Emergency Practice Innovation Centre, St. Vincent's Hospital, Melbourne, Victoria 3068, Australia.
Emerg Med Australas. 2010 Feb;22(1):21-9. doi: 10.1111/j.1742-6723.2009.01254.x. Epub 2010 Feb 4.
We examined whether a previously validated verbal dyspnoea rating scale, and/or other demographic and clinical parameters, could predict ED departure status, among ED patients presenting with shortness of breath.
In this prospective observational study, a convenience sample of patients presenting to an inner urban adult tertiary hospital ED with shortness of breath were assessed at triage using objective and subjective breathlessness parameters. These included respiratory rate, oxygen saturation, heart rate, systolic blood pressure and verbal dyspnoea scores. A verbal dyspnoea score for worst dyspnoea during the current episode and basic demographic and presentation characteristics were also collected. These variables were assessed as predictors of ED departure status (inpatient admission or ED discharge) using logistic regression.
From a sample of 253 participants, verbal dyspnoea scores > or =8 predicted inpatient admission 89% specificity (95% confidence interval [CI] 82.1-93.4), and scores < or =3 predicted discharge with 95% specificity (95% CI 89.5-98.0). For patients with shortness of breath as the primary complaint, the combination of verbal dyspnoea score > or =6, heart rate > or =94 bpm at triage and ambulance arrival predicted admission with 90% sensitivity (95% CI 82-95%) and 84% specificity (95% CI 73-92%). These same variables predicted admission for all patients with 84% sensitivity (95% CI 75.8-89.2) and 79% specificity (95% CI 71.5-85.5).
Verbal dyspnoea score, alone and in combination with heart rate and arrival transport, can accurately predict admission. Once validated they might be useful in assessing, prioritizing and making rapid site of care decisions for breathless patients presenting to the ED.
我们研究了在因呼吸急促而到急诊就诊的患者中，以前验证过的言语呼吸困难评分量表和/或其他人口统计学和临床参数是否可以预测 ED 离院状态。
在这项前瞻性观察研究中，对在城市成人三级医院 ED 因呼吸急促就诊的便利样本患者，在分诊时使用客观和主观呼吸困难参数进行评估。这些参数包括呼吸频率、氧饱和度、心率、收缩压和言语呼吸困难评分。还收集了当前发作期间最严重呼吸困难的言语呼吸困难评分和基本人口统计学和就诊特征。使用逻辑回归评估这些变量对 ED 离院状态（住院或 ED 出院）的预测作用。
在 253 名患者样本中，言语呼吸困难评分>或=8 预测住院的特异性为 89%（95%置信区间 [CI] 82.1-93.4），评分<或=3 预测出院的特异性为 95%（95% CI 89.5-98.0）。对于以呼吸急促为主要主诉的患者，言语呼吸困难评分>或=6、分诊时心率>或=94 bpm 和救护车到达预测住院的敏感性为 90%（95% CI 82-95%）和特异性为 84%（95% CI 73-92%）。对于所有患者，这些相同的变量预测住院的敏感性为 84%（95% CI 75.8-89.2%）和特异性为 79%（95% CI 71.5-85.5%）。
言语呼吸困难评分单独或与心率和到达交通工具相结合，可准确预测住院。一旦验证，它们可能有助于评估、优先考虑和快速做出呼吸急促患者的护理地点决策。
