Delays in treatment following aneurysmal subarachnoid haemorrhage

Background Aneurysmal subarachnoid haemorrhage (aSAH) is a serious form of stroke with high fatality and long-term morbidity. Receiving treatment for aSAH ‚Äöv¢¬ß12.5h from onset is associated with optimal outcomes for the patient while receiving treatment up to 24h after onset is still beneficial. However, the extent of delays in treatment of aSAH and the causes of delays are not well understood, which hinders the development of interventions to reduce delays and improve outcomes. Aims (1) To quantify time to treatment of aSAH (2) To identify factors associated with time to treatment of aSAH Methods The thesis used a pragmatic mixed-methods research approach to address the aims. The thesis consists of three original studies presented across 4 research chapters. Study 1: A systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and was registered in PROSPERO (Reg No. CRD42019132748). We searched four electronic databases (MEDLINE, EMBASE, Web of Science, and Google Scholar) for manuscripts published from January 1998 using pre-designated search terms and search strategy. Main outcomes were duration of delays of time intervals from onset of aSAH to definitive treatment and/or factors related to time to treatment. Study 2: A novel mixed-methods multiple case study approach was used that included in-depth interviews with stakeholders involved in individual aSAH cases, focusing on events from onset to treatment at two Australian tertiary referral centres during 2019-2020. Quantitative data were extracted from medical records including date and times. We developed the DIAMOND approach to analyse and synthesise mixed-methods data from across and within clinically focused case studies. Within-case analysis identified barriers and facilitators in 4 phases (pre-hospital, presentation, transfer, in-hospital), which we then triangulated with the quantified time in each phase to determine significant influencing factors. Finally, we conducted thematic analysis across cases in early (<12.5h) and delayed (>12.5h) treatment group using a case-study matrix. Study 3: A retrospective cohort study of confirmed first-ever aSAH cases from two Australian tertiary referral centres during 2010-2016 was used to examine time to treatment and its predictors. We used hospital and ambulance records to extract time from onset to treatment (endovascular coiling or neurosurgical clipping), demographics, clinical details of the aSAH, risk factors, pre-hospital care, and presenting symptoms. We examined predictors of time from onset to treatment as a continuous outcome using linear regression and as a categorical variable ‚ÄövÑv=very early‚ÄövÑv¥ (‚Äöv¢¬ß12.5h), early (12.5-24h) and ‚ÄövÑv=late‚ÄövÑv¥ (>24h reference category) using multinomial regression. Results: Study 1 (Chapter 3): A total of 64 studies with 16 different time intervals in the pathway of aSAH patients were identified. Measures of time to treatment varied between studies (e.g. cut-off timepoints or absolute mean/median duration). Factors associated with time to treatment fell into two categories ‚ÄövÑv¨ individual (n=9 factors e.g. age, sex, clinical characteristics) and health system (n=8 factors, e.g. pre-hospital delay or presentation out-of-hours). Demographic factors were not associated with time to treatment. More severe aSAH reduced treatment delay in most studies. Prehospital delays (patients delay, late referral, late arrival of ambulance, being transferred between hospitals or arriving at the hospital outside of office hours) were associated with treatment delay. Inhospital factors (patients with complications, procedure before definitive treatment, slow work-up, type of treatment) were less associated with treatment delay. Study 2: Results are presented across Chapter 4 and Chapter 5. Chapter 4: Twenty-seven cases with 90 interviewees yielded five themes related to facilitators or barriers of timely treatment. ‚ÄövÑv¿Early recognition‚ÄövÑvp led to urgent response. ‚ÄövÑv¿Accessibility to health care‚ÄövÑvp depended on patient‚ÄövÑv¥s location, transport, and environmental conditions. Good ‚ÄövÑv¿Coordination‚ÄövÑvp between and within health services was a key facilitator. ‚ÄövÑv¿Complexity‚ÄövÑvp of patient‚ÄövÑv¥s condition affected time to treatment in multiple time periods. ‚ÄövÑv¿Availability of resources‚ÄövÑvp was identified most frequently during the diagnostic and treatment phases as both barrier and facilitator. Chapter 5: Median (IQR) time to treatment was 15.1 (9.0, 24.1) hours among 27 cases (74.1% female). Only 37% of cases had treatment within 12.5 hours of onset. Qualitative and quantitative data triangulation following the results in Chapter 4 identified three key themes influencing timely treatment of aSAH. Early recognition of aSAH and good coordination during pre-hospital and diagnosis phases, and availability of resources for treatment during in-hospital period were main facilitators for treatment within 12.5 hours from onset. Lack of recognition of aSAH at onset and lack of resources for immediate in-hospital treatment were major barriers for more delayed treatment. Study 3 (Chapter 6): Among 575 patients (mean [SD] age 54.1 [14.5] years; 69.9% female), 482 were treated with median (IQR) time to treatment of 19.4 (10.6, 31.0) hours and 30% treated very early, 32% treated early and 38% treated late. In multivariable analyses, patients presenting with strokelike symptoms, arriving by ambulance and with extensive aSAH (modified Fisher grade 2-3) had shorter time to treatment and were more likely to receive treatment early. In contrast, people living further away and that had cerebral angiography had longer time to treatment and were more often treated late. Conclusions A substantial proportion of patients with aSAH were not treated within timeframes associated with better outcomes. The pathway from onset to definitive treatment of a patients with aSAH consists of multiple stages with multiple influencing factors. Using a robust pragmatic mixed-methods approach, we have identified key factors associated with time to treatment, many of which have not been well documented in the literature such as presenting symptoms, recognition of aSAH and urgency of response, service coordination or availability of resources for treatment. Challenges remain for the diagnosis and treatment for people presenting with lower grade aSAH and no neurological symptoms. Interventions to improve community awareness, recognition and diagnosis of aSAH may reduce delay to treatment.