A Reduction in Time with Electronic Monitoring In Stroke (ARTEMIS): study protocol for a randomised multicentre trial

Optimal patient protocols in regional acute stroke care

In acute stroke care two proven reperfusion treatments exist: (1) a blood thinner and (2) an interventional procedure. The interventional procedure can only be given in a stroke centre with specialized facilities. Rapid initiation of either is key to improving the functional outcome (often emphasized by the common phrase in acute stroke care "time=brain"). Delays between the moment the ambulance is called and the initiation of one or both reperfusion treatment(s) should therefore be as short as possible. The speed of the process strongly depends on five factors: patient location, regional patient allocation by emergency medical services (EMS), travel times of EMS, treatment locations, and in-hospital delays. Regional patient allocation by EMS and treatment locations are sub-optimally configured in daily practice. Our aim is to construct a mathematical model for the joint decision of treatment locations and allocation of acute stroke patients in a region, such that the time until treatment is minimized. We describe acute stroke care as a multi-flow two-level hierarchical facility location problem and the model is formulated as a mixed integer linear program. The objective of the model is the minimization of the total time until treatment in a region and it incorporates volume-dependent in-hospital delays. The resulting model is used to gain insight in the performance of practically oriented patient allocation protocols, used by EMS. We observe that the protocol of directly driving to the nearest stroke centre with special facilities (i.e., the mothership protocol) performs closest to optimal, with an average total time delay that is 3.9% above optimal. Driving to the nearest regional stroke centre (i.e., the drip-and-ship protocol) is on average 8.6% worse than optimal. However, drip-and-ship performs better than the mothership protocol in rural areas and when a small fraction of the population (at most 30%) requires the second procedure, assuming sufficient patient volumes per stroke centre. In the experiments, the time until treatment using the optimal model is reduced by at most 18.9 minutes per treated patient. In economical terms, assuming 150 interventional procedures per year, the value of medical intervention in acute stroke can be improved upon up to € 1,800,000 per year.

MR CLEAN-NO IV: intravenous treatment followed by endovascular treatment versus direct endovascular treatment for acute ischemic stroke caused by a proximal intracranial occlusion-study protocol for a randomized clinical trial

Background

Endovascular treatment (EVT) has greatly improved the prognosis of acute ischemic stroke (AIS) patients with a proximal intracranial large vessel occlusion (LVO) of the anterior circulation. Currently, there is clinical equipoise concerning the added benefit of intravenous alteplase administration (IVT) prior to EVT. The aim of this study is to assess the efficacy and safety of omitting IVT before EVT in patients with AIS caused by an anterior circulation LVO.

Methods

MR CLEAN-NO IV is a multicenter randomized open-label clinical trial with blinded outcome assessment (PROBE design). Patients ≥ 18 years of age with a pre-stroke mRS < 3 with an LVO confirmed on CT angiography/MR angiography eligible for both IVT and EVT are randomized to receive either IVT (0.9 mg/kg) followed by EVT, or direct EVT in a 1:1 ratio. The primary objective is to assess superiority of direct EVT. Secondarily, non-inferiority of direct EVT compared to IVT before EVT will be explored. The primary outcome is the score on the modified Rankin Scale at 90 days. Ordinal regression with adjustment for prognostic variables will be used to estimate treatment effect. Secondary outcomes include reperfusion graded with the eTICI scale after EVT and stroke severity (National Institutes of Health Stroke Scale) at 24 h. Safety outcomes include intracranial hemorrhages scored according to the Heidelberg criteria. A total of 540 patients will be included.

Discussion

IVT prior to EVT might facilitate early reperfusion before EVT or improved reperfusion rates during EVT. Conversely, among other potential adverse effects, the increased risk of bleeding could nullify the beneficial effects of IVT. MR CLEAN-NO IV will provide insight into whether IVT is still of added value in patients eligible for EVT.

Trial registration

www.isrctn.com: ISRCTN80619088. Registered on 31 October 2017.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05063-5.

Clinical prediction of thrombectomy eligibility: A systematic review and 4-item decision tree

BACKGROUND

A clinical large anterior vessel occlusion (LAVO)-prediction scale could reduce treatment delays by allocating intra-arterial thrombectomy (IAT)-eligible patients directly to a comprehensive stroke center.

AIM

To subtract, validate and compare existing LAVO-prediction scales, and develop a straightforward decision support tool to assess IAT-eligibility.

METHODS

We performed a systematic literature search to identify LAVO-prediction scales. Performance was compared in a prospective, multicenter validation cohort of the Dutch acute Stroke study (DUST) by calculating area under the receiver operating curves (AUROC). With group lasso regression analysis, we constructed a prediction model, incorporating patient characteristics next to National Institutes of Health Stroke Scale (NIHSS) items. Finally, we developed a decision tree algorithm based on dichotomized NIHSS items.

RESULTS

We identified seven LAVO-prediction scales. From DUST, 1316 patients (35.8% LAVO-rate) from 14 centers were available for validation. FAST-ED and RACE had the highest AUROC (both >0.81, p < 0.01 for comparison with other scales). Group lasso analysis revealed a LAVO-prediction model containing seven NIHSS items (AUROC 0.84). With the GACE (Gaze, facial Asymmetry, level of Consciousness, Extinction/inattention) decision tree, LAVO is predicted (AUROC 0.76) for 61% of patients with assessment of only two dichotomized NIHSS items, and for all patients with four items.

CONCLUSION

External validation of seven LAVO-prediction scales showed AUROCs between 0.75 and 0.83. Most scales, however, appear too complex for Emergency Medical Services use with prehospital validation generally lacking. GACE is the first LAVO-prediction scale using a simple decision tree as such increasing feasibility, while maintaining high accuracy. Prehospital prospective validation is planned.