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Prognostic indicators of short-term survival of ineffective airway clearance in children with acute respiratory infection: a longitudinal study.

Lívia Maia PascoalMarcos Venícius de Oliveira LopesViviane Martins da SilvaDaniel Bruno Resende ChavesBeatriz Beltrão AmorimMarília Mendes NunesNatália Barreto de Castro
Published in: Contemporary nurse (2020)
Background: Studies that establish the indicators of clinical status deterioration of Ineffective airway clearance remain scarce. Prognostic studies provide data for nurses identify clinical indicators that suggest a higher chance of early development of a nursing diagnosis. Objective: To identify the prognostic indicators of short-term survival of ineffective airway clearance (IAC) in children with acute respiratory infection (ARI). Design: A prospective open cohort study. Methods: This study was with a group of 136 children with acute respiratory infection who were followed for a minimum of six and a maximum of ten consecutive days. Children who had not completed six days of monitoring or who were carriers of diseases that would alter the specific symptoms of respiratory infection were excluded. The survival rate of ineffective airway clearance was calculated using Nelson-Aalen's method. A Cox regression model was used to analyze the influence of clinical indicators on survival time of this diagnosis. Results: The diagnosis survival rate was extremely low (only 0.4% on the 5th day of follow-up). The greatest reduction in survival rate was observed in the first 48 h (survival rate = 2.5%). Four defining characteristics associated with a worse prognosis of IAC among children with ARI: ineffective cough (RR = 5.86; 95% CI: 3.53-9.72), absence of cough (RR = 2.92; 95% CI: 1.68-5.08), adventitious breath sounds (RR = 2.47; 95% CI: 2.01-3.03), and diminished breath sounds (RR = 1.23; 95% CI: 1.05-1.45). Conclusion: Four clinical indicators showed a strong relationship with an increased risk of worsening clinical status associated with this nursing diagnosis. Impact statement: Clinical deterioration related to ineffective airway clearance among children with acute respiratory infection is fast and requires particular attention from nurses.
Keyphrases
  • healthcare
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  • machine learning
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