A nomogram that could assist physicians in predicting severe respiratory syncytial virus (RSV)–associated bronchiolitis early on was established and validated in a recent study.
A novel nomogram may help physicians predict severe respiratory syncytial virus (RSV)–associated bronchiolitis in its early clinical stages, according to a study published in BMC Infectious Diseases. The nomogram could also help physicians choose the best treatment for the disease.
RSV is the most common cause of bronchiolitis, which is a lower respiratory tract disease caused by respiratory virus infection. Bronchiolitis causes medical and economic burden, with 108,000 individuals from the United States hospitalized for bronchiolitis in 2016. RSV makes up 41%-83% of all patients with bronchiolitis. This study aimed to “validate a nomogram for predicting the risk of severe RSV-associated bronchiolitis among infants and young children and provide a theoretical basis for clinical identification.”
Individuals who were hospitalized for RSV-associated bronchiolitis at Tianjin Children’s Hospital from January 2018 to December 2021 were evaluated for this study. Patients were included if they were less than 2 years of age, had symptoms and signs of lower respiratory disease, and had a positive nucleic acid of RSV test of their nasopharyngeal secretions. Patients were excluded if they had the illness for more than 2 weeks prior to admittance, had a nosocomial infection, had automatic discharge or death during hospitalization, had a co-bacterial infection, or incomplete medical records.
Demographic information was collected at admission, and patients were randomly assigned to a nomogram training group and a validation group. Discrimination ability was used to evaluate the performance of the prediction model. Total scores of each patient were calculated based on the nomogram for better clinical application.
There were 325 children included in the study, 63.4% of whom were male, and 125 cases were classified as severe RSV infections. A total of 227 children were divided into the training group and 98 into the validation group; 90 and 35 patients with severe RSV were separated into the training and validation groups, respectively.
Children in the training group with severe RSV infection had a younger median age (3 m vs 6 m), a lower median weight at admission (6.5 kg vs 8.4 kg), higher preterm birth rate (17.8% vs 8%), higher cesarean section rate (62.2% vs 47.4%), longer median duration of hospital stay (7 days vs 5 days), and faster median respiratory rate (51b vs 40b) compared with patients with mild RSV.
A univariate logistic regression model found that age (odds ratio [OR], 0.90; 95% CI, 0.85-0.95), weight at admission (OR, 0.74; 95% CI, 0.65-0.85), children from rural areas (OR, 2.01; 95% CI, 1.15-3.51), preterm birth (OR, 2.48; 95% CI, 1.09-5.62), cesarean section (OR, 1.82; 95% CI, 1.06-3.14), breathing rate (OR, 1.16; 95% CI, 1.11-1.21), level of creatine kinase-MB (OR, 1.02; 95% CI, 1.00-1.03), and lactate dehydrogenase (OR, 1.002; 95% CI, 1.000-1.004) were all predictors of severe RSV-associated bronchiolitis.
A multivariate regression analysis found these same factors were associated with severe RSV-associated bronchiolitis, as well as outpatient use of glucocorticoids (OR, 2.27; 95% CI, 1.05-4.9) and lymphocyte percentage (OR, 0.97; 95% CI, 0.95-0.99).
The factors identified by the multivariable regression analysis were presented with a nomogram, and the mean area under curve (AUC) of the nomogram was 0.784 (95% CI, 0.722-0.846) based on the training group. The accuracy was similar in the validation group, with an AUC value of 0.832 (95% CI, 0.741-0.923)
Environmental factors, which could affect severity of RSV infections, were not considered in this data set or in medical records. Respiratory pathogens were examined but other viruses, such as rhinovirus and human bocavirus, have been found to increase the hospitalization rate of RSV-associated bronchiolitis and were not examined. These results are not applicable to children in other age groups. The study was also conducted at a single center, which could limit its applicability to broader settings.
The researchers concluded that the nomogram could predict severe RSV-associated bronchiolitis in early clinical stages, making it helpful for physicians to use.
Yan J, Zhao L, Zhang T, et al. Development and validation of a nomogram for predicting severe respiratory syncytial virus-associated bronchiolitis. BMC Infect Dis. 2023;23:249. doi:10.1186/s12879-023-08179-y