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Impact of active intervention in high-risk heart failure patients under a team-based remote monitoring unit
Session:
Sessão de Posters 40 - Insuficiência cardíaca - da Preservada ao Transplante
Speaker:
Sofia Jacinto
Congress:
CPC 2024
Topic:
D. Heart Failure
Theme:
10. Chronic Heart Failure
Subtheme:
10.6 Chronic Heart Failure - Clinical
Session Type:
Cartazes
FP Number:
---
Authors:
Sofia Jacinto; Bárbara Lacerda Teixeira; Madalena Coutinho Cruz; Guilherme Portugal; Bruno Valente; Ana Lousinha; Pedro Silva Cunha; Cátia Guerra; Sofia Barquinha; Ana Teresa Timóteo; Rui Cruz Ferreira; Mário Martins Oliveira
Abstract
<p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-family:Calibri,sans-serif"><span style="color:black">Background</span></span></strong><span style="font-family:Calibri,sans-serif"><span style="color:black">: Heart failure (HF) risk algorithms included in cardiac electronic implantable devices (CEID) can identify HF patients (P) at higher risk of 30-day hospitalization following a data transmission. These predictive models include physiological parameters, such as thoracic impedance, arrhythmia burden, percentage of pacing, night heart rate, heart rate variability or P activity levels. Multidisciplinary team-based care in remote monitoring (RM) programs may be a way to further positively impact outcomes in this population.</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-family:Calibri,sans-serif"><span style="color:black">Aim:</span></span></strong> <span style="font-family:Calibri,sans-serif"><span style="color:#242424">We aim to assess the predictive value of machine learning HF algorithms in P classified as “high-risk”, and the impact of an active intervention flow-chart by a team-based in a RM unit in order to reduce HF hospitalizations.</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-family:Calibri,sans-serif"><span style="color:#242424">Methods:</span></span></strong> <span style="font-family:Calibri,sans-serif"><span style="color:black">A single-centre prospective analysis of P with “high-risk” HF alerts generated by CEID with two different HF algorithms from two different brands. Exclusion criteria included P under 18 years old and P without HF. We compared outcomes in two different groups: P in which an action was taken (INTERV; lifestyle changes, diuretics optimization and/or call for observation in the HF clinic/Day Hospital), and P in which, after a standard questionnaire by phone, no changes were prompted (NO INTERV). HF hospitalization at 30 days was compared between the two groups.</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-family:Calibri,sans-serif"><span style="color:#242424">Results</span></span></strong><span style="font-family:Calibri,sans-serif"><span style="color:black">: Out of 46 HF P under RM, there were 40 “high-risk” HF alerts (mean of 1.7 alerts per P) in 23P (71±10 years, 83% males) from June to November 2023. Underlying diseases were ischemic cardiomyopathy (n=13; 57%), non-ischemic cardiomyopathy (n=6; 26%) or valvular heart disease (n=4; 17%). Mean left ventricular (LV) ejection fraction at baseline was 27±8% and New York Heart Association (NYHA) classification was II (71%), III (14%) and IV (14%). P had a CRT-D in 18 cases (78%) and an ICD in 5 (22%). Most of the alerts were due to a decreased thoracic impedance, higher burden of atrial arrhythmias and low P activity. An immediate intervention was prompted in 16 cases (40%). In 24P (60%), daily monitoring was maintained and no changes were made. HF hospitalization at 30 days occurred in 19% of the intervention group and in 8% of the non-intervention group (p=0.373).</span></span></span></span></span></p> <p style="text-align:justify"><span style="font-size:medium"><span style="font-family:"Times New Roman",serif"><span style="color:#000000"><strong><span style="font-family:Calibri,sans-serif"><span style="color:#242424">Conclusion</span></span></strong><span style="font-family:Calibri,sans-serif"><span style="color:#242424">: In a RM-based follow-up program of P with severe LV dysfunction, “high-risk” alerts for HF decompensation are a common finding. In this preliminary study, we found no significant differences between INTERV and NO INTERV groups regarding hospitalization. More data are need to evaluate the role of a prompt intervention after a “high-risk” score transmission.</span></span></span></span></span></p>
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