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Rendimiento diRendimiento diagnóstico de un algoritmo basado en ecografía clínica para el diagnóstico de insuficiencia cardiaca aguda en pacientes que consultan en urgencias por disnea / Diagnostic performance of a clinical ultrasound-based algorithm for acute heart failure in patients presenting to the emergency department with dyspnea
L’Hermitte, Nicolas; Markarian, Thibaut; Grau Mercier, Laura; Coisy, Fabien; Muller, Laurent; Saadi, Laysa; Claret, Pierre Géraud; Krebs, Hugo; Bobbia, Xavier.
Affiliation
  • L’Hermitte, Nicolas; Nîmes University Hospital. Emergency Department. Montpellier University. Nîmes. Francia
  • Markarian, Thibaut; Timone University Hospital. Department of Emergency Medicine. Marsella. Francia
  • Grau Mercier, Laura; Nîmes University Hospital. Emergency Department. Montpellier University. Nîmes. Francia
  • Coisy, Fabien; Nîmes University Hospital. Emergency Department. Montpellier University. Nîmes. Francia
  • Muller, Laurent; Intensive Care Unit, Nîmes University Hospital. Emergency and Critical Care Medicine. Department of Anesthesiology. Nîmes. Francia
  • Saadi, Laysa; Intensive Care Unit, Nîmes University Hospital. Emergency and Critical Care Medicine. Department of Anesthesiology. Nîmes. Francia
  • Claret, Pierre Géraud; Nîmes University Hospital. Emergency Department. Montpellier University. Nîmes. Francia
  • Krebs, Hugo; Nîmes University Hospital. Emergency Department. Montpellier University. Nîmes. Francia
  • Bobbia, Xavier; Montpellier University Hospital. Emergency Department. Montpellier University. Montpellier. Francia
Emergencias (Sant Vicenç dels Horts) ; 36(2): 1-7, Abr. 2024. graf, tab
Article in Es | IBECS | ID: ibc-231796
Responsible library: ES1.1
Localization: ES15.1 - BNCS
RESUMEN
Objetivos. Analizar el rendimiento diagnóstico de un algoritmo ecográfico que incluye el tiempo de desaceleración precoz del flujo mitral (TD) para establecer el diagnóstico de insuficiencia cardiaca aguda (ICA) en pacientes que consultan en un servicio de urgencias hospitalario (SUH) por disnea. Métodos. Análisis prospectivo de una muestra de conveniencia de pacientes que consultan por disnea aguda en un SUH. El algoritmo ecográfico incluyó la ecografía pulmonar y cuatro parámetros ecocardiográficos, se midió MAPSE (desplazamiento sistólico del plano del anillo mitral), medidas doppler de flujo mitral, medidas doppler tisular en el anillo mitral lateral y TD. El diagnóstico final fue asignado por 2 médicos ciegos entre sí y a los hallazgos ecográficos. Resultados. Se incluyeron 166 pacientes adultos, la edad media fue de 76 años (DE 13) y 79 eran mujeres (48%). Hubo 62 pacientes (37%) con un diagnóstico final de ICA. La concordancia entre asignadores fue buena para el diagnóstico de ICA (κ = 0,71). El algoritmo clasificó a todos los pacientes, no hubo ningún diagnóstico indeterminado. El rendimiento diagnóstico del algoritmo mostró un área bajo la curva de 0,91 (IC 95%: 0,86-0,96), sensibilidad del 87% (IC 95%: 76%-94%), especificidad del 95% (IC 95%: 89%-98%), razón de verosimilitud positiva del 18,1 (IC 95%: 7,7-42,8), razón de verosimilitud negativa del 0,14 (IC 95%: 0,07-0,26). Conclusiones. Un algoritmo ecográfico que incluye el TD tiene un buen rendimiento para el diagnóstico de ICA en pacientes que acuden a SUH por disnea. Además, el uso de TD permite clasificar a todos los pacientes. (AU)
ABSTRACT
Objective. 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. Methods. 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. Results. 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). Conclusions. 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. (AU)
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Full text: 1 Collection: 06-national / ES Database: IBECS Main subject: Ultrasonography / Diagnosis / Dyspnea / Emergency Service, Hospital / Heart Failure / Lung Limits: Aged / Female / Humans / Male Language: Es Journal: Emergencias (Sant Vicenç dels Horts) Year: 2024 Document type: Article

Full text: 1 Collection: 06-national / ES Database: IBECS Main subject: Ultrasonography / Diagnosis / Dyspnea / Emergency Service, Hospital / Heart Failure / Lung Limits: Aged / Female / Humans / Male Language: Es Journal: Emergencias (Sant Vicenç dels Horts) Year: 2024 Document type: Article