38 Patient and Environmental Factors Influencing Recognition, Response Time, and Treatment of In-Hospital Stroke

Background Approximately one in ten strokes occur in hospital whilst the patient is hospitalised for another reason. Existing research suggests that delays in recognition of in-hospital stroke (IHS) result in poorer outcomes compared to those with community-onset stroke. We aim to describe the characteristics of an IHS population and to phenotype the patient and/or environmental factors most likely to account for delays in recognition and response times. Methods Patients diagnosed with having an ischemic stroke while admitted to hospital for a non-stroke reason were identified through our hospital's stroke registry. We collected patient demographics along with the ward and service they were admitted under and if they underwent any invasive procedures prior to the stroke event. The patient cohort was dichotomised based on patient specific or environmental factors. We then calculated the likelihood of symptom recognition, medical review, and neuroimaging occurring within the 4.5 hour thrombolysis window between the two groups using the chi squared test. Results Fifty IHS occurred in the study time period. 52% were male, average age 74 (SD 12.7 years). 34 (68%) were admitted medically, and 16 (32%) surgically. 27 (54%) were assessed within the time frame for thrombolysis. Of these, seven received acute stroke treatment and the remaining 19 had contraindications to treatment. Patients presenting with collapse (67% vs 4%, p=0.011), limb weakness (85% vs 52%, p=0.011) or aphasia (63% vs 9%, p=0.019) were more likely to be recognised. Patients whose symptoms were recognised by a non-staff member (52% vs 78%, p=0.026) and those presenting out of hours (56% vs 70%, p=0.047) or with delirium (85% vs 39%, 0.051) were more likely to be missed. Conclusion In-hospital strokes are frequently missed due to the complexities of the patients involved. Education programs targeted at enhancing stroke pickup among hospital staff could potentially decrease delays and improve patient outcomes.