Montpellier University, UR UM 103 IMAGINE, Emergency Department, Nîmes University Hospital, Nîmes, Francia.
Department of Emergency Medicine, Timone University Hospital, Marsella, Francia. UMR 1263 Center of Cardiovascular and Nutrition Research (C2VN), Aix-Marseille University, INSERM, INRAE, Marsella, Francia.
Emergencias. 2024 Apr;36(2):109-115. doi: 10.55633/s3me/011.2024.
To study the diagnostic performance of an ultrasound-based algorithm that includes the deceleration time (DT) of early mitral filling to establish a diagnosis of acute heart failure (AHF) in patients who come to an emergency department because of dyspnea.
Prospective analysis in a convenience sample of patients who came to a hospital emergency department with acute dyspnea. The algorithm included ultrasound findings and 4 echocardiographic findings as follows: mitral annular plane systolic excursion, Doppler mitral flow velocity, tissue Doppler imaging measure of the lateral annulus, and the DT of early mitral filling. The definitive diagnosis was made by 2 physicians blinded to each other's diagnosis and the ultrasound findings.
A total of 166 adult patients with a mean (SD) age of 76 (13) years were included; 79 (48%) were women. AHF was the definitive diagnosis in 62 patients (37%). Diagnostic agreement was good between the 2 physicians (κ = 0.71). The algorithm classified all the patients, and there were no undetermined diagnoses. Diagnostic performance indicators for the ultrasound-based algorithm integrating early DT findings were as follows: area under the receiver operating characteristic curve, 0.91 (95% CI, 0.86-0.96); sensitivity, 87% (95% CI, 76%-94%); specificity, 95% (95% CI, 89%-98%); positive likelihood ratio, 18.1 (95% CI, 7.7-42.8); and negative likelihood ratio, 0.14 (95% CI, 0.07-0.26).
The ultrasound-based algorithm integrating the DT of early mitral filling performs well for diagnosing AHF in emergency patients with dyspnea. The inclusion of early DT allows all patients to be diagnosed.
研究一种基于超声的算法,该算法包括早期二尖瓣充盈的减速时间(DT),以诊断因呼吸困难而就诊急诊科的急性心力衰竭(AHF)患者。
对因急性呼吸困难就诊医院急诊科的患者进行方便样本的前瞻性分析。该算法包括超声发现和 4 项超声心动图发现,如下所示:二尖瓣环平面收缩期位移、二尖瓣血流速度多普勒、外侧瓣环组织多普勒成像测量、早期二尖瓣充盈的 DT。通过 2 名对彼此的诊断和超声发现均不知情的医生做出明确诊断。
共纳入 166 例平均(SD)年龄为 76(13)岁的成年患者,其中 79 例(48%)为女性。62 例(37%)患者被明确诊断为 AHF。2 名医生之间的诊断一致性较好(κ=0.71)。该算法对所有患者进行了分类,没有不确定的诊断。整合早期 DT 发现的基于超声的算法的诊断性能指标如下:受试者工作特征曲线下面积,0.91(95%置信区间,0.86-0.96);敏感度,87%(95%置信区间,76%-94%);特异度,95%(95%置信区间,89%-98%);阳性似然比,18.1(95%置信区间,7.7-42.8);阴性似然比,0.14(95%置信区间,0.07-0.26)。
整合早期二尖瓣充盈 DT 的基于超声的算法在诊断因呼吸困难而就诊急诊科的 AHF 患者时性能良好。纳入早期 DT 可使所有患者得到诊断。