[Anemia, a new severity factor in young infants with acute viral bronchiolitis?]

Development and validation of a nomogram for predicting severe respiratory syncytial virus-associated bronchiolitis

BACKGROUND

Respiratory syncytial virus (RSV) is the most common cause of bronchiolitis and is related to the severity of the disease. This study aimed to develop and validate a nomogram for predicting severe bronchiolitis in infants and young children with RSV infection.

METHODS

A total of 325 children with RSV-associated bronchiolitis were enrolled, including 125 severe cases and 200 mild cases. A prediction model was built on 227 cases and validated on 98 cases, which were divided by random sampling in R software. Relevant clinical, laboratory and imaging data were collected. Multivariate logistic regression models were used to determine optimal predictors and to construct nomograms. The performance of the nomogram was evaluated by the area under the characteristic curve (AUC), calibration ability and decision curve analysis (DCA).

RESULTS

There were 137 (60.4%) mild and 90 (39.6%) severe RSV-associated bronchiolitis cases in the training group (n = 227) and 63 (64.3%) mild and 35 (35.7%) severe cases in the validation group (n = 98). Multivariate logistic regression analysis identified 5 variables as significant predictive factors to construct the nomogram for predicting severe RSV-associated bronchiolitis, including preterm birth (OR = 3.80; 95% CI, 1.39-10.39; P = 0.009), weight at admission (OR = 0.76; 95% CI, 0.63-0.91; P = 0.003), breathing rate (OR = 1.11; 95% CI, 1.05-1.18; P = 0.001), lymphocyte percentage (OR = 0.97; 95% CI, 0.95-0.99; P = 0.001) and outpatient use of glucocorticoids (OR = 2.27; 95% CI, 1.05-4.9; P = 0.038). The AUC value of the nomogram was 0.784 (95% CI, 0.722-0.846) in the training set and 0.832 (95% CI, 0.741-0.923) in the validation set, which showed a good fit. The calibration plot and Hosmer‒Lemeshow test indicated that the predicted probability had good consistency with the actual probability both in the training group (P = 0.817) and validation group (P = 0.290). The DCA curve shows that the nomogram has good clinical value.

CONCLUSION

A nomogram for predicting severe RSV-associated bronchiolitis in the early clinical stage was established and validated, which can help physicians identify severe RSV-associated bronchiolitis and then choose reasonable treatment.

Determination of predictive risk factors for severe bronchiolitis

BACKGROUND

The aim of this study was to determine the predictive risk factors for development of severe bronchiolitis in patients with acute bronchiolitis with no previous chronic disease.

METHODS

Four hundred forty children aged 1-24 months hospitalised with acute bronchiolitis, were examined between February 2018 and February 2019 in this prospective study.

RESULTS

Eighty-five cases were regarded as severe bronchiolitis and 355 as mild-moderate bronchiolitis. Statistically significant differences were observed between the severe and mild-moderate bronchiolitis groups in terms of weight-for-age z-scores, history of bronchiolitis, haemoglobin levels, and time elapsed between the onset of symptoms and admission. Weight-for-age z-scores, the mean time interval between the onset of symptoms and admission, and mean haemoglobin values were lower in the severe bronchiolitis group while the mean number of bronchiolitis attacks was higher than in the mild-moderate bronchiolitis group. Logistic regression analysis determined that a low weight-for-age z-score increased the risk of severe bronchiolitis development 0.56-fold (CI: 0.409-0.760), a short duration between the onset of symptoms and admission increased the risk 0.62-fold (CI: 0.519-0.735), a frequent history of bronchiolitis increased the risk 1.81-fold (CI: 1.135-2.968) and low haemoglobin levels increased the risk 0.72-fold (CI: 0.537-0.969).

CONCLUSION

Low weight-for-age z-scores, a short duration between the onset of symptoms and admission, a high number of previous attacks and low haemoglobin levels were identified as independent parameters of severe bronchiolitis development.