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Trial registered on ANZCTR


Registration number
ACTRN12615001023549
Ethics application status
Approved
Date submitted
11/09/2015
Date registered
1/10/2015
Date last updated
1/11/2017
Type of registration
Prospectively registered

Titles & IDs
Public title
Using thermal clothing to reduce heart failure morbidity during winter: a randomised controlled trial
Scientific title
Efficacy of thermal clothing in reducing hospitalisations during winter for heart failure patients
Secondary ID [1] 287445 0
Nil known
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Heart Failure 296160 0
Condition category
Condition code
Cardiovascular 296444 296444 0 0
Other cardiovascular diseases

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
Thermal clothing: two thermal tops, two pairs of thermal socks, one thermal hat.

A large display indoor temperature monitor to be placed inside the home.

A single A4 advisory sheet on when to wear the thermals, with the recommendation to wear the thermals in the following circumstances:
1. If the indoor temperature is below 18.0 degrees C when you wake up, then wear the thermals under your normal clothes during the day.
2. If the indoor temperature is below 18.0 degrees C degrees just before you go to bed, then wear the thermals in bed.
3. If you are going outside for 10 minutes or more and the outdoor temperature is below 18.0 degrees C, then wear the thermals under your normal clothes.

The intervention period is from 1 May 2016 to 30 September 2016 (5 months).

Adherence to the thermals will be monitored using a self-completed clothing diary for one week during July 2016.
Intervention code [1] 292816 0
Treatment: Other
Intervention code [2] 292886 0
Lifestyle
Comparator / control treatment
No extra clothing (standard care) and no advice about the dangers of cold bar what the participants will read in the participant information sheet.
Control group
Active

Outcomes
Primary outcome [1] 296063 0
Number of days in hospital using combined data on private hospital admissions from Medicare data and public hospital admissions from the Queensland Hospital Admitted Patient Data Collection.
Timepoint [1] 296063 0
1 May 2016 to 30 September 2016
Secondary outcome [1] 317438 0
Quality of life using EQ-5D
Timepoint [1] 317438 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)
Secondary outcome [2] 317439 0
Sleep quality using the Pittsburgh sleep questionnaire
Timepoint [2] 317439 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)
Secondary outcome [3] 317440 0
Number of GP visits during winter using Medicare data
Timepoint [3] 317440 0
1 May 2016 to 30 September 2016
Secondary outcome [4] 317441 0
Overall healthcare usage using a combination of: i) Medicare data, ii) the Queensland Emergency Department Information System, and iii) the Queensland Hospital Admitted Patient Data Collection
Timepoint [4] 317441 0
1 May 2016 to 30 September 2016
Secondary outcome [5] 317442 0
Systolic blood pressure using sphygmomanometer
Timepoint [5] 317442 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)
Secondary outcome [6] 317443 0
Blood viscosity by blood sample analysis
Timepoint [6] 317443 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)
Secondary outcome [7] 317637 0
Cholesterol by blood sample analysis
Timepoint [7] 317637 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)
Secondary outcome [8] 317638 0
Fibrinogen by blood sample analysis
Timepoint [8] 317638 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)
Secondary outcome [9] 317639 0
c-reactive protein by blood sample analysis
Timepoint [9] 317639 0
Midwinter (July 2016) and the end of winter (Sep/Oct 2016)

Eligibility
Key inclusion criteria
Have a diagnosis of either systolic or diastolic heart failure
Minimum age
50 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
1. Are pregnant (highly unlikely).
2. A serious co-morbidity (e.g., cancer) or a serious physical impairment that prevents the participant from dressing themselves.
3. Live in a residential care facility.
4. Are unable to give informed consent.
5. Were involved in our previous pilot.

Study design
Purpose of the study
Treatment
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Patients will be identified and approached in Dr Platts’ cardiology clinic and cardiology wards at The Prince Charles Hospital. The approach and consent will be made by a research nurse.

The nurse will first complete the informed consent procedure and baseline questionnaire using a computer tablet. At this point they will not know the treatment allocation.

The random allocation will occur once the nurse reaches the end of the baseline questions and clicks a button. Treatment allocation will be held using the REDCap (Research Electronic Data Capture) data management software.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
We aim to recruit 120 patients who will be randomised to receive the thermals or not. A randomisation list will be created using the R software (www.r-project.org). The list will be in randomly permuted blocks in a 1:1 ratio using the "blockrand" function. We will stratify by recruitment location (ward/clinic) because of the higher risk of subsequent events for ward patients.

The randomisation list will be created by the study statistician, and only they will be able to view the randomised groups.
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Parallel
Other design features
Phase
Phase 3
Type of endpoint/s
Efficacy
Statistical methods / analysis
Data will be analysed using an intention-to-treat approach, so if a participant in the thermal group did not wear the thermals, they will be still be included in the final analysis as a member of the thermal group.

PRIMARY OUTCOME

We will compare the number of days in hospital between the two groups using the bias corrected bootstrap to create non-parametric 95% confidence intervals for the difference between the mean number of days in hospital between the two groups. A parametric analysis would be a Poisson regression model with a dependent variable of number of days and independent variable of treatment group. However, in the pilot study we could not use the Poisson model because the assumption of independence between days was violated.

To control for the differing lengths of observation times between participants we will divide each participants total number of days in hospital by their number of days under study. This is important because some participants may not be recruited until June.

SECONDARY OUTCOMES

We will compare the number of GP visits during winter using the same method as per the primary outcome. We will compare quality of life in midwinter and the end of winter using a mixed model with the quality of life score as the dependent variable, treatment group as the key independent variable, baseline quality of life as an independent variable and a random intercept to control for the within-participant correlation. This same analysis of covariance (ANCOVA) model will be used to compare sleep quality, blood pressures and cardiovascular risk factors.

SAMPLE SIZE

Sixty participants per group gives us an 80% power to detect a 40% reduction (effect size) in winter hospitalisation rates. This uses a Poisson regression model with a baseline rate of one hospitalisation per winter. We used a one-sided p-value of 5%. We used a one-sided test in order to reduce the sample size and save costs and time. Our focus is on the key decision to use thermals as a preventative measure rather than the hypothesis test. For this decision there is no difference between equivalence and thermals doing harm.

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
1/04/2016
Actual
5/04/2016
Date of last participant enrolment
Anticipated
31/05/2016
Actual
2/06/2016
Date of last data collection
Anticipated
Actual
30/09/2016
Sample size
Target
120
Accrual to date
Final
91
Recruitment in Australia
Recruitment state(s)
QLD
Recruitment hospital [1] 4333 0
The Prince Charles Hospital - Chermside
Recruitment postcode(s) [1] 10476 0
4032 - Chermside

Funding & Sponsors
Funding source category [1] 292023 0
Charities/Societies/Foundations
Name [1] 292023 0
The Heart Foundation
Country [1] 292023 0
Australia
Primary sponsor type
University
Name
Queensland University of Technology
Address
60 Musk Avenue, Kelvin Grove, Queensland 4059
Country
Australia
Secondary sponsor category [1] 290693 0
Hospital
Name [1] 290693 0
The Prince Charles Hospital
Address [1] 290693 0
627 Rode Road, Chermside, Queensland 4032
Country [1] 290693 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 293509 0
Human Research Ethics Committee Metro North Hospital and Health Service
Ethics committee address [1] 293509 0
The Prince Charles Hospital
Building 14
Rode Road, Chermside QLD 4032
Ethics committee country [1] 293509 0
Australia
Date submitted for ethics approval [1] 293509 0
Approval date [1] 293509 0
08/09/2015
Ethics approval number [1] 293509 0
HREC/15/QPCH/215

Summary
Brief summary
Winter is a surprisingly dangerous time in Australia with greatly increased rates of death and hospitalisation. Winter death rates are 47% higher for heart failure and 32% higher for hypertensive disease compared with summer. Warm countries like Australia have a far greater winter increase in morbidity and mortality than cold countries like Sweden. This is because many Australian homes are inadequately insulated or heated, with indoor temperatures in winter often below 18 degrees C. This cold exposure increases blood pressure and inflammatory factors, which increases the risk of an acute cardiovascular event.
Home insulation and heating have both been proven to improve cardiovascular health and wellbeing during winter. This study will test if personal insulation also improves cardiovascular health. Heart failure patients will be randomised to receive no intervention or a pack containing thermal tops, hats and socks, indoor temperature monitors, and advice on when to wear the thermals. Our primary hypothesis is that winter hospital admissions will be reduced, and we will also examine improvements in blood pressure, inflammatory factors, quality of life, sleep and personal insulation.
This will be the world’s largest study of the health benefits of personal insulation, and will build on our work with heart failure patients at The Prince Charles Hospital. Thermal clothes are a cheap and simple intervention that could greatly reduce winter morbidity and mortality across Australia.
Trial website
Trial related presentations / publications
Main results published: Barnett AG, Stewart I, Beevers A, et al Thermal clothing to reduce heart failure morbidity during winter: a randomised controlled trial. BMJ Open 2017;7:e017592. doi: 10.1136/bmjopen-2017-017592.

Trial data available on figshare: https://figshare.com/articles/Thermal_clothing_clinical_trial/4649231
Public notes
Attachments [1] 558 558 0 0
/AnzctrAttachments/369285-01_G_ThermalProtocol_v1_20150807.pdf

Contacts
Principal investigator
Name 60198 0
A/Prof Adrian Barnett
Address 60198 0
Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, Queensland 4059
Country 60198 0
Australia
Phone 60198 0
+61731386010
Fax 60198 0
Email 60198 0
[email protected]
Contact person for public queries
Name 60199 0
Adrian Barnett
Address 60199 0
Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, Queensland 4059
Country 60199 0
Australia
Phone 60199 0
+61731386010
Fax 60199 0
Email 60199 0
[email protected]
Contact person for scientific queries
Name 60200 0
Adrian Barnett
Address 60200 0
Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, Queensland 4059
Country 60200 0
Australia
Phone 60200 0
+61731386010
Fax 60200 0
Email 60200 0
[email protected]

No information has been provided regarding IPD availability


What supporting documents are/will be available?

Current supporting documents:


Updated to:
Doc. No.TypeCitationLinkEmailOther DetailsAttachment
23393 -999999  

Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
SourceTitleYear of PublicationDOI
EmbaseThermal clothing to reduce heart failure morbidity during winter: A randomised controlled trial.2017https://dx.doi.org/10.1136/bmjopen-2017-017592
N.B. These documents automatically identified may not have been verified by the study sponsor.