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An In vitro Model to Study Immune Responses of Human Peripheral Blood Mononuclear Cells to Human Respiratory Syncytial Virus Infection
Published on: December 10, 2013
Predictors of a normal chest x-ray in respiratory syncytial virus infection
M C Kneyber1, K G Moons, R de Groot
1Department of Paediatrics, Sophia Children's Hospital/University Hospital Rotterdam, The Netherlands.
Insights
A new prediction model accurately identifies children with respiratory syncytial virus (RSV) who are unlikely to need a chest x-ray, potentially reducing unnecessary imaging for lower respiratory tract infections (LRTI).
Area of Science:
- Pediatrics
- Infectious Diseases
- Radiology
Background:
- Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infections (LRTI) in infants and young children.
- Chest x-rays are commonly used in evaluating infants with RSV-related LRTI, but their necessity is often debated.
Purpose of the Study:
- To develop and validate a prediction model for estimating the probability of a normal chest x-ray in children with RSV infection.
- To identify easily obtainable diagnostic parameters that can guide decisions on whether to perform a chest x-ray.
Main Methods:
- A logistic regression model was developed using data from 287 children with RSV infection.
- Patient history, clinical variables, and laboratory data were analyzed.
- The model's predictive accuracy was assessed using the area under the receiver operating curve (ROC-area).
Main Results:
- A normal chest x-ray was predicted by factors including increasing age, birth weight, presence of rhinitis, absence of retractions, and higher arterial oxygen saturation.
- The prediction model achieved an ROC-area of 0.80 in both derivation and validation sets.
- The model was successfully transformed into a score chart for practical application.
Conclusions:
- A prediction model utilizing readily available patient characteristics and clinical data can accurately predict normal chest x-rays in children with RSV.
- This model serves as a valuable tool to help clinicians decide when a chest x-ray is not required for RSV patients.
- Implementing this model may help reduce unnecessary radiographic procedures in pediatric RSV cases.
Abstract:
Respiratory syncytial virus (RSV) accounts for the majority of lower respiratory tract infections (LRTI) in infants and young children. A chest x-ray is frequently performed in infants with LRTI caused by RSV. The aim of this study was to develop and validate a prediction model to estimate the probability for a normal chest x-ray in children with RSV infection. For this purpose, easy obtainable diagnostic parameters were used. This prediction model may be applied to decide which patients do not require a chest x-ray. The data of 287 children admitted with RSV infection or diagnosed as such in the outpatient department of the Sophia Children's Hospital between 1992-1996 were studied. The derivation set comprised 232 patients (1992-1995), and the validation set contained 55 patients (1995-1996). A chest x-ray was designated as normal when atelectasis, hyperinflation, or pulmonary infiltrates were absent. In order to develop a prediction model, patient history and clinical and laboratory variables were consecutively entered into a logistic regression model according to the diagnostic workup that was practiced at the time. Variables with P < or = 0.10 were retained in the model. The predictive accuracy of the multivariable models was examined using the area under receiver operating curve (ROC-area). In 202 (87%) patients from the derivation set, a chest x-ray was performed. A normal chest x-ray could be predicted by increasing age, increasing birth weight, presence of rhinitis, absence of retractions, and increasing arterial oxygen saturation. The ROC-area was 0.80 in the derivation and validation sets. This prediction model was transformed into a score chart. In conclusion, a normal chest x-ray can accurately be predicted, using a model including easily obtainable patient characteristics, and clinical and laboratory variables. This model may be a useful tool in deciding whether or not to perform a chest x-ray in patients with RSV infections.
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