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European Journal of Heart Failure 2008 10(11):1143-1148; doi:10.1016/j.ejheart.2008.08.004
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© 2008 European Society of Cardiology

Influence of Home Monitoring on the clinical status of heart failure patients: Design and rationale of the IN-TIME study

Arash Aryaa,*, Michael Blockb, Josef Kautznerc, Thorsten Lewalterd, Heinrich Mörtele, Stefan Sackf, Burghard Schumacherg, Peter Søgaardh, Milos Taborskyi, Daniela Hussera, Gerhard Hindricksa and IN-TIME investigators

a Herzzentrum Leipzig, Germany
b Klinik Augustinum München Germany
c IKEM Praha Czech Republic
d Universitätsklinikum Bonn Germany
e BIOTRONIK GmbH & Co. KG, Study Center Erlangen Germany
f Westdeutsches Herzzentrum Essen Germany
g Herz- und Gefäßklinikum Bad Neustadt GmbH Germany
h Gentofte Hospital Hellerup Denmark
i Hospital Na Homolce Praha Czech Republic

* Corresponding author. Herzzentrum Leipzig, Strümpellstr. 39, 04289 Leipzig, Germany, Tel.: +49 341 8651413; fax: +49 341 8651460. E-mail address: dr.arasharya{at}gmail.com (A. Arya).


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Summary
 References
 
Background: Despite optimal drug and device therapy, frequent hospitalisations due to decompensated heart failure remain an issue. Early detection of decompensation could prevent hospitalisation in patients with congestive heart failure. The recently introduced Home Monitoring functionality of implanted devices is a promising new telecardiology technique which provides information on the status of heart failure. Home Monitoring observation of heart failure patients could lead to early detection of preclinical decompensation, enable early intervention before clinical decompensation, and thus could prevent hospitalisations.

Objective: The IN-TIME study is designed to assess the impact of Home Monitoring on the early detection of worsening congestive heart failure and the clinical status of heart failure patients.

Study design: Approximately 620 patients will be prospectively randomised to patient management guided by Home Monitoring analysis or standard care and followed for 12 months. The endpoints committee will adjudicate events in a blinded fashion. The primary endpoint is a composite of all-cause mortality, unplanned hospitalisation due to worsening heart failure, NYHA class and patient global self assessment (Packer score). The study should complete recruitment during 2009 and report in late 2010.

Key Words: IN-TIME study • Heart failure • Home monitoring • Patient management • Early detection

Received March 4, 2008; Revised June 25, 2008; Accepted August 18, 2008


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Summary
 References
 
Heart failure is one of the leading causes of death and hospitalisation in developed countries. It is often associated with multiple co-morbidities and complications and a decreased quality of life. Common heart failure co-morbidities include anaemia, depression, diabetes, atrial and ventricular arrhythmias, hypertension, and renal dysfunction.

Many new therapeutic options have been successfully introduced to prevent the worsening of heart failure, to treat its symptoms and prevent complications and thus to decrease mortality and enhance the quality of life of patients with congestive heart failure. These options include optimised medical treatment (i.e. diuretics, beta-blockers, ACE-inhibitors, and spironolactone), and device therapy with implantable defibrillators and cardiac resynchronisation therapy.

Although these therapy options have significantly improved the mortality and the morbidity in patients with heart failure [1-4], frequent re-hospitalisations due to worsening heart failure remain an issue [5]. Several studies have evaluated the potential predictors of hospitalisation in these patients [6-9]. Although it was not possible to find predictors for all events — up to 40% of events were not preceded by any change in a measurable parameter — the majority of events was predictable by parameters like atrial fibrillation [6], the number of premature ventricular beats per hour [7], heart rate [6,10] or heart rate variability [7,10]. In addition, other studies have shown that continuous monitoring of vital parameters like weight, blood pressure and heart rate, using external telemedicine devices, can improve outcomes in heart failure patients [11-13]. The feasibility of telemonitoring in large populations was shown by the Home or Hospital in Heart Failure (HHH) study [14]. The Coordinating Study Evaluating Outcomes of Advising and Counselling in Heart Failure (COACH) has shown that nurse-led telecare alone is not enough to significantly reduce death and hospitalisation rates [15].

Implant based telecardiology, e.g. by modern devices with Home MonitoringTM (HM) capability, offers the opportunity to observe a number of different parameters which may be potentially useful for detecting clinical decompensation, on a daily basis. Data transmission is performed automatically and independent of the patient, thus increasing compliance. The transmitted parameters include but are not restricted to (a) heart rhythm parameters like mean heart rate, mean heart rate at night, ventricular extrasystoles per hour, heart rate variability, atrial fibrillation burden, and the occurrence of atrial or ventricular tachyarrhythmias, (b) heart failure associated parameters like patient activity, and (c) technical parameters like the percentage of bi-ventricular pacing. All measured values are transmitted every day at a programmable time (default 01:00am). Additionally, specific event messages can be sent after the occurrence of tachyarrhythmias and for deviations from preset technical parameters, such as lead impedances. For further diagnostics, high-resolution intracardiac electrograms are transmitted after tachyarrhythmia event messages. This unique system allows the attending physician to monitor each patient very closely and to react in time to prevent potential cardiovascular events at an early stage.

The INfluence of Home Monitoring on The clinIcal Management of heart failurE patients with impaired left ventricular function (IN-TIME) study is designed to assess the impact of HM on the clinical status of heart failure patients and early detection of worsening congestive heart failure.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Summary
 References
 
2.1. Purpose and design
The goal of IN-TIME is thus to analyse the impact of a regular HM evaluation on the clinical status of heart failure patients. Patients with symptomatic heart failure and reduced ejection fraction (≤35%) receiving an implantable cardioverter defibrillator (ICD) or a cardiac resynchronisation therapy device with defibrillator backup (CRT-D) will be randomised to either prospective patient management by HM analysis or standard care. The clinical status of patients will be estimated using the established Packer Score [13], a composite endpoint of death, re-hospitalisation, NYHA class and quality of life. The IN-TIME study is designed as a prospective, randomised, open, and controlled multicentre study. Approximately 620 patients in approximately 50 centres (outside US) will be enrolled. Tables 1 and 2 show the inclusion and exclusion criteria. To exclude the period of highest mortality after newly diagnosed heart failure, only patients with chronic heart failure (duration ≥3 months) will be included.


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  		Table 1 Inclusion criteria

 


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  		Table 2 Exclusion criteria

 
2.2. Endpoints
2.2.1. Primary endpoint
The study hypothesis will be evaluated based on the composite endpoint introduced by Milton Packer in 2001, the Packer Score [16]. This score combines mortality, heart failure hospitalisation, NYHA classification and a patient self assessment as a last observation carried forward analysis. This composite score is already in use in other major clinical trials including the predictors of response to cardiac resynchronisation (PROSPECT) study, and the resynchronisation reverses remodelling in systolic left ventricular dysfunction (REVERSE) study [17,18].

Each patient will be followed for 12 months after randomisation. At the completion of the follow up period, randomised patients will be classified as improved, unchanged, or worsened, based upon the events such as death, overnight hospitalisation for worsening heart failure, change in NYHA class, change in the patient's global assessment score, or discontinuation of the study protocol due to worsening heart failure, lack of therapeutic response or treatment failure, including device failure (Table 3). As heart failure is a progressive disease, patient classification as "improved" and "unchanged" will be counted as improved clinical status for the primary study hypothesis. Each hospital admission will be analysed to determine whether or not the patient experienced and was admitted due to worsening heart failure and whether or not this was the primary reason for admission or the admission was due to other reasons such as myocardial infarction or atrial fibrillation. Only patients who are reported to have worsening heart failure as the primary or secondary reason of hospitalisation and who have also undergone an intensification of therapy (i.e. receiving intra-venous medication for heart failure or a substantial increase in oral diuretic therapy for heart failure) will be deemed to have worsening heart failure. The final classification of hospital admissions due to worsening heart failure will be made by a blinded endpoints committee.


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  		Table 3 Packer score classification

 
2.2.2. Secondary endpoints
The secondary endpoints are listed in Table 4. All endpoints combined in the Packer score will be analysed separately to estimate their relative impact on the primary endpoint. Death will be classified according to mode (sudden death, stroke, myocardial infarction, end stage heart failure, etc.). Sudden death is defined as death within 1 h of the onset of symptoms or unwitnessed death which occurs unexpectedly and without recognisable causes. The classification of the secondary endpoints will be made by a blinded endpoints committee.


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  		Table 4 Secondary endpoints

 
The number of and reason for additional follow ups initiated due to HM alarms for clinical or technical reasons, as well as the workflow of alarm message management will be measured to gain insight into the procedures involved in HM analysis.

A specified set of HM parameters (Table 5) known from the literature for their potential predictive value in cardiac risk assessment will be analysed for correlations with adverse events (e.g. death or hospitalisations due to worsening heart failure). Results of this analysis will be used to advance the development of a highly specific predictor for imminent cardiovascular events.


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  		Table 5 Potential predictors transmitted by the Home Monitoring system

 
2.3. Study conduct (Fig. 1)
This study will be conducted in compliance with Good Clinical Practice, including the International Conference on Harmonisation Guidelines, and the principles outlined in the Declaration of Helsinki (Br Med J 1964;ii:177). The study will be conducted with the approval of all appropriate national and local ethics committees. Patients who have given informed consent and who fulfil the inclusion/exclusion criteria will be screened and asked to participate. If the patient subsequently decides or is advised not to participate in the trial, the reason will be documented on the study termination form (Fig. 1).


Figure 01
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  		Fig. 1 Study conduct. HM: Home Monitoring.

 
After giving informed consent, patients will be enrolled to the study and receive, as indicated by European guidelines, either a dual chamber ICD or CRT-D device (Lumax® DR-T or Lumax® HF-T, BIOTRONIK GmbH & Co. KG, Germany) capable of transmitting HM messages. At discharge the HM functionality will be activated and the patient will be registered at the HM Service Center (BIOTRONIK GmbH & Co. KG, Germany). A run-in phase of one month after discharge will be used for further optimisation of heart failure therapy and for securing the correct functioning of HM transmissions.

Randomisation to the HM or control groups will be conducted one month after discharge from the hospital. Patients in the HM group will remain under the supervision of the attending physician and will be monitored at least once per week. Patients in the control group will be deregistered and will then be re-registered within a special study group. No investigator will have access to these patient data and the patients will not be monitored remotely. Interventions for these patients will be triggered only during device follow ups or if initiated by the patient. After study termination for each patient, the attending physician will have access to the data for this patient again.

After randomisation, patients will be followed for 12 months according to the clinical standard at each participating centre. It is solely up to the treating physician how to guide the patients. No special requirements apart from European guidelines are placed on the therapy as part of the study. Certain HM messages will lead to patient phone calls that may result in additional follow ups, patient visits to the General Practitioner, or other changes in therapy.

Transmitted HM data will be analysed retrospectively after termination of the patients participation in the study. To investigate the predictive value of HM parameters, 30 day time intervals preceding cardiovascular events will be analysed with respect to trends in HM data and occurrence of tachyarrhythmias and compared to random intervals without events (controls).

2.4. Home monitoring
2.4.1. Home monitoring system
During HM surveillance, medical and technical data from the implanted device are sent to a modified mobile phone, the Cardio Messenger. This device transmits the data via a mobile phone network to the HM Service Center (BIOTRONIK GmbH & Co. KG, Germany). There, the data are put into an easily accessible form and can then be viewed by a physician online via the Internet on a secure website. Special event messages will reach the physician by fax, SMS or email. Trend messages containing most parameters that are measurable with the device will be transmitted on a daily basis. These parameters include device and battery status, pacing impedances, bradycardia, tachycardia and CRT statistics, mean heart rates, patient activity, heart rate variability and current programming of the device.

Event messages are sent immediately after termination of the respective episode. Event messages include time and duration of the episode, initial detection zone, decision of the supraventricular tachycardia discrimination algorithm, PP and RR values at detection and termination, delivered therapy details, as well as an uncompressed three-channel intracardiac electrogram including all marker channels for 9-30 s prior to detection and 4-14 s prior to termination (mean total length 30 s). Thus, the transmitted data enables a physician to improve the monitoring of a patient's health condition, heart rhythm and the correct functioning of the device. In case of an emergency or any type of medical complaints, the patient is instructed to contact a physician immediately, as the HM Service is not an emergency information system.

2.5. Data analysis
A Central Monitoring Unit located at the Herzzentrum Leipzig (Germany) and consisting of one physician and two specially trained nurses will perform all analyses of the HM data. Trend messages will be analysed for distinct visible trends in patient activity and number of premature ventricular complexes per hour at least once per week, event messages will be analysed on a daily basis.

2.6. Intervention rules
Actions will be triggered after specified events (see Table 6). All such events have to be reported by the Central Monitoring Unit to the corresponding clinic within 1 h after detection. Patient contact will be performed by the attending physician as a standardised telephone questionnaire on the same day. There will be no uniformed predefined approach to the triggered event, however the attending physician will decide on any action triggered by the event, based on European guidelines. Although this will result in different managements for the same triggered event between various centres, it should reflect the real daily decision making and management of patients with heart failure. Actions initiated by the physician may include consultation by telephone, advising the patient to visit a general practitioner, or initiation of an additional follow up at the clinic. Feedback to the Central Monitoring Unit concerning the patient call has to be given within 48 h after the initial message. If no feedback is given, the message will be sent again. Nurse-led HF management is not included in the trial.


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  		Table 6 Intervention triggers

 
2.7. Committees
2.7.1. Steering committee
This committee is responsible for developing and monitoring the implementation of the protocol, as well as a re-evaluation of the intervention triggers if required. The committee is supported by the study manager and is responsible for ensuring timely publication of the results.

2.7.2. Adverse event and endpoint committee
This committee is responsible for classifying all events that could potentially contribute to an endpoint or adverse event. Events will be adjudicated in a blinded fashion. The committee will classify the reason for hospitalisations and the mode of death as either related or not related to worsening of heart failure. Doctor's letters and autopsy reports will be sought where relevant.

2.8. Randomisation
Randomisation is performed through a centralised, concealed process implemented by the sponsor. Stratification is done by centre, with variable and randomised block length.

2.9. Statistics
2.9.1. Statistical power
IN-TIME is designed to test the study hypotheses with a conventional two-sided {alpha} value of 0.05 and a statistical power (1–β) of 80%. Event rates are based on the estimated event rates of the trials CHARM [19,20], PROSPECT [17], and REVERSE [18]. A rate of 70% patients with improved or unchanged clinical status was thus estimated for the control group. Including a dropout rate of 5% during the run-in phase of the study, and a number of 620 enrolled patients, the study will be powered to detect a 10% increase of improved or unchanged clinical status from 70 to 80%, as defined above.

Although some telecare studies, e.g. COACH [15], have experienced a slight increase of short hospitalisations in the intervention group due to early interventions, this increase is not accounted for in this calculation, as only hospitalisations due to worsening heart failure are measured for the primary endpoint, and HM is expected to exchange these with outpatient visits or short hospitalisations due to reasons that might lead to worsening heart failure.

2.9.2. Statistical analysis plan
The statistical analysis for the primary outcome will use Pearson's C2 test. The statistical analysis for time to event outcomes will be performed using the log rank test.

For metric data sets, the mean values, standard deviation, median, maximum and minimum, as well as the 95% confidence interval will be stated. For categorical data, absolute and relative frequencies are determined, and the exact 95% confidence interval calculated. A binomial test will be performed in the context of a confirmatory analysis of relative frequencies. A t-test will be performed in the context of a confirmatory analysis of metric data. If a Kolmogorov-Smirnov test shows that there is no normal distribution, a non-parametric Wilcoxon test or, for the interindividual comparison of two data sets, a Mann-Whitney U-test will be performed. In case of multiple analyses for a special problem, the significance level will be adjusted with the Bonferroni-Holm method. The exploratory endpoint considering potentially important predictive factors will be done by discriminant analysis. For all hypotheses, a significance level of p=0.05 is considered statistically significant.

2.10. Timelines
The first patient was randomised in July 2007, at the time of writing 166 patients have been randomised. Recruitment is expected to complete in July 2009 and the study should close in summer 2010.


   3. Summary
Top
 Abstract
 1. Introduction
 2. Methods
 3. Summary
References
 
The IN-TIME study is a large, multicentre, international, randomised trial analysing the impact of a regular HM evaluation on the clinical status and outcome of heart failure patients. The study hypothesis will be evaluated based on the composite endpoint introduced by Milton Packer in 2001, the Packer Score [16]. This score combines mortality, heart failure hospitalisation, NYHA classification and a patient self assessment as a last observation carried forward analysis. In addition, based on the gathered HM data the investigators will try to introduce a composite reliable predictor of decompensation and hospitalisation in patients with congestive heart failure. The goal of the study is to improve clinical management and outcome in patients with heart failure.


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Summary
 References
 

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