Cell-based Therapies for Cardiovascular Repair: How small things matter

__Abstract__ Cardiovascular disease accounts for almost half of the deaths in the Western world and 25% in developing countries, despite significant therapeutic and interventional advances. It is estimated that by the year 2020, cardiovascular disease will surpass infectious disease, to become the world’s leading cause of mortality and morbidity. Approximately half of the cardiovascular mortality is due to acute myocardial infarction, whereas subsequent heart failure and stable coronary artery disease account for the majority of morbidity. Stem cell therapy to reduce the burden of cardiovascular disease has been the topic of extensive research over the past decade. The assumption that multipotent cells can graft to the injured heart and incorporate into the host’s myocardium, thereby contributing to contractility and improving cardiac function, is considered to be the holy grail for cardiac cell therapy. Hence, the first attempt of cardiac cell therapy more than a decade ago was with skeletal myoblasts (SkM) in end-stage heart failure patients. These progenitor cells are derived from striated skeletal muscle, and are destined to become contracting myofibers. It was hypothesized that, once injected into myocardial scars, these SkM would differentiate into contractile units in vivo, and actually contribute to the contractile apparatus. Unfortunately, clinical reality turned out to be less manipulable, and subsequent research has indicated that the road towards the holy grail is still long and comprises many obstacles on the way. More specifically, injected SkM did not actually incorporate into scars, but rather formed re-entry circuits for ventricular arrhythmias, whereas cardiac function was not enhanced following SkM injection. In the clinical arena, these disappointing results were rather generalized into the notion that cardiovascular cell therapy did not work. However, as there are several different cardiovascular pathologies and even more different stem cell types, cell therapy is not a single entity. Therefore, the last decade has been devoted to unraveling numerous questions, as 1) what is the ideal stem cell type and dose; 2) what cardiovascular disease types qualify for stem cell therapy; 3) when should stem cell therapy be initiated; 4) how should cells be administered; 5) what is the best surrogate end point to evaluate the effect of cell therapy; etcetera. This thesis aims to clarify some of these questions, and summarizes our current knowledge about cardiovascular cell therapy

Echocardiographic features of an atypical presentation of rapidly progressive cardiac amyloidosis

We present the case of a 66 year old male who presented with dyspnea and reduced exercise tolerance. Echocardiography demonstrated impaired left ventricular (LV) function and restrictive diastolic function with pronounced concentric left ventricular hypertrophy (LVH) without a history of hypertension and no aortic valve stenosis. Differential diagnostics of concentric LVH are discussed in detail. In the current case, cardiac amyloidosis (AL) amyloidosis was diagnosed and confirmed by serum amyloid P (SAP) scintigraphy and abdominal fat aspiration biopsy. This case shows the rapid decline in clinical condition with progression of cardiac involvement of AL. As discussed in detail, cardiac involvement in AL-amyloidosis generally denotes a poor prognosis, regardless of the method of treatment

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

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

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

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

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

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

RELEASE-HF study:a protocol for an observational, registry-based study on the effectiveness of telemedicine in heart failure in the Netherlands

Introduction:Meta-analyses show postive effects of telemedicine in heart failure (HF) management on hospitalisation, mortality and costs. However, these effects are heterogeneous due to variation in the included HF population, the telemedicine components and the quality of the comparator usual care. Still, telemedicine is gaining acceptance in HF management. The current nationwide study aims to identify (1) in which subgroup(s) of patients with HF telemedicine is (cost-)effective and (2) which components of telemedicine are most (cost-) effective. Methods and analysis:The RELEASE-HF ('REsponsible roLl-out of E-heAlth through Systematic Evaluation -Heart Failure') study is a multicentre, observational, registry-based cohort study that plans to enrol 6480 patients with HF using data from the HF registry facilitated by the Netherlands Heart Registration. Collected data include patient characteristics, treatment information and clinical outcomes, and are measured at HF diagnosis and at 6 and 12 months afterwards. The components of telemedicine are described at the hospital level based on closed-ended interviews with clinicians and at the patient level based on additional data extracted from electronic health records and telemedicine-generated data. The costs of telemedicine are calculated using registration data and interviews with clinicians and finance department staff. To overcome missing data, additional national databases will be linked to the HF registry if feasible. Heterogeneity of the effects of offering telemedicine compared with not offering on days alive without unplanned hospitalisations in 1 year is assessed across predefined patient characteristics using exploratory stratified analyses. The effects of telemedicine components are assessed by fitting separate models for component contrasts. Ethics and dissemination:The study has been approved by the Medical Ethics Committee 2021 of the University Medical Center Utrecht (the Netherlands). Results will be published in peer-reviewed journals and presented at (inter)national conferences. Effective telemedicine scenarios will be proposed among hospitals throughout the country and abroad, if applicable and feasible.</p

RELEASE-HF study:a protocol for an observational, registry-based study on the effectiveness of telemedicine in heart failure in the Netherlands

Introduction:Meta-analyses show postive effects of telemedicine in heart failure (HF) management on hospitalisation, mortality and costs. However, these effects are heterogeneous due to variation in the included HF population, the telemedicine components and the quality of the comparator usual care. Still, telemedicine is gaining acceptance in HF management. The current nationwide study aims to identify (1) in which subgroup(s) of patients with HF telemedicine is (cost-)effective and (2) which components of telemedicine are most (cost-) effective. Methods and analysis:The RELEASE-HF ('REsponsible roLl-out of E-heAlth through Systematic Evaluation -Heart Failure') study is a multicentre, observational, registry-based cohort study that plans to enrol 6480 patients with HF using data from the HF registry facilitated by the Netherlands Heart Registration. Collected data include patient characteristics, treatment information and clinical outcomes, and are measured at HF diagnosis and at 6 and 12 months afterwards. The components of telemedicine are described at the hospital level based on closed-ended interviews with clinicians and at the patient level based on additional data extracted from electronic health records and telemedicine-generated data. The costs of telemedicine are calculated using registration data and interviews with clinicians and finance department staff. To overcome missing data, additional national databases will be linked to the HF registry if feasible. Heterogeneity of the effects of offering telemedicine compared with not offering on days alive without unplanned hospitalisations in 1 year is assessed across predefined patient characteristics using exploratory stratified analyses. The effects of telemedicine components are assessed by fitting separate models for component contrasts. Ethics and dissemination:The study has been approved by the Medical Ethics Committee 2021 of the University Medical Center Utrecht (the Netherlands). Results will be published in peer-reviewed journals and presented at (inter)national conferences. Effective telemedicine scenarios will be proposed among hospitals throughout the country and abroad, if applicable and feasible.</p

Self-Administered Intranasal Etripamil Using a Symptom-Prompted, Repeat-Dose Regimen for Atrioventricular-Nodal-Dependent Supraventricular Tachycardia (RAPID): A Multicentre, Randomised Trial

BACKGROUND: Etripamil is a fast-acting, intranasally administered calcium-channel blocker in development for on-demand therapy outside a health-care setting for paroxysmal supraventricular tachycardia. We aimed to evaluate the efficacy and safety of etripamil 70 mg nasal spray using a symptom-prompted, repeat-dose regimen for acute conversion of atrioventricular-nodal-dependent paroxysmal supraventricular tachycardia to sinus rhythm within 30 min. METHODS: RAPID was a multicentre, randomised, placebo-controlled, event-driven trial, conducted at 160 sites in North America and Europe as part 2 of the NODE-301 study. Eligible patients were aged at least 18 years and had a history of paroxysmal supraventricular tachycardia with sustained, symptomatic episodes (≥20 min) as documented by electrocardiogram. Patients were administered two test doses of intranasal etripamil (each 70 mg, 10 min apart) during sinus rhythm; those who tolerated the test doses were randomly assigned (1:1) using an interactive response technology system to receive either etripamil or placebo. Prompted by symptoms of paroxysmal supraventricular tachycardia, patients self-administered a first dose of intranasal 70 mg etripamil or placebo and, if symptoms persisted beyond 10 min, a repeat dose. Continuously recorded electrocardiographic data were adjudicated, by individuals masked to patient assignment, for the primary endpoint of time to conversion of paroxysmal supraventricular tachycardia to sinus rhythm for at least 30 s within 30 min after the first dose, which was measured in all patients who administered blinded study drug for a confirmed atrioventricular-nodal-dependent event. Safety outcomes were assessed in all patients who self-administered blinded study drug for an episode of perceived paroxysmal supraventricular tachycardia. This trial is registered at ClinicalTrials.gov, NCT03464019, and is complete. FINDINGS: Between Oct 13, 2020, and July 20, 2022, among 692 patients randomly assigned, 184 (99 from the etripamil group and 85 from the placebo group) self-administered study drug for atrioventricular-nodal-dependent paroxysmal supraventricular tachycardia, with diagnosis and timing confirmed. Kaplan-Meier estimates of conversion rates by 30 min were 64% (63/99) with etripamil and 31% (26/85) with placebo (hazard ratio 2·62; 95% CI 1·66-4·15; p INTERPRETATION: Using a symptom-prompted, self-administered, initial and optional-repeat-dosing regimen, intranasal etripamil was well tolerated, safe, and superior to placebo for the rapid conversion of atrioventricular-nodal-dependent paroxysmal supraventricular tachycardia to sinus rhythm. This approach could empower patients to treat paroxysmal supraventricular tachycardia themselves outside of a health-care setting, and has the potential to reduce the need for additional medical interventions, such as intravenous medications given in an acute-care setting. FUNDING: Milestone Pharmaceuticals

Additional file 2 of Pneumococcal pericarditis in a patient with newly diagnosed diabetes mellitus: a case report

Additional file 2. Medication administered from admission until the sudden clinical deterioration