Department of Cardiology, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France; Faculté de Médecine Pierre et Marie Curie, university Paris 6, Paris, France; Institute of Cardiometabolism and Nutrition (ICAN), Paris, France.
Department of Cardiology, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France.
Arch Cardiovasc Dis. 2014 Feb;107(2):105-11. doi: 10.1016/j.acvd.2014.01.004. Epub 2014 Feb 18.
Management of increased referrals for transthoracic echocardiography (TTE) examinations is a challenge. Patients with normal TTE examinations take less time to explore than those with heart abnormalities. A reliable method for assessing pretest probability of a normal TTE may optimize management of requests.
To establish and validate, based on requests for examinations, a simple algorithm for defining pretest probability of a normal TTE.
In a retrospective phase, factors associated with normality were investigated and an algorithm was designed. In a prospective phase, patients were classified in accordance with the algorithm as being at high or low probability of having a normal TTE.
In the retrospective phase, 42% of 618 examinations were normal. In multivariable analysis, age and absence of cardiac history were associated to normality. Low pretest probability of normal TTE was defined by known cardiac history or, in case of doubt about cardiac history, by age>70 years. In the prospective phase, the prevalences of normality were 72% and 25% in high (n=167) and low (n=241) pretest probability of normality groups, respectively. The mean duration of normal examinations was significantly shorter than abnormal examinations (13.8 ± 9.2 min vs 17.6 ± 11.1 min; P=0.0003).
A simple algorithm can classify patients referred for TTE as being at high or low pretest probability of having a normal examination. This algorithm might help to optimize management of requests in routine practice.
增加经胸超声心动图(TTE)检查的转诊管理是一项挑战。与心脏异常患者相比,TTE 检查正常的患者所需的检查时间更短。一种可靠的方法来评估 TTE 正常的预测概率,可能有助于优化请求的管理。
基于检查申请,建立并验证一种用于定义 TTE 正常预测概率的简单算法。
在回顾性阶段,研究了与正常情况相关的因素,并设计了一种算法。在前瞻性阶段,根据算法将患者分为 TTE 正常的高概率和低概率组。
在回顾性阶段,618 次检查中有 42%正常。多变量分析表明,年龄和无心脏病史与正常情况相关。低 TTE 正常预测概率定义为已知心脏病史,或对心脏病史有疑问时,年龄>70 岁。在前瞻性阶段,高预测概率(n=167)和低预测概率(n=241)组的正常检查比例分别为 72%和 25%。正常检查的平均持续时间明显短于异常检查(13.8±9.2 分钟比 17.6±11.1 分钟;P=0.0003)。
一种简单的算法可以将 TTE 转诊患者分为正常检查高概率和低概率组。该算法可能有助于优化常规实践中的请求管理。