Estimation of stroke outcomes based on time to thrombolysis and thrombectomy

Allen, Michael; Pearn, Kerry; Stein, Ken; James, Martin

doi:10.1101/2020.07.18.20156653

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…If the patient received thrombolysis‚ then the probability of a good outcome was based on age group and time to treatment using our previously published method. 22 Three alternative "what if?" scenarios were investigated for each hospital:…”

Section: Clinical Pathway Simulationmentioning

confidence: 99%

Use of Clinical Pathway Simulation and Machine Learning to Identify Key Levers for Maximizing the Benefit of Intravenous Thrombolysis in Acute Stroke

Allen

James

Frost

et al. 2022

Stroke

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Background: Expert opinion is that about 20% of emergency stroke patients should receive thrombolysis. Currently, 11% to 12% of patients in England and Wales receive thrombolysis, ranging from 2% to 24% between hospitals. The aim of this study was to assess how much variation is due to differences in local patient populations, and how much is due to differences in clinical decision-making and stroke pathway performance, while estimating a realistic target thrombolysis use. Methods: Anonymised data for 246 676 emergency stroke admissions to 132 acute hospitals in England and Wales between 2016 and 2018 was obtained from the Sentinel Stroke National Audit Programme data. We used machine learning to learn decisions on who to give thrombolysis to at each hospital. We used clinical pathway simulation to model effects of changing pathway performance. Qualitative research was used to assess clinician attitudes to these methods. Three changes were modeled: (1) arrival-to-treatment in 30 minutes, (2) proportion of patients with determined stroke onset times set to at least the national upper quartile, (3) thrombolysis decisions made based on majority vote of a benchmark set of hospitals. Results: Of the modeled changes, any single change was predicted to increase national thrombolysis use from 11.6% to between 12.3% to 14.5% (clinical decision-making having the most effect). Combined, these changes would be expected to increase thrombolysis to 18.3%, but there would still be significant variation between hospitals depending on local patient population. Clinicians engaged well with the modeling, but those from hospitals with lower thrombolysis use were most cautious about the methods. Conclusions: Machine learning and clinical pathway simulation may be applied at scale to national stroke audit data, allowing extended use and analysis of audit data. Stroke thrombolysis rates of at least 18% look achievable in England and Wales, but each hospital should have its own target.

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Section: Clinical Pathway Simulationmentioning

confidence: 99%

Use of Clinical Pathway Simulation and Machine Learning to Identify Key Levers for Maximizing the Benefit of Intravenous Thrombolysis in Acute Stroke

Allen

James

Frost

et al. 2022

Stroke

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“… 15 We have published the detailed method and code used to estimate outcomes. 16 This method is a development of the method of Holodinsky et al, 17 and incorporates the known decay of effectiveness of IVT 4 and MT 18 over time.…”

Section: Methodsmentioning

confidence: 99%

National implementation of reperfusion for acute ischaemic stroke in England: How should services be configured? A modelling study

Allen

Pearn

Ford

et al. 2021

European Stroke Journal

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Objectives To guide policy when planning thrombolysis (IVT) and thrombectomy (MT) services for acute stroke in England, focussing on the choice between ‘mothership’ (direct conveyance to an MT centre) and ‘drip-and-ship’ (secondary transfer) provision and the impact of bypassing local acute stroke centres. Design Outcome-based modelling study. Setting 107 acute stroke centres in England, 24 of which provide IVT and MT (IVT/MT centres) and 83 provide only IVT (IVT-only units). Participants 242,874 emergency admissions with acute stroke over 3 years (2015–2017). Intervention Reperfusion delivered by drip-and-ship, mothership or ‘hybrid’ models; impact of additional travel time to directly access an IVT/MT centre by bypassing a more local IVT-only unit; effect of pre-hospital selection for large artery occlusion (LAO). Main outcome measures Population benefit from reperfusion, time to IVT and MT, admission numbers to IVT-only units and IVT/MT centres. Results Without pre-hospital selection for LAO, 94% of the population of England live in areas where the greatest clinical benefit, assuming unknown patient status, accrues from direct conveyance to an IVT/MT centre. However, this policy produces unsustainable admission numbers at these centres, with 78 out of 83 IVT-only units receiving fewer than 300 admissions per year (compared to 3 with drip-and-ship). Implementing a maximum permitted additional travel time to bypass an IVT-only unit, using a pre-hospital test for LAO, and selecting patients based on stroke onset time, all help to mitigate the destabilising effect but there is still some significant disruption to admission numbers, and improved selection of patients suitable for MT selectively reduces the number of patients who would receive IVT at IVT-only centres, challenging the sustainability of IVT expertise in IVT-only centres. Conclusions Implementation of reperfusion for acute stroke based solely on achieving the maximum population benefit potentially leads to destabilisation of the emergency stroke care system. Careful planning is required to create a sustainable system, and modelling may be used to help planners maximise benefit from reperfusion while creating a sustainable emergency stroke care system.

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“…Clinical outcome from reperfusion is quantified in terms of a disability-free outcome three months after stroke (a modified Rankin Scale score of 0-1/6 describes either no or only minor non-disabling symptoms [14]). We have published the detailed method and code used to estimate outcomes [15]. This method is a development of the method of Holodinsky et al [16], and incorporates the known decay of effectiveness of IVT [4] and MT [17] over time.…”

Section: Clinical Outcomementioning

confidence: 99%

Implementing the NHS England Long Term Plan for stroke: how should reperfusion services be configured? A modelling study

Allen¹,

Pearn²,

Ford³

et al. 2021

Preprint

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Objectives: To guide policy when planning reperfusion thrombolysis (IVT) and thrombectomy (MT) services for acute stroke in England, focussing on the choice between ‘mothership’ (direct conveyance to an MT centre) and ‘drip-and-ship' (secondary transfer for MT after local IVT) provision and the impact of bypassing local acute stroke centres.Methods: Computer modelling was used to estimate the likely outcomes from reperfusion therapies, along with admission numbers to units, based on expected times to IVT and MT.Results: Without pre-hospital selection for LAO, 94% of the population of England live in areas where the greatest clinical benefit accrues from direct conveyance to an IVT/MT centre. If this model was followed then net benefit from reperfusion is predicted to be increased from 31 to 34 additional disability-free outcomes / 1,000 admissions. However, this policy produces unsustainable admission numbers at these centres, and depletes all but 19 IVT-only units of all stroke admissions. Implementing a maximum permitted additional travel time to bypass an IVT-only unit, or using a pre-hospital test for LAO, both increase net benefit over the current drip-and-ship model, but produce a similar destabilising effect on acute systems of care. Use of IVT-only units manage admission numbers to IVT/MT centres.Conclusions: The mothership model reduces time to MT at the cost of increased time to IVT, but the benefit of faster MT is predicted to lead to a modest improvement in overall outcomes. Providing a sustainable national system of acute stroke care requires a hybrid of mothership and drip-and-ship provision.

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Estimation of stroke outcomes based on time to thrombolysis and thrombectomy

Cited by 3 publications

References 22 publications

Use of Clinical Pathway Simulation and Machine Learning to Identify Key Levers for Maximizing the Benefit of Intravenous Thrombolysis in Acute Stroke

Use of Clinical Pathway Simulation and Machine Learning to Identify Key Levers for Maximizing the Benefit of Intravenous Thrombolysis in Acute Stroke

National implementation of reperfusion for acute ischaemic stroke in England: How should services be configured? A modelling study

Implementing the NHS England Long Term Plan for stroke: how should reperfusion services be configured? A modelling study

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