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2. Soluble Suppression of Tumorigenicity-2 Predicts Mortality and Right Heart Failure in Patients With a Left Ventricular Assist Device

Author

Cardiologie, Onderzoek Precision medicine, CTC, Circulatory Health, Team Medisch, MCS-team, CDL Cluster 24/7 centraal laboratorium, Other research (not in main researchprogram), Regenerative Medicine and Stem Cells, Numan, Lieke, Aarts, Emmeke, Ramjankhan, Faiz, Oerlemans, Marish I.F., van der Meer, Manon G., de Jonge, Nicolaas, Oppelaar, Anne Marie, Kemperman, Hans, Asselbergs, Folkert W., Van Laake, Linda W., Cardiologie, Onderzoek Precision medicine, CTC, Circulatory Health, Team Medisch, MCS-team, CDL Cluster 24/7 centraal laboratorium, Other research (not in main researchprogram), Regenerative Medicine and Stem Cells, Numan, Lieke, Aarts, Emmeke, Ramjankhan, Faiz, Oerlemans, Marish I.F., van der Meer, Manon G., de Jonge, Nicolaas, Oppelaar, Anne Marie, Kemperman, Hans, Asselbergs, Folkert W., and Van Laake, Linda W.

Published
2024

3. FLAVOUR Study: FLow profiles And postoperative VasOplegia after continUous-flow left ventriculaR assist device implantation

Author

AIOS Anesthesiologie, Cardiologie, Onderzoek Precision medicine, CTC, Circulatory Health, Team Medisch, Regenerative Medicine and Stem Cells, Medische Staf Spoedeisende Hulp, Kersten, Bas J., Numan, Lieke, van der Schoot, Marnix M., de Jong, Michel, Ramjankhan, Faiz, Aarts, Emmeke, Oerlemans, Marish I.F.J., van Laake, Linda W., de Waal, Eric E.C., AIOS Anesthesiologie, Cardiologie, Onderzoek Precision medicine, CTC, Circulatory Health, Team Medisch, Regenerative Medicine and Stem Cells, Medische Staf Spoedeisende Hulp, Kersten, Bas J., Numan, Lieke, van der Schoot, Marnix M., de Jong, Michel, Ramjankhan, Faiz, Aarts, Emmeke, Oerlemans, Marish I.F.J., van Laake, Linda W., and de Waal, Eric E.C.

Published
2024

4. Soluble Suppression of Tumorigenicity‐2 Predicts Mortality and Right Heart Failure in Patients With a Left Ventricular Assist Device

Author

Numan, Lieke, primary, Aarts, Emmeke, additional, Ramjankhan, Faiz, additional, Oerlemans, Marish I. F., additional, van der Meer, Manon G., additional, de Jonge, Nicolaas, additional, Oppelaar, Anne‐Marie, additional, Kemperman, Hans, additional, Asselbergs, Folkert W., additional, and Van Laake, Linda W., additional

Published
2024
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7. Survival after HeartMate 3 left ventricular assist device implantation: real‐world data from Europe

Author

Numan, Lieke, primary, Schramm, Rene, additional, Oerlemans, Marish I.F.J., additional, van der Kaaij, Niels P., additional, Aarts, Emmeke, additional, Ramjankhan, Faiz Z., additional, Oppelaar, Anne‐Marie, additional, Morshuis, Michiel, additional, Guenther, Sabina P.W., additional, Zimpfer, Daniel, additional, Riebandt, Julia, additional, Wiedemann, Dominik, additional, Asselbergs, Folkert W., additional, and Van Laake, Linda W., additional

Published
2023
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9. Monitoring left ventricular assist device parameters to detect flow- and power-impacting complications: a proof of concept

Author

Moazeni, Mehran, Numan, Lieke, Szymanski, M., Van Der Kaaij, Niels P, Asselbergs, Folkert W, van Laake, Linda W, Aarts, Emmeke, Moazeni, Mehran, Numan, Lieke, Szymanski, M., Van Der Kaaij, Niels P, Asselbergs, Folkert W, van Laake, Linda W, and Aarts, Emmeke

Abstract

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.

Published
2023

10. Survival after HeartMate 3 left ventricular assist device implantation: real-world data from Europe

Author

Numan, Lieke, Schramm, Rene, Oerlemans, Marish I F J, van der Kaaij, Niels P, Aarts, Emmeke, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Morshuis, Michiel, Guenther, Sabina P W, Zimpfer, Daniel, Riebandt, Julia, Wiedemann, Dominik, Asselbergs, Folkert W, Van Laake, Linda W, Numan, Lieke, Schramm, Rene, Oerlemans, Marish I F J, van der Kaaij, Niels P, Aarts, Emmeke, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Morshuis, Michiel, Guenther, Sabina P W, Zimpfer, Daniel, Riebandt, Julia, Wiedemann, Dominik, Asselbergs, Folkert W, and Van Laake, Linda W

Published
2023

11. Incidence and risk factors of late right heart failure in chronic mechanical circulatory support

Author

Felix, Susanne E A, Numan, Lieke, Oerlemans, Marish I F, Aarts, E, Ramjankhan, Faiz Z, Gianoli, Monica, Asselbergs, Folkert W, De Jonge, Nicolaas, Van Laake, Linda W, Felix, Susanne E A, Numan, Lieke, Oerlemans, Marish I F, Aarts, E, Ramjankhan, Faiz Z, Gianoli, Monica, Asselbergs, Folkert W, De Jonge, Nicolaas, and Van Laake, Linda W

Abstract

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.

Published
2023

12. Developing a personalized remote patient monitoring algorithm: a proof-of-concept in heart failure

Author

Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Houtgraaf, Jaco, Rutten, Frans H, Oberski, Daniel L, Laake, Linda W van, Asselbergs, Folkert W, Aarts, Emmeke, Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Houtgraaf, Jaco, Rutten, Frans H, Oberski, Daniel L, Laake, Linda W van, Asselbergs, Folkert W, and Aarts, Emmeke

Abstract

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.

Published
2023

13. Identifying patients at risk: multi-centre comparison of HeartMate 3 and HeartWare left ventricular assist devices

Author

Numan, Lieke, Zimpfer, Daniel, Zadok, Osnat Itzhaki Ben, Aarts, Emmeke, Morshuis, Michiel, Guenther, Sabina P W, Riebandt, Julia, Wiedemann, Dominik, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Ben-Gal, Tuvia, Ben-Avraham, Binyamin, Asselbergs, Folkert W, Schramm, Rene, Van Laake, Linda W, Numan, Lieke, Zimpfer, Daniel, Zadok, Osnat Itzhaki Ben, Aarts, Emmeke, Morshuis, Michiel, Guenther, Sabina P W, Riebandt, Julia, Wiedemann, Dominik, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Ben-Gal, Tuvia, Ben-Avraham, Binyamin, Asselbergs, Folkert W, Schramm, Rene, and Van Laake, Linda W

Abstract

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 pa

Published
2023

14. Monitoring left ventricular assist device parameters to detect flow- and power-impacting complications: a proof of concept

Author

Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences, Leerstoel Klugkist, Moazeni, Mehran, Numan, Lieke, Szymanski, M., Van Der Kaaij, Niels P, Asselbergs, Folkert W, van Laake, Linda W, Aarts, Emmeke, Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences, Leerstoel Klugkist, Moazeni, Mehran, Numan, Lieke, Szymanski, M., Van Der Kaaij, Niels P, Asselbergs, Folkert W, van Laake, Linda W, and Aarts, Emmeke

Published
2023

15. Survival after HeartMate 3 left ventricular assist device implantation: real-world data from Europe

Author

Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Numan, Lieke, Schramm, Rene, Oerlemans, Marish I F J, van der Kaaij, Niels P, Aarts, Emmeke, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Morshuis, Michiel, Guenther, Sabina P W, Zimpfer, Daniel, Riebandt, Julia, Wiedemann, Dominik, Asselbergs, Folkert W, Van Laake, Linda W, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Numan, Lieke, Schramm, Rene, Oerlemans, Marish I F J, van der Kaaij, Niels P, Aarts, Emmeke, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Morshuis, Michiel, Guenther, Sabina P W, Zimpfer, Daniel, Riebandt, Julia, Wiedemann, Dominik, Asselbergs, Folkert W, and Van Laake, Linda W

Published
2023

16. Incidence and risk factors of late right heart failure in chronic mechanical circulatory support

Author

Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Felix, Susanne E A, Numan, Lieke, Oerlemans, Marish I F, Aarts, E, Ramjankhan, Faiz Z, Gianoli, Monica, Asselbergs, Folkert W, De Jonge, Nicolaas, Van Laake, Linda W, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Felix, Susanne E A, Numan, Lieke, Oerlemans, Marish I F, Aarts, E, Ramjankhan, Faiz Z, Gianoli, Monica, Asselbergs, Folkert W, De Jonge, Nicolaas, and Van Laake, Linda W

Published
2023

17. Developing a personalized remote patient monitoring algorithm: a proof-of-concept in heart failure

Author

Leerstoel Klugkist, Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences, Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Houtgraaf, Jaco, Rutten, Frans H, Oberski, Daniel L, Laake, Linda W van, Asselbergs, Folkert W, Aarts, Emmeke, Leerstoel Klugkist, Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences, Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Houtgraaf, Jaco, Rutten, Frans H, Oberski, Daniel L, Laake, Linda W van, Asselbergs, Folkert W, and Aarts, Emmeke

Published
2023

18. Identifying patients at risk: multi-centre comparison of HeartMate 3 and HeartWare left ventricular assist devices

Author

Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Numan, Lieke, Zimpfer, Daniel, Zadok, Osnat Itzhaki Ben, Aarts, Emmeke, Morshuis, Michiel, Guenther, Sabina P W, Riebandt, Julia, Wiedemann, Dominik, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Ben-Gal, Tuvia, Ben-Avraham, Binyamin, Asselbergs, Folkert W, Schramm, Rene, Van Laake, Linda W, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Numan, Lieke, Zimpfer, Daniel, Zadok, Osnat Itzhaki Ben, Aarts, Emmeke, Morshuis, Michiel, Guenther, Sabina P W, Riebandt, Julia, Wiedemann, Dominik, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Ben-Gal, Tuvia, Ben-Avraham, Binyamin, Asselbergs, Folkert W, Schramm, Rene, and Van Laake, Linda W

Published
2023

20. Monitoring left ventricular assist device parameters to detect flow- and power-impacting complications: a proof of concept

Author

Onderzoek Precision medicine, Team Medisch, CTC, Circulatory Health, Regenerative Medicine and Stem Cells, Moazeni, Mehran, Numan, Lieke, Szymanski, Mariusz K, Van der Kaaij, Niels P, Asselbergs, Folkert W, van Laake, Linda W, Aarts, Emmeke, Onderzoek Precision medicine, Team Medisch, CTC, Circulatory Health, Regenerative Medicine and Stem Cells, Moazeni, Mehran, Numan, Lieke, Szymanski, Mariusz K, Van der Kaaij, Niels P, Asselbergs, Folkert W, van Laake, Linda W, and Aarts, Emmeke

Published
2023

21. Identifying patients at risk: multi-centre comparison of HeartMate 3 and HeartWare left ventricular assist devices

Author

Onderzoek Precision medicine, CTC, Circulatory Health, Team Medisch, Regenerative Medicine and Stem Cells, Numan, Lieke, Zimpfer, Daniel, Zadok, Osnat Itzhaki Ben, Aarts, Emmeke, Morshuis, Michiel, Guenther, Sabina P W, Riebandt, Julia, Wiedemann, Dominik, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Ben-Gal, Tuvia, Ben-Avraham, Binyamin, Asselbergs, Folkert W, Schramm, Rene, Van Laake, Linda W, Onderzoek Precision medicine, CTC, Circulatory Health, Team Medisch, Regenerative Medicine and Stem Cells, Numan, Lieke, Zimpfer, Daniel, Zadok, Osnat Itzhaki Ben, Aarts, Emmeke, Morshuis, Michiel, Guenther, Sabina P W, Riebandt, Julia, Wiedemann, Dominik, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Ben-Gal, Tuvia, Ben-Avraham, Binyamin, Asselbergs, Folkert W, Schramm, Rene, and Van Laake, Linda W

Published
2023

22. Developing a personalized remote patient monitoring algorithm: a proof-of-concept in heart failure

Author

Onderzoek Precision medicine, Verpleegkundig Specialisten Cardiologie, HAG Hart- Vaatziekten, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Datascience, Regenerative Medicine and Stem Cells, Team Medisch, Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Houtgraaf, Jaco, Rutten, Frans H, Oberski, Daniel L, van Laake, Linda W, Asselbergs, Folkert W, Aarts, Emmeke, Onderzoek Precision medicine, Verpleegkundig Specialisten Cardiologie, HAG Hart- Vaatziekten, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Datascience, Regenerative Medicine and Stem Cells, Team Medisch, Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Houtgraaf, Jaco, Rutten, Frans H, Oberski, Daniel L, van Laake, Linda W, Asselbergs, Folkert W, and Aarts, Emmeke

Published
2023

23. Survival after HeartMate 3 left ventricular assist device implantation: real-world data from Europe

Author

Onderzoek Precision medicine, Team Medisch, Circulatory Health, CTC, MCS-team, Regenerative Medicine and Stem Cells, Numan, Lieke, Schramm, Rene, Oerlemans, Marish I F J, van der Kaaij, Niels P, Aarts, Emmeke, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Morshuis, Michiel, Guenther, Sabina P W, Zimpfer, Daniel, Riebandt, Julia, Wiedemann, Dominik, Asselbergs, Folkert W, Van Laake, Linda W, Onderzoek Precision medicine, Team Medisch, Circulatory Health, CTC, MCS-team, Regenerative Medicine and Stem Cells, Numan, Lieke, Schramm, Rene, Oerlemans, Marish I F J, van der Kaaij, Niels P, Aarts, Emmeke, Ramjankhan, Faiz Z, Oppelaar, Anne-Marie, Morshuis, Michiel, Guenther, Sabina P W, Zimpfer, Daniel, Riebandt, Julia, Wiedemann, Dominik, Asselbergs, Folkert W, and Van Laake, Linda W

Published
2023

24. Incidence and risk factors of late right heart failure in chronic mechanical circulatory support

Author

Aios en Stafsecr. Cardiologie, Onderzoek Precision medicine, Team Medisch, Circulatory Health, CTC, Regenerative Medicine and Stem Cells, Felix, Susanne E A, Numan, Lieke, Oerlemans, Marish I F, Aarts, E, Ramjankhan, Faiz Z, Gianoli, Monica, Asselbergs, Folkert W, de Jonge, Nicolaas, van Laake, Linda W, Aios en Stafsecr. Cardiologie, Onderzoek Precision medicine, Team Medisch, Circulatory Health, CTC, Regenerative Medicine and Stem Cells, Felix, Susanne E A, Numan, Lieke, Oerlemans, Marish I F, Aarts, E, Ramjankhan, Faiz Z, Gianoli, Monica, Asselbergs, Folkert W, de Jonge, Nicolaas, and van Laake, Linda W

Published
2023

25. Identifying patients at risk: multi‐centre comparison of HeartMate 3 and HeartWare left ventricular assist devices

Author

Numan, Lieke, primary, Zimpfer, Daniel, additional, Zadok, Osnat Itzhaki Ben, additional, Aarts, Emmeke, additional, Morshuis, Michiel, additional, Guenther, Sabina P.W., additional, Riebandt, Julia, additional, Wiedemann, Dominik, additional, Ramjankhan, Faiz Z., additional, Oppelaar, Anne‐Marie, additional, Ben‐Gal, Tuvia, additional, Ben‐Avraham, Binyamin, additional, Asselbergs, Folkert W., additional, Schramm, Rene, additional, and Van Laake, Linda W., additional

Published
2023
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28. A personalized remote patient monitoring system based on daily measurements of body weight, heart rate, and blood pressure to early detect deterioration in heart failure patients

Author

Moazeni, Mehran, Numan, Lieke, Brons, Maaike, Rutten, Frans H., Oberski, Daniel, Laake, L.W.V, Asselbergs, Folkert W., and Aarts, Emmeke

Subjects
Intensive longitudinal data, Remote patient monitoring, Process monitoring, Heart failure, Statistical process control chart, Dynamic monitoring
Abstract

Aims Non-invasive remote patient monitoring is an increasingly popular technique to detect early clinical deterioration in heart failure patients. Previous studies have shown mixed results on the sensitivity and specificity of such systems. Therefore, we developed a novel individualized biometric monitoring algorithm, and evaluated it by comparison with simple rule-of-thumb algorithms and a moving average convergence-divergence algorithm. Methods and Results Transmitted daily bodyweight, heartrate, and systolic blood pressure were collected in 78 patients for a period of 279±128 days, during which 31 patients experienced 64 events of clinical deterioration of heart failure. The algorithm was informed by both cross sectional and patient-specific longitudinal information, predicting a dynamic patient-specific biometric value at each time point. Large deviations from the predicted measurement triggered an alarm. Sensitivity and area under the curve were higher (57% and 63% respectively) for the personalized monitoring approach when monitoring bodyweight only, in comparison to the rule-of-thumb (42% and 52%) and moving average convergence-divergence algorithms (12% and 52%). Similarly, when combining bodyweight with heart rate and systolic blood pressure, the personalized monitoring approach outperformed (70% and 64%) rule-of-thumb (47% and 55%) in terms of sensitivity and area under the curve. Source code for the algorithm is made publicly available. Conclusion The proposed personalized algorithm based on combining bodyweight, heart rate, and systolic blood pressure measurements is a promising tool for predicting early deterioration of heart failure. Heart rate monitoring performed better compared to bodyweight. Before clinical application, the algorithm should be tested in randomized controlled trials. This repository contains code and datageneratedfor the manuscript: "A personalized remote patient monitoring system based on daily measurements of body weight, heart rate, and blood pressure to early detect deterioration in heart failure patients". It comprehends: (1) PRECISION-HF Rcode file with an example,(2) MACD Rcode file with an example. User can download "bank.csv" and "non-bank.csv" files as an examplary input data sets.&nbsp

Published
2022
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29. Propensity score-based analysis of long-term outcome of patients on HeartWare and HeartMate 3 left ventricular assist device support

Author

Numan, Lieke, Ramjankhan, Faiz Z, Oberski, Daniel L, Oerlemans, Martinus I F J, Aarts, Emmeke, Gianoli, Monica, Van Der Heijden, Joris J, De Jonge, Nicolaas, Van Der Kaaij, Niels P, Meuwese, Christiaan L, Mokhles, Mostafa M, Oppelaar, Anne-Marie, De Waal, Eric E C, Asselbergs, Folkert W, Van Laake, Linda W, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, and Cardiology

Subjects
lcsh:Diseases of the circulatory (Cardiovascular) system, medicine.medical_specialty, LVAD, Centrifugal continuous flow pump, medicine.medical_treatment, Left ventricular assist device, law.invention, Brain Ischemia, Randomized controlled trial, law, Mechanical circulatory support, Internal medicine, Original Research Articles, medicine, Humans, Original Research Article, Propensity Score, Retrospective Studies, Proportional hazards model, business.industry, Hazard ratio, medicine.disease, Confidence interval, MCS, Stroke, lcsh:RC666-701, Ventricular assist device, Heart failure, Propensity score matching, Cardiology, Heart-Assist Devices, business, Cardiology and Cardiovascular Medicine, Destination therapy
Abstract

Aims Left ventricular assist device therapy has become the cornerstone in the treatment of end‐stage heart failure and is increasingly used as destination therapy next to bridge to transplant or recovery. HeartMate 3 (HM3) and HeartWare (HVAD) are centrifugal continuous flow devices implanted intrapericardially and most commonly used worldwide. No randomized controlled trials have been performed yet. Analysis based on large registries may be considered as the best alternative but has the disadvantage of different standard of care between centres and missing data. Bias is introduced, because the decision which device to use was not random, even more so because many centres use only one type of left ventricular assist device. Therefore, we performed a propensity score (PS)‐based analysis of long‐term clinical outcome of patients that received HM3 or HVAD in a single centre. Methods and results Between December 2010 and December 2019, 100 patients received HVAD and 81 patients HM3 as primary implantation at the University Medical Centre Utrecht. We performed PS matching with an extensive set of covariates, resulting in 112 matched patients with a median follow‐up of 28 months. After PS matching, survival was not significantly different (P = 0.21) but was better for HM3. The cumulative incidences for haemorrhagic stroke (P = 0.01) and pump thrombosis (P = 0.02) were significantly higher for HVAD patients. The cumulative incidences for major bleeding, ischaemic stroke, right heart failure, and driveline infection were not different between the groups. We found no interaction between the surgeon who performed the implantation and survival (P = 0.59, P = 0.78, and P = 0.89). Sensitivity analysis was performed, by PS matching without patients on preoperative temporary support resulting in 74 matched patients. This also resulted in a non‐significant difference in survival (P = 0.07). The PS‐adjusted Cox regression showed a worse but non‐significant (P = 0.10) survival for HVAD patients with hazard ratio 1.71 (95% confidence interval 0.91–3.24). Conclusions Survival was not significantly different between both groups after PS matching, but was better for HM3, with a significantly lower incidence of haemorrhagic stroke and pump thrombosis for HM3. These results need to be interpreted carefully, because matching may have introduced greater imbalance on unmeasured covariates. A multicentre approach of carefully selected centres is recommended to enlarge the number of matched patients.

Published
2021
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31. Data-driven monitoring in patients on left ventricular assist device support

Author

Numan, Lieke, Moazeni, Mehran, Oerlemans, Marish I.F.J., Aarts, Emmeke, Kaaij, Niels P. Van Der, Asselbergs, Folkert W., Laake, Linda W. Van, Numan, Lieke, Moazeni, Mehran, Oerlemans, Marish I.F.J., Aarts, Emmeke, Kaaij, Niels P. Van Der, Asselbergs, Folkert W., and Laake, Linda W. Van

Abstract

Introduction: Despite an increasing population of patients supported with a left ventricular assist device (LVAD), it remains a complex therapy, and patients are frequently admitted. Therefore, a strict follow-up including frequent hospital visits, patient self-management and telemonitoring is needed. Areas covered: The current review describes the principles of LVADs, the possibilities of (tele)monitoring using noninvasive and invasive devices. Furthermore, possibilities, challenges, and future perspectives in this emerging field are discussed. Expert Opinion: Several studies described initial experiences on telemonitoring in LVAD patients, using mobile phone applications to collect clinical data and pump data. This may replace frequent hospital visits in near future. In addition, algorithms were developed aiming to early detect pump thrombosis or driveline infections. Since not all complications are reflected by pump parameters, data from different sources should be combined to detect a broader spectrum of complications in an early stage. We need to focus on the development of sophisticated but understandable algorithms and infrastructure combining different data sources, while addressing essential aspects such as data safety, privacy, and cost-effectiveness.

Published
2022

32. Hyperpolypharmacy is a predictor of mortality after left ventricular assist device (LVAD) implantation

Author

MS Geriatrie, Onderzoek Precision medicine, CTC, Cardiovasculaire Immunologie, Team Medisch, MCS-team, Circulatory Health, Regenerative Medicine and Stem Cells, Dautzenberg, Lauren, Numan, Lieke, Knol, Wilma, Gianoli, Monica, van der Meer, Manon G., Troost-Oppelaar, Anne Marie, Westendorp, Aline F., Emmelot-Vonk, Marielle H., van Laake, Linda W., Koek, Huiberdina L., MS Geriatrie, Onderzoek Precision medicine, CTC, Cardiovasculaire Immunologie, Team Medisch, MCS-team, Circulatory Health, Regenerative Medicine and Stem Cells, Dautzenberg, Lauren, Numan, Lieke, Knol, Wilma, Gianoli, Monica, van der Meer, Manon G., Troost-Oppelaar, Anne Marie, Westendorp, Aline F., Emmelot-Vonk, Marielle H., van Laake, Linda W., and Koek, Huiberdina L.

Published
2022

33. Data-driven monitoring in patients on left ventricular assist device support

Author

Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences, Leerstoel Klugkist, Numan, Lieke, Moazeni, Mehran, Oerlemans, Marish I.F.J., Aarts, Emmeke, Kaaij, Niels P. Van Der, Asselbergs, Folkert W., Laake, Linda W. Van, Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences, Leerstoel Klugkist, Numan, Lieke, Moazeni, Mehran, Oerlemans, Marish I.F.J., Aarts, Emmeke, Kaaij, Niels P. Van Der, Asselbergs, Folkert W., and Laake, Linda W. Van

Published
2022

34. Data-driven monitoring in patients on left ventricular assist device support

Author

Onderzoek Precision medicine, Team Medisch, Circulatory Health, Regenerative Medicine and Stem Cells, Numan, Lieke, Moazeni, Mehran, Oerlemans, Marish I F J, Aarts, Emmeke, Van Der Kaaij, Niels P, Asselbergs, Folkert W, Van Laake, Linda W, Onderzoek Precision medicine, Team Medisch, Circulatory Health, Regenerative Medicine and Stem Cells, Numan, Lieke, Moazeni, Mehran, Oerlemans, Marish I F J, Aarts, Emmeke, Van Der Kaaij, Niels P, Asselbergs, Folkert W, and Van Laake, Linda W

Published
2022

35. Propensity score-based analysis of long-term outcome of patients on HeartWare and HeartMate 3 left ventricular assist device support

Author

Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Numan, Lieke, Ramjankhan, Faiz Z, Oberski, Daniel L, Oerlemans, Martinus I F J, Aarts, Emmeke, Gianoli, Monica, Van Der Heijden, Joris J, De Jonge, Nicolaas, Van Der Kaaij, Niels P, Meuwese, Christiaan L, Mokhles, Mostafa M, Oppelaar, Anne-Marie, De Waal, Eric E C, Asselbergs, Folkert W, Van Laake, Linda W, Leerstoel Klugkist, Methodology and statistics for the behavioural and social sciences, Numan, Lieke, Ramjankhan, Faiz Z, Oberski, Daniel L, Oerlemans, Martinus I F J, Aarts, Emmeke, Gianoli, Monica, Van Der Heijden, Joris J, De Jonge, Nicolaas, Van Der Kaaij, Niels P, Meuwese, Christiaan L, Mokhles, Mostafa M, Oppelaar, Anne-Marie, De Waal, Eric E C, Asselbergs, Folkert W, and Van Laake, Linda W

Published
2021

36. Propensity score-based analysis of long-term outcome of patients on HeartWare and HeartMate 3 left ventricular assist device support

Author

Onderzoek Vrouw Hart & Vaatziekten, Onderzoek Precision medicine, CTC, Circulatory Health, Datascience, Team Medisch, Medische Staf Intensive Care, Medische staf Anesthesiologie, Regenerative Medicine and Stem Cells, Numan, Lieke, Ramjankhan, Faiz Z., Oberski, Daniel L., Oerlemans, Martinus I.F.J., Aarts, Emmeke, Gianoli, Monica, Van Der Heijden, Joris J., De Jonge, Nicolaas, Van Der Kaaij, Niels P., Meuwese, Christiaan L., Mokhles, Mostafa M., Oppelaar, Anne Marie, De Waal, Eric E.C., Asselbergs, Folkert W., Van Laake, Linda W., Onderzoek Vrouw Hart & Vaatziekten, Onderzoek Precision medicine, CTC, Circulatory Health, Datascience, Team Medisch, Medische Staf Intensive Care, Medische staf Anesthesiologie, Regenerative Medicine and Stem Cells, Numan, Lieke, Ramjankhan, Faiz Z., Oberski, Daniel L., Oerlemans, Martinus I.F.J., Aarts, Emmeke, Gianoli, Monica, Van Der Heijden, Joris J., De Jonge, Nicolaas, Van Der Kaaij, Niels P., Meuwese, Christiaan L., Mokhles, Mostafa M., Oppelaar, Anne Marie, De Waal, Eric E.C., Asselbergs, Folkert W., and Van Laake, Linda W.

Published
2021

37. Wireless Remote Home Monitoring of Vital Signs in Patients Discharged Early After Esophagectomy: Observational Feasibility Study

Author

Onderzoek Heart at Risk, Circulatory Health, Onderzoek Precision medicine, MS CGO, Cancer, Medische staf Anesthesiologie, Brain, Breteler, Martine J M, Numan, Lieke, Ruurda, Jelle P, van Hillegersberg, Richard, van der Horst, Sylvia, Dohmen, Daan A J, van Rossum, Mathilde C, Kalkman, Cor J, Onderzoek Heart at Risk, Circulatory Health, Onderzoek Precision medicine, MS CGO, Cancer, Medische staf Anesthesiologie, Brain, Breteler, Martine J M, Numan, Lieke, Ruurda, Jelle P, van Hillegersberg, Richard, van der Horst, Sylvia, Dohmen, Daan A J, van Rossum, Mathilde C, and Kalkman, Cor J

Published
2020

38. Are current wireless monitoring systems capable of detecting adverse events in high-risk surgical patients?: A descriptive study

Author

Onderzoek Heart at Risk, Circulatory Health, Onderzoek Precision medicine, MS CGO, Cancer, Divisie Beeld & Oncologie, Zorgeenheid Traumatologie, Medische staf Anesthesiologie, Brain, Breteler, Martine J M, KleinJan, Eline, Numan, Lieke, Ruurda, Jelle P, Van Hillegersberg, Richard, Leenen, Luke P H, Hermans, Mathilde, Kalkman, Cor J, Blokhuis, Taco J, Onderzoek Heart at Risk, Circulatory Health, Onderzoek Precision medicine, MS CGO, Cancer, Divisie Beeld & Oncologie, Zorgeenheid Traumatologie, Medische staf Anesthesiologie, Brain, Breteler, Martine J M, KleinJan, Eline, Numan, Lieke, Ruurda, Jelle P, Van Hillegersberg, Richard, Leenen, Luke P H, Hermans, Mathilde, Kalkman, Cor J, and Blokhuis, Taco J

Published
2020

42. Monitoring left ventricular assist device parameters to detect flow- and power-impacting complications: a proof of concept.

Author

Moazeni M, Numan L, Szymanski MK, Van der Kaaij NP, Asselbergs FW, van Laake LW, and Aarts E

Abstract

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., Competing Interests: Conflict of interest: M.M., L.N., M.S., N.K., F.W.A, and E.A. report no competing interests. L.W.L. received consultancy fees from Medtronic, Abbott Vifor, Novartis, outside the submitted work., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2023
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43. Developing a personalized remote patient monitoring algorithm: a proof-of-concept in heart failure.

Author

Moazeni M, Numan L, Brons M, Houtgraaf J, Rutten FH, Oberski DL, van Laake LW, Asselbergs FW, and Aarts E

Abstract

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., Competing Interests: Conflict of interest: M.M., L.N., M.B., J.H., F.H.R., D.L.O., F.W.A, and E.A. report no competing interests. L.W.L. received consultancy fees from Medtronic, Abbott Vifor, Novartis, outside the submitted work., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2023
Full Text
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