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Feasibility of Virtual Optimization of Guideline Directed Medical Therapy in Hospitalized Patients with HFrEF During the Covid-19 Pandemic: The IMPLEMENT-HF Pilot Study

INTRODUCTION: Implementation of GDMT for HFrEF remains low. We assessed the feasibility of a virtual GDMT Team for optimization of GDMT during hospitalization for non-CV conditions. HYPOTHESIS: A GDMT Team will improve GDMT optimization compared with usual care. METHODS: Consecutive hospitalized pat...

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Detalles Bibliográficos
Autores principales: Bhatt, Ankeet S., Varshney, Anubodh, Moscone, Alea, Cunningham, Jonathan, Jering, Karola, Sinnenberg, Lauren, Nekoui, Mahan, Buckley, Leo, Cook, Brian, Dempsey, Jillian, Kelly, Julie, Knowles, Danielle, Lupi, Kenneth, Malloy, Rhynn, Matta, Lina, Rhoten, Megan, Hinchey, Emily, McElrath, Erin, Alobaidly, Maryam, Amato, Mary, Ulbricht, Catherine, Ting, Clara, Bernier, Thomas, Choudhry, Niteesh, Adler, Dale S., Vaduganathan, Muthiah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527179/
http://dx.doi.org/10.1016/j.cardfail.2020.09.467
Descripción
Sumario:INTRODUCTION: Implementation of GDMT for HFrEF remains low. We assessed the feasibility of a virtual GDMT Team for optimization of GDMT during hospitalization for non-CV conditions. HYPOTHESIS: A GDMT Team will improve GDMT optimization compared with usual care. METHODS: Consecutive hospitalized patients with HFrEF≤40% were prospectively identified. Patients with critical illness, cardiology consult, de-novo HF, COVID-19 & SBP ≤90mmHg were excluded. February 3 to March 1, 2020 served as a pre-intervention period during which patients were screened, but did not receive GDMT Team interventions. From March 2 to June 21, 2020, a pharmacist-physician team provided up to 1 suggestion daily for GDMT optimization (evidence-based ß-blockers, ACEi/ARB/ARNI, & MRA) to treating teams based on an evidence-based algorithm. The primary outcome of a composite GDMT optimization score, the net of positive therapeutic changes (+1 for new initiations/uptitrations) & negative therapeutic changes (-1 for discontinuations/downtitrations) during hospitalization, was compared between the pre- vs. post-intervention periods. Multivariable linear regression models were built adjusting associations for clinical factors. Safety outcomes requiring intervention or GDMT downtitration were identified. RESULTS: Of 187 encounters, 84 (45%) met eligibility criteria: 28 pre-intervention, 56 post-intervention. Mean age was 68±11 yrs, 70% men, and 61% White. Of 88 GDMT Team suggestions, 49 (56%) were followed by discharge. During the intervention, cumulative COVID-19 hospitalizations rose from 0 to 11085 in MA. Mean GDMT optimization score was -0.14 (95% CI: -0.58 to +0.30) pre-intervention & +0.64 (95% CI: +0.35 to +0.93) post-intervention (P=0.004). In a model inclusive of demographics, comorbidities, vital signs, potassium levels, eGFR, & LVEF, the intervention was the only factor associated with higher GDMT optimization score (β coeff 0.89; P=0.008). Safety events included 1 instance each of AKI, hyperkalemia, bradycardia, & hypotension. CONCLUSION: Admission for non-CV conditions is a feasible setting for GDMT optimization. A virtual GDMT Team was associated with improved GDMT; this implementation strategy warrants testing in a prospective RCT.