Modern Technologies in Lower Respiratory Tract Infections in Children

Bronchiolitis, a viral infection, is the main representation of LRTIs in infants. It affects the small airways, causing breathing- and feeding difficulties. Today, treatment relies on subjective evaluations, lacking objective measures for assessment. This increases the risk of both under- and over treating patients. In the long term, bronchiolitis increases risk of asthma, but it is unknown who the high-risk patients for chronic lung disease are.

Lung ultrasonography (LUS) has emerged as a promising tool for assessing bronchiolitis severity and progression of the disease. The investigators will explore its use to improve diagnostic accuracy and treatment decisions, and develop AI-driven scoring tools for novel technology.

Additionally, tidal breathing flow volume loops (TBFVL) offer a non-invasive method for evaluating airway obstruction in infants, with the potential to assess severity of bronchiolitis, treatment efficacy and post-infection lung function.

In this project the investigators will combine the use of these modern technologies to improve treatment and follow-up of infants with LRTIs.

The main aim for this observational study is to assess the utility of lung ultrasonography (LUS) and tidal flow volume loops (TBFVL) in infant lower respiratory tract infections (LRTIs) for individual risk stratification in acute and chronic settings. This aims to refine the management of bronchiolitis, identifying high-risk patients for chronic lung disease to tailor treatment and follow-up protocols.

The project has three secondary objectives.

1. To assess correlation between LUS and TBFVL findings with clinical score at admission, length of stay, need of respiratory support and ICU admissions. 2. To assess duration of symptoms following acute bronchiolitis and evaluate the use of LUS and TBFVL in objectively examine post-infectious sequela. 3. To evaluate the long-term impact of bronchiolitis on lung function through clinical follow-up after a 12 month period.

Lower respiratory tract infections (LRTIs) stand as the leading cause of hospitalization, while asthma is the leading cause of chronic lung disease among children in Nordic countries. The project seeks to improve risk stratification and treatment protocols in both acute and chronic settings.

In the acute setting, the project endeavors to prognosticate individual patient outcomes, thereby individualize treatment and mitigating unnecessary hospital admissions, use of respiratory support and antibiotic administration. Additionally there is potential of more aggressive treatment to selected patients. The study aims to improve the understanding of pathophysiological processes of LRTIs in infants, providing objective metrics to evaluate disease severity and individualize treatment.

The investigators aim to validate the utility, validity, and simplicity of handheld ultrasound devices as bedside diagnostic tools for this common disease, alongside affirming the value of tidal flow volume loops (TBFVL) in acute and chronic settings to assess airway obstruction in infants. Combining these modern technologies, evaluating affliction of both the parenchyme and the airways will probide a new perspective in treatment of LRTIs. In addition the project will strive to develop novel technology with AI-driven scoring tools of LUS.

Furthermore, the project aims to examine the trajectory of symptoms post-LRTI and facilitate the early identification of patients with high-risk of chronic lung disease. Early detection of asthma and other chronic lung diseases holds the potential to improve outcomes and mitigate the need for hospitalization, thus easing both economic and emotional burdens associated with the disease.

For caregivers, the lack of information concerning symptom duration and risk of future disease represents a significant knowledge gap. The project aims to address this, by examining post-infection symptom duration and identifying high-risk cohorts predisposed to chronic lung disease. This has the potential to both improve information, personalize follow-up and reduce hospital readmissions.