Pascoal Livia Maia, Lopes Marcos Venícios de Oliveira, da Silva Viviane Martins, Beltrão Beatriz Amorim, Chaves Daniel Bruno Resende, Herdman T Heather, Lira Ana Luisa Brandão de Carvalho, Teixeira Iane Ximenes, Costa Alice Gabrielle de Sousa
Federal University of Maranhão, Fortaleza, Brazil.
Federal University of Ceará, Fortaleza, Brazil
J Child Health Care. 2016 Sep;20(3):324-32. doi: 10.1177/1367493515598648. Epub 2015 Aug 26.
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.
识别具有良好预测能力的临床指标，可使护士将患者所呈现临床情况中的现有变异性降至最低，并准确识别代表真实临床状况的护理诊断。本研究的目的是分析北美护理诊断协会（NANDA-I）对急性呼吸道感染儿童护理诊断无效气道清除（IAC）的临床指标的准确性。这是一项前瞻性队列研究，对一组136名儿童进行了为期6至10天的连续随访。为了进行数据分析，计算了临床指标的准确性指标，并在广义估计方程模型中呈现出统计学意义。在首次评估中，91.9%的儿童存在IAC。异常呼吸音呈现出最佳的准确性指标。无效咳嗽呈现出高敏感性值。呼吸频率变化、眼睛睁大、呼吸音减弱和发声困难呈现出高阳性预测值。总之，异常呼吸音在诊断急性呼吸道感染儿童的IAC方面显示出最佳预测能力。
