Surgically implanted endovascular, microaxial left ventricular assist device: A single institution study.

Objective: The Impella 5.5 (Abiomed, Inc), a surgically implanted endovascular microaxial left ventricular assist device, is increasingly used worldwide and there have been more than 10,000 implants. The purpose of this study is to describe a large-volume, single-center experience with the use of the Impella 5.5. Methods: Data were obtained retrospectively from patients supported with the Impella 5.5 implanted at our institution from May 1, 2020, to December 31, 2022. Demographic, operative, and postoperative outcomes for each group are described. Results are reported in median (interquartile range) or n (%). The entire cohort was divided into 5 main groups based on the intention to treat at the time of the Impella 5.5 implantation: (1) patients who had a planned Impella 5.5 implanted at the time of high-risk cardiac surgery; (2) patients with cardiogenic shock; (3) patients bridged to a durable left ventricular assist device; (4) patients bridged to transplant; and (5) patients with postcardiotomy shock who received an unplanned Impella 5.5 implant. Results: A total of 126 patients were supported with the Impella 5.5. Overall survival to device explant was 76.2%, with 67.5% surviving to discharge. Midterm survival was assessed with a median follow-up time of 318 days and demonstrated an overall survival of 60.3% and a median of 650 days (549-752). Conclusions: Outcomes after using the Impella 5.5 are variable depending on the indication of use. Patient selection may be of utmost importance and requires further experience with this device to determine who will benefit from insertion.

Management of severe tricuspid valve regurgitation due to ruptured papillary muscle in a patient with mediastinitis early after heart transplant.

Objective: Even though severe tricuspid regurgitation is not uncommon after cardiac transplantation, primary severe tricuspid regurgitation is rare. We present such a case with additional complexities. Methods: The patient was 44-year-old man with a HeartWare durable left ventricular assist device (Heartware Inc) who received a temporary right ventricular assist device (RVAD) with a ProtekDuo cannula (LivaNova Inc USA) for refractory ventricular fibrillation and underwent a heart transplant as United Network for Organ Sharing Status 1, in the presence of partially compensated cardiogenic shock, renal failure. Given complex re-operative surgery in a volume-overloaded patient with unknown pulmonary vascular resistance, an RVAD cannula was preserved and re- inserted during cardiac transplant. Postoperatively he required hemodialysis, had severe primary tricuspid regurgitation discovered after RVAD removal and developed Enterobacter mediastinitis. He underwent complex tricuspid valve repair for flail tricuspid leaflet due to ruptured papillary muscle likely due to RVAD cannula injury, after multiple mediastinal washouts and was followed by delayed chest reconstruction. Results: The patient is doing well, 6 months after discharge to home, asymptomatic, without re-admissions, on renal recovery path, with no tricuspid regurgitation and good biventricular function. Conclusions: Replacing the tricuspid valve in presence of hemodialysis catheter, immunosuppression and mediastinitis could be high risk for endocarditis. Even though we have short-term follow-up, tricuspid valve repair can be an effective way of managing primary severe regurgitation especially when there is a desire or need to avoid valve replacement.

Electronic Health Record-Based Deep Learning Prediction of Death or Severe Decompensation in Heart Failure Patients.

BACKGROUND: Surgical mechanical ventricular assistance and cardiac replacement therapies, although life-saving in many heart failure (HF) patients, remain high-risk. Despite this, the difficulty in timely identification of medical therapy nonresponders and the dire consequences of nonresponse have fueled early, less selective surgical referral. Patients who would have ultimately responded to medical therapy are therefore subjected to the risk and life disruption of surgical therapy. OBJECTIVES: The purpose of this study was to develop deep learning models based upon commonly-available electronic health record (EHR) variables to assist clinicians in the timely and accurate identification of HF medical therapy nonresponders. METHODS: The study cohort consisted of all patients (age 18 to 90 years) admitted to a single tertiary care institution from January 2009 through December 2018, with International Classification of Disease HF diagnostic coding. Ensemble deep learning models employing time-series and densely-connected networks were developed from standard EHR data. The positive class included all observations resulting in severe progression (death from any cause or referral for HF surgical intervention) within 1 year. RESULTS: A total of 79,850 distinct admissions from 52,265 HF patients met observation criteria and contributed >350 million EHR datapoints for model training, validation, and testing. A total of 20% of model observations fit positive class criteria. The model C-statistic was 0.91. CONCLUSIONS: The demonstrated accuracy of EHR-based deep learning model prediction of 1-year all-cause death or referral for HF surgical therapy supports clinical relevance. EHR-based deep learning models have considerable potential to assist HF clinicians in improving the application of advanced HF surgical therapy in medical therapy nonresponders.