Clinical indicators of ineffective airway clearance in children with acute respiratory infection

Author:

Pascoal Livia Maia1,Lopes Marcos Venícios de Oliveira2,da Silva Viviane Martins2,Beltrão Beatriz Amorim2,Chaves Daniel Bruno Resende2,Herdman T Heather3,Lira Ana Luisa Brandão de Carvalho4,Teixeira Iane Ximenes2,Costa Alice Gabrielle de Sousa2

Affiliation:

1. Federal University of Maranhão, Fortaleza, Brazil

2. Federal University of Ceará, Fortaleza, Brazil

3. NANDA International, Kaukauna, WI, USA

4. Federal University of Rio Grande do Norte, Natal, Brazil

Abstract

The identification of clinical indicators with good predictive ability allows the nurse to minimize the existing variability in clinical situations presented by the patient and to accurately identify the nursing diagnosis, which represents the true clinical condition. The purpose of this study was to analyze the accuracy of NANDA-I clinical indicators of the nursing diagnosis ineffective airway clearance (IAC) in children with acute respiratory infection. This was a prospective cohort study conducted with a group of 136 children and followed for a period of time ranging from 6 to 10 consecutive days. For data analysis, the measures of accuracy were calculated for clinical indicators, which presented statistical significance in a generalized estimated equation model. IAC was present in 91.9% of children in the first assessment. Adventitious breath sounds presented the best measure of accuracy. Ineffective cough presented a high value of sensitivity. Changes in respiratory rate, wide-eyed, diminished breath sounds, and difficulty vocalizing presented high positive predictive values. In conclusion, adventitious breath sounds showed the best predictive ability to diagnose IAC in children with respiratory acute infection.

Publisher

SAGE Publications

Subject

Pediatrics,Pediatrics, Perinatology, and Child Health

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3