Penaloza Andrea, Verschuren Franck, Meyer Guy, Quentin-Georget Sybille, Soulie Caroline, Thys Frédéric, Roy Pierre-Marie
Emergency Department, Cliniques Universitaires St-Luc, Université Catholique de Louvain, Belgium.
Ann Emerg Med. 2013 Aug;62(2):117-124.e2. doi: 10.1016/j.annemergmed.2012.11.002. Epub 2013 Feb 21.
The assessment of clinical probability (as low, moderate, or high) with clinical decision rules has become a cornerstone of diagnostic strategy for patients with suspected pulmonary embolism, but little is known about the use of physician gestalt assessment of clinical probability. We evaluate the performance of gestalt assessment for diagnosing pulmonary embolism.
We conducted a retrospective analysis of a prospective observational cohort of consecutive suspected pulmonary embolism patients in emergency departments. Accuracy of gestalt assessment was compared with the Wells score and the revised Geneva score by the area under the curve (AUC) of receiver operating characteristic curves. Agreement between the 3 methods was determined by κ test.
The study population was 1,038 patients, with a pulmonary embolism prevalence of 31.3%. AUC differed significantly between the 3 methods and was 0.81 (95% confidence interval [CI] 0.78 to 0.84) for gestalt assessment, 0.71 (95% CI 0.68 to 0.75) for Wells, and 0.66 (95% CI 0.63 to 0.70) for the revised Geneva score. The proportion of patients categorized as having low clinical probability was statistically higher with gestalt than with revised Geneva score (43% versus 26%; 95% CI for the difference of 17%=13% to 21%). Proportion of patients categorized as having high clinical probability was higher with gestalt than with Wells (24% versus 7%; 95% CI for the difference of 17%=14% to 20%) or revised Geneva score (24% versus 10%; 95% CI for the difference of 15%=13% to 21%). Pulmonary embolism prevalence was significantly lower with gestalt versus clinical decision rules in low clinical probability (7.6% for gestalt versus 13.0% for revised Geneva score and 12.6% for Wells score) and non-high clinical probability groups (18.3% for gestalt versus 29.3% for Wells and 27.4% for revised Geneva score) and was significantly higher with gestalt versus Wells score in high clinical probability groups (72.1% versus 58.1%). Agreement between the 3 methods was poor, with all κ values below 0.3.
In our retrospective study, gestalt assessment seems to perform better than clinical decision rules because of better selection of patients with low and high clinical probability.
采用临床决策规则评估临床概率（低、中或高）已成为疑似肺栓塞患者诊断策略的基石，但对于医生对临床概率的整体评估的应用了解甚少。我们评估了整体评估在诊断肺栓塞方面的表现。
我们对急诊科连续的疑似肺栓塞患者的前瞻性观察队列进行了回顾性分析。通过受试者操作特征曲线的曲线下面积（AUC）将整体评估的准确性与Wells评分和修订后的Geneva评分进行比较。通过κ检验确定这三种方法之间的一致性。
研究人群为1038例患者，肺栓塞患病率为31.3%。三种方法的AUC差异显著，整体评估的AUC为0.81（95%置信区间[CI] 0.78至0.84），Wells评分为0.71（95%CI 0.68至0.75），修订后的Geneva评分为0.66（95%CI 0.63至0.70）。整体评估将患者归类为临床概率低的比例在统计学上高于修订后的Geneva评分（43%对26%；差异17%的95%CI = 13%至21%）。整体评估将患者归类为临床概率高的比例高于Wells评分（24%对7%；差异17%的95%CI = 14%至20%）或修订后的Geneva评分（24%对10%；差异15%的95%CI = 13%至21%）。在临床概率低的组（整体评估为7.6%，修订后的Geneva评分为13.0%，Wells评分为12.6%）和非高临床概率组（整体评估为18.3%，Wells评分为29.3%，修订后的Geneva评分为27.4%）中，整体评估的肺栓塞患病率显著低于临床决策规则，而在高临床概率组中，整体评估的肺栓塞患病率显著高于Wells评分（72.1%对58.1%）。三种方法之间的一致性较差，所有κ值均低于0.3。
在我们的回顾性研究中，整体评估似乎比临床决策规则表现更好，因为它能更好地筛选出临床概率低和高的患者。
