RESUMEN
Respiratory syncytial virus (RSV) is well known for causing a potentially severe course of bronchiolitis in infants. Many paediatric healthcare workers claim to be able to diagnose RSV based on cough sound, which was evaluated in this study. Parents of children < 1 year old admitted to the paediatric ward because of airway complaints were asked to record cough sounds of their child. In all children, MLPA analysis-a variation of PCR analysis-on nasopharyngeal swab was performed (golden standard). Sixteen cough fragments representing 4 different viral pathogens were selected and presented to paediatric healthcare workers. Thirty-two paediatric nurses, 16 residents and 16 senior staff members were asked to classify the audio files and state whether the cough was due to RSV infection or not. Senior staff, nurses and residents correctly identified RSV with a sensitivity of 76.2%, 73.1% and 51.3% respectively. Correct exclusion of RSV cases was performed with a specificity of 60.8%, 60.2% and 65.3% respectively. Sensitivity ranged from 0 to 100% between colleagues; no one correctly identified all negatives. Residents had significantly lower rates of sensitivity than senior staff and nurses. This was strongly related to work experience, in which more than 3.5 years of work experience was related to the best result.Conclusion: Senior staff and nurses were better in making a cough-based diagnosis of RSV compared to residents. Both groups were able to detect the same proportion of true RSV patients based on cough sounds compared to bedside tests but could not validly distinguish RSV from other pathogens based on cough sounds. What is Known: ⢠Many paediatric healthcare workers claim to be capable of diagnosing RSV in infants based on cough sound ⢠Up to now, no studies investigating the recognisability of RSV based on cough sound are published What is New: ⢠Senior staff and paediatric nurses performed better than various other bedside tests in diagnosing RSV but could not replace MLPA analysis ⢠Residents need at least 3.5 years of work experience to be able to make a RSV diagnosis based on cough sound.
Asunto(s)
Bronquiolitis , Infecciones por Virus Sincitial Respiratorio , Virus Sincitial Respiratorio Humano , Niño , Tos/diagnóstico , Tos/etiología , Hospitalización , Humanos , Lactante , Infecciones por Virus Sincitial Respiratorio/complicaciones , Infecciones por Virus Sincitial Respiratorio/diagnósticoRESUMEN
The interpretation of medical images is a primary task for radiologists. Besides two-dimensional (2D) images, current imaging technologies allow for volumetric display of medical images. Whereas current radiology practice increasingly uses volumetric images, the majority of studies on medical image interpretation is conducted on 2D images. The current study aimed to gain deeper insight into the volumetric image interpretation process by examining this process in twenty radiology trainees who all completed four volumetric image cases. Two types of data were obtained concerning scroll behaviors and think-aloud data. Types of scroll behavior concerned oscillations, half runs, full runs, image manipulations, and interruptions. Think-aloud data were coded by a framework of knowledge and skills in radiology including three cognitive processes: perception, analysis, and synthesis. Relating scroll behavior to cognitive processes showed that oscillations and half runs coincided more often with analysis and synthesis than full runs, whereas full runs coincided more often with perception than oscillations and half runs. Interruptions were characterized by synthesis and image manipulations by perception. In addition, we investigated relations between cognitive processes and found an overall bottom-up way of reasoning with dynamic interactions between cognitive processes, especially between perception and analysis. In sum, our results highlight the dynamic interactions between these processes and the grounding of cognitive processes in scroll behavior. It suggests, that the types of scroll behavior are relevant to describe how radiologists interact with and manipulate volumetric images.