Clinical-Ultrasound Model to Predict the Clinical Course in Bronchiolitis

临床超声模型预测毛细支气管炎的临床病程

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Abstract

BACKGROUND: The aim of the present study was to develop a clinical-ultrasound model for early detection of hospital admission, pediatric intensive care unit (PICU) admission, and oxygen requirement in children diagnosed with acute bronchiolitis (AB). Furthermore, the prognostic ability of models including sonographic data from antero-lateral, lateral-posterior, and posterior areas (eight zones) vs. antero-lateral and lateral-posterior areas (six zones) vs. only antero-lateral areas (four zones) was analyzed. METHODS: A prospective study was conducted on infants under 12 months with AB. A lung ultrasound (LUS) was performed within 24 h of hospital care and analyzed using the Lung Ultrasound Combined Score (LUCS) based on the ultrasound patterns and their extent. Regression models combining LUCS (using eight, six, or four lung areas) with age and clinical scale were created. RESULTS: A total of 90 patients were included (62 admitted to the ward, 15 to PICU), with a median age of 3.7 months. Clinical-ultrasound models with eight and six lung zones predicted hospital admission (AUC 0.89), need for oxygen therapy (AUC 0.88), and its duration (40% explanatory capacity). Models using four lung areas had lower prognostic yield. No model predicted PICU admission needs or duration. CONCLUSIONS: The ultrasound pattern and its extension combined with clinical information may be useful to predict hospital admission and oxygen requirement.

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