Classification tree to screen for the nursing diagnosis Ineffective airway clearance

• Published in: Revista Brasileira de Enfermagem Vol. 71; no. 5; pp. 2353 - 2358
• Main Authors: Chaves, Daniel Bruno Resende, Pascoal, Lívia Maia, Beltrão, Beatriz Amorim, Nunes, Marília Mendes, Leandro, Tânia Alteniza, Silva, Viviane Martins da, Lopes, Marcos Venícios de Oliveira
• Format: Journal Article
• Language: English
• Published: Brazil Associação Brasileira de Enfermagem 01.09.2018
• Subjects: Airway management; Algorithms; Brazil - epidemiology; Chi-Square Distribution; Classification; Clinical decision making; Cross-Sectional Studies; Decision making; Diagnóstico de Enfermería; Enfermería; Enfermería Pediátrica; Female; Humans; Infant; Infections; Male; Mass Screening - methods; Medical diagnosis; Medical procedures; Niño; Nursing; Nursing care; Nursing Diagnosis - methods; Nursing Diagnosis - statistics & numerical data; Pediatrics; Respiratory diseases; Respiratory Insufficiency - diagnosis; Respiratory Insufficiency - epidemiology; Respiratory Tract Infections - complications; Respiratory Tract Infections - diagnosis; Respiratory Tract Infections - epidemiology; Signos y Síntomas; Brazil
• ISSN: 0034-7167; 1984-0446; 1984-0446
• DOI: 10.1590/0034-7167-2017-0085

to identify the defining characteristics of Ineffective airway clearance with better predictive power using classification trees. the predictive power of the defining characteristics of Ineffective airway clearance was evaluated based on classification trees generated from the data of 249 children with acute respiratory infection. Ineffective cough and adventitious breath sounds were identified as the main defining characteristics when screening for Ineffective airway clearance in accordance with trees based on three different computational algorithms. Ineffective coughing and adventitious breath sounds had better predictive capacity for Ineffective airway clearance in the sample.