Abstract TP38: Drip and Ship versus Direct Transfer to Comprehensive Stroke Center

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Abstract

Introduction: The success of thrombectomy trials for acute ischemic stroke create 2 options for prehospital decision-making-(1) transport the patient to the nearest endovascular capable center (ECC) even though this may mean bypassing a closer non-ECC (mothership model): or (2) transport to nECC for intravenous thrombolysis and then transfer the patient to the nearest ECC for endovascular therapy (drip and ship model).

Methods: A decision- analytical modelling study was constructed to simulate a 50-year old man with acute stroke. Input probabilities were derived from recent literature with thrombectomy data and outcomes from the HERMES. We include extensive subgroup analysis by varying each possible time interval and evaluate the two strategies under different circumstances. Multiple sensitivity analysis were performed to give the threshold values.

Results: In the base case calculation , we found Mothership to be the better strategy. The results shows when time to nECC is 30 min, Mothership is the better strategy until the time to ECC exceeds 93 min, or when it takes less than 126 min to transfer patients from nECC to ECC. When the time to nECC is 90 min, Drip and Ship becomes the better strategy regardless of the additional time to ECC and the transfer time. Subsequently we assigned the time to perform IA in transferred patients as 1.5 longer than patients who are directly sent to ECC and performed further sensitivity analyses. When nECC is within 30 min away, Drip and Ship is the better strategy when it takes more than 78 min to get to ECC, regardless of the transfer time.

Conclusion: We have used decision analysis, modelling based technique to address the problem of acute stroke triage from a population-based perspective. By feeding in the time to the nearest ECC and nECC, the EMS and stroke team can make the most appropriate decision on where to transfer the patient for the best outcomes based on the currently available data.

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