Bacillus Calmette-Guérin-related cold thigh abscess as an unusual cause of thigh swelling in infants following BCG vaccine administration: a case series

<p>Abstract</p> <p>Introduction</p> <p>Thigh swelling in an infant can be a symptom of a simple benign condition or a life-threatening condition. We observed a cluster of thigh swelling episodes in infants in which the cause was Bacillus Calmette-Guérin-related cold thigh abscess. We report this unusual case series to raise awareness about this diagnosis.</p> <p>Case presentations</p> <p>We performed a retrospective review of five infants (four boys and one girl) who presented with Bacillus Calmette-Guérin-related left thigh abscess. The swelling was noticed by the parents at a mean period of three months prior to presentation. The ages at presentation were five, five, eight and nine months for the boys, and six months for the girl. All of the patients were healthy Saudi infants, and received the Bacillus Calmette-Guérin vaccine at birth. Clinically, all of the patients were well and did not demonstrate signs of systemic infection. All patients underwent needle aspiration, with subsequent incision and drainage in four of the five cases. The cultures obtained from the abscess fluids were the key to establishing the diagnosis. Only three patients (60%) received antituberculosis drugs. Wound healing lasted for a mean period of approximately seven months. Two-year follow-up was unremarkable for all of our patients.</p> <p>Conclusions</p> <p>Technical errors continue to be significant in the development of vaccine-related complications. Bacillus Calmette-Guérin-related cold thigh abscess is an extremely rare entity.</p

Quantifying sources of bias in longitudinal data linkage studies of child abuse and neglect: measuring impact of outcome specification, linkage error, and partial cohort follow-up

Abstract Background Health informatics projects combining statewide birth populations with child welfare records have emerged as a valuable approach to conducting longitudinal research of child maltreatment. The potential bias resulting from linkage misspecification, partial cohort follow-up, and outcome misclassification in these studies has been largely unexplored. This study integrated epidemiological survey and novel administrative data sources to establish the Alaska Longitudinal Child Abuse and Neglect Linkage (ALCANLink) project. Using these data we evaluated and quantified the impact of non-linkage misspecification and single source maltreatment ascertainment use on reported maltreatment risk and effect estimates. Methods The ALCANLink project integrates the 2009–2011 Alaska Pregnancy Risk Assessment Monitoring System (PRAMS) sample with multiple administrative databases through 2014, including one novel administrative source to track out-of-state emigration. For this project we limited our analysis to the 2009 PRAMS sample. We report on the impact of linkage quality, cohort follow-up, and multisource outcome ascertainment on the incidence proportion of reported maltreatment before age 6 and hazard ratios of selected characteristics that are often available in birth cohort linkage studies of maltreatment. Results Failure to account for out-of-state emigration biased the incidence proportion by 12% (from 28.3%w to 25.2%w), and the hazard ratio (HR) by as much as 33% for some risk factors. Overly restrictive linkage parameters biased the incidence proportion downwards by 43% and the HR by as much as 27% for some factors. Multi-source linkages, on the other hand, were of little benefit for improving reported maltreatment ascertainment. Conclusion Using the ALCANLink data which included a novel administrative data source, we were able to observe and quantify bias to both the incidence proportion and HR in a birth cohort linkage study of reported child maltreatment. Failure to account for out-of-state emigration and low-quality linkage methods may induce bias in longitudinal data linkage studies of child maltreatment which other researchers should be aware of. In this study multi-agency linkage did not lead to substantial increased detection of reported maltreatment. The ALCANLink methodology may be a practical approach for other states interested in developing longitudinal birth cohort linkage studies of maltreatment that requires limited resources to implement, provides comprehensive data elements, and can facilitate comparability between studies

Administrative applications

Nurse managers play a critical role in ensuring an appropriate number and mix of staff are available to ensure safe patient care is provided. When leadership decisions are effective, we see improved patient care outcomes, better staff performance, increased job satisfaction and staff retention. However, when decision making is less effective both patients and staff can be negatively impacted. The impact is particularly noticeable for patients who may experience increased adverse events, including greater risk of dying. Making evidence-based staffing decisions can be challenging for nurse managers given the complexity of today’s workplace and importantly, a lack of access to real-time data. Many factors impact on their decisions including nursing shortages; challenges to skills mix (human capital such as experience and qualifications); staff stress, burnout and fatigue; changes to the complexity of patient care needs; an aging workforce and communication inefficiencies. There are many workload measurement tools used internationally, but most are not based on real-time data showing patient acuity, bed occupancy rates and the quality and availability of staffing resources, all factors which are necessary to make cost-effective staffing decisions. Instead, nurse managers are left with many static and disparate reporting systems that do not meet managerial requirements for decision-making. This can result in increased workloads and stress for nurse managers, which also ultimately impact clinical staff. Hospitals need to develop and use software systems which will harness existing data, allowing nurse managers to extract, analyze and interpret data in a timely manner to support appropriate and safe nurse staffing decisions