Lieke Numan

This study aims to associate the incidence of postoperative vasoplegia and short-term survival to the implantation of various left ventricular assist devices differing in hemocompatibility and flow profiles. The overall incidence of vasoplegia was 25.3% (73/289 patients) and 30.3% (37/122), 25.0% (18/72), and 18.9% (18/95) in the axial flow (AXF), centrifugal flow (CF), and centrifugal flow with artificial pulse (CFAP) group, respectively. Vasoplegia was associated with longer intensive care (ICU) and hospital length of stay (LOS) and mortality. ICU and in-hospital LOS and 1-year mortality were the lowest in the CFAP group. Post hoc analysis resulted in a p-value of 0.43 between AXF and CF; 0.35 between CF and CFAP; and 0.06 between AXF and CFAP. Although there is a trend in diminished incidence of vasoplegia, pooled logistic regression using flow profile and variables that remained after feature selection showed that flow profile was not an independent predictor for postoperative vasoplegia. Graphical

Background: Soluble suppression of tumorigenicity‐2 (sST2) predicts mortality in patients with heart failure. The predictive value of sST2 in patients with a left ventricular assist device remains unknown. Therefore, we studied the relationship between sST2 and outcome after left ventricular assist device implantation. Methods and Results: sST2 levels of patients with a left ventricular assist device implanted between January 2015 and December 2022 were included in this observational study. The median follow‐up was 25 months, during which 1573 postoperative sST2 levels were measured in 199 patients, with a median of 29 ng/mL. Survival of patients with normal and elevated preoperative levels was compared using Kaplan‐Meier analysis, which did not differ significantly ( P =0.22) between both groups. The relationship between postoperative sST2, survival, and right heart failure was evaluated using a joint model, which showed a significant relationship between the absolute sST2 level and mortality, with a hazard ratio (HR) of 1.20 (95% CI, 1.10–1.130; P P =0.01) for right heart failure, both per 10‐unit sST2 increase. The sST2 instantaneous change was not predictive for survival or right heart failure ( P =0.99 and P =0.94, respectively). Multivariate joint model analysis showed a significant relationship between sST2 with mortality adjusted for NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide), with an HR of 1.19 (95% CI, 1.00–1.42; P =0.05), whereas the HR of right heart failure was not significant (1.22 [95% CI, 0.94–1.59]; P =0.14), both per 10‐unit sST2 increase. Conclusions: Time‐dependent postoperative sST2 predicts all‐cause mortality after left ventricular assist device implantation after adjustment for NT‐proBNP. Future research is warranted into possible target interventions and the optimal monitoring frequency.

Aims: The number of patients on left ventricular assist device (LVAD) support increases due to the growing number of patients with end-stage heart failure and the limited number of donor hearts. Despite improving survival rates, patients frequently suffer from adverse events such as cardiac arrhythmia and major bleeding. Telemonitoring is a potentially powerful tool to early detect deteriorations and may further improve outcome after LVAD implantation. Hence, we developed a personalized algorithm to remotely monitor HeartMate3 (HM3) pump parameters aiming to early detect unscheduled admissions due to cardiac arrhythmia or major bleeding. Methods and results: The source code of the algorithm is published in an open repository. The algorithm was optimized and tested retrospectively using HeartMate 3 (HM3) power and flow data of 120 patients, including 29 admissions due to cardiac arrhythmia and 14 admissions due to major bleeding. Using a true alarm window of 14 days prior to the admission date, the algorithm detected 59 and 79% of unscheduled admissions due to cardiac arrhythmia and major bleeding, respectively, with a false alarm rate of 2%. Conclusion: The proposed algorithm showed that the personalized algorithm is a viable approach to early identify cardiac arrhythmia and major bleeding by monitoring HM3 pump parameters. External validation is needed and integration with other clinical parameters could potentially improve the predictive value. In addition, the algorithm can be further enhanced using continuous data.

Background: Algorithms to monitor pump parameters are needed to further improve outcomes after left ventricular assist device (LVAD) implantation. Previous research showed a restored circadian rhythm in pump parameters in patients on HeartWare (HVAD) support. Circadian patterns in HeartMate3 (HM3) were not studied before, but this is important for the development of LVAD monitoring algorithms. Hence, we aimed to describe circadian patterns in HM3 parameters and their relation to patterns in heart rate (HR).Methods: 18 HM3 patients were included in this study. HM3 data were retrieved at a high frequency (one sample per 1 or 2 h) for 1–2 weeks. HR was measured using a wearable biosensor. To study overall patterns in HM3 parameters and HR, a heatmap was created. A 24‐h cosine was fitted on power and HR separately. The relationship between the amplitude of the fitted cosines of power and HR was calculated using Spearman correlation.Results: A lower between patient variability was found in power compared with flow and PI. 83% of the patients showed a significant circadian rhythmicity in power (p < 0.001–0.04), with a clear morning increase. All patients showed significant circadian rhythmicity in HR (p < 0.001–0.02). The amplitudes of the circadian rhythm in power and HR were not correlated (Spearman correlation of 0.32, p = 0.19).Conclusions: A circadian rhythm of pump parameters is present in the majority of HM3 patients. Higher frequency pump parameter data should be collected, to enable early detection of complications in the future development of predictive algorithms.

Aims: Non-invasive remote patient monitoring is an increasingly popular technique to aid clinicians in the early detection of worsening heart failure (HF) alongside regular follow-ups. However, previous studies have shown mixed results in the performance of such systems. Therefore, we developed and evaluated a personalized monitoring algorithm aimed at increasing positive-predictive-value (PPV) (i.e. alarm quality) and compared performance with simple rule-of-thumb and moving average convergence-divergence algorithms (MACD). Methods and results: In this proof-of-concept study, the developed algorithm was applied to retrospective data of daily bodyweight, heart rate, and systolic blood pressure of 74 HF-patients with a median observation period of 327 days (IQR: 183 days), during which 31 patients experienced 64 clinical worsening HF episodes. The algorithm combined information on both the monitored patients and a group of stable HF patients, and is increasingly personalized over time, using linear mixed-effect modelling and statistical process control charts. Optimized on alarm quality, heart rate showed the highest PPV (Personalized: 92%, MACD: 2%, Rule-of-thumb: 7%) with an F1 score of (Personalized: 28%, MACD: 6%, Rule-of-thumb: 8%). Bodyweight demonstrated the lowest PPV (Personalized: 16%, MACD: 0%, Rule-of-thumb: 6%) and F1 score (Personalized: 10%, MACD: 3%, Rule-of-thumb: 7%) overall compared methods. Conclusion: The personalized algorithm with flexible patient-tailored thresholds led to higher PPV, and performance was more sensitive compared to common simple monitoring methods (rule-of-thumb and MACD). However, many episodes of worsening HF remained undetected. Heart rate and systolic blood pressure monitoring outperformed bodyweight in predicting worsening HF. The algorithm source code is publicly available for future validation and improvement.

Background: Late right heart failure (LRHF) is a common complication during long‐term left ventricular assist device (LVAD) support. We aimed to identify risk factors for LRHF after LVAD implantation.Methods: Patients undergoing primary LVAD implantation between 2006 and 2019 and surviving the perioperative period were included for this study (n = 261). Univariate Cox proportional hazards analysis was used to assess the association of clinical covariates and LRHF, stratified for device type. Variables with p < 0.10 entered the multivariable model. In a subset of patients with complete echocardiography or right catheterization data, this multivariable model was extended. Postoperative cardiopulmonary exercise test data were compared in patients with and without LRHF.Results: Nineteen percentage of patients suffered from LRHF after a median of 12 months, of which 67% required hospitalization. A history of atrial fibrillation (AF) (HR: 2.06 [1.08–3.93], p = 0.029), a higher preoperative body mass index (BMI) (HR: 1.07 [1.01–1.13], p = 0.023), and intensive care unit (ICU) duration (HR: 1.03 [1.00–1.06], p = 0.025) were independent predictors of LHRF in the multivariable model. A significant relation between the severity of tricuspid regurgitation (TR) and LRHF (HR: 1.91 [1.13–3.21], p = 0.016) was found in patients with echocardiographic data. Patients with LRHF demonstrated a lower maximal workload and peak VO2 at 6 months postoperatively.Conclusion: A history of AF, BMI, and longer ICU stay may help identify patients at high risk for LRHF. Severity of TR was significantly related to LRHF in a subset of patients

Aims: Since the withdrawal of HeartWare (HVAD) from the global market, there is an ongoing discussion if and which patients require prophylactically exchange for a HeartMate 3 (HM3). Therefore, it is important to study outcome differences between HVAD and HM3 patients. Because centres differ in patient selection and standard of care, we performed a propensity score (PS)-based study including centres that implanted both devices and aimed to identify which HVAD patients are at highest risk. Methods and results: We performed an international multi-centre study (n = 1021) including centres that implanted HVAD and HM3. PS-matching was performed using clinical variables and the implanting centre. Survival and complications were compared. As a sensitivity analysis, PS-adjusted Cox regression was performed. Landmark analysis with conditional survival >2 years was conducted to evaluate long-term survival differences. To identify which HVAD patients may benefit from a HM3 upgrade, Cox regression using pre-operative variables and their interaction with device type was performed. Survival was significantly better for HM3 patients (P < 0.01) in 458 matched patients, with a median follow-up of 23 months. Within the matched cohort, HM3 patients had a median age of 58 years, and 83% were male, 80% of the HVAD patients were male, with a median age of 59 years. PS-adjusted Cox regression confirmed a significantly better survival for HM3 patients when compared with HVAD, with a HR of 1.46 (95% confidence interval 1.14–1.85, P < 0.01). Pump thrombosis (P < 0.01) and ischaemic stroke (P < 0.01) occurred less in HM3 patients. No difference was found for haemorrhagic stroke, right heart failure, driveline infection, and major bleeding. Landmark-analysis confirmed a significant difference in conditional survival >2 years after implantation (P = 0.03). None of the pre-operative variable interactions in the Cox regression were significant. Conclusions: HM3 patients have a significantly better survival and a lower incidence of ischaemic strokes and pump thrombosis than HVAD patients. This survival difference persisted after 2 years of implantation. Additional research using post-operative variables is warranted to identify which HVAD patients need an upgrade to HM3 or expedited transplantation.

Background Soluble suppression of tumorigenicity-2 (sST2) predicts mortality in heart failure patients. The predictive value of sST2 in left ventricular assist device (LVAD) patients remains unknown. Therefore, we studied the relationship between sST2 and outcome after LVAD implantation. Methods Patients implanted between January 2015 and December 2022 were included. Survival of patients with normal and elevated pre-operative sST2 levels was compared using Kaplan-Meier analysis. The relationship between post-operative sST2, survival and right heart failure (RHF) was evaluated using a Joint Model (JM). Multivariate JM analysis adjusted for serially measured NT-proBNP was performed. Results The median follow-up was 25 months, during which 1573 post-operative sST2 levels were measured in 199 patients, with a median of 29 ng/ml. Survival in patients with normal or elevated pre-operative sST2 levels (n=86) did not differ significantly (p=0.22). Time-dependent post-operative sST2 levels were significantly associated with mortality, with a hazard ratio (HR) of 1.20 (95% CI: 1.10-1.30, pConclusion Time-dependent post-operative sST2 predicts all-cause mortality after LVAD implantation independently of NT-proBNP. Future research is warranted into possible target interventions and the optimal monitoring frequency.