Effect of Barthel Index on the Risk of Thirty-Day Mortality in Patients With Acute Heart Failure Attending the Emergency Department: A Cohort Study of Nine Thousand Ninety-Eight Patients From the Epidemiology of Acute Heart Failure in Emergency Departments Registry

Rosselló, Xavier; Miró, Òscar; Llorens, Pere; Jacob, Javier; Herrero‐Puente, Pablo; Gil, Víctor; Espiga, Fernando Richard; Vidán, María Teresa; Bueno, Héctor; Pocock, Stuart J.; Martín‐Sánchez, Francisco Javier; Fuentes, Marta; Gil, Cristina; Alonso, Héctor; Garmila, Pablo; Adrada, Esther Rodríguez; García, Guillermo; Yañez-Palma, M.C.; López, Sergio Iglesias; Escoda, Rosa; Xipell, Carolina; Sánchez, Carolina; Gaytán, Josep María; Pérez‐Durá, María José; Salvo, Eva; Pavón, José; Noval, Antonio; Torres, José Manuel; López‐Grima, María Luisa; Valero, Amparo; Juan, Marian Ángeles; Aguirre, Alfons; Morales, Julián Errasti; Masó, Silvia Mínguez; Alonso, María Isabel; Ruiz, Francisco; Franco, José Miguel; Dı́az, Elena; Mecina, Ana Belén; Tost, Josep; Sánchez, Susana; Carbajosa, Virginia; Piñera, Pascual; Nicolás, José Andrés Sánchez; Garate, Raquel Torres; Alquézar, Aitor; Rizzi, Miguel Alberto; Herrera, Sergio; Roset, Álex; Cabello, Irene; Richard, Fernando; Pérez, José María Álvarez; Díez, María Pilar López; Álvarez, Joaquín Vázquez; Morilla, Ana Alonso; Irimia, Andrea; Javaloyes, Patricia; Marquina, Víctor; Jiménez, Inmaculada; Hernández, Néstor; Brouzet, Benjamín; Ramos, Sergio; López, Ana; Andueza, Juan Antonio; Sevillano, José Antonio; Romero, Rodolfo; Calvache, Roberto; Lorca, María Teresa; Calderón, Luis; Arriaga, Beatriz Amores; Sierra, Beatríz; Mojarro, Enrique Martín; Bécquer, Lisette Travería; Burillo, Guillermo; García, Lluís Llauger; LaSalle, Gerard Corominas; Urbano, Carmen Agüera; García, Ana; Padial, Soto Elisa Delgado; Ferrer, Ester Soy; Garrido, Manuel; Lucas, Francisco Javier; Gaya, Rut

doi:10.1016/j.annemergmed.2018.12.009

Cited by 29 publications

(12 citation statements)

References 25 publications

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“…Among the 761 screened citations, 28 studies published over the last 10 years 8,20,24,35–59 met the inclusion criteria after full-text review (Figure 1). These 28 studies included 19 different risk models that had been used in AHF patients in the ED setting to predict clinical outcomes (Table 1).…”

Section: Resultsmentioning

confidence: 99%

Risk stratification scores for patients with acute heart failure in the Emergency Department: A systematic review

Miró

Rosselló

Platz

et al. 2020

European Heart Journal. Acute Cardiovascular Care

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Aims This study aimed to systematically identify and summarise all risk scores evaluated in the emergency department setting to stratify acute heart failure patients. Methods and results A systematic review of PubMed and Web of Science was conducted including all multicentre studies reporting the use of risk predictive models in emergency department acute heart failure patients. Exclusion criteria were: (a) non-original articles; (b) prognostic models without predictive purposes; and (c) risk models without consecutive patient inclusion or exclusively tested in patients admitted to a hospital ward. We identified 28 studies reporting findings on 19 scores: 13 were originally derived in the emergency department (eight exclusively using acute heart failure patients), and six in emergency department and hospitalised patients. The outcome most frequently predicted was 30-day mortality. The performance of the scores tended to be higher for outcomes occurring closer to the index acute heart failure event. The eight scores developed using acute heart failure patients only in the emergency department contained between 4–13 predictors (age, oxygen saturation and creatinine/urea included in six scores). Five scores (Emergency Heart Failure Mortality Risk Grade, Emergency Heart Failure Mortality Risk Grade 30 Day mortality ST depression, Epidemiology of Acute Heart Failure in Emergency department 3 Day, Acute Heart Failure Risk Score, and Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure) have been externally validated in the same country, and two (Emergency Heart Failure Mortality Risk Grade and Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure) further internationally validated. The c-statistic for Emergency Heart Failure Mortality Risk Grade to predict seven-day mortality was between 0.74–0.81 and for Multiple Estimation of risk based on Emergency department Spanish Score In patients with Acute Heart Failure to predict 30-day mortality was 0.80–0.84. Conclusions There are several scales for risk stratification of emergency department acute heart failure patients. Two of them are accurate, have been adequately validated and may be useful in clinical decision-making in the emergency department i.e. about whether to admit or discharge.

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Section: Resultsmentioning

confidence: 99%

Risk stratification scores for patients with acute heart failure in the Emergency Department: A systematic review

Miró

Rosselló

Platz

et al. 2020

European Heart Journal. Acute Cardiovascular Care

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“…Details of the design and conduct of the EAHFE have previously been published elsewhere. 5,16 Briefly, patient inclusion is performed by the attending emergency physician using the Framingham clinical diagnostic criteria 17 and confirmed by the principal investigator of each centre to ensure that all patients fulfilled the clinical diagnostic criteria of AHF. The diagnosis was confirmed by natriuretic peptide determinations or echocardiography following the European Society of Cardiology (ESC) criteria 12 for approximately 92% of patients.…”

Section: Methodsmentioning

confidence: 99%

“…This model has been validated at a national 18 and international level 19 in separate cohorts. Risk factors included in these model are: Barthel index score at ED visit, 16 age, systolic blood pressure, New York Heart Association (NYHA) class IV, potassium level, NT-proBNP, troponin level, low output symptoms, respiratory rate, oxygen saturation, ACS, creatinine level and hypertrophy on ECG. Using these already known predictors, multivariate models assessing the association between precipitant factors and 30-day mortality were adjusted for 11 out of these 13 predictors, excluding systolic blood pressure and ACS given that they were inherently related to some precipitant factors.…”

Section: Methodsmentioning

confidence: 99%

Editor’s Choice– Impact of identifying precipitating factors on 30-day mortality in acute heart failure patients

Rosselló

Gil

Escoda

et al. 2019

European Heart Journal: Acute Cardiovascular Care

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Background: The aim of this study was to describe the prevalence and prognostic value of the most common triggering factors in acute heart failure. Methods: Patients with acute heart failure from 41 Spanish emergency departments were recruited consecutively in three time periods between 2011 and 2016. Precipitating factors were classified as: (a) unrecognized; (b) infection; (c) atrial fibrillation; (d) anaemia; (e) hypertension; (f) acute coronary syndrome; (g) non-adherence; and (h) two or more precipitant factors. Unadjusted and adjusted logistic regression models were used to assess the association between 30-day mortality and each precipitant factor. The risk of dying was further evaluated by week intervals over the 30-day follow-up to assess the period of higher vulnerability for each precipitant factor. Results: Approximately 69% of our 9999 patients presented with a triggering factor and 1002 died within the first 30 days (10.0%). The most prevalent factors were infection and atrial fibrillation. After adjusting for 11 known predictors, acute coronary syndrome was associated with higher 30-day mortality (odds ratio (OR) 1.87; 95% confidence interval (CI) 1.02–3.42), whereas atrial fibrillation (OR 0.75; 95% CI 0.56–0.94) and hypertension (OR 0.34; 95% CI 0.21–0.55) were significantly associated with better outcomes when compared to patients without precipitant. Patients with infection, anaemia and non-compliance were not at higher risk of dying within 30 days. These findings were consistent across gender and age groups. The 30-day mortality time pattern varied between and within precipitant factors. Conclusions: Precipitant factors in acute heart failure patients are prevalent and have a prognostic value regardless of the patient’s gender and age. They can be managed with specific treatments and can sometimes be prevented.

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“…Exacerbación de síntomas de Insuficiencia cardiaca: Aumento transitorio de gravedad de síntomas o aparición de nuevos, posteriores al evento de insuficiencia cardíaca aguda en un paciente con antecedente de insuficiencia cardiaca crónica 11 .…”

Section: Variable De Resultadounclassified

“…En otro artículo realizado en el interior del país, han probado utilizar la puntuación de CHADS2, utilizada en fibrilación auricular, para evaluar su desempeño al aplicarla en pacientes con ICA cuyo desenlace sea la muerte; sin embargo, se encontró que este no predecía adecuadamente la mortalidad. 9 En la actualidad, existen distintos modelos predictivos de ICA, los cuales utilizan diversas variables para estimar el riesgo de muerte en pacientes con esta patología 10,11 . Los modelos predictivos de ICA muestran variables como el historial médico (ej.…”

Section: Capítulo I: Introducciónunclassified

Modelos predictivos de muerte o exacerbación en Insuficiencia Cardiaca Aguda: Una revisión sistemática

Ortega¹,

Reyes²

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1. Introducción y Objetivos: Existe un gran número de modelos predictivos de desenlaces en Insuficiencia Cardíaca Aguda; sin embargo, no se conoce la utilidad clínica. Se evaluará el desempeño de los modelos incluidos en el artículo. 2. Metodología: Se realizó una revisión sistemática de los modelos predictivos de desenlaces adversos. Por lo que se realizó una búsqueda en 6 bases bibliográficas, incluyéndose todo artículo original que reporte modelos de predicción. Se utilizó la herramienta PROBAST para valorar el riesgo de sesgo en los artículos. 3. Resultados: De 2498 artículos seleccionados, 39 fueron incluidos. La mayoría provienen de Europa (46.1%), 20 de ellos evalúan mortalidad, mientras que 21 demostraron bajo riesgo de sesgo y buena aplicabilidad utilizando la herramienta de evaluación PROBAST. El sexo masculino fue el mayoritario en el 69% de artículos. La morbilidad más común es hipertensión arterial. Todos los modelos fueron validados, y más del 50% cuentan con validación externa. Borovac JA et al. presenta el AUC más alto, con 0.907. Catorce modelos utilizaron el modelo de calibración de Hosmer-Lemeshow. Ningún artículo contó con beneficio neto. 4. Conclusión: : Los estudios no muestran una adecuada evaluación de desempeño, al no presentar todas las estadísticas de medición que existen; es necesario el desarrollo de nuevos modelos con la descripción completa de estadísticas de desempeño, para llevar a cabo una adecuada comparación.

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Effect of Barthel Index on the Risk of Thirty-Day Mortality in Patients With Acute Heart Failure Attending the Emergency Department: A Cohort Study of Nine Thousand Ninety-Eight Patients From the Epidemiology of Acute Heart Failure in Emergency Departments Registry

Cited by 29 publications

References 25 publications

Risk stratification scores for patients with acute heart failure in the Emergency Department: A systematic review

Risk stratification scores for patients with acute heart failure in the Emergency Department: A systematic review

Editor’s Choice– Impact of identifying precipitating factors on 30-day mortality in acute heart failure patients

Modelos predictivos de muerte o exacerbación en Insuficiencia Cardiaca Aguda: Una revisión sistemática

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