Tratamiento a distancia de la insuficiencia cardiaca mediante el algoritmo HeartLogic. Registro RE-HEART / Remote heart failure management using the HeartLogic algorithm. RE-HEART registry

Introducción y objetivos HeartLogic es un algoritmo multiparamétrico incorporado a desfibriladores automáticos implantables (DAI). La alerta asociada predice descompensaciones de insuficiencia cardiaca (IC). Nuestro objetivo es analizar la asociación entre alertas y eventos clínicos bajo un protocolo de seguimiento común en un registro multicéntrico. Métodos Se evaluaron la fase 1 (investigadores ciegos al estado de la alerta) y las fases 2 y 3 (tras la activación de HeartLogic, según práctica local y un protocolo común respectivamente). Resultados Se incluyó a 288 pacientes en 15 centros. En fase 1, tras una media de observación de 10 meses, hubo 73 alertas (0,72 alertas/paciente-año), con 8 hospitalizaciones y 2 visitas a urgencias por IC (0,10 eventos/año-paciente). No hubo hospitalizaciones fuera del periodo de alerta. Las fases activas tuvieron una media de seguimiento de 16 (IC95%, 15-22) meses, con 277 alertas (0,89 alertas/año-paciente); 33 se asociaron con hospitalizaciones o muerte por IC, 46 con descompensaciones menores y 78 con otros eventos. La tasa de alertas inexplicables fue 0,39/año-paciente. Fuera del estado de alerta solo hubo una hospitalización y una descompensación menor. La mayoría de las alertas (el 82% en fase 2 y el 81% en fase 3; p=0,861) se gestionaron a distancia. La mediana de NT-proBNP fue superior en estado de alerta que fuera de él (7.378 frente a 1.210 pg/ml; p <0,001). Conclusiones El índice HeartLogic se asoció con descompensaciones de IC y otros eventos relevantes, con baja tasa de alertas inexplicables. Un protocolo estandarizado permitió detectar y actuar a distancia con seguridad sobre las alertas (AU)

Introduction and objectives HeartLogic is a multiparametric algorithm incorporated into implantable cardioverter-defibrillators (ICD). The associated alerts predict impending heart failure (HF) decompensations. Our objective was to analyze the association between alerts and clinical events and to describe the implementation of a protocol for remote management in a multicenter registry. Methods We evaluated study phase 1 (the investigators were blinded to the alert state) and phases 2 and 3 (after HeartLogic activation, managed as per local practice and with a standardized protocol, respectively). Results We included 288 patients from 15 centers. In phase 1, the median observation period was 10 months and there were 73 alerts (0.72 alerts/patient-y), with 8 hospitalizations and 2 emergency room admissions for HF (0.10 events/patient-y). There were no HF hospitalizations outside the alert period. In the active phases, the median follow-up was 16 (95%CI, 15-22) months and there were 277 alerts (0.89 alerts/patient-y); 33 were associated with HF hospitalizations or HF death (n=6), 46 with minor decompensations, and 78 with other events. The unexplained alert rate was 0.39 alerts/patient-y. Outside the alert state, there was only 1 HF hospitalization and 1 minor HF decompensation. Most alerts (82% in phase 2 and 81% in phase 3; P=.861) were remotely managed. The median NT-proBNP value was higher within than outside the alert state (7378 vs 1210 pg/mL; P <.001). Conclusions The HeartLogic index was frequently associated with HF-related events and other clinically relevant situations, with a low rate of unexplained events. A standardized protocol allowed alerts to be safely and remotely detected and appropriate action to be taken on them (AU)

Role of sCD40L in the prediction of super response to cardiac resynchronization therapy / Rol de sCD40L en la predicción de súper respuesta a la terapia de resincronización cardiaca

Background: The aim of this paper is to analyze the roleof the biomarkers Interleukin 6, Tumoral Necrosis Factor α,sCD40L, high sensitive Troponin T, high sensitive C-ReactiveProtein and Galectin-3 in predicting super response (SR) toCardiac Resynchronization Therapy (CRT), as they have notbeen studied in this field before. Methods: Clinical, electrocardiographic and echocardiographic data was obtained preimplant and after one year.SR was defined as reduction in LVESV ≥ 30% at one yearfollow-up. Blood samples were extracted preimplant. Multivariate logistic regression and ROC curves were performed. Results: 50 patients were included, 23 (46%) were SR. Characteristics related to SR were: female (35 vs. 11%, p = 0.04),suffering from less ischemic cardiomyopathy (13 vs. 63%,p < 0.0001) and lateral (0 vs. 18%, p = 0.03), inferior (4 vs.33%, p = 0.01) and posterior infarction (0 vs. 22%, p = 0.01);absence of mitral regurgitation (47% vs. 22%, p = 0.04), wider QRS width (157.7 ± 22.9 vs. 140.8 ± 19.2ms, p = 0.01), higher concentrations of sCD40L (6.9 ± 5.1 vs. 4.4 ± 3.3 ng/mL,p = 0.02), and left ventricular lead more frequent in lateralmedial position (69 vs. 26%, p = 0.002). QRS width, lateralmedial position of the lead and absence of mitral regurgitation were independent predictors of SR. sCD40L showeda moderate direct correlation with SR (r = 0.39, p = 0.02) andwith the reduction of LVESV (r = 0.44, p = 0.02). Conclusion: sCD40L correlates significantly with SR to CRT.QRS width, absence of mitral regurgitation and lateral medial position of the lead are independent predictors of SRin this cohort.(AU)

Fundamento: Analizar los biomarcadores Interleuquina 6,factor de necrosis tumoral α, sCD40L, troponina T hipersensible, proteína Creactiva hipersensible y galectina-3 en lapredicción de súper-respuesta (SR) a la terapia de resincronización cardiaca (TRC), ya que no han sido valorados conanterioridad. Material y métodos: Se recopilaron datos clínicos, electrocardiográficos y ecocardiográficos preimplante y al año.Se definió SR como disminución del VTSVI ≥ 30% al añode seguimiento. Las muestras sanguíneas fueron extraídaspreimplante. Se realizó regresión logística multivariante ycurvas ROC. Resultados: Se incluyeron 50 pacientes, 23 (46%) fueronSR.Las características relacionadas con la SR fueron: ser mujer (35 vs. 11%, p = 0,04), sufrir menos cardiopatía isquémica(13 vs. 63%, p < 0,0001) e infarto lateral (0 vs. 18%, p = 0,03),inferior (4 vs. 33%, p = 0,01) y posterior (0 vs. 22%, p = 0,01); ausencia de insuficiencia mitral (47% vs. 22%, p = 0,04), mayor anchura del QRS (157,7 ± 22,9 vs. 140,8 ± 19,2 ms, p = 0,01), mayorconcentración de sCD40L (6,9 ± 5,1 vs. 4,4 ± 3,3 ng/mL, p = 0,02),y electrodo ventricular izquierdo más frecuentemente en posición lateral media (69 vs. 26%, p = 0,002). El QRS, la posiciónlateral media del electrodo y la ausencia de insuficiencia mitral fueron predictores independientes de SR. sCD40L mostróuna correlación moderada directa con SR (r = 0,39, p = 0,02) ycon la disminución del VTSVI (r = 0,44, p = 0,02). Conclusiones: sCD40L se correlaciona significativamentecon SR a la TRC. El QRS, la ausencia de insuficiencia mitraly la posición lateral media del electrodo son predictores independientes de SR en esta cohorte.(AU)

Role of sCD40L in the prediction of super-response to cardiac resynchronization therapy.

BACKGROUND: The aim of this paper is to analyze the role of the biomarkers Interleukin 6, Tumoral Necrosis Factor a, sCD40L, high sensitive Troponin T, high sensitive C-Reactive Protein and Galectin-3 in predicting super response (SR) to Cardiac Resynchronization Therapy (CRT), as they have not been studied in this field before. METHODS: Clinical, electrocardiographic and echocardiographic data was obtained preimplant and after one year. SR was defined as reduction in LVESV = 30% at one year follow-up. Blood samples were extracted preimplant. Multivariate logistic regression and ROC curves were performed. RESULTS: 50 patients were included, 23 (46%) were SR. Characteristics related to SR were: female (35 vs. 11%, p?=?0.04), suffering from less ischemic cardiomyopathy (13 vs. 63%, p?