Large vessel occlusive stroke with milder baseline severity shows better collaterals and reduced harm from thrombectomy transfer delays.

BACKGROUND: Patients with large vessel occlusion (LVO) stroke presenting with milder baseline clinical severity are common and require endovascular thrombectomy. However, such patients are difficult to recognize using pre-hospital severity-based triage tools and therefore are likely to require a secondary inter-hospital transfer if transported to a non-thrombectomy center. Given the potential for milder severity to represent better underlying cerebrovascular collateral circulation, it is unknown whether transfer delays are still associated with poorer post-stroke outcomes in this patient group. AIMS: We primarily aimed to examine whether the harmful effect of inter-hospital transfer delay for thrombectomy was different for LVO patients with mild or severe deficits. Secondarily, we also investigated whether imaging markers of collateral circulation were different between severity groups. METHODS: Registry data from two large Australian thrombectomy centers were used to identify all directly presenting and secondarily transferred LVO patients undergoing thrombectomy, divided into those with lower (NIHSS < 10) and higher (NIHSS ⩾ 10) baseline deficits. The primary outcome was the functional independence or return to baseline defined as modified Rankin Scale 0-2 or baseline at 90 days. Patients with complete baseline CT-perfusion data were analyzed for imaging markers of collateral circulation by baseline severity group. RESULTS: A total of 1210 LVO patients undergoing thrombectomy were included, of which 273 (22.6%) had lower baseline severity. Despite similar thrombolysis and recanalization rates, transferred patients had lower odds of achieving the primary outcome compared to the primary presentation to a thrombectomy center, where baseline severity was higher (adjusted odds ratio (aOR) 0.759 (95% CI 0.576-0.999)), but not when severity was lower (aOR 1.357 (95% CI 0.764-2.409), p-interaction = 0.122). In the imaging analysis of 436 patients, those with milder severity showed smaller median ischemic core volumes (12.6 (IQR 0.0-17.9) vs 27.5 (IQR 6.5-37.1) mL, p < 0.001)), higher median perfusion mismatch ratio (10.8 (IQR 4.8-54.5) vs 6.6 (IQR 3.5-16.5), p < 0.001), and lower median hypoperfusion intensity ratio (0.25 (IQR 0.18-0.38) vs 0.40 (IQR 0.22-0.57), p < 0.001). DISCUSSION: Patients receiving secondary inter-hospital transfer for thrombectomy had poorer outcomes compared to those presenting directly to a thrombectomy center if baseline deficits were severe, but this difference was not observed when baseline deficits were milder. This result may potentially be due to our secondary findings of significantly improved collateral circulation markers in lower-severity LVO patients. As such, failure of pre-hospital screening tools to detect lower-severity LVO patients for pre-hospital bypass to a thrombectomy center may not necessarily deleteriously affect outcome. DATA ACCESS STATEMENT: Anonymized data not published within this article will be made available on request from any qualified investigator.

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.