Health Care–Associated Infections and the Radiology Department
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Health care-associated infections (HCAIs) are a significant concern for both health care workers (HCWs) and patients. They are a major contributing factor of disease in industrialized countries, and are responsible for significant morbidity, mortality, and a direct annual financial loss of $6-7 billion in North America alone. They are an increasingly challenging health issue due to multidrug-resistant pathogens such as methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci among others, along with an increasing number of susceptible patients. Over the last three decades, the risk of HCAIs has increased in the radiology department (RD) in part because of an increased number of patients visiting the department and an increase in the utilization of imaging modalities. In this review, we will discuss how patients and staff can be exposed to HCAIs in the RD, including contaminated inanimate surfaces, radiology equipment, and associated medical devices. As the role of medical imaging has extended from primarily diagnosis to include more interventions, the implementation and development of standardized infection minimization protocols and infection control procedures are vital in the RD, particularly in interventional radiology. With globalisation and the rapid movement of people regionally, nationally, and globally, there is greater risk of exposure to contagious diseases such as Ebola, especially if infected patients are undiagnosed when they travel. For effective infection control, advanced training and education of HCWs in the RD is essential. The purpose of this article is to provide an overview of HCAIs as related to activities of the RD. We will discuss the following major topics including the variety of HCAIs commonly encountered, the role of the RD in HCAIs, transmission of infections to patients and HCWs in the RD, standard infection prevention measures, and the management of susceptible/infected patients in the RD. We shall also examine the role of, and the preparedness of, HCWs, including RD technologists and interventional radiologists, who may be exposed to undiagnosed, yet infected patients. We shall conclude with a brief discussion of the role of further research related to HCAIs. Learning Objectives After the completion of this review article, the readers will • Understand the exposure and role of radiology department in health care-associated infections, • Know the causes/modes/transmission of infections in radiology department, • Be conscious of standard disinfection protocols, • Be aware of current and future strategies required for the effective control of health care-associated infection in the radiology department. This is a CME article and provides the equivalent of 2 hours of continuing education that may be applied to your professional development credit system. A 10-question multiple-choice quiz follows this reading. Please note that no formalized credit (category A) is available from CAMRT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it