Jessalyn K Holodinsky1,2, Alka B Patel1,3, John Thornton4,5, Noreen Kamal6, Lauren R Jewett7, Peter J Kelly8, Sean Murphy9,10, Ronan Collins11, Thomas Walsh12, Simon Cronin13,14, Sarah Power15, Paul Brennan15, Alan O'hare15, Dominick Jh McCabe16,17,18, Barry Moynihan19, Seamus Looby15, Gerald Wyse20, Joan McCormack21, Paul Marsden22, Joseph Harbison23, Michael D Hill1,2,6,24,25,26, David Williams5,9. 1. Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada. 2. Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada. 3. O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada. 4. Department of Neuroradiology, Royal College of Surgeons in Ireland, Dublin, Ireland. 5. Beaumont Hospital, Dublin, Ireland. 6. Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada. 7. Department of Geography, University of Calgary, Calgary, Alberta, Canada. 8. Neurovascular Unit for Translational and Therapeutics Research, Mater Misericordiae University Hospital/University College Dublin, Dublin, Ireland. 9. Department of Geriatric and Stroke Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland. 10. Mater Misericordiae University Hospital, Dublin, Ireland. 11. Department of Geriatric and Stroke Medicine, Tallaght Hospital, Dublin, Ireland. 12. 12Department of Stroke and Geriatric Medicine, Galway University Hospital, Galway, Ireland. 13. Cork NeuroScience Centre, University College Cork, Cork, Ireland. 14. Department of Neurology, Cork University Hospital, Cork, Ireland. 15. 15Department of Neuroradiology, Beaumont Hospital, Dublin, Ireland. 16. 16Department of Neurology, Stroke Service, and Vascular Neurology Research Foundation, The Adelaide and Meath Hospital (incorporating the National Children's Hospital), Dublin, Ireland. 17. Department of Clinical Neurosciences, UCL Institute of Neurology, London, UK. 18. Academic Unit of Neurology, School of Medicine, Trinity College Dublin, Dublin, Ireland. 19. 19Department of Geriatric and Stroke Medicine, Beaumont Hospital, Dublin, Ireland. 20. Department of Neuroradiology, Cork University Hospital, Cork, Ireland. 21. Faculty of Science and Health, Dublin City University, Dublin, Ireland. 22. Department of Public Health, Health Services Executive, Tulamore, Ireland. 23. Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland. 24. Department of Radiology, University of Calgary, Calgary, Alberta, Canada. 25. Department of Medicine, University of Calgary, Calgary, Alberta, Canada. 26. Calgary Stroke Program, University of Calgary, Calgary, Alberta, Canada.
Abstract
INTRODUCTION: In ischaemic stroke care, fast reperfusion is essential for disability free survival. It is unknown if bypassing thrombolysis centres in favour of endovascular thrombectomy (mothership) outweighs transport to the nearest thrombolysis centre for alteplase and then transfer for endovascular thrombectomy (drip-and-ship). We use conditional probability modelling to determine the impact of treatment times on transport decision-making for acute ischaemic stroke. MATERIALS AND METHODS: Probability of good outcome was modelled using a previously published framework, data from the Irish National Stroke Register, and an endovascular thrombectomy registry at a tertiary referral centre in Ireland. Ireland was divided into 139 regions, transport times between each region and hospital were estimated using Google's Distance Matrix Application Program Interface. Results were mapped using ArcGIS 10.3. RESULTS: Using current treatment times, drip-and-ship rarely predicts best outcomes. However, if door to needle times are reduced to 30 min, drip-and-ship becomes more favourable; even more so if turnaround time (time from thrombolysis to departure for the endovascular thrombectomy centre) is also reduced. Reducing door to groin puncture times predicts better outcomes with the mothership model. DISCUSSION: This is the first case study modelling pre-hospital transport for ischaemic stroke utilising real treatment times in a defined geographic area. A moderate improvement in treatment times results in significant predicted changes to the optimisation of a national acute stroke patient transport strategy. CONCLUSIONS: Modelling patient transport for system-level planning is sensitive to treatment times at both thrombolysis and thrombectomy centres and has important implications for the future planning of thrombectomy services.
INTRODUCTION: In ischaemic stroke care, fast reperfusion is essential for disability free survival. It is unknown if bypassing thrombolysis centres in favour of endovascular thrombectomy (mothership) outweighs transport to the nearest thrombolysis centre for alteplase and then transfer for endovascular thrombectomy (drip-and-ship). We use conditional probability modelling to determine the impact of treatment times on transport decision-making for acute ischaemic stroke. MATERIALS AND METHODS: Probability of good outcome was modelled using a previously published framework, data from the Irish National Stroke Register, and an endovascular thrombectomy registry at a tertiary referral centre in Ireland. Ireland was divided into 139 regions, transport times between each region and hospital were estimated using Google's Distance Matrix Application Program Interface. Results were mapped using ArcGIS 10.3. RESULTS: Using current treatment times, drip-and-ship rarely predicts best outcomes. However, if door to needle times are reduced to 30 min, drip-and-ship becomes more favourable; even more so if turnaround time (time from thrombolysis to departure for the endovascular thrombectomy centre) is also reduced. Reducing door to groin puncture times predicts better outcomes with the mothership model. DISCUSSION: This is the first case study modelling pre-hospital transport for ischaemic stroke utilising real treatment times in a defined geographic area. A moderate improvement in treatment times results in significant predicted changes to the optimisation of a national acute stroke patient transport strategy. CONCLUSIONS: Modelling patient transport for system-level planning is sensitive to treatment times at both thrombolysis and thrombectomy centres and has important implications for the future planning of thrombectomy services.
Entities:
Keywords:
Ischaemic stroke; endovascular therapy; health services research; thrombolysis
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