Difference in clinical features and prognosis of severe adenoviral pneumonia in children with different ages

Severe Adenovirus Pneumonia Masked by Influenza Virus in an 11-Year-Old Child: A Case Report

Background

Adenovirus pneumonia progresses rapidly, with a high rate of progression to severe pneumonia, but the early clinical manifestations lack specificity and are not easy to be recognized.

Methods

Reviewing the relevant literatures, we studied and summarized the early recognition, clinical features and treatment outlook of severe adenovirus pneumonia Case Presentation: An 11-year-old child with community-acquired pneumonia, with influenza A antigen positive by colloidal gold, which further developed into acute respiratory distress syndrome after hospitalization. Three days later, adenovirus was detected positively by PCR of throat swab and diagnosed as severe adenovirus pneumonia. After aggressive treatment, her condition improved and was discharged from the hospital.

Conclusion

Clinically, adenovirus combined with influenza virus infection is uncommon, and adenovirus infection is even rarer in adolescent children.

Risk factors and prediction models for bronchiolitis obliterans after severe adenoviral pneumonia

Severe adenoviral pneumonia (SAP) can cause post-infectious bronchiolitis obliterans (PIBO) in children. We aimed to investigate the relevant risk factors for PIBO and develop a predictive nomogram for PIBO in children with SAP. This prospective study analysed the clinical data of hospitalised children with SAP and categorised them into the PIBO and non-PIBO groups. Least absolute shrinkage and selection operator (LASSO) regressions were applied to variables that exhibited significant intergroup differences. Logistic regression was adopted to analyse the risk factors for PIBO. Additionally, a nomogram was constructed, and its effectiveness was assessed using calibration curves, C-index, and decision curve analysis. A total of 148 hospitalised children with SAP were collected in this study. Among them, 112 achieved favourable recovery, whereas 36 developed PIBO. Multivariable regression after variable selection via LASSO revealed that aged < 1 year (OR, 2.38, 95% CI, 0.82-6.77), admission to PICU (OR, 24.40, 95% CI, 7.16-105.00), long duration of fever (OR, 1.16, 95% CI, 1.04-1.31), and bilateral lung infection (OR, 8.78, 95% CI, 1.32-195.00) were major risk factors for PIBO. The nomogram model included the four risk factors: The C-index of the model was 0.85 (95% CI, 0.71-0.99), and the area under the curve was 0.85 (95% CI, 0.78-0.92). The model showed good calibration with the Hosmer-Lemeshow test (χ2 = 8.52, P = 0.38) and was useful in clinical settings with decision curve analysis.

CONCLUSION

Age < 1 year, PICU admission, long fever duration, and bilateral lung infection are independent risk factors for PIBO in children with SAP. The nomogram model may aid clinicians in the early diagnosis and intervention of PIBO.

WHAT IS KNOWN

• Adenoviruses are the most common pathogens associated with PIBO. • Wheezing, tachypnoea, hypoxemia, and mechanical ventilation are the risk factors for PIBO.

WHAT IS NEW

• Age < 1 year, admission to PICU, long duration of fever days, and bilateral lung infection are independent risk factors for PIBO in children with SAP. • A prediction model presented as a nomogram may help clinicians in the early diagnosis and intervention of PIBO.

Pediatric adenovirus pneumonia: clinical practice and current treatment

Adenovirus pneumonia is common in pediatric upper respiratory tract infection, which is comparatively easy to develop into severe cases and has a high mortality rate with many influential sequelae. As for pathogenesis, adenoviruses can directly damage target cells and activate the immune response to varying degrees. Early clinical recognition depends on patients' symptoms and laboratory tests, including those under 2 years old, dyspnea with systemic toxic symptoms, atelectasis or emphysema in CT image, decreased leukocytes, and significantly increased C-reaction protein (CRP) and procalcitonin (PCT), indicating the possibility of severe cases. Until now, there is no specific drug for adenovirus pneumonia, so in clinical practice, current treatment comprises antiviral drugs, respiratory support and bronchoscopy, immunomodulatory therapy, and blood purification. Additionally, post-infectious bronchiolitis obliterans (PIBO), hemophagocytic syndrome, and death should be carefully noted. Independent risk factors associated with the development of PIBO are invasive mechanical ventilation, intravenous steroid use, duration of fever, and male gender. Meanwhile, hypoxemia, hypercapnia, invasive mechanical ventilation, and low serum albumin levels are related to death. Among these, viral load and serological identification are not only "gold standard" for adenovirus pneumonia, but are also related to the severity and prognosis. Here, we discuss the progress of pathogenesis, early recognition, therapy, and risk factors for poor outcomes regarding severe pediatric adenovirus pneumonia.

Prediction of mortality in pneumonia patients with connective tissue disease treated with glucocorticoids or/and immunosuppressants by machine learning

Objectives

The assessment of accurate mortality risk is essential for managing pneumonia patients with connective tissue disease (CTD) treated with glucocorticoids or/and immunosuppressants. This study aimed to construct a nomogram for predicting 90-day mortality in pneumonia patients using machine learning.

Methods

Data were obtained from the DRYAD database. Pneumonia patients with CTD were screened. The samples were randomly divided into a training cohort (70%) and a validation cohort (30%). A univariate Cox regression analysis was used to screen for prognostic variables in the training cohort. Prognostic variables were entered into the least absolute shrinkage and selection operator (Lasso) and a random survival forest (RSF) analysis was used to screen important prognostic variables. The overlapping prognostic variables of the two algorithms were entered into the stepwise Cox regression analysis to screen the main prognostic variables and construct a model. Model predictive power was assessed using the C-index, the calibration curve, and the clinical subgroup analysis (age, gender, interstitial lung disease, diabetes mellitus). The clinical benefits of the model were assessed using a decision curve analysis (DCA). Similarly, the C-index was calculated and the calibration curve was plotted to verify the model stability in the validation cohort.

Results

A total of 368 pneumonia patients with CTD (training cohort: 247; validation cohort: 121) treated with glucocorticoids or/and immunosuppressants were included. The univariate Cox regression analysis obtained 19 prognostic variables. Lasso and RSF algorithms obtained eight overlapping variables. The overlapping variables were entered into a stepwise Cox regression to obtain five variables (fever, cyanosis, blood urea nitrogen, ganciclovir treatment, and anti-pseudomonas treatment), and a prognostic model was constructed based on the five variables. The C-index of the construction nomogram of the training cohort was 0.808. The calibration curve, DCA results, and clinical subgroup analysis showed that the model also had good predictive power. Similarly, the C-index of the model in the validation cohort was 0.762 and the calibration curve had good predictive value.

Conclusion

In this study, the nomogram developed performed well in predicting the 90-day risk of death in pneumonia patients with CTD treated with glucocorticoids or/and immunosuppressants.

Lactate dehydrogenase and the severity of adenoviral pneumonia in children: A meta-analysis

BACKGROUND

Children with severe adenoviral pneumonia (ADVP) have poor prognosis and high risk of mortality. We performed a meta-analysis to evaluate the association between pretreatment lactate dehydrogenase (LDH) and severity, postinfectious bronchiolitis obliterans (PIBO), and mortality in children with ADVP.

METHODS

Relevant observational studies were identified by search of PubMed, Embase, Web of Science, Wanfang, and CNKI databases from inception to August 3, 2022. A random effect model was used to pool the results by incorporating the potential between-study heterogeneity.

RESULTS

Overall, 23 studies with 4,481 children with ADVP were included in this meta-analysis. Results of meta-analysis showed that children with severe ADVP had a significantly higher level of pretreatment LDH as compared to those with non-severe ADVP (standard mean difference [SMD]: 0.51, 95% confidence interval [CI]: 0.36 to 0.66, p < 0.001; I ² = 69%). Besides, pooled results also suggested that the pretreatment LDH was significantly higher in children who developed PIBO as compared to those who did not (SMD: 0.47, 95% CI: 0.09 to 0.84, p = 0.02, I ² = 80%). Finally, results of the meta-analysis also confirmed that a higher pretreatment LDH (>500 IU/L) was a risk factor of increased mortality during hospitalization (odds ratio: 3.10, 95% CI: 1.62 to 5.92, p < 0.001, I ² = 0%). Sensitivity analyses by excluding one dataset at a time showed consistent results.

CONCLUSION

High pretreatment LDH may be associated with disease severity, development of PIBO, and increased risk of mortality in children with ADVP.