Trial Review

The ANZCTR website will be unavailable from 1pm until 3pm (AEDT) on Wednesday the 30th of October for website maintenance. Please be sure to log out of the system in order to avoid any loss of data.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR


Registration number
ACTRN12624001168549
Ethics application status
Approved
Date submitted
21/08/2024
Date registered
25/09/2024
Date last updated
25/09/2024
Date data sharing statement initially provided
25/09/2024
Type of registration
Prospectively registered

Titles & IDs
Public title
Digital Technologies for Stroke Prevention Trial (DIGITS Trial)
Scientific title
Digital technologies for stroke prevention: a randomised controlled trial evaluating the effectiveness of blood pressure reduction in individuals aged 35 years or older diagnosed with TIA or minor stroke
Secondary ID [1] 312793 0
Nil known
Universal Trial Number (UTN)
Trial acronym
DIGITS
Linked study record

Health condition
Health condition(s) or problem(s) studied:
stroke secondary prevention 334854 0
Condition category
Condition code
Stroke 331408 331408 0 0
Ischaemic

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
The Intervention will be a combination of the two digital tools:
The Intervention will be a complementary use of the two digital tools to provide personalised recommendations on secondary stroke prevention and support their implementation:

(1) The PreventS-MD web app for clinicians (accessible through service-owned computers or tablets via a dedicated URL for the lifetime of the study), now referred to as a "web-app".
(2) The Stroke Riskometer mobile-app for patients (free to download on smartphones or tablets for Android and iOS via Google Play and Apple Store, respectively) now referred to as "mobile-app”.

These digital tools will be used sequentially. The web-app will be used by a healthcare professional to collect information about stroke risk factors, calculate stroke risk, and compose additional discharge summary that include tailored recommendations and explanation graphs. Personal nearest goals for the patient's health behaviour change will be optionally set using the PreventS-MD Goal-setting feature. The same information will be transferred via QR code to the patient’s mobile-app, for use by the patient post-discharge to follow these recommendations, including goal setting and medication reminders.

(1) The PreventS-MD web app:
The PreventS-MD web-app is built on the same core stroke risk assessment algorithm as the Stroke Riskometer mobile-app but is designed to be used by healthcare providers in conjunction with existing electronic patient management systems of outpatient clinics and hospitals and expanded by several additional features. Examples of stroke risk factors that will be used for the risk assessment algorithm are age, sex, ethnicity, smoking history, alcohol consumption, fruit and vegetable intake, physical activity, lipid and glucose levels, and medical history.
At baseline, clinicians will complete the assessment using the Prevents-MD web app. Stroke Clinical Nurse or Stroke Physician will deliver the intervention. They will then have a consultation with participants to review the summary and provide necessary recommendations. A one-time 15–20-minute session is required to complete the Prevents-MD assessment and review the recommendations with the participant. At least two weeks before commencing the data collections all clinicians will receive training on the overview of the trial and the use of the web app. The training will take about two hours, with an additional one-hour mock session arranged. The Primary Investigator, Trial Manager, Assistant Manager, and Technical Support Team will present the relevant sections. The training will be delivered both in person and online (based on preference and availability of the clinicians). All sessions will be recorded, and the links will be shared via the study’s Microsoft Teams channel. These recordings, along with other materials such as study protocols and task checklists, will be available for review.
After the assessment is completed, the web-app algorithm calculates both the absolute and relative 5- and 10-year risk of stroke, generates a comprehensive conclusion, and suggests recommendations on controlling the revealed risk factors. The clinician can easily compose the final summary by selecting necessary recommendations and graphs. Goal-setting options based on the assessments will be discussed with patients to motivate adherence to these recommendations.
Goal-setting options based on the assessments will be discussed with patients by clinicians at baseline to motivate adherence to the given recommendations. The same information will be transferred via QR code to the patient’s Riskometer mobile app, for use by the participant post-discharge to follow these recommendations, including goal setting and medication reminders.
If the intervention gets delivered before the participant gets discharged from the hospital it will be face-to-face. If the participant gets discharged, the clinician will deliver the intervention over the phone.
Two examples of recommendations that the clinician can select to be given to the participants below:
A) Smoking:
Smoking cigarettes, pipes, or cigars increases your risk of heart attack and stroke by up to 60%. The longer a person is a smoker, the greater their risk of having a stroke and heart attack.
Smoking electronic cigarettes (vaping) also significantly increases the risk of stroke and heart attack, compared to non-smokers, and does not help people quit smoking.
Smoking narrows and hardens the blood vessels which carry blood throughout the body. This reduces blood flow and makes the blood more likely to clot. Smoking also contributes to brain aneurysms which are where the wall of a blood vessel is damaged, and it stretches out to form a balloon filled with blood. An aneurysm can burst and cause internal bleeding.
Passive/second-hand smoking also increases the chances of having a stroke.
If you stop smoking today, the risk of stroke and heart attack due to smoking will begin to drop immediately and after about 5 years your risk of stroke and heart attack as the result of smoking will virtually disappear.
There are various methods of quitting smoking and advice, and support is available from you doctor and smoking cessation services.
B) Sedentary lifestyle:
Adequate physical activity will reduce your risk of stroke and also increase your physical fitness and emotional wellness. Adequate physical activity usually means moderate activity for 30-45 minutes, at least 4 times a week for adults and every day for children. Moderate activity is activity that makes you slightly warm and a little out of breath.
Good examples of moderate activity are brisk walking, jogging, bicycling, swimming, and gardening. Importantly, physical activity must fit into your daily routine and be pleasant so that you enjoy doing it regularly.
The key is to exercise regularly, however exercise does not have to be very strenuous or time consuming to be effective. For example, the health benefits of brisk walking are only slightly less than the benefits of jogging. If you have any health conditions you should consult your treating doctor before starting or changing your physical activity.


(2) The Stroke Riskometer mobile-app:
The Stroke Riskometer App is an evidence-based app that assesses an individual’s risk of stroke, based on user input on demographic and risk factor information. The risk factors are similar to the web-app and the intervention will be focused on lifestyle and medication adherence. On completion of the assessment, the App provides information on the pertinent risk factors identified for that individual, information in the management of these risk factors (including videos from relevant experts), options for goal setting and tracking lifestyle behaviours, medication reminders and other self-nominated reminders, (e.g., going for a walk), and information about stroke (signs, and actions to take).
The app may be used for both the primary and secondary prevention of stroke. The app was developed and validated by Feigin and Krishnamurthi et.al. at the Auckland University of Technology (AUT) in collaboration with national and international experts, non-government organisations (NGOs), international researchers and community groups. The App’s stroke risk calculation algorithm was validated against the established Framingham Stroke Risk Score and Stroke and found to have comparable stroke risk prediction. The app also incorporates several evidence-based tools to promote behaviour change aligned with internationally recognised stroke prevention guidelines, including provision of absolute and relative risk of stroke; personalised risk factor profile and their management; goal setting and notifications to engage in behaviour modification; and information on stroke risk factors and warning signs; Face, Arm, Speech, Time (FAST).
After the initial consultation using the web-app, clinicians will encourage participants to download and use the Stroke Riskometer App in their own time, etc. Personal nearest goals for the patient's health behaviour change will be optionally set using the PreventS-MD Goal-setting feature. The same information will be transferred via QR code to the patient’s mobile-app, for use by the patient post-discharge to follow these recommendations, including goal setting and medication reminders. The unblinded community support Research Assistants who will be trained on the use Stroke Riskometer app, will contact IG participants to support with the installation and troubleshooting of technical issues.
The frequency and duration of engagement with the app will vary depending on the individual. At the 12-month follow-up, participants will complete the System Usability Scale (SUS) and be asked about the frequency of app usage over the last 3 months, as well as the average length of time spent using health apps per week (<30 min, 30-60 min, >60 min, >120 min).
Adherence to the use of the app will be monitored solely through participants' self-reports via surveys. No monitoring data will be available from app analytics.
Intervention code [1] 329323 0
Prevention
Comparator / control treatment
At baseline participants in the USUAL CARE GROUP (UCG) will be informed of their group assignment post randomisation. They will receive the usual hospital discharge summary package and their usual follow-up medical care by their doctor. During the study if baseline physical measurements are required (such as blood pressure, blood glucose, height, and weight), a home visit by a study researcher will be arranged. UCG participants will receive telephone assessments at 3, 9 and 12 months, and a face-to-face assessment at 6 months post randomisation. The 6-month assessment will take place in- person, as the researcher will do a measure of weight and blood pressure. Blood cholesterol and glucose levels will be tested using a finger prick test where a small amount of blood will be collected and tested using a blood test machine. UCG participants will not be informed about the INTERVENTION GROUP (IG) intervention. At the end of their last assessment (at 12 months), the researcher will offer them an information package if they wish to receive one. This package will include educational materials and guidelines on ways to reduce the risk of stroke. Note, the whole intervention cannot be provided to UCG participants as it needs a clinicians input for the PreventS-MD.
Control group
Active

Outcomes
Primary outcome [1] 339161 0
Change in systolic blood pressure
Timepoint [1] 339161 0
At baseline and 6-months post randomisation (plus 4 weeks or minus 2 weeks)
Secondary outcome [1] 438830 0
Stroke risk (5-year absolute)
Timepoint [1] 438830 0
At baseline, 6- and 12- months post-randomisation
Secondary outcome [2] 438831 0
Change in LS7 scores for individual behavioural risk factors (diet, PA, smoking)
Timepoint [2] 438831 0
At baseline, 3-, 6- 9- and 12-months post-randomisation compared to Baseline
Secondary outcome [3] 438832 0
Change in proportion of participants in ‘high’ to ‘low’ risk on LS7
Timepoint [3] 438832 0
At baseline and 6-months post randomisation
Secondary outcome [4] 438833 0
Changes total-cholesterol- to- HDL ratio
Timepoint [4] 438833 0
At baseline and 6-months post randomisation
Secondary outcome [5] 438834 0
Stroke awareness
Timepoint [5] 438834 0
At baseline, 6- and 12-months post randomisation
Secondary outcome [6] 438835 0
Health-related quality of life
Timepoint [6] 438835 0
At baseline, 6- and 12-months post randomisation
Secondary outcome [7] 438836 0
Cognitive assessment score
Timepoint [7] 438836 0
At baseline, 6- and 12-months post randomisation
Secondary outcome [8] 438838 0
Medication adherence
Timepoint [8] 438838 0
At baseline, 3-, 6-, 9- and 12-months.
Secondary outcome [9] 438839 0
CVD adverse outcomes (fatal and nonfatal stroke, TIA, myocardial infarction and heart failure, death attributable to CVD and all-cause mortality)
This will be assessed as a composite outcome.
Timepoint [9] 438839 0
At baseline, 3-, 6-, 9- and 12-months post randomisation
Secondary outcome [10] 438840 0
Healthcare and community service costs: National Minimum Dataset (NMDS) (New Zealand)
This will be assessed as a composite outcome.
Timepoint [10] 438840 0
At 3-, 6-, 9- and 12- months post-randomisation post randomisation
Secondary outcome [11] 438841 0
Productivity level NMDS (NZ)
Timepoint [11] 438841 0
At 3-, 6-, 9- and 12- months post randomisation.
Secondary outcome [12] 438842 0
Implementation evaluation of PreventS-MD and the Stroke Riskometer App
Timepoint [12] 438842 0
At 6- months post randomisation
Secondary outcome [13] 439501 0
Alcohol/ drug use
Timepoint [13] 439501 0
At baseline, 3-, 6- 9- and 12- months post-randomisation compared to Baseline
Secondary outcome [14] 439508 0
Changes HDL level
Timepoint [14] 439508 0
At baseline and 6-months post randomisation
Secondary outcome [15] 439549 0
Stroke risk (10-year absolute)
Timepoint [15] 439549 0
At baseline, 6- and 12- months post-randomisation
Secondary outcome [16] 439550 0
Stroke risk (5-year relative)
Timepoint [16] 439550 0
At baseline, 6- and 12- months post-randomisation
Secondary outcome [17] 439551 0
Stroke risk (10-year relative)
Timepoint [17] 439551 0
At baseline, 6- and 12- months post-randomisation
Secondary outcome [18] 439552 0
Change in proportion of participants in ‘intermediate’ to ‘low’ risk on LS7
Timepoint [18] 439552 0
At baseline and 6-months post randomisation
Secondary outcome [19] 439553 0
Depression assessment
Timepoint [19] 439553 0
At baseline, 6-, 12-months post-randomisation
Secondary outcome [20] 439554 0
Anxiety assessments
Timepoint [20] 439554 0
At baseline, 6-, 12-months post-randomisation

Eligibility
Key inclusion criteria
1. People aged 35-85 years old diagnosed with TIA or minor stroke (including recurrent events) with ambulant modified Rankin Scale (mRS) score 0-3 at discharge or independent in activities of daily living in the past 90 days.
2. Admitted to one of the two Auckland based hospitals or identified via outpatient clinics or primary care for minor stroke or TIA.
3. Can converse in English.
4. Systolic blood pressure greater than or equal to 130 mmHg, or greater than or equal to 120 mmHg if on blood pressure medications.
5. Has access to a Smartphone or Smart Device (iPad, Tablet).
6. Provides written informed consent.
Minimum age
35 Years
Maximum age
85 Years
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
1. History of major stroke, subarachnoid haemorrhage or major myocardial infarction (verified through Clinical Portal medical records)
2. Life-threatening conditions with a life-expectancy less than 5 years.
3. Current (in the past year) significant clinical depression/anxiety measured by the Hospital Anxiety and Depression questionnaire (HADS) at a level greater than or equal to 14 in either or both the depression and anxiety domains (either in clinical records or at screening) OR psychiatric conditions (based on medical records).
4. History (past year) of alcohol or drug/ substance abuse.
5. Dependent on others (living in a rest-home/care facility).
6. Unable to have telephone assessments due to hearing difficulties.
7. Significant cognitive impairment or pre-existing diagnosis of dementia, e.g., at screening (T-MoCA less than 15). People with less than 12 years education and those for whom English is not the first language will score an additional point for each circumstance.
8. Participation in another current RCT or major research study.

Study design
Purpose of the study
Prevention
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
The study manager will inform the study nurse of the allocation of patients in their hospital. The nurse will then receive a REDCap link to complete the PreventS assessment.
The randomisation form in REDCap will be a hidden form, visible only to the study managers and data manager. The community research assistants will not have access to the randomisation form.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Eligible patients will be randomly assigned to either IG or UG using a computer-generated, blocked stratified randomisation procedure performed by the Biostatistician.
Masking / blinding
Blinded (masking used)
Who is / are masked / blinded?


The people assessing the outcomes
Intervention assignment
Parallel
Other design features
Phase
Not Applicable
Type of endpoint/s
Statistical methods / analysis

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
1/10/2024
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
360
Accrual to date
Final
Recruitment outside Australia
Country [1] 26521 0
New Zealand
State/province [1] 26521 0

Funding & Sponsors
Funding source category [1] 317224 0
Government body
Name [1] 317224 0
The Health Research Council of New Zealand (HRC)
Country [1] 317224 0
New Zealand
Primary sponsor type
University
Name
Auckland University of Technology
Address
Country
New Zealand
Secondary sponsor category [1] 319499 0
None
Name [1] 319499 0
Address [1] 319499 0
Country [1] 319499 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 315961 0
Northern B Health and Disability Ethics Committee 
Ethics committee address [1] 315961 0
Ethics committee country [1] 315961 0
New Zealand
Date submitted for ethics approval [1] 315961 0
23/04/2024
Approval date [1] 315961 0
11/06/2024
Ethics approval number [1] 315961 0
2024 EXP 20178
Ethics committee name [2] 315966 0
Auckland Health Research Ethics Committee
Ethics committee address [2] 315966 0
Ethics committee country [2] 315966 0
New Zealand
Date submitted for ethics approval [2] 315966 0
24/06/2024
Approval date [2] 315966 0
05/08/2024
Ethics approval number [2] 315966 0
24/202 Digital Technologies for Stroke Prevention Trial

Summary
Brief summary
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 136354 0
Prof Rita Krishnamurthi
Address 136354 0
National Institute for Stroke and Applied Neurosciences, School of Clinical Sciences, Faculty of Health and Environmental Sciences, Auckland University of Technology , 90 Akoranga Drive Northcote, Auckland 0627
Country 136354 0
New Zealand
Phone 136354 0
+64 21556071
Fax 136354 0
Email 136354 0
[email protected]
Contact person for public queries
Name 136355 0
Dr Shabnam Jalili-Moghaddam
Address 136355 0
National Institute for Stroke and Applied Neurosciences, School of Clinical Sciences, Faculty of Health and Environmental Sciences, Auckland University of Technology , 90 Akoranga Drive Northcote, Auckland 0627
Country 136355 0
New Zealand
Phone 136355 0
+64 0800947260
Fax 136355 0
Email 136355 0
[email protected]
Contact person for scientific queries
Name 136356 0
Prof Rita Krishnamurthi
Address 136356 0
National Institute for Stroke and Applied Neurosciences, School of Clinical Sciences, Faculty of Health and Environmental Sciences, Auckland University of Technology , 90 Akoranga Drive Northcote, Auckland 0627
Country 136356 0
New Zealand
Phone 136356 0
+64 21556071
Fax 136356 0
Email 136356 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
No/undecided IPD sharing reason/comment


What supporting documents are/will be available?




Results publications and other study-related documents

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

Documents added automatically
No additional documents have been identified.