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Stroke Mimics Early experience of a ‘stroke divert’ in rural Cambridgeshire.

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Presentation on theme: "Stroke Mimics Early experience of a ‘stroke divert’ in rural Cambridgeshire."— Presentation transcript:

1 Stroke Mimics Early experience of a ‘stroke divert’ in rural Cambridgeshire

2 What’s a Stroke mimic? A patient labelled as suffering either stroke/TIA or possible stroke/TIA, subsequently diagnosed with another condition

3 Mimic activity What mimic rate did we expect? 30% often quoted 2011, 50% coming from UCL HASU Can London really monitor this activity?

4 ABN 2012: CHANGES IN WORKLOAD AND CASE MIX IN A LONDON HASU OVER TIME J Winston, et al. Royal Free; UCLJ Winston Audit admission rates and case mix over 15 months. Admission rates increased linearly. Thrombolysis call rates did not contribute significantly to this increase. Case mix changes assessed by studying discharge summaries from 2 months 1 year apart (October 2010 and 2011). Male bias in 2010 and a female bias in 2011 (p<0.05 by χ2test). Number with a TIA/infarct/ICH was similar (127 and 128). Number of non-stroke diagnoses at discharge increased significantly (46 to 76). Implications for acute general neurological/stroke services in the UK. (UC)London HASU data

5 Figure 1 The proportion of suspected stroke patients with an eventual diagnosis of stroke or TIA, from a systematic review and meta- analysis of case series, stratified by the context of assessment (emergency department, primary care, stroke unit/neurovascular clinic, ambulance or other referral sources). The width of each diamond represents the 95% CI of the pooled proportion Fernandes PM,Whiteley WN, Hart SR, et al. Pract Neurol 2013;13:21–28. Mimic literature review

6 New pathway 60% of Hinchingbrooke catchment diverted to CUH – Balance to PDH

7 The flow diverter Ambulance tool Hinchingbrooke ED attendees assess with Rosier In Hosp cases discussed – NB; Manchester divert for Tpa only with repat of non treated cases straight back from ED to DGH or home

8 Pathways from other services -London possible scenarios: 3a. 999 call – Ambulance will attend and paramedics will assess the patient. If found to be FAST positive they will be taken to the nearest HASU (category A call). – If FAST negative and a stroke is still suspected they will also go to the nearest HASU.

9 Mimic mix (varies with age)

10 Stroke chameleons--Unusual clinical manifestations of strokes and strokes disguised as other clinical processes acute confusional states seizures with acute stroke sensory symptoms movement disorders

11 Impact of mimic activity – Workload for ambulance, ED, radiol, Gmed, Neuro and stroke – Capacity planning – Further deskilling of DGHs

12 Addenbrooke’s experience Stroke – Admission rate, transfer times, LOS, thrombolysis, outcomes and repatriation rate Mimics – Diagnoses, Admission rates, Bed days and LOS

13 Case finding - method NHS awash with data Francis, Bristol babies.. Existing CUH stroke database ED ‘4 hour’ data base – attendances per calendar month – Cases found using GP post code

14 Case finding - method – Xls data sheet from ED postcodes of cases and GPs routinely collected clinical data) – Assume attendees with non Hunts GP could not be Hunts area stroke transfers – Existing ‘pathways’ for ENT, Ophthalmology, and major trauma excluded. Tertiary referrals ditto. – retrospective summaries and imaging review (me and MS) Further notes review ongoing

15 Results – 199 probable pathway transfers over 24 weeks 21 from Hinchingbrooke ED (8 vascular) – 159 definite pathway transfers 85 mimics 74 vascular – stroke 58 – TIA 16 – Predicted; 112 strokes mimics per year

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18 76% admitted 50 vasc, 292 bed days

19 Conclusions Total stroke numbers predictable Mimic rate at least 100%

20 What next Data should inform pathway design – Ambulance, ED, Radiology, stroke teams etc – Impact on sustainability of stroke and other local services Mimic – management planning – Mimic tariffs

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