Stroke is causing 6.6 million deaths and is a major cause of disability worldwide in 2019. There remains an urgent need for interventions that improve outcomes which can be implemented with wide applicability for stroke. ACT-GLOBAL is a multi-factorial, multi-arm, multi-stage, randomised, global adaptive platform trial for stroke, aiming to identify the treatment/s associated with the highest chance of improving outcome in stroke patients. In ACT-GLOBAL multiple questions will be evaluated simultaneously and sequentially as data accrues and can evaluate interactions between different treatment options.

Stroke is the second leading cause of death, worldwide. It is also the second largest cause of disability-adjusted-life-years (DALYs) lost after ischaemic heart disease in developing countries, and third largest contributor to DALYs in developed countries (after ischaemic heart disease, low back and neck pain). In 2019, the absolute numbers of new strokes (12.2 million), stroke-related deaths (6.6 million), and people living with stroke (101.5 million) had increased globally from 1990 (70%, 43%, and 85% increases, respectively).

Steady progress has been made in establishing specific management strategies for patients affected by, or at high-risk of, stroke. Unfortunately, only a few acute treatments have been proven to be beneficial: thrombolysis, endovascular thrombectomy, hemicraniectomy, stroke unit care, and aspirin. There is a continued need for interventions that improve outcomes which can be implemented with wide applicability for stroke.

ACT-GLOBAL is an investigator-initiated, multi-factorial, multi-arm, multi-stage, randomised, global adaptive platform trial for stroke, aiming to find the treatment/s associated with the highest chance of improving outcome after stroke. In ACT-GLOBAL multiple questions will be evaluated simultaneously and sequentially as data accrues and can evaluate interactions between different treatment options.

Frequent adaptive analyses are conducted to assess whether a given intervention is superior, inferior, or equivalent either within a domain or for specific populations within the domain. Where it is anticipated that interactions between interventions in different domains may be likely, the statistical models will allow evaluation of such interactions. Each intervention within a domain with prospectively defined and mutually exclusive strata (sub-groups) of participants will be evaluated within the strata, while information from one stratum may be used (via 'borrowing') to contribute to the analysis of the effect of that intervention in other strata. Specific interventions or subgroups within overall populations may be dropped or cease to enrol, based on pre-specified rules.

The adaptive design allows new interventions or domains or both to be introduced. A Response Adaptive Randomisation algorithm may be used to preferentially randomize participants to interventions that appear to be performing better in domains where applicable.

Unlike traditional trial designs which explicitly prohibit co-enrollment of patients into different trials or multiple therapies, or use a factorial design, the adaptive platform design allows investigators to replicate the real-world environment to estimate possible synergy, competitive interference, or safety profiles of complex treatment protocols.

Platform Inclusion Criteria:

1. Age ≥18 years
2. Clinical diagnosis of stroke

Platform Exclusion Criteria:

There are no platform level exclusion criteria

Each state and domain will specify additional inclusion and exclusion criteria in the respective Domain-Specific Registration. Patients who fulfill the overall platform criteria will be assessed for enrollment into each active domain.

After a domain is completed, the archived de-identified limited dataset of randomized participants will be transmitted to and stored in the ACT-GLOBAL Data Repository, for use by researchers. Data can be shared after publication of the main results unless specified otherwise in domain-specific registration.

Data can be shared after publication of the main results.

Data can be shared after publication of the main results, based on approval of a submitted protocol to the Publication Committee and relevant ethics review. Data can be shared to bona fide researchers with experience in medical research, and with no conflict of interest that may potentially influence their interpretation of any analyses, and employed by a recognised academic institute, health service organisation, commercial research organisation of from the pharmaceutical industry. The data sharing will be only for analyses within the constraints of the consent under which the data were originally gathered consent.

Data sharing with industry will be according to relevant contracts with appropriate approvals from all stake holders.