviewed utilized retrospective designs, the weight-training sports appear to have relatively low rates of injury compared with common team sports. Future weight-training sport injury epidemiology research needs to be improved, particularly in terms of the use of prospective designs, diagnosis of injury, and changes in risk exposure