Stroke, Transient Ischemic Attack
Conditions
Keywords
SMARTWATCH
Brief summary
After a first stroke or transient ischemic attack (TIA), the risk of recurrence is high in the weeks and months following the initial event. There are several modifiable risk factors that can reduce this risk, such as blood pressure, diet, physical activity, and smoking. Many stroke patients (NIHSS \< 5) have a low daily step count during the early recovery period, despite a good functional prognosis. Active smartwatches provide real-time feedback, track progress, and set personalized walking goals, thereby boosting motivation and adherence to physical activity recommendations. The combination of advice provided by nurses and active behavioral coaching supported by a smartwatch, compared to passive monitoring, could significantly increase daily step counts over a 12-week period. The results of this research will help guide future large-scale secondary prevention strategies integrating digital health and structured nursing support.
Detailed description
To meet the study's objectives, 50 patients who have recently suffered a stroke or a transient ischemic attack (TIA) (\< 30 days) will be recruited at Brest University Hospital. Participation in this study will last 12 weeks. It consists of 3 visits, described below: =\> Visit #1: Enrollment (hospital) Enrollment will take place during a routine hospital visit. The investigator will obtain the patient's written consent. Randomization will then be performed to assign the patient to a group ("active" or "passive" watch). For all patients ("active" and "passive" watch groups): * Program led by nurses, conducted as part of routine care following a recent ischemic stroke or TIA (secondary prevention). * Issuance of a smartwatch and a smartphone * Data collection (sociodemographic information, medical history, current treatments, risk factors) * Questionnaires * Clinical examination, neurological examination, and blood draw. For patients in the "passive" smartwatch group: o The smartwatch will collect data passively, without notifications. For patients in the "active" smartwatch group: * Setting daily step goals and assessing potential obstacles * Scheduling regular calls (twice a week) for the duration of the study. * Visit #2: Phone call For all patients (both "active" and "passive" watch): * Phone contact to collect data on changes in risk factors and the occurrence of events of interest (stroke, TIA, and cardiovascular events). * Questionnaires * Visit #3: End of study (hospital) The end-of-study visit will take place at the hospital during a scheduled routine care appointment: * Assessment with a nurse as part of the secondary prevention program (routine care) * Data collection (risk factors) * Questionnaires * Clinical examination, neurological examination, and blood draw * Return of the smartwatch and smartphone
Interventions
OTHERSmartwatch-Guided Secondary Prevention after Stroke
Setting daily walking goals, assessing obstacles Regular phone calls (twice a week) to review progress, adjust goals, and provide support
Sponsors
University Hospital, Brest
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
NONE
Intervention model description
* A prospective, randomized, parallel-group, superiority trial with 1:1 allocation.. * Randomization: Computer-generated, stratified by baseline steps (\<4,000 vs ≥4,000) * Blinding: Due to the behavioral nature of the intervention, participants and nurses cannot be blinded. * Outcome assessors will remain blinded to treatment allocation. * A CONSORT flowchart will document the passage from screening → randomization → follow-up. → end of study * Baseline (B), weeks (W) 12: o Face-to-face consultation: B and W12: Nurse + Clinical study technician for all patients * W6: phone call to provide feedback and get the information * Behavior multicomponent strategies (2X/week) for the active arm (Clinical study technician watch or phone incentive/prompt)
Eligibility
Sex/Gender
ALL
Age
40 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
* Age ≤ 40-75 * Patients with recent minor ischemic stroke or TIA, initial NIHSS ≤5 (\< 30 days) * mRS ≤2 before stroke and on discharge * Patient with Wifi access (for data transmission) * Able to understand smartwatch instructions * Written informed consent * Ambulatory ≥10 meters without assistance and without walking aid * Expected to live at home during the study period.
Exclusion criteria
* Patients with transient neurological deficits resolving within one hour and normal brain imaging will be excluded * Not affiliated to social security * Patient under legal protection or deprived of liberty by a judicial or administrative decision * Patient whose follow-up will be impossible * Cognitive impairment interfering with participation (e.g., MoCA \<20). * Unstable cardiac conditions preventing walking goals. * Major visual or upper limb impairment preventing use of the smartwatch. * Life expectancy \<1 year. * Already highly active (\>10,000 steps/day, or about 1.5 hours of walking). * Participation in competing interventional trials.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| To determine whether the addition of an active smartwatch providing structured feedback to a nurse-led activity program produces a significantly greater increase in daily step count over 12 weeks compared with the same program paired with a passive smart | Week 12 | Difference in steps/day at 12 weeks between both arms (average of the final 14 valid days) (target Δ ≥ 1500) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| To evaluate feasibility to smartwatch wear | Week 6 and Week 12 | Wear-time adherence at W6 and W12 |
| To evaluate adherence to smartwatch wear | Week 6 and Week 12 | System Usability Scale (SUS) at W6 and W12 |
| To evaluate acceptability of digital feedback. | Week 6 and Week 12 | TAM (technology Acceptance Model) at W6 and W12 |
| To assess the impact of active smartwatch feedback on sedentary time. | day 1 to week 12 | Resting time (excluding sleep) at baseline, W6 and W12 |
| To assess the impact of active smartwatch feedback on gait-related activity patterns. | day 1 to week 12 | gait performance metrics (data from the smartwatch) |
| To assess the impact of active smartwatch feedback on blood pressure. | day 1 to week 12 | Continuous mean SBP and DBP and time-in-range at baseline, W6 and W12 |
| To monitor falls | day 1 to week 12 | Number of falls (collected continuously via the smartwatch) between baseline and W6 and between baseline and W12. |
| To monitor cardiovascular events (atrial fibrillation, AF), | day 1 to week 12 | Number of cardiovascular events between baseline and W12. |
| To examine effects on quality of life | day 1 to week 12 | Quality of life : physical and mental SF-36 auto-questionnaire scores at baseline, W6 and W12 |
| To examine effects on risk factors | Day 1, week 6 and week 12 | LDL cholesterol, alcohol, tobacco, weight and waist circumference at baseline and W12 |
| Recurrence and cardiovascular events | day 1 to week 12 | Recurrent stroke or TIA or cardiovascular events at W6 and W12 and in case of alert or hospitalization |
| To examine effects on fatigue | day 1 to week 12 | Fatigue : FAS and MFIS auto-questionnaires scores at baseline, W6 and W12 |
| To examine effects on cognition | day 1 to week 12 | Cognition : MoCA-short score at baseline, W6 and W12 |
| To examine effects on depression | day 1 to week 12 | Mood : PHQ-2 auto-questionnaire score at baseline, W6 and W12 |
| To examine effects on sleep | day 1 to week 12 | Sleep : efficiency and fragmentation at baseline, W6 and W12 and continuous |
Countries
France
Contacts
CONTACTSerge TIMSIT Pr, Neurologist
Outcome results
None listed