AIIHPC REPORT

THE ROLE OF CONNECTED HEALTH IN THE DIAGNOSIS OF AUTONOMIC DYSFUNCTION IN CANCER

CLINICAL FELLOW:

Dr Brenda O’Connor1,2

SUPERVISOR:

Professor Declan Walsh1,2,3

AFFILIATIONS:

1. Our Lady’s Hospice & Care Services

2. School of Medicine & Medical Science, University College Dublin

3. School of Medicine, Trinity College Dublin

LAY SUMMARY

The Autonomic Nervous System regulates the “automatic” functions of the body such as blood pressure, heart rate, breathing, stomach function, temperature regulation and bladder function. When this system becomes unbalanced, it affects many body functions and can cause a variety of symptoms. These include tiredness, reduced appetite, weight loss, nausea, blackouts and falls.

Limited studies suggest that autonomic nervous system disturbance is common in advanced cancer. This disorder remains poorly understood. Causes may include both the cancer itself and chemotherapy. Assessment is complex, can only be undertaken in hospital and does not represent real life activities. Admission for this type of investigation is not desirable in seriously ill cancer patients. Modern, mobile medical devices may provide the solution.

This study investigates if mobile medical technology can effectively measure autonomic dysfunction in cancer. Participants wear 4 small medical devices for approximately 75 minutes. These record blood pressure, heart rate, temperature and sweat production both at rest and during a series of activities. The devices transmit wirelessly to a central computer for analysis.

The study is comprised of three stages:

Study A: Pilot study with healthy volunteers

Study B: Early stage cancer patients at St. Vincent’s Hospitals

Study C: Advanced cancer patients at Our Lady’s Hospice & Care Services

The acceptability of this device for participants, both practical and psychological is explored. On pilot end, a review of the study will take place. Where possible, adjustments will be made for any challenges encountered before patient recruitment.

It is hoped that this study will determine which one of these devices is most effective in measuring autonomic nervous system disturbance.


BACKGROUND

Cancer

Cancer is a high prevalence, high impact disorder that impairs function, mobility and social interaction. People with cancer experience multiple, fluctuating symptoms that are complex to measure and difficult to record.1 If the underlying cause of these symptoms can be characterised, quality of life can be enhanced through more targeted treatment strategies.1 Dysfunction of the autonomic nervous system is a common disorder in cancer.

Autonomic Nervous System

The autonomic nervous system (ANS) is an involuntary nervous system which innervates every organ in the body.2 The ANS regulates important bodily functions which include blood pressure, heart rate, thermoregulation, respiration, gastrointestinal, bladder and sexual function.2 Limited studies report ANS dysfunction in 50-80% of advanced cancer patients.3-7

Autonomic Nervous System Dysfunction

Autonomic dysfunction predisposes patients to a number of symptoms which include fatigue, reduced appetite, weight loss, shortness of breath, blackouts, falls, and even sudden death.8 Autonomic dysfunction is an important prognostic indicator in cancer.6-8 Postulated causes include decreased physical activity, medications, chemotherapy, and paraneoplastic processes.6-8

The pathophysiology of autonomic dysfunction remains poorly understood. Ewing’s protocol has become the gold standard objective assessment of autonomic dysfunction.7,9,10 This protocol measure sympathetic and parasympathetic activity by analysing end organ responses to a series of physiological stressors. The assessment takes approximately 30 minutes. This assessment is cumbersome, challenging and can only be carried out in a clinical setting. Inpatient admission for this investigation is not desirable in seriously ill patients with advanced cancer and acts as a barrier to adequate treatment of this disorder. Further studies on autonomic dysfunction must address novel methods to provide a reliable proxy for current standardised tests. Advances in wireless medical technology may provide the solution.

Connected Health and Autonomic Dysfunction

Autonomic dysfunction remains under-researched, poorly understood and thus under-diagnosed. New low-cost, low-power wearable sensors for long-term measurement of cardiovascular, gastrointestinal and thermoregulatory functions could revolutionise autonomic dysfunction management. To date, these devices have not been applied in a clinical setting in cancer. Simplified investigations could negate the need for inpatient care. Larger populations could be studied in real life settings.

This study investigates the feasibility and user interface of prototype wireless technology in the measurement of ANS dysfunction in cancer. Parasympathetic and sympathetic autonomic function is assessed by cardiovascular and thermoregulatory responses to physiological stressors:

a.  Parasympathetic function: Cardiovascular (heart rate variability)

b.  Sympathetic function: Cardiovascular (blood pressure variability) and thermoregulatory (sweat production and core temperature alteration)

OBJECTIVES

Primary

1.  Conduct a feasibility study to examine if wireless technology can objectively measure autonomic dysfunction in cancer

a.  Cardiovascular Autonomic Function:

i.  Electrocardiography (ECG)

ii.  Blood Pressure (BP) Monitor

iii. Stroke Volume Sensor

b.  Thermoregulatory Function

i.  Core Temperature Monitor

ii.  Galvanic Skin Response (GSR) Sensor

2.  Determine the wireless device user interface with:

a.  Volunteer

b.  Patient

c.  Researcher

Secondary

1.  Assess the prevalence of autonomic dysfunction in participants with:

a.  Non-metastatic cancer

b.  Metastatic cancer

2.  Correlate subjective symptom reports with objective device results

METHODS

Study Design

This is a prospective observational feasibility study. Autonomic function is analysed in three populations:

Study A: Pilot with healthy volunteers (physicians and nurses in clinical practice)

Study B: Non-metastatic cancer patients pre-chemotherapy

Study C: Metastatic cancer patients

Participant Selection

Participants in Study A are healthy staff volunteers at Our Lady’s Hospice & Care Services (OLH&CS). Study B participants will be recruited in the Oncology Day wards at St Vincent’s Hospital Group. Study C participants will be recruited from the out-patient palliative care services at OLH&CS.

Patients are recruited if they have a loco-regional or metastatic solid tumour diagnosis, are aged ≥18 years, have an Eastern Cooperative Oncology Group (ECOG) performance status of ≤ 2, can lie supine with 1 supporting pillow and can stand /mobilise unaided.

Exclusion criteria are: established diagnosis of diabetes mellitus, dementia or delirium, a clinical diagnosis of dehydration, the presence of a pacemaker or an Implantable Cardiac Defibrillator (ICD), an abnormal resting electrocardiograph (ECG), oxygen saturation of less than 90% on room air, the need for continuous oxygen use, or a life expectancy of <7 days.

Research Approval

Ethical approval was granted by St Vincent’s Healthcare Group Ethics and Medical Research Committee. Approval to conduct research at St Vincent’s Hospital Group was also granted by the Medical Board and the Data Manager.

Approval to enrol staff and patients was granted by OLH&CS Education and Research Committee.

Study Devices

This study is undertaken with our technology collaborators Tyndall National Institute (TNI) in Cork. Several collaborative meetings were held with the chief project engineer to discuss the features of the technology. The existing technology needed adjustment to maximise comfort and utility for the advanced cancer population. TNI conducted further research to develop the most suitable design. Alterations to the research protocol were required based on their device refinement. Prototype technology has since been reviewed by the researcher and feedback given to technology partners for further adjustment.

Four wireless devices have been developed to measure the multifaceted components of cardiovascular (cardiac output, heart rate and blood pressure variability) and thermoregulatory (core temperature and sweat production) autonomic function. These devices are applied to the participant for the study duration:

1.  Thoracic Sensor Belt: Measures electrocardiography (ECG), core temperature and cardiac output

2.  Wrist Band: Galvanic Skin Response (GSR) sensor measures sweat production

3.  Arm Device: Wireless blood pressure (BP) monitor

4.  Ankle Sensor: Wireless inertial measurement unit to correlate measurements with activity

Each device relays encrypted data via Bluetooth to a central pre-programmed base station positioned within 10 metres of the participant. Please see appendix 1 for a detailed description.

A number of unforeseen challenges resulted in full technology development and deployment being delayed by several months. These include TNI resource constraints (personnel), and technological challenges related to device interoperability. A key component of this technology is the need for each device to communicate with all other devices and the central base station. Final design testing is in progress and it is hoped that recruitment will begin in December 2014.

Data Collection

An initial interview establishes demographic details, current medications, caffeine/nicotine intake and the participant’s autonomic symptom profile.

Objective autonomic function tests are conducted using a modified Ewing’s protocol suitable for cancer patients.4,7,10

Modified Ewing’s Classification System of Autonomic Dysfunction10

The presence or absence of autonomic dysfunction is detected by an assessment protocol which measures end organ responses to physiological stressors. SV and GSR are continuously recorded throughout the test period. ECG and blood pressure are monitored during parasympathetic and sympathetic tests:

PARASYMPATHETIC

1.  Heart Rate Response to Deep Breathing (Normal Value ≥15 beats/min)

Maximum and minimum heart rate during the first 3 successive breathing cycles is calculated from the shortest and longest R-R interval. The mean of the differences between the maximum and minimum R-R intervals during the three successive cycles is calculated.

2.  Heart Rate Response to Valsalva Manoeuvre (Normal Value ≥ 1.21)

Participants are requested to blow into a mouthpiece at a pressure of 40mmHg for 15 seconds. This is repeated 3 times and the best/maximum response is used for analysis. A minimum of 30mmHg for 12 seconds is required for inclusion. The heart rate normally increases during the manoeuvre followed by a rebound bradycardia after release. Heart rate response is calculated as the ratio of the maximum R-R interval shortly after to the minimum R-R during the manoeuvre.

3.  Heart Rate Response to Standing (Normal Value ≥1.04)

Participants are requested to stand quickly from the supine position. Normally an immediate increase in heart rate occurs, maximal at around the 15th beat, followed by a relative bradycardia, maximal around the 30th beat. Heart rate response is measured as the ratio of the maximum R-R interval at the 30th beat, to the minimum R-R interval at the 15th beat.

SYMPATHETIC

4.  Blood Pressure Response to Standing (Normal: Systolic drop ≤10mmHg)

This assessment takes place simultaneously with the Heart Rate Response to Standing. BP on the left arm is measured after the patient has been lying supine for 5 minutes. On standing from the supine position, BP is measured every 1 minute to a total of 5 minutes. The difference in systolic and diastolic blood pressures is taken as the measure of postural blood pressure change.

On completion of these assessments, a questionnaire examines the acceptability of wireless device use in participants.

Data Analysis

1.  Ewing’s existing classification system will be used to categorise autonomic function

i.  Normal: All tests normal or one borderline

ii.  Early dysfunction: One of three heart rate tests abnormal or two borderline

iii.  Definite dysfunction: Two or more heart rate tests abnormal

iv.  Severe dysfunction: Two or more heart rate tests abnormal plus one BP test abnormal

v.  Atypical pattern: Any other combination of abnormal tests

TEST / NORMAL / BORDERLINE / ABNORMAL
Heart Rate Response
Valsalva Manoeuvre / ≥1.21 / ≤1.20
Deep Breathing / ≥15 beats/min / 11-14 beats/ min / ≤10 beats/ min
Standing / ≥1.04 / 1.01-1.03 / ≤1.00
Blood Pressure Response
Standing / ≥ 10mm Hg / 11-29mm Hg / ≤30mm Hg

2.  Data in metastatic and non-metastatic cancer patients is compared to that of healthy volunteers

3.  Objective autonomic function results are correlated with subjective symptom reports

4.  The acceptability of wireless monitor use in participants is assessed

i.  Practical

ii.  Psychosocial

FINDINGS

Due to the significant delays outlined above, this study is yet to be completed. Results will be submitted as soon as they are available.

IMPLICATIONS FOR PRACTICE

This research is diagnostic in nature. Study outcomes will define effective sensor streams to measure autonomic dysfunction in this population with a view to replacing existing cumbersome measures.

We will gain further insight into modern non-invasive techniques to screen for and monitor cancer related autonomic dysfunction. Effective technology will facilitate the investigation of predisposing factors or associated symptom profiles. This will enable targeted treatment and close supervision of effect.

PLANS FOR DISSEMINATION/OUTPUT FROM STUDY

Research outcomes will be disseminated to the academic community through presentation at national and international conferences, and publication in peer reviewed palliative medicine and oncology journals. Results will be disseminated locally at OLH&CS Palliative Medicine Grand Rounds.

REFERENCES

1.  Fainsinger R, Nekolaichuk C, Lawlor PG, Neumann C, Hanson J, Vigano A. A mulicenter study of the revised Edmonton Staging System for classifying pain in advanced cancer patients. J Pain Symptom Manage. 2005;29:224-37

2.  Gabella G. Autonomic Nervous System. eLS: John Wiley & Sons, Ltd; 2001

3.  Bruera E, Chadwick S, Fox R, Hanson J, MacDonald N. Study of cardiovascular autonomic insufficiency in patients with advanced cancer. Cancer Treat Rep. 1986;70:1383-7

4.  Walsh D, Nelson K. Autonomic nervous system dysfunction in advanced cancer. Support Care Cancer. 2002;10:523-8

5.  Strasser F, Palmer JL, Schover LR, Yusuf SW, Pisters K, Vassilopoulou-Sellin R, et al. The impact of hypogonadism and autonomic dysfunction on fatigue, emotional function, and sexual desire in male patients with advanced cancer: a pilot study. Cancer. 2006 Dec 15;107(12):2949-57

6.  Fadul N, Strasser F, Palmer JL, Yusuf SW, Guo Y, Li Z, et al. The association between autonomic dysfunction and survival in male patients with advanced cancer: a preliminary report. J Pain Symptom Manage. 2010 Feb;39(2):283-90

7.  Stone CA, Kenny RA, Nolan B, Lawlor PG. Autonomic dysfunction in patients with advanced cancer; prevalence, clinical correlates and challenges in assessment. BMC palliative care. 2012;11:3

8.  Chiang JK, Koo M, Kuo TB, Fu CH. Association between cardiovascular autonomic functions and time to death in patients with terminal hepatocellular carcinoma. J Pain Symptom Manage. 2010 Apr;39(4):673-9

9.  Guo Y, Palmer JL, Strasser F, Yusuf SW, Bruera E. Heart rate variability as a measure of autonomic dysfunction in men with advanced cancer. European journal of cancer care. 2013 Apr 30.

10. Ewing DJ, Martyn DN, Young RJ et al. The value of cardiovascular autonomic function tests: 10 years experience in diabetes. Diabetes Care. 1985; 8(5): 491-498