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Risk factors for airway clearance dysfunction in children with severe pneumonia: a retrospective study of LASSO model
Xiaoyan Ding1, Jing Bai1, Rui Liu1
1Department of Pediatrics, Beijing Anzhen Nanchong Hospital of Capital Medical University & Nanchong Central Hospital, Nanchong, Sichuan, China.
Insights
Children with severe pneumonia face a high risk of airway clearance dysfunction (ACD). Mechanical ventilation, CRP, PCT, IL-6, and IgA levels are key indicators for assessing ACD risk in these patients.
Area of Science:
- Pediatric Pulmonology
- Critical Care Medicine
- Respiratory Physiology
Background:
- Severe pneumonia in children presents a significant clinical challenge, often leading to complications.
- Airway clearance dysfunction (ACD) is a recognized complication in pediatric severe pneumonia.
- Identifying risk factors for ACD is crucial for timely intervention and improved patient outcomes.
Purpose of the Study:
- To investigate the types and risk factors associated with airway clearance dysfunction (ACD) in children diagnosed with severe pneumonia.
- To identify specific clinical and biochemical markers that predict the development of ACD.
- To evaluate the combined predictive value of identified risk factors for ACD.
Main Methods:
- A retrospective study involving 147 children with severe pneumonia.
- Analysis of demographic and clinical characteristics, including incidence and types of ACD.
- Application of LASSO regression and multivariate Logistic regression for risk factor identification.
- Construction of Receiver Operating Characteristic (ROC) curves to assess predictive accuracy.
Main Results:
- An incidence rate of 42.86% for ACD was observed, characterized by ineffective coughing, thick sputum, dyspnea, and tachypnea.
- Significant differences between ACD and non-ACD groups included age, mechanical ventilation use, nutritional status, and comorbid conditions.
- Elevated C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6), along with lower immunoglobulin A (IgA) levels, were associated with ACD.
- A combined predictive model using mechanical ventilation, CRP, PCT, IL-6, and IgA demonstrated a high Area Under the Curve (AUC) of 0.882 for ACD prediction.
Conclusions:
- Children with severe pneumonia are susceptible to ACD, influenced by factors including mechanical ventilation, CRP, PCT, IL-6, and IgA.
- These identified factors provide a valuable tool for assessing ACD risk in pediatric severe pneumonia.
- Clinical strategies should be developed to enhance airway clearance and support recovery in affected children.
Background:
This study aimed to investigate the types and risk factors of airway clearance dysfunction (ACD) in children with severe pneumonia based on LASSO regression and multivariate Logistic regression analysis.
Methods:
This study was approved by the Hospital Ethics Committee. A retrospective study was conducted on 147 children with severe pneumonia admitted between January 2024 and October 2024. Demographic and clinical characteristics were collected, and the incidence and types of ACD were analyzed. Patients with ACD were assigned to the ACD group, while those without ACD were assigned to the non-ACD group. LASSO regression and multivariate Logistic regression were used to identify risk factors for ACD in these children, and ROC curves were constructed to evaluate the predictive value of these factors for ACD.
Results:
A total of 63 cases of ACD were observed among children with severe pneumonia, including ineffective coughing, thick sputum, dyspnea, nasal flaring/ increased nasal congestion, tachypnea, and oxygen saturation <93%, with an incidence rate of 42.86%. Significant differences were found between the ACD group and non-ACD group in terms of age, mechanical ventilation, nutritional status, comorbid respiratory failure, comorbid heart failure, pulmonary rales, and pulmonary rhonchi (P < 0.05). Additionally, the ACD group had lower platelet count (PLT), immunoglobulin A (IgA), and immunoglobulin M (IgM) levels, while C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) levels were higher compared to the non-ACD group (P < 0.05). Variable screening was performed using the LASSO regression model, identifying three significant influencing factors. These were incorporated into a Logistic regression model, which revealed that mechanical ventilation, CRP, PCT, IL-6, and IgA were influencing factors for ACD in children with severe pneumonia. Based on these findings, an ROC curve was constructed, demonstrating that the combined prediction of mechanical ventilation, CRP, PCT, IL-6, and IgA for ACD in children with severe pneumonia achieved an AUC of 0.882, significantly higher than the AUC of any single indicator (P < 0.05).
Conclusion:
Children with severe pneumonia are at risk of developing ACD, which may be influenced by mechanical ventilation, CRP, PCT, IL-6, and IgA levels. These five factors can be used to assess the risk of ACD in children with severe pneumonia. Accordingly, clinical measures should be developed to improve airway clearance ability and promote recovery in these patients.
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